Smartphone use and social media addiction in undergraduate students

Nichapa Parasin; Monthinee Watthanasuwakul; Palagon Udomkichpagon; Teerachai Amnuaylojaroen

doi:10.12688/f1000research.128545.1

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Brief Report

Smartphone use and social media addiction in undergraduate students

[version 1; peer review: 2 not approved]

Nichapa Parasin¹, Monthinee Watthanasuwakul¹, Palagon Udomkichpagon¹, Teerachai Amnuaylojaroen ²

PUBLISHED 15 Dec 2022

Author details Author details

¹ School of Allied Health Science, University of Phayao, Phayao, Phayao, 56000, Thailand
² School of Energy and Environment, University of Phayao, Phayao, 56000, Thailand

Nichapa Parasin
Roles: Conceptualization, Data Curation, Formal Analysis, Funding Acquisition, Investigation, Methodology, Project Administration, Resources, Software, Supervision, Validation, Writing – Original Draft Preparation

Monthinee Watthanasuwakul
Roles: Data Curation, Formal Analysis, Validation

Palagon Udomkichpagon
Roles: Data Curation, Validation, Visualization

Teerachai Amnuaylojaroen
Roles: Supervision, Writing – Original Draft Preparation, Writing – Review & Editing

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REVIEWER STATUS

Abstract

Background: Children’s use of social media has increased significantly over the past decade. As a result, they are susceptible to smartphone addiction. In particular, parents' and children's well-being and behaviors are negatively affected by smartphone addiction. Such addiction likely affects both physical performance and lifestyle. Adolescents utilize their smartphones while performing other tasks. The secondary task might divert attention away from the primary task. Reaction time is the combination of brain processing and muscular movement. Texting or communicating on a smartphone while performing another task may affect reaction time. Thus, the purpose of this study was to explore the influence of smartphone use on reaction time in undergraduate students who were addicted to smartphones.
Methods: The Smartphone Addiction Scale-Short Version (SAS-SV) was used to assign 64 undergraduate students to the smartphone addiction group (n = 32) and the control group (n = 32). The reaction time (RT) of an organism is used to determine how rapidly it responds to stimuli. All participants were examined on the RT test under three conditions: no smartphone use (control), texting, and chatting on a smartphone. Participants were questioned by smartphone through text message or chat with the support of a researcher during the texting and conversation conditions. While responding to the questions, the participant was administered an RT test.
Results: The results showed that smartphone addiction tends to have a reduced influence on reaction time when compared to the control group. Also, texting or conversing on a smartphone while doing other work had a substantial impact on reaction time in the undergraduates.
Conclusions: Combining smartphone use with other activities tends to reduce undergraduate students' reaction time.

Keywords

Smart phone addiction, Social media addiction, Children, Smart phone used

Corresponding authors: Nichapa Parasin, Teerachai Amnuaylojaroen

Competing interests: No competing interests were disclosed.

Grant information: This research was supported by the Thailand Science Research and Innovation fund and the University of Phayao (Grant No. FF66-UoE010).
The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Copyright: © 2022 Parasin N et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

How to cite: Parasin N, Watthanasuwakul M, Udomkichpagon P and Amnuaylojaroen T. Smartphone use and social media addiction in undergraduate students [version 1; peer review: 2 not approved]. F1000Research 2022, 11:1524 (https://doi.org/10.12688/f1000research.128545.1) First published: 15 Dec 2022, 11:1524 (https://doi.org/10.12688/f1000research.128545.1) Latest published: 30 Sep 2024, 11:1524 (https://doi.org/10.12688/f1000research.128545.3)

Introduction

The Internet is tremendously useful in a variety of applications, including productive electronic commerce, instant knowledge sharing, cultural exchange, and enjoyment.¹^–³ Smartphones are devices that combine Internet and phone functionality. They provide qualitatively distinguishing features in addition to the benefits of the Internet. Children use smartphones to watch videos, express themselves, communicate with friends, and search for information. The portability and convenience of a smartphone allow it to be utilized anywhere and at any time. However, although smartphones provide several benefits in our lives, we must be aware of their negative implications, the most concerning of which is smartphone addiction, which relates to the unrestrained use of smartphones. Individuals with smartphone addiction endure emotional, mental, and physical challenges.²^,³

Even though smartphone addiction does not remain listed in the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition⁴ or the upcoming International Classification of Diseases, Eleventh Revision, evidence suggests that there is an increasing perception of the issue.⁵ Smartphone addiction is a new type of addictive behavior that has developed from the rapid proliferation of smartphones across the internet, resulting in a severe behavioral addiction.⁶ According to the National Information Society Agency in Korea, smartphone addiction surpasses internet addiction.⁷ Lin et al.⁸ identified four characteristics of smartphone addiction, including compulsion, functional impairment, tolerance, and withdrawal. Smartphone addiction has been found to correlate with a variety of negative effects on physical health, including brain tumors, cancer, a weakened immune system, neck and wrist pain, and sleep disorders.⁹^,¹⁰ Prolonged smartphone use at nighttime might cause insomnia, stress, and sadness.¹¹ Screen time and Internet use have been shown to have an impact on sleep,¹²^,¹³ and SNS addicts have been shown to have poorer sleep quality than non-SNS addicts.¹⁴

Adolescents, in particular, are at a significant risk of becoming addicted to smartphones. They are inextricably linked to their smartphones, which they consider to be a second personality.¹⁵ In addition, the adolescents spent the most time of their daily routine with smartphone applications, such as, mobile messengers, web browsing, gaming, and social media.¹⁶ Several smartphone owners insist that they could not really operate without their devices.¹⁷ Adolescents go through a variety of physical and psychological changes during their growth. Despite the fact that teenagers depend on their parents for survival and identity, they are also working to separate themselves from them in order to grow as individuals and carve out a place for themselves. Adolescents become more dependent on smartphones during these transitional periods. Compared to adults, they are significantly more sensitive to and embrace new technologies. Adolescents express themselves online as “digital natives,” aiming to stay current with fashion trends, using a variety of apps, and seeking emotional connections and support.¹⁸ They specialize in multitasking and require fast feedback and input.¹⁸

Furthermore, social comparison, concern for one's reputation, and identity formation are all long-standing characteristics of adolescence,¹⁹ as is the need for social approval and acceptance, which is impacted by the judgment of one's peers.²⁰^,²¹ However, current smartphones enhance the negative potential of addictive behavior, especially through the amplification of anxiety as adolescents navigate the power dynamics that support their online connectivity.²² In another aspect, power dynamics influence who youth seek acceptance from online, how they use smartphones, and how they understand online content. Furthermore, internet comparisons between oneself and others may become more common and increase relative deprivation, reducing self-esteem and negatively damaging mental health. When these characteristics, such as novelty seeking in teenagers, are combined with their immature control abilities, they are predisposed to developing smartphone and social media addiction.²³ In this study, we examined the features of smartphone addiction in adolescents aged 18 to 22 years. In addition, we sought to examine if there would be a difference in reaction times between those who didn't use smartphones and those who did in a smartphone-addicted undergraduate student. Furthermore, we compared the smartphone use patterns of a risk group for smartphone addiction and a normal user group, as well as the risk variables for smartphone addiction.

Methods

Study design and setting

This is a cross-sectional study (blind assessor and statistician) that included 64 graduate students who used a smartphone for social media every day for at least a year before participation. The data was collected in a laboratory room at the Department of Physical Therapy, School of Allied Health Science, University of Phayao, between February and August 2019.

Participants

The participants were recruited via poster advertising in the local area. The primary outcome of the study was sample size that was calculated as follow (eq (1))

(1)

n = \frac{2 s^{2} {(Z_{\propto} + Z_{β})}^{2}}{d^{2}}

when n is number of sample sizes, s is standard deviation,

Z_{\propto}

is z-score at 95% confidence level,

Z_{β}

is 99% confidence level, d is mean difference of virtual reaction time. In this study, we used “d = 0.45” and “s = 0.58” as follow,²⁴ while Z_β and Z_α were 0.842 and 1.96, respectively.

An initial sample size was 29 in each group which allowing for a dropout rate of 10% (n=3). Finally, at least 64 participants (32 per group) were recruited in this study. The participant recruited for this study was undergraduate students aged between 18 and 22 years, and had used smartphones for social media every day for at least a year before participation. Also, the question survey was developed in this study to exclude participants who had myopia, poor vision, impaired vision, or color blindness, as well as auditory or any perception deficiencies, upper body muscle weakness, sensory loss associated with any type of neurological illness, major surgery, or limb injuries.

Ethical considerations

The purposes and processes of the study was explained to the participants before the experiment began, and all participants were promised that their data would be kept anonymous and confidential. Informed consent was signed from all subjects before they participated in the study. The study was conducted in accordance with the Declaration of Helsinki, and the Human Ethic Committee of the University of Phayao approved the project (No.2/095/61, effective from 5 November 2018 to 5 November 2019).

Measurement

The reaction time (RT) of an organism is an assessment of how rapidly it responds to a stimulus. The RT is the amount of time that passes between when the stimulus is sent and when the subject shows the relevant voluntary reaction. Three forms of RT were characterized by DukeElder S.²⁵; Luce²⁶; Welford.²⁷ (1) Simple RT: In this scenario, there is only one stimulus and one reaction. (2) Recognition RT: Any stimulus should be responded to, whereas others should not. (3) Choice RT: There are several stimuli and reactions in this situation. The nervous system recognizes the stimulus in human RT. The message is subsequently relayed to the brain by the neurons. The message is sent from the brain to the spinal cord, and eventually to the hands and fingers. Average RTs have been reported to be approximately about 190 and 160 m/s for light and sound stimuli, respectively.²⁷ Fast RTs can be beneficial in some activities, such as athletics and sports, but slow RTs might have catastrophic consequences when driving.

The Multichoice Reaction Timer (Grand Sport brand, 383059/No.BHX 0012), produced in Bangkok (Thailand), was used to measure the reaction time to visual stimuli as well as the response time (Figure 1). It consists of a simple interface for the researcher with controls for generating stimuli, a monitor displaying the light of communicated stimuli in three colors (red, blue, and yellow), a set of three hand-operated buttons, and a screen of the obtained score with a second's precision. The two stations of the apparatus were placed along a line 2 meters apart, such that the controller could perceive the optical pulses but the controller's interface was out of the subject's range of vision. A hand-operated toggle and a visual stimulus were used to measure response time to a single stimulus. Each subject was told to sit in front of the light box with their hands on the table. The participants were instructed to press the button as soon as they saw a light on the box (red, blue, or yellow), which measured the response time in seconds while three light stimuli were used randomly in the ten trials and repeated three times for each condition recorded in the exam. The average response time from the test were used for the analysis of the risk for smartphone addiction. s.

Figure 1. Flowchart of the Study.

Procedure

After signing the informed consent form, the participants were screened by the researcher based on the inclusion and exclusion criteria. Then, all participants were separated into two groups based on their scores on the Smartphone Addiction Scale Thai Short Version (SAS-SV-TH).²⁸ The participants were scheduled for general data collection (age, weight, height, and duration and frequency of smartphone use) and an RT test with the researcher. The study was carried out on the same day at the University of Phayao's Department of Physical Therapy, School of Allied Health Science. To prevent the effects of exhaustion produced by everyday responsibilities, the trials were conducted in the morning in a well-lit, silent room with only the investigators present. It is a self-report evaluation of 10 items with Likert's type ratings of 1–6 (1 = strongly disagree and 6 = strongly agree) meant to identify a prospective high-risk category for smartphone addiction. The scale's dependability was demonstrated by a Cronbach's alpha of 0.911.²⁹ Subjects with an SAS-SV-TH score of more than 31 points (in male) or 33 points (in female) were allocated to the smartphone addiction group.²⁹

The RT test was administered to all participants in three conditions: no smartphone use (control), texting, and chatting on a smartphone. During the control condition, participants did not have access to their devices and had no interaction with other people or devices in a distraction-free area with only study professionals present for supervision. During the texting and conversation conditions, participants were questioned via smartphone (through text message or chat) with the assistance of a researcher. The subject was given an RT test while answering the questions as listed in Table 1.

Table 1. Questionnaire for interview.

No. of Question	Texting	Conversation
1	Your name	What are your hobbies?
2	Faculty, school name	What is your favorite sport?
3	Year in school	Have you seen a movie lately? What was the story about?
4	Gender	What book have you read recently? What was the book about?
5	Date of birth	What is your part-time job?
6	Age	What subject are you good at?
7	Favorite foods	What is your weak subject?
8	Favorite colors	What are you career plans?

Statistical analysis

STATA version 17 was used for all statistical analyses. The data is presented as the mean standard deviation (SD) (eq (1)).

(1)

SD = \sqrt{\frac{\sum {(x_{i} - μ)}^{2}}{n}}

$x_{i}$ is each value of population

$μ$ is the population mean

n is the size of population

The one-sample Kolmogorov–Smirnov test (eq (2)) was performed to check the normality of the distribution of each continuous variable.

(2)

D = Maximum |F_{0} (X) - F_{r} (X)|

$F_{0} (X)$ = Observed cumulative frequency distribution of a random sample of n observations.

$F_{r} (X)$ = The theoretical frequency distribution.

Because of the general distribution of data used, sample t-tests were employed to compare the RT between the addiction group and the control group in three conditions. In a within-group analysis, the mean values of RT between the control, texting, and talking conditions were compared by the pair sample t-test. Statistical significance was determined using p-values < 0.05.

Results

Figure 1 depicts a flow diagram of the recruitment process. The eligibility of 102 subjects was determined. Overall, 38 participants were excluded because they did not match the inclusion criteria (n = 18) or declined to participate (n = 20). The demographic information of all participants is listed in Table 2. A total of 64 undergraduate students (13 males, mean age 20.61±1.16 years) were selected from the University of Phayao, Phayao Province in Thailand.³⁰ They were separated into two groups according to the SAS-SV score. There weren't any statistically significant distinctions in gender, age, weight, or height between the two groups. The SAS-SV-TH score difference was only statistically significant at a p-value of 0.000.

Table 2. Demographic Information.

Characteristics	Addiction group (n=32)	Control group (n=32)	p-value
Gender (M/F, n)	7/25	6/26	-
Age (years)	20.67±1.203	20.53±1.135	0.502
Weight (kg)	53.15±9.93	54.57±10.60	0.614
Height (cm.)	160.47±7.7	163.08±6.90	0.160
SAS-SV-Score	37.06±4.43	25.69±3.51	0.000*

* A significant baseline difference.

In an among-group analysis (Table 3), the addiction group tended to have a slightly higher RT than the control group. Still, there was no difference in the average changes in RT between the addiction group and the control group. While comparing among the three conditions of smartphone use (Figure 2), a within-group analysis, the RT of the conversation and texting conditions in both groups was significantly improved compared with their control condition. In the smartphone group, the RT in the texting condition (1.742 ± 0.599 s) was significantly greater (p-value < 0.001) than in the talking condition (1.309 ± 0.322 s.) and also in the control condition (1.044 ± 0.221 s.). Similarly, in the control group, there was a significant (p-value < 0.001) difference in RT between talking (1.225 ± 0.272 s) and in the control condition (0.995 ± 0.284 s.). Moreover, there was the greatest increase in RT between the control condition and the texting condition (p-value < 0.001).

Table 3. Average Reaction Times of both groups across all condition of smartphone use.

Reaction Times (s) in three conditions of Smartphone use	Smartphone addiction group (n=32)	Control group (n=32)	p-value
Control condition (no use)	1.044 ± 0.221	0.995 ± 0.284	0.439
Talking condition	1.309 ± 0.322	1.225 ± 0.272	0.267
Texting condition	1.742 ± 0.599	1.735 ± 0.599	0.964

Figure 2. Reaction time in the difference conditions of the smartphone use.

Discussion

In any of the three conditions, there wasn't any substantial difference in visual reaction time (VRT) here between the smartphone addict group and the control group. The results were not inconsistent with our hypothesis that smartphone-addicted people may show a lower VRT. However, there are possible mechanisms that provide for the different hypotheses. Perhaps the most likely mechanism is the idea that those individuals who are smartphone addicts have a higher rate of smartphone use. Social networking was the most popular smartphone application among the smartphone addicts. The average usage time of texting or talking was almost 30 minutes per session, with several sessions per day. On the other hand, individuals in the control group took only 5–15 minutes per time for entertainment applications. In the test conditions, the smartphone addicts group had similar smartphone usage. Eye-hand coordination when texting in social networking apps and when performing repetitive tasks such as performance practice and brain training has been found.³¹ As a result, the participants were unable to use the extra time to extend their reach duration. Rather, they finished the assignment in the same amount of time, allowing them more opportunity to switch focus and optimize dual-task attention. This impacts the brain and results in improved cognitive functioning.³²

Furthermore, the participants in both groups demonstrated the same results for VRT in 3 conditions of smartphone use. When texting and talking on their smartphones, all participants exhibit slower VRT. Dual-task interference, according to capacity theory, results from the concurrent allocation of a restricted group of general-purpose resources, or efficient clustering.³³^,³⁴ When mixed tasks exceed (consolidated or specific) resource availability, one or both activities perform poorly. Bottleneck accounts, on the other hand, stress the serial structure of the dual-task process as a result of single-channel screening or information timetabling during the stimuli decoding, identification, and judgment phases.³⁵ Since such instances of disturbance exist, it is argued that the nervous system temporarily delays operations solely on a single task in favor of processes on the prioritized task, resulting in poor efficiency on the non-priority activity. Participants may have coordinated task prioritizing by altering the timing or scheduling of tasks to improve the processing of information and prevent a processing bottleneck.³⁵^–³⁸ This result was consistent with the study by Yu and Huang³⁹ which reported that dual tasking significantly increases the RT. Increased reaction times due to cognitive distraction have been reported earlier.⁴⁰ This shows that the stimuli can be seen or heard while doing another task but are not processed normally as the brain is overloaded. Our study shows that the RT during the talking condition of smartphone use is faster than the texting condition. The expenditure on decision making, and planning was much higher in the texting condition. Texting caused participants to physically move their focus between the smartphone and light stimulation, in addition to turning cognitive resources in a similar direction that conversation does.⁴¹ There are limitations to this study that must be considered. Our study only investigated the reaction time for light stimuli. Future research should attempt to evaluate auditory reaction time, as well as studies in a different age group.

Conclusions

This study was conducted on 64 teenagers to investigate the effect of smartphone use for social media on Visual Reaction Time (VRT). There was no significant difference statistically in the reaction time between adolescents with and without smartphone addiction in all test conditions (no smartphone use, texting, and talking using a smartphone). However, the adolescents show prolonged reaction times when they must perform the dual-tasking. Therefore, the adolescent should avoid other activities when using a smartphone.

Data availability

Underlying data

Figshare: The Study of Smartphone Use and Social Media Addiction in Children, https://doi.org/10.6084/m9.figshare.21688259.v1.³⁰

This project contains the following underlying data.

‐ Reaction-time_data_For-share.xlsx
‐ Survey_use.pdf

Data are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0).

Acknowledgments

The authors would like to acknowledge School of Allied Health Science, University of Phayao for supporting the Multichoice Reaction Timer in this study.

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Version 3

VERSION 3 PUBLISHED 15 Dec 2022

Author details Author details

¹ School of Allied Health Science, University of Phayao, Phayao, Phayao, 56000, Thailand
² School of Energy and Environment, University of Phayao, Phayao, 56000, Thailand

Monthinee Watthanasuwakul
Roles: Data Curation, Formal Analysis, Validation

Palagon Udomkichpagon
Roles: Data Curation, Validation, Visualization

Teerachai Amnuaylojaroen
Roles: Supervision, Writing – Original Draft Preparation, Writing – Review & Editing

Competing interests

No competing interests were disclosed.

Grant information

This research was supported by the Thailand Science Research and Innovation fund and the University of Phayao (Grant No. FF66-UoE010).
The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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© 2022 Parasin N et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Parasin N, Watthanasuwakul M, Udomkichpagon P and Amnuaylojaroen T. Smartphone use and social media addiction in undergraduate students [version 1; peer review: 2 not approved]. F1000Research 2022, 11:1524 (https://doi.org/10.12688/f1000research.128545.1)

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Reviewer Report 07 Feb 2024

Hariom K. Solanki, Department of Community Medicine, Maulana Azad Medical College, Delhi, New Delhi, Uttar Pradesh, India

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https://doi.org/10.5256/f1000research.141145.r235225

Dear Authors
There are certain comments/ queries / suggestions with respect to this manuscript. Please address them to improve upon the manuscript.

1. The title of the manuscript does not reflect the main objective and results presented in the manuscript.
2. "In this study, we examined the features of smartphone addiction in adolescents aged 18 to 22 years" - there is no result presented with respect to this objective in the study. Also, adolescent age group does not include people 20 or above as per the World Health Organization definition. If some other operational definition has been used, please cite the source.
3. Fig 1 does not correspond to flowchart as the claim is made in the text in results section. In any case participant recruitment flowchart should be included in the methods section (when you put the correct figure in the manuscript)
4. The number of exclusions seems to be too large. What were the reasons to exclude all participants for myopia, impaired vision - were they still excluded if they were either corrected with glasses or were only of mild degree in nature?

Is the work clearly and accurately presented and does it cite the current literature?

Partly
Is the study design appropriate and is the work technically sound?

Partly
Are sufficient details of methods and analysis provided to allow replication by others?

Yes
If applicable, is the statistical analysis and its interpretation appropriate?

Yes
Are all the source data underlying the results available to ensure full reproducibility?

Partly
Are the conclusions drawn adequately supported by the results?

Partly

Competing Interests: No competing interests were disclosed.

Reviewer Expertise: Public Health, Epidemiology, Primary Health Care

I confirm that I have read this submission and believe that I have an appropriate level of expertise to state that I do not consider it to be of an acceptable scientific standard, for reasons outlined above.

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Report a concern

Author Response 13 Apr 2024

Teerachai Amnuaylojaroen, School of Energy and Environment, University of Phayao, Phayao, 56000, Thailand

13 Apr 2024

Author Response
Dear Reviewer,

We appreciate the opportunity to revise our manuscript entitled " Smartphone used and social media addiction in undergraduate student" and would like to thank the reviewers for ... Continue reading
Dear Reviewer,

We appreciate the opportunity to revise our manuscript entitled " Smartphone used and social media addiction in undergraduate student" and would like to thank the reviewers for their insightful comments and suggestions. We have carefully considered each point and have made substantial revisions to our manuscript (as seen in Track Change). Since many of the texts in the revised manuscript have been edited to cover all comments/suggestion, we have listed the overall changes in the revised version of the manuscript for more understanding in brief as follows:

In the title, it has been changed from " Smartphone used and social media addiction in undergraduate student" to “The Impact of Smartphone Addiction on Reaction Time in Undergraduate Students: An Experimental Study”

In the introduction, we have inserted many of texts in this section for more correspondingly to the point of the objective in study.

In the methodology, we have also inserted and revisde many of texts in this section based on the suggestions/comments from all reviewers such as the flowchart of the study, explanation of the exclusion criteria, type of RT used in this study, as well as additional statistical analysis of this study.

In the result, we have adding the report of the descriptive statistical, and ANOVA analysis based on the suggestion by reviewer.

In the discussion, we have adding the limitation of the study, and mention of hypothesis based on the suggestion by reviewer.

Finally, we appreciate the reviewers' constructive feedback and hope that our revisions adequately address your concerns.

Thank you for considering our revised manuscript. We look forward to hearing from you.

Sincerely,
Authors

Reviewer 2

Dear Authors
There are certain comments/ queries / suggestions with respect to this manuscript. Please address them to improve upon the manuscript.

The title of the manuscript does not reflect the main objective and results presented in the manuscript.

Answer: Thank you very much for your kind suggestion. The title has been changed to “The Impact of Smartphone Addiction on Reaction Time in Undergraduate Students: An Experimental Study”

"In this study, we examined the features of smartphone addiction in adolescents aged 18 to 22 years" - there is no result presented with respect to this objective in the study. Also, adolescent age group does not include people 20 or above as per the World Health Organization definition. If some other operational definition has been used, please cite the source.

Answer: Thank you very much for your kind comment. For more accurately in the word “adolescent” used in this study, we have explained the definition of the word “adolescent” and “undergraduate”, as well as the overlappint in the age of both words in the introduction section as follows:

“Meanwhile some of the individuals who are predominant smartphone users are adolescents. Adolescence, as delineated by developmental psychology and esteemed organizations such as the World Health Organization (WHO), covers from early adolescence to late adolescence. In many definitions, it may also comprise young adults up to the age of 19 or even stretch into the early 20s. Undergraduates, in contrast, refer to those who are actively pursuing a bachelor's degree at a college or university. The terms 'undergraduate' and 'adolescent' refer to separate facets of an individual's existence. Although there are variations, there is a significant convergence in the normal age range linked to each. Adolescence, as per developmental psychology and organizations such the World Health Organization (WHO), refers to the period from early to late teens and may even include young adults up to the age of 19 or even early 20s in certain definitions. Most undergraduates commence their tertiary studies promptly after finishing secondary education, usually at approximately 18 or 19 years old. As a result, a significant proportion of college students are in the late adolescent stage.”

For more accuraltely understandble, we have edited the objective in this study with a word of “undergraduate” instead of “adolescent” as follows:

“The increasing significance of smartphones in everyday life, particularly among undergraduate student aged 18 to 22, emphasizes the delicate link between technology use and mental well-being. The objective of this study is to explore the impact of smartphone addiction on cognitive abilities, particularly reaction times, and to analyze the psychosocial repercussions of excessive smartphone usage. This initial investigation primarily examines the direct influence of smartphone addiction on reaction times while also recognizing the potential involvement of several risk factors.”

Fig 1 does not correspond to flowchart as the claim is made in the text in results section. In any case participant recruitment flowchart should be included in the methods section (when you put the correct figure in the manuscript).

Answer: Thank you very much for your comment. We have added the new flow chart figure in the manuscript as follows:

Figure 1 Flowchart of inclusion participants

The number of exclusions seems to be too large. What were the reasons to exclude all participants for myopia, impaired vision - were they still excluded if they were either corrected with glasses or were only of mild degree in nature?

Answer: Thank you very much for your comment. In this study, participants with myopia and impaired vision from certain studies, especially those focusing on cognitive tasks, reaction times, or visual processing, were excluded for several reasons. Firstly, we need to control our visual acuity. Since this study relies heavily on visual stimuli aims to ensure that all participants have a similar baseline for visual acuity to reduce variability in response times or accuracy that could be attributed to differences in vision rather than the cognitive or behavioral variable being studied. This issue was discussed by Bach (1996) who revealed the importance of accurately measuring visual acuity in research settings and how variations in acuity can affect the reliability of visual assessments. At the same time, we are concerned about the impact on reaction times. Since this study measures reaction times to visual stimuli, variations in vision clarity could introduce significant confounders, as those with uncorrected visual impairments might inherently respond more slowly or inaccurately. This issue was reported by Strang et al., (1999) who illustrate that even mild visual impairments can significantly impact the speed and accuracy of visual processing, thereby supporting the rationale for controlling visual acuity in studies where reaction time is a critical measure.

We have also added this explaination in the subsection of Participant in the Methodology section.

Ref:

Strang, N. C., Atchison, D. A., & Woods, R. L. (1999). Effects of defocus and pupil size on human reaction time. Journal of the Optical Society of America A, 16(3), 412-418.

Bach, M. (1996). The Freiburg Visual Acuity test-automatic measurement of visual acuity. Optometry and Vision Science, 73(1), 49-53.
Dear Reviewer,

We appreciate the opportunity to revise our manuscript entitled " Smartphone used and social media addiction in undergraduate student" and would like to thank the reviewers for their insightful comments and suggestions. We have carefully considered each point and have made substantial revisions to our manuscript (as seen in Track Change). Since many of the texts in the revised manuscript have been edited to cover all comments/suggestion, we have listed the overall changes in the revised version of the manuscript for more understanding in brief as follows:

In the title, it has been changed from " Smartphone used and social media addiction in undergraduate student" to “The Impact of Smartphone Addiction on Reaction Time in Undergraduate Students: An Experimental Study”

In the introduction, we have inserted many of texts in this section for more correspondingly to the point of the objective in study.

In the methodology, we have also inserted and revisde many of texts in this section based on the suggestions/comments from all reviewers such as the flowchart of the study, explanation of the exclusion criteria, type of RT used in this study, as well as additional statistical analysis of this study.

In the result, we have adding the report of the descriptive statistical, and ANOVA analysis based on the suggestion by reviewer.

In the discussion, we have adding the limitation of the study, and mention of hypothesis based on the suggestion by reviewer.

Finally, we appreciate the reviewers' constructive feedback and hope that our revisions adequately address your concerns.

Thank you for considering our revised manuscript. We look forward to hearing from you.

Sincerely,
Authors

Reviewer 2

Dear Authors
There are certain comments/ queries / suggestions with respect to this manuscript. Please address them to improve upon the manuscript.

The title of the manuscript does not reflect the main objective and results presented in the manuscript.

Answer: Thank you very much for your kind suggestion. The title has been changed to “The Impact of Smartphone Addiction on Reaction Time in Undergraduate Students: An Experimental Study”

"In this study, we examined the features of smartphone addiction in adolescents aged 18 to 22 years" - there is no result presented with respect to this objective in the study. Also, adolescent age group does not include people 20 or above as per the World Health Organization definition. If some other operational definition has been used, please cite the source.

Answer: Thank you very much for your kind comment. For more accurately in the word “adolescent” used in this study, we have explained the definition of the word “adolescent” and “undergraduate”, as well as the overlappint in the age of both words in the introduction section as follows:

“Meanwhile some of the individuals who are predominant smartphone users are adolescents. Adolescence, as delineated by developmental psychology and esteemed organizations such as the World Health Organization (WHO), covers from early adolescence to late adolescence. In many definitions, it may also comprise young adults up to the age of 19 or even stretch into the early 20s. Undergraduates, in contrast, refer to those who are actively pursuing a bachelor's degree at a college or university. The terms 'undergraduate' and 'adolescent' refer to separate facets of an individual's existence. Although there are variations, there is a significant convergence in the normal age range linked to each. Adolescence, as per developmental psychology and organizations such the World Health Organization (WHO), refers to the period from early to late teens and may even include young adults up to the age of 19 or even early 20s in certain definitions. Most undergraduates commence their tertiary studies promptly after finishing secondary education, usually at approximately 18 or 19 years old. As a result, a significant proportion of college students are in the late adolescent stage.”

For more accuraltely understandble, we have edited the objective in this study with a word of “undergraduate” instead of “adolescent” as follows:

“The increasing significance of smartphones in everyday life, particularly among undergraduate student aged 18 to 22, emphasizes the delicate link between technology use and mental well-being. The objective of this study is to explore the impact of smartphone addiction on cognitive abilities, particularly reaction times, and to analyze the psychosocial repercussions of excessive smartphone usage. This initial investigation primarily examines the direct influence of smartphone addiction on reaction times while also recognizing the potential involvement of several risk factors.”

Fig 1 does not correspond to flowchart as the claim is made in the text in results section. In any case participant recruitment flowchart should be included in the methods section (when you put the correct figure in the manuscript).

Answer: Thank you very much for your comment. We have added the new flow chart figure in the manuscript as follows:

Figure 1 Flowchart of inclusion participants

The number of exclusions seems to be too large. What were the reasons to exclude all participants for myopia, impaired vision - were they still excluded if they were either corrected with glasses or were only of mild degree in nature?

Answer: Thank you very much for your comment. In this study, participants with myopia and impaired vision from certain studies, especially those focusing on cognitive tasks, reaction times, or visual processing, were excluded for several reasons. Firstly, we need to control our visual acuity. Since this study relies heavily on visual stimuli aims to ensure that all participants have a similar baseline for visual acuity to reduce variability in response times or accuracy that could be attributed to differences in vision rather than the cognitive or behavioral variable being studied. This issue was discussed by Bach (1996) who revealed the importance of accurately measuring visual acuity in research settings and how variations in acuity can affect the reliability of visual assessments. At the same time, we are concerned about the impact on reaction times. Since this study measures reaction times to visual stimuli, variations in vision clarity could introduce significant confounders, as those with uncorrected visual impairments might inherently respond more slowly or inaccurately. This issue was reported by Strang et al., (1999) who illustrate that even mild visual impairments can significantly impact the speed and accuracy of visual processing, thereby supporting the rationale for controlling visual acuity in studies where reaction time is a critical measure.

We have also added this explaination in the subsection of Participant in the Methodology section.

Ref:

Strang, N. C., Atchison, D. A., & Woods, R. L. (1999). Effects of defocus and pupil size on human reaction time. Journal of the Optical Society of America A, 16(3), 412-418.

Bach, M. (1996). The Freiburg Visual Acuity test-automatic measurement of visual acuity. Optometry and Vision Science, 73(1), 49-53.
Competing Interests: The authors declares no competing of interests. Close
Report a concern
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COMMENTS ON THIS REPORT

Author Response 13 Apr 2024

Teerachai Amnuaylojaroen, School of Energy and Environment, University of Phayao, Phayao, 56000, Thailand

13 Apr 2024

Author Response
Dear Reviewer,

We appreciate the opportunity to revise our manuscript entitled " Smartphone used and social media addiction in undergraduate student" and would like to thank the reviewers for ... Continue reading
Dear Reviewer,

We appreciate the opportunity to revise our manuscript entitled " Smartphone used and social media addiction in undergraduate student" and would like to thank the reviewers for their insightful comments and suggestions. We have carefully considered each point and have made substantial revisions to our manuscript (as seen in Track Change). Since many of the texts in the revised manuscript have been edited to cover all comments/suggestion, we have listed the overall changes in the revised version of the manuscript for more understanding in brief as follows:

In the title, it has been changed from " Smartphone used and social media addiction in undergraduate student" to “The Impact of Smartphone Addiction on Reaction Time in Undergraduate Students: An Experimental Study”

In the introduction, we have inserted many of texts in this section for more correspondingly to the point of the objective in study.

In the methodology, we have also inserted and revisde many of texts in this section based on the suggestions/comments from all reviewers such as the flowchart of the study, explanation of the exclusion criteria, type of RT used in this study, as well as additional statistical analysis of this study.

In the result, we have adding the report of the descriptive statistical, and ANOVA analysis based on the suggestion by reviewer.

In the discussion, we have adding the limitation of the study, and mention of hypothesis based on the suggestion by reviewer.

Finally, we appreciate the reviewers' constructive feedback and hope that our revisions adequately address your concerns.

Thank you for considering our revised manuscript. We look forward to hearing from you.

Sincerely,
Authors

Reviewer 2

Dear Authors
There are certain comments/ queries / suggestions with respect to this manuscript. Please address them to improve upon the manuscript.

The title of the manuscript does not reflect the main objective and results presented in the manuscript.

Answer: Thank you very much for your kind suggestion. The title has been changed to “The Impact of Smartphone Addiction on Reaction Time in Undergraduate Students: An Experimental Study”

"In this study, we examined the features of smartphone addiction in adolescents aged 18 to 22 years" - there is no result presented with respect to this objective in the study. Also, adolescent age group does not include people 20 or above as per the World Health Organization definition. If some other operational definition has been used, please cite the source.

Answer: Thank you very much for your kind comment. For more accurately in the word “adolescent” used in this study, we have explained the definition of the word “adolescent” and “undergraduate”, as well as the overlappint in the age of both words in the introduction section as follows:

“Meanwhile some of the individuals who are predominant smartphone users are adolescents. Adolescence, as delineated by developmental psychology and esteemed organizations such as the World Health Organization (WHO), covers from early adolescence to late adolescence. In many definitions, it may also comprise young adults up to the age of 19 or even stretch into the early 20s. Undergraduates, in contrast, refer to those who are actively pursuing a bachelor's degree at a college or university. The terms 'undergraduate' and 'adolescent' refer to separate facets of an individual's existence. Although there are variations, there is a significant convergence in the normal age range linked to each. Adolescence, as per developmental psychology and organizations such the World Health Organization (WHO), refers to the period from early to late teens and may even include young adults up to the age of 19 or even early 20s in certain definitions. Most undergraduates commence their tertiary studies promptly after finishing secondary education, usually at approximately 18 or 19 years old. As a result, a significant proportion of college students are in the late adolescent stage.”

For more accuraltely understandble, we have edited the objective in this study with a word of “undergraduate” instead of “adolescent” as follows:

“The increasing significance of smartphones in everyday life, particularly among undergraduate student aged 18 to 22, emphasizes the delicate link between technology use and mental well-being. The objective of this study is to explore the impact of smartphone addiction on cognitive abilities, particularly reaction times, and to analyze the psychosocial repercussions of excessive smartphone usage. This initial investigation primarily examines the direct influence of smartphone addiction on reaction times while also recognizing the potential involvement of several risk factors.”

Fig 1 does not correspond to flowchart as the claim is made in the text in results section. In any case participant recruitment flowchart should be included in the methods section (when you put the correct figure in the manuscript).

Answer: Thank you very much for your comment. We have added the new flow chart figure in the manuscript as follows:

Figure 1 Flowchart of inclusion participants

The number of exclusions seems to be too large. What were the reasons to exclude all participants for myopia, impaired vision - were they still excluded if they were either corrected with glasses or were only of mild degree in nature?

Answer: Thank you very much for your comment. In this study, participants with myopia and impaired vision from certain studies, especially those focusing on cognitive tasks, reaction times, or visual processing, were excluded for several reasons. Firstly, we need to control our visual acuity. Since this study relies heavily on visual stimuli aims to ensure that all participants have a similar baseline for visual acuity to reduce variability in response times or accuracy that could be attributed to differences in vision rather than the cognitive or behavioral variable being studied. This issue was discussed by Bach (1996) who revealed the importance of accurately measuring visual acuity in research settings and how variations in acuity can affect the reliability of visual assessments. At the same time, we are concerned about the impact on reaction times. Since this study measures reaction times to visual stimuli, variations in vision clarity could introduce significant confounders, as those with uncorrected visual impairments might inherently respond more slowly or inaccurately. This issue was reported by Strang et al., (1999) who illustrate that even mild visual impairments can significantly impact the speed and accuracy of visual processing, thereby supporting the rationale for controlling visual acuity in studies where reaction time is a critical measure.

We have also added this explaination in the subsection of Participant in the Methodology section.

Ref:

Strang, N. C., Atchison, D. A., & Woods, R. L. (1999). Effects of defocus and pupil size on human reaction time. Journal of the Optical Society of America A, 16(3), 412-418.

Bach, M. (1996). The Freiburg Visual Acuity test-automatic measurement of visual acuity. Optometry and Vision Science, 73(1), 49-53.
Dear Reviewer,

We appreciate the opportunity to revise our manuscript entitled " Smartphone used and social media addiction in undergraduate student" and would like to thank the reviewers for their insightful comments and suggestions. We have carefully considered each point and have made substantial revisions to our manuscript (as seen in Track Change). Since many of the texts in the revised manuscript have been edited to cover all comments/suggestion, we have listed the overall changes in the revised version of the manuscript for more understanding in brief as follows:

In the title, it has been changed from " Smartphone used and social media addiction in undergraduate student" to “The Impact of Smartphone Addiction on Reaction Time in Undergraduate Students: An Experimental Study”

In the introduction, we have inserted many of texts in this section for more correspondingly to the point of the objective in study.

In the methodology, we have also inserted and revisde many of texts in this section based on the suggestions/comments from all reviewers such as the flowchart of the study, explanation of the exclusion criteria, type of RT used in this study, as well as additional statistical analysis of this study.

In the result, we have adding the report of the descriptive statistical, and ANOVA analysis based on the suggestion by reviewer.

In the discussion, we have adding the limitation of the study, and mention of hypothesis based on the suggestion by reviewer.

Finally, we appreciate the reviewers' constructive feedback and hope that our revisions adequately address your concerns.

Thank you for considering our revised manuscript. We look forward to hearing from you.

Sincerely,
Authors

Reviewer 2

Dear Authors
There are certain comments/ queries / suggestions with respect to this manuscript. Please address them to improve upon the manuscript.

The title of the manuscript does not reflect the main objective and results presented in the manuscript.

Answer: Thank you very much for your kind suggestion. The title has been changed to “The Impact of Smartphone Addiction on Reaction Time in Undergraduate Students: An Experimental Study”

"In this study, we examined the features of smartphone addiction in adolescents aged 18 to 22 years" - there is no result presented with respect to this objective in the study. Also, adolescent age group does not include people 20 or above as per the World Health Organization definition. If some other operational definition has been used, please cite the source.

Answer: Thank you very much for your kind comment. For more accurately in the word “adolescent” used in this study, we have explained the definition of the word “adolescent” and “undergraduate”, as well as the overlappint in the age of both words in the introduction section as follows:

“Meanwhile some of the individuals who are predominant smartphone users are adolescents. Adolescence, as delineated by developmental psychology and esteemed organizations such as the World Health Organization (WHO), covers from early adolescence to late adolescence. In many definitions, it may also comprise young adults up to the age of 19 or even stretch into the early 20s. Undergraduates, in contrast, refer to those who are actively pursuing a bachelor's degree at a college or university. The terms 'undergraduate' and 'adolescent' refer to separate facets of an individual's existence. Although there are variations, there is a significant convergence in the normal age range linked to each. Adolescence, as per developmental psychology and organizations such the World Health Organization (WHO), refers to the period from early to late teens and may even include young adults up to the age of 19 or even early 20s in certain definitions. Most undergraduates commence their tertiary studies promptly after finishing secondary education, usually at approximately 18 or 19 years old. As a result, a significant proportion of college students are in the late adolescent stage.”

For more accuraltely understandble, we have edited the objective in this study with a word of “undergraduate” instead of “adolescent” as follows:

“The increasing significance of smartphones in everyday life, particularly among undergraduate student aged 18 to 22, emphasizes the delicate link between technology use and mental well-being. The objective of this study is to explore the impact of smartphone addiction on cognitive abilities, particularly reaction times, and to analyze the psychosocial repercussions of excessive smartphone usage. This initial investigation primarily examines the direct influence of smartphone addiction on reaction times while also recognizing the potential involvement of several risk factors.”

Fig 1 does not correspond to flowchart as the claim is made in the text in results section. In any case participant recruitment flowchart should be included in the methods section (when you put the correct figure in the manuscript).

Answer: Thank you very much for your comment. We have added the new flow chart figure in the manuscript as follows:

Figure 1 Flowchart of inclusion participants

The number of exclusions seems to be too large. What were the reasons to exclude all participants for myopia, impaired vision - were they still excluded if they were either corrected with glasses or were only of mild degree in nature?

Answer: Thank you very much for your comment. In this study, participants with myopia and impaired vision from certain studies, especially those focusing on cognitive tasks, reaction times, or visual processing, were excluded for several reasons. Firstly, we need to control our visual acuity. Since this study relies heavily on visual stimuli aims to ensure that all participants have a similar baseline for visual acuity to reduce variability in response times or accuracy that could be attributed to differences in vision rather than the cognitive or behavioral variable being studied. This issue was discussed by Bach (1996) who revealed the importance of accurately measuring visual acuity in research settings and how variations in acuity can affect the reliability of visual assessments. At the same time, we are concerned about the impact on reaction times. Since this study measures reaction times to visual stimuli, variations in vision clarity could introduce significant confounders, as those with uncorrected visual impairments might inherently respond more slowly or inaccurately. This issue was reported by Strang et al., (1999) who illustrate that even mild visual impairments can significantly impact the speed and accuracy of visual processing, thereby supporting the rationale for controlling visual acuity in studies where reaction time is a critical measure.

We have also added this explaination in the subsection of Participant in the Methodology section.

Ref:

Strang, N. C., Atchison, D. A., & Woods, R. L. (1999). Effects of defocus and pupil size on human reaction time. Journal of the Optical Society of America A, 16(3), 412-418.

Bach, M. (1996). The Freiburg Visual Acuity test-automatic measurement of visual acuity. Optometry and Vision Science, 73(1), 49-53.
Competing Interests: The authors declares no competing of interests. Close
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Reviewer Report 12 Jul 2023

Richard J. E. James, University of Nottingham, Nottingham, England, UK

Not Approved

https://doi.org/10.5256/f1000research.141145.r175532

This study reports the findings of an experimental study into the relationship between smartphone addiction, defined by cutoffs on the Thai translation of the SAS-SV, and reaction time performance on a dual task paradigm. No differences were found between the SA groups on task performance. I liked the use of an experimental design, and that the data was made publicly available. However, there are a number of issues with the manuscript as it presently stands, outlined below. In particular, I found the lack of hypotheses, issues with some methodological details, and conceptualizations of smartphone addiction affected the overall soundness of the manuscript, but these can be addressed with revisions. My comments are outlined below:

The title includes reference to social media addiction, but this does not appear to be measured in the study. Social media use is included as an inclusion criteria, but the study is not measuring social media addiction.
There are some points where conceptualizations of behavioral addictions are a bit unclear. For instance, at the bottom of the first paragraph, the references for the claim that individuals with smartphone addiction endure various challenges are two papers on problematic internet use from the late 1990s. I think more specific and relevant evidence could be incorporated here.
Similarly in the second paragraph there are number of claims made about the severity of smartphone addiction that are open for debate. There is a critical literature that has highlighted many of the issues with the measurement of smartphone addiction, how it relates to other behavioural addictions (e.g. if somebody is using their phone extensively for social media use, do they have a smartphone, or a social media addiction?), and whether this translates into clinically meaningful levels of harm.
Again, some of the claims regarding smartphone addiction and adolescence are again debatable. The claim they are inextricably linked, and consider it to be a 'second personality' are particularly questionable. The vast majority of the literature samples adolescents and university students, and so this may be biased by the lack of research compared to other groups.
The final paragraph starts discussing social comparison, but it wasn't entirely clear how this related to the manuscript, and whether it ought to be included.
The introduction didn't introduce the rationale for the use of the dual tasking design, which I thought was a notable oversight that ought to be amended. No hypotheses were presented about the relationship between performance on the dual performance task and smartphone addiction - would one expect people with elevated levels of smartphone addiction severity to be faster or slower on the task?
The introduction also makes reference to comparing risk variables for smartphone addiction, but this doesn't seem to be reported in the results.
I appreciate that the authors' have conducted a power analysis to justify their sample size. However, my reading of this section is that the study is powered for the experimental effect (i.e. between the control, texting and calling conditions), and not any putative smartphone addiction effect. Therefore, it is not clear whether the data is appropriately powered for the effects the authors are trying to test. I suspect the study is underpowered for the purpose of testing any such effect. This should be included as a limitation.
The reporting of reaction times could be streamlined, and easier to follow for readers. For instance, I wasn't clear on the need for the distinction between the three different types of RT.
More details regarding of the statistical analysis ought to be reported. To me, the analysis conducted look like 3 sets of addiction vs. non-addiction group analyses for each condition, but this is not clear from the information presented. I think the type of analysis could be reported, as could the test statistics and a measure of error.
Hypotheses are only mentioned for the first time at the beginning of the discussion.
The discussion was unclear in places. The second half of the first paragraph starts discussing findings about the amount of smartphone use per session, but this isn't reported elsewhere in the manuscript. This was reported as being collected in the survey included with the data, but the methods talk about a different interview. The methods could be amended to make these passages clearer.

Is the work clearly and accurately presented and does it cite the current literature?

Partly
Is the study design appropriate and is the work technically sound?

Partly
Are sufficient details of methods and analysis provided to allow replication by others?

Yes
If applicable, is the statistical analysis and its interpretation appropriate?

Partly
Are all the source data underlying the results available to ensure full reproducibility?

Yes
Are the conclusions drawn adequately supported by the results?

Partly

Competing Interests: No competing interests were disclosed.

Reviewer Expertise: Gambling, behavioural addiction, smartphone addiction

CITE

Report a concern

Author Response 13 Apr 2024

Teerachai Amnuaylojaroen, School of Energy and Environment, University of Phayao, Phayao, 56000, Thailand

13 Apr 2024

Author Response
Dear Reviewer,

We appreciate the opportunity to revise our manuscript entitled " Smartphone used and social media addiction in undergraduate student" and would like to thank the reviewers for ... Continue reading
Dear Reviewer,

We appreciate the opportunity to revise our manuscript entitled " Smartphone used and social media addiction in undergraduate student" and would like to thank the reviewers for their insightful comments and suggestions. We have carefully considered each point and have made substantial revisions to our manuscript (as seen in Track Change). Since many of the texts in the revised manuscript have been edited to cover all comments/suggestion, we have listed the overall changes in the revised version of the manuscript for more understanding in brief as follows:

In the title, it has been changed from " Smartphone used and social media addiction in undergraduate student" to “The Impact of Smartphone Addiction on Reaction Time in Undergraduate Students: An Experimental Study”

In the introduction, we have inserted many of texts in this section for more correspondingly to the point of the objective in study.

In the methodology, we have also inserted and revisde many of texts in this section based on the suggestions/comments from all reviewers such as the flowchart of the study, explanation of the exclusion criteria, type of RT used in this study, as well as additional statistical analysis of this study.

In the result, we have adding the report of the descriptive statistical, and ANOVA analysis based on the suggestion by reviewer.

In the discussion, we have adding the limitation of the study, and mention of hypothesis based on the suggestion by reviewer.

Finally, we appreciate the reviewers' constructive feedback and hope that our revisions adequately address your concerns.

Thank you for considering our revised manuscript. We look forward to hearing from you.

Sincerely,
Authors

Reviewer 1

This study reports the findings of an experimental study into the relationship between smartphone addiction, defined by cutoffs on the Thai translation of the SAS-SV, and reaction time performance on a dual task paradigm. No differences were found between the SA groups on task performance. I liked the use of an experimental design, and that the data was made publicly available. However, there are a number of issues with the manuscript as it presently stands, outlined below. In particular, I found the lack of hypotheses, issues with some methodological details, and conceptualizations of smartphone addiction affected the overall soundness of the manuscript, but these can be addressed with revisions. My comments are outlined below:

The title includes reference to social media addiction, but this does not appear to be measured in the study. Social media use is included as an inclusion criteria, but the study is not measuring social media addiction.

Answer: Thank you very much for your kind suggestion. The title has been changed to “The Impact of Smartphone Addiction on Reaction Time in Undergraduate Students: An Experimental Study”

There are some points where conceptualizations of behavioral addictions are a bit unclear. For instance, at the bottom of the first paragraph, the references for the claim that individuals with smartphone addiction endure various challenges are two papers on problematic internet use from the late 1990s. I think more specific and relevant evidence could be incorporated here.

Answer: Thank you very much for your kind suggestion. At the first paragraph in the introduction section, we have added some statements for more specific and relevant evidences as follows:

“Prolonged use of smartphones exposes individuals to several detrimental physical and psychological effects. For example, dry eyes, carpal tunnel syndrome, repetitive strain injury, wrist, neck, back, and shoulder pain, migraine headaches, thumb, index, and middle finger pain, and phantom pocket vibration syndrome are physical symptoms associated with smartphone addiction.^{4 ,} ⁵ (AlBarashdi et al., 2016; Sebastian & Jinesh, 2018)."

Similarly in the second paragraph there are number of claims made about the severity of smartphone addiction that are open for debate. There is a critical literature that has highlighted many of the issues with the measurement of smartphone addiction, how it relates to other behavioural addictions (e.g. if somebody is using their phone extensively for social media use, do they have a smartphone, or a social media addiction?), and whether this translates into clinically meaningful levels of harm.

Answer: Thank you very much for your kind suggestion. At the second paragraph, in the introduction section, we have inserted some statements for the issues of smartphone addiction realted to several detrimental psychological impacts as follows:

“It has also been found to have detrimental psychological impacts¹⁶(Kuss & Griffiths, 2011). Excessive use of smartphones negatively affects the quality of students' sleep ^{17 ,} ^{18, 19}^{, 20,} (Ibrahim et al., 2018; Kurugodiyavar et al., 2017; Sahin et al., 2013; Wang et al., 2019) and result in insomnia ²¹(Van Deursen et al., 2015). Many studies have established a correlation between smartphone usage and mental disorders, such as stress and anxiety ²² (Boumosleh & Jaalouk, 2017). Other potential adverse consequences include loss of control ²³(Gupta et al., 2016) and maladaptive behavioral problems ²⁴ (Hwang et al., 2012). Smartphone addiction has a poor correlation with both life satisfaction and performance in school ²⁵(Samaha & Hawi, 2016).”

Again, some of the claims regarding smartphone addiction and adolescence are again debatable. The claim they are inextricably linked, and consider it to be a 'second personality' are particularly questionable. The vast majority of the literature samples adolescents and university students, and so this may be biased by the lack of research compared to other groups.

Answer: We acknowledge the focus of existing research on adolescents and university students, highlighting this as a limitation and noting the potential for selection bias. This sets the stage for why your study is mindful of broader implications. We have inserted several texts to explain those as follows:

“A substantial amount of study has been devoted to the examination of smartphone addiction, with university students and adolescents serving as the primary cohorts for investigation (Kuss & Griffiths, 2011; Sahin et al., 2013). Although the emphasis has resulted in significant findings regarding the trends and repercussions of using smartphones among the youth population, it also presents the possibility of selection bias. The focus on younger age groups and life stages in this analysis of smartphone addiction might not encompass its intricacies (Ibrahim et al., 2018; Kurugodiyavar et al., 2017). In the context of this study's invalidity, this study seeks to contribute by examining the broader consequences associated with smartphone addiction. Through this approach, we aim to contribute to a more holistic comprehension of its ramifications, recognizing that the phenomenon of smartphone addiction transcends the conventional focus on adolescent and university students.”

The final paragraph starts discussing social comparison, but it wasn't entirely clear how this related to the manuscript, and whether it ought to be included.

Answer: Thank you very much for your kind comment. For more accurately related to the manuscript objective, we have revised the final paragraph in the introduction section as follows:

“The increasing significance of smartphones in everyday life, particularly among young adults aged 18 to 22, emphasizes the delicate link between technology use and mental well-being. The objective of this study is to explore the impact of smartphone addiction on cognitive abilities, particularly reaction times, and to analyze the psychosocial repercussions of excessive smartphone usage. This initial investigation primarily examines the direct influence of smartphone addiction on reaction times while also recognizing the potential involvement of several risk factors.”

The introduction didn't introduce the rationale for the use of the dual tasking design, which I thought was a notable oversight that ought to be amended. No hypotheses were presented about the relationship between performance on the dual performance task and smartphone addiction - would one expect people with elevated levels of smartphone addiction severity to be faster or slower on the task?

Answer: Thank you very much for your kind comment. We have added a paragraph for the rationale for the use of the dual tasking in the introduction sectoion as follows:

“Dual-tasking refers to the act of executing two activities simultaneously, whereas multitasking refers to the act of performing more than two tasks simultaneously³⁴(Won et al., 2012). Engaging in activities such as walking or working while simultaneously utilizing various features of a smartphone can be referred to as dual- or multitasking. Nevertheless, engaging in multiple tasks simultaneously can potentially result in a loss of cognitive capacity, hence increasing the risk of experiencing a fall or injury in an unforeseen and unintentional circumstance. The capacity to sustain equilibrium in both stationary and moving scenarios serves as the foundation for executing functional tasks during the course of diverse routine activities ³⁵(Vuillerme et al., 2002). The functional activities requiring dynamic balance are achieved by the coordinated interplay of the ankle joints, knee joints, hip joints, and their respective accompanying muscles, as well as the shoulder joints and their surrounding muscles. Cognitive ability is closely linked to dynamic balance. Engaging in dual-tasking with a smartphone while walking, such as listening to music, sending a message, online surfing, or playing a game, is known to impair the dynamic balance required for functional activities by diminishing cognitive capacity. The act of using a mobile phone while walking is a common scenario known as a dual-task paradigm ³⁶(Plummer et al., 2013). This means that individuals are required to concurrently engage in mobile phone operations and walking duties. The notion of finite capacity scheduling suggests that the outcome of different activities determines the extent to which cognitive or motor performance is affected ^37,38(Coker, 2017; Wickens and Damos, 2020). The mobile phone task involves integrating numerous single activities, such as mathematics, language, memory, and motor skills, while walking, as opposed to doing a single task individually. The demand for cognitive resources in this activity is notably higher compared to other simpler activities ³⁹(Tan et al., 2022). Prior research has demonstrated that engaging in the dual-task paradigm of using a mobile phone while walking is more prone to inducing diminished awareness of the environment, impaired motor function in the lower extremities, and distraction compared to other uncomplicated tasks performed while walking among pedestrians ^40,⁴¹(Kim et al., 2020; Tan et al., 2022).”

The introduction also makes reference to comparing risk variables for smartphone addiction, but this doesn't seem to be reported in the results.

Answer: Thank you very much for you comment. For more correspondly to the main objective of the study that is to examine the effect of smartphone addiction on reaction times, not comparing the risk variable to the smartphone addiction. We have revised the introduction appropriately.

I appreciate that the authors' have conducted a power analysis to justify their sample size. However, my reading of this section is that the study is powered for the experimental effect (i.e. between the control, texting and calling conditions), and not any putative smartphone addiction effect. Therefore, it is not clear whether the data is appropriately powered for the effects the authors are trying to test. I suspect the study is underpowered for the purpose of testing any such effect. This should be included as a limitation.

Answer: Thank you very much for you kind comment. We have added a paragraph of the limitation in study in the last paragraph of the discussion section as follows:

“Although this study utilized a careful methodology, which involved conducting a power analysis to determine the required sample size for detecting variations in reaction times under control, texting, and calling conditions, it is crucial to acknowledge a potential limitation in our examination of the impacts of smartphone addiction. The initial power analysis was primarily intended to ensure an adequate sample size for detecting the experimental effects of dual-tasking conditions. However, it may not have been properly adjusted to accurately identify the more subtle but important influence of different levels of smartphone addiction on these cognitive tasks. After careful consideration, we acknowledge that the study may not have enough statistical power to definitively investigate the subtle impacts that the intensity of smartphone addiction may have on individuals' performance in these activities. This constraint implies that the conclusions on smartphone addiction should be approached with care since the study could not have possessed sufficient statistical strength to identify all significant effects linked to the intensity of smartphone addiction. Subsequent investigations in this field would be enhanced by performing a power analysis particularly designed to evaluate the impact of smartphone addiction. This may involve increasing the sample size or employing a more precise measure of addiction intensity. It is essential to overcome this constraint in order to enhance our comprehension of the cognitive consequences of smartphone addiction and to create specific therapies to reduce its negative impacts. Regarding the results and the original hypotheses of this investigation, further research should explore in greater detail the subtle mechanisms by which extended smartphone usage impacts cognitive functions. Conducting research on auditory reaction times and expanding the study to include various age groups could yield a more comprehensive comprehension of the cognitive consequences associated with smartphone addiction. Furthermore, future research should investigate the possible task-specific cognitive adjustments in those who use smartphones frequently, which could help reduce the anticipated detrimental impacts on dual-task performance.”

The reporting of reaction times could be streamlined, and easier to follow for readers. For instance, I wasn't clear on the need for the distinction between the three different types of RT.

Answer: Thank you very much for your suggestion. For clear understanding to the reader, we have inserted several texts indicating specifically RT’ type in the subsection of Measurement in Methodology section as follows:

“In this study, Choice RT involves multiple stimuli and multiple responses, which directly corresponds to the setup of the study where participants respond to different colored lights with different buttons. The need to recognize the color of the light and choose the correct button to press makes it a choice reaction time task, as there are several stimuli (different colors) and several possible responses (different buttons).
This study focuses on the evaluation of reaction times (RT) as a method for measuring the rate at which an individual reacts to a stimuli. It is crucial to specify that the specific sort of reaction time we are emphasizing is referred to as 'Choice RT.' The relevance of this particular type of reaction time lies in the fact that participants are presented with various stimuli and are required to make a deliberate choice on the appropriate response to carry out.
In further detail, Choice RT scenarios are distinguished by the existence of multiple potential stimuli, each necessitating a separate and specific reaction. Our experimental setup involves presenting participants with lights of varying hues, specifically red, blue, and yellow. Participants are required to hit a designated button for each color. This choice element distinguishes it from 'Simple RT,' which involves a single stimulus and automatic reaction, and from 'Recognition RT,' where the aim is to respond to certain stimuli while ignoring others.

More details regarding of the statistical analysis ought to be reported. To me, the analysis conducted look like 3 sets of addiction vs. non-addiction group analyses for each condition, but this is not clear from the information presented. I think the type of analysis could be reported, as could the test statistics and a measure of error.

Answer: We acknownledge for the additional statistical analysis. We have added a couple paragraph to report the statistical analysis with descriptive statistical and ANOVA analysis in the results section as follows:

“Analyzing the reaction times under different smartphone usage situations reveals clear trends for persons with and without addiction in Table 4. The non- addiction group exhibited the shortest average reaction time of 0.99 seconds after avoiding from smartphone usage. The results also showed a relatively narrow range of values, as evidenced by the standard deviation of 0.28 seconds. Participating in phone conversations increased response time to an average of 1.22 seconds, while the variation remained similar to the condition when no phone was used. Nevertheless, the texting activity showed the most notable increase, with an average response time of 1.73 seconds and a significantly larger standard deviation, indicating more variation in how texting impacted the reaction times of persons in this particular group. In comparison, the addiction group exhibited a slightly higher initial response time of 1.04 seconds when not using smartphones, while the range of values was narrower. The effect of phone calls was particularly noticeable among those with addiction, as their average response time increased to 1.309 seconds and was accompanied by a higher standard deviation, indicating a larger variation in response times among individuals. The "Addiction" group also saw a comparable impact from texting, with an average reaction time of 1.74 seconds and the largest level of variability across all conditions, as demonstrated by the standard deviation. Reaction times consistently increased in both groups as they transitioned from avoiding smartphones to texting. Although the "Addiction" group had somewhat greater average reaction times in every situation, their reaction times were more consistent under the no-use condition compared to the "No addiction" group. The 95% confidence intervals for the "Addiction" group exhibited higher values, indicating a potential association between addiction and longer reaction times. However, the overlapping intervals of the two groups suggest that the difference in reaction times between the two groups is not significant. In summary, the descriptive statistics reveal a noticeable pattern of longer reaction times linked to the usage of smartphones, particularly for tasks that demand more cognitive effort, such as texting.
The ANOVA analysis in Table 5 showed that those without addiction had an F-statistic of 29.41 and a p-value of roughly < 0.001, which indicates high significance. This result demonstrates a statistically significant difference in response times when comparing the absence of smartphone usage, making phone calls, and sending text messages among individuals in this group. The inference is that the nature of smartphone engagement significantly impacts the response times of non-addicted persons, with certain activities resulting in slower reactions compared to others. Similarly, the analysis conducted for the "Addiction" group yielded an F-statistic of 23.18, along with a significant p-value of roughly < 0.001. This validates that, similar to the "No addiction" group, there are statistically significant disparities in reaction time among those with addiction across the three smartphone-using circumstances. The experimental conditions in which the reaction time was assessed (absence of smartphone usage, during a phone call, or while texting) significantly influenced the recorded reaction times. The notable F-statistics in both groups indicate that the change in reaction times is not consistent across conditions; rather, it fluctuates based on whether individuals were not utilizing their smartphones, were involved in a phone call, or were texting. The p-values, which are significantly lower than the typical alpha level of 0.05, provide strong evidence that the observed changes in reaction times are not a result of random chance but rather indicate a genuine impact of the smartphone use condition. These findings emphasize the significance of the circumstances in which smartphones are used when evaluating their influence on cognitive performance, specifically in terms of reaction time.
In summary, the descriptive statistics and ANOVA analyses provide a thorough understanding of how reaction times are affected by smartphone usage in different situations for persons with and without addiction. The descriptive statistics indicate that reaction times exhibit an upward trend as individuals transition from not using smartphones to making phone calls, and then to sending text messages, for both groups. The heightened fluctuation in reaction times seen while texting, as indicated by the greater standard deviations, implies that this task may necessitate additional cognitive resources, thereby exerting a more pronounced impact on reaction times. This pattern is consistent for both the non-addiction and addiction groups, although individuals with addiction exhibit somewhat faster reaction times overall. The one-way ANOVA results provide additional support for these findings, demonstrating statistically significant variations in reaction times among the three smartphone use circumstances within each group. The "No addiction" group's F-statistic and p-value suggest that various smartphone activities have a differential impact on reaction times. The addiction group likewise has a significant impact of smartphone use circumstances on reaction times, as evidenced by the ANOVA results.”

Hypotheses are only mentioned for the first time at the beginning of the discussion.

Answer: Thank you very much for your suggestion. We have recognized the mention of the hypothesis in the discussion, many texts have been inserted in the discussion section as follows:

“This study aims to investigate the influence of smartphone addiction on visual reaction time (VRT) in several settings, such as control, texting, and chatting situations, as hypothesized. The results of our study did not support our initial hypothesis, which suggested that those with higher degrees of smartphone addiction would have slower VRT due to cognitive overload. Specifically, we found no significant differences in VRT between the group of individuals with smartphone addiction and the control group, regardless of the settings. This result implies a more intricate relationship between smartphone addiction and cognitive performance than originally anticipated.”

“Although we hypothesized that regular smartphone use, which requires higher cognitive capacities, could hinder the ability to perform two tasks simultaneously, resulting in longer reaction times, the findings did not confirm this expectation. One potential reason for this surprising discovery could be attributed to the adaptive capacities of individuals who use smartphones frequently. The study found that social networking was the most popular smartphone application among those with addiction, and they used it for much longer periods of time compared to the control group. The significant involvement with smartphones may have resulted in a type of task-specific cognitive adjustment, allowing these individuals to retain similar VRTs as those who are less involved with smartphones.”

“The lack of significant disparities in VRT among the groups contradicts our initial assumptions and prompts a reassessment of the ways in which smartphone addiction impacts cognitive function. According to capacity theory and bottleneck accounts, we hypothesized that the dual-task interference would be more pronounced in those with smartphone addiction. Nevertheless, the comparable performance observed in both groups indicates that factors such as task prioritization and cognitive resource allocation likely have a substantial influence on moderating the impact of smartphone usage on attention and reaction times.”

The discussion was unclear in places. The second half of the first paragraph starts discussing findings about the amount of smartphone use per session, but this isn't reported elsewhere in the manuscript. This was reported as being collected in the survey included with the data, but the methods talk about a different interview. The methods could be amended to make these passages clearer.

Answer: Thank you very much for your comment. We have inserted many texts to make these passages clearer in the subsection of Procedure in the Methodology section as follows:

“Following the initial evaluation using the SAS-SV-TH, participants were monitored during different experimental sessions intended to replicate their usual smartphone usage. Every session was designed to simulate a practical setting for texting or talking, with a duration that nearly reflected their self-reported typical usage, which was around 30 minutes. In order to obtain a thorough understanding of everyday smartphone usage, participants were involved in multiple sessions of such nature throughout the day. This methodology enabled us to gather detailed information on the potential impact of extended and repetitive smartphone usage within a 24-hour period on reaction speeds.”
Dear Reviewer,

We appreciate the opportunity to revise our manuscript entitled " Smartphone used and social media addiction in undergraduate student" and would like to thank the reviewers for their insightful comments and suggestions. We have carefully considered each point and have made substantial revisions to our manuscript (as seen in Track Change). Since many of the texts in the revised manuscript have been edited to cover all comments/suggestion, we have listed the overall changes in the revised version of the manuscript for more understanding in brief as follows:

In the title, it has been changed from " Smartphone used and social media addiction in undergraduate student" to “The Impact of Smartphone Addiction on Reaction Time in Undergraduate Students: An Experimental Study”

In the introduction, we have inserted many of texts in this section for more correspondingly to the point of the objective in study.

In the methodology, we have also inserted and revisde many of texts in this section based on the suggestions/comments from all reviewers such as the flowchart of the study, explanation of the exclusion criteria, type of RT used in this study, as well as additional statistical analysis of this study.

In the result, we have adding the report of the descriptive statistical, and ANOVA analysis based on the suggestion by reviewer.

In the discussion, we have adding the limitation of the study, and mention of hypothesis based on the suggestion by reviewer.

Finally, we appreciate the reviewers' constructive feedback and hope that our revisions adequately address your concerns.

Thank you for considering our revised manuscript. We look forward to hearing from you.

Sincerely,
Authors

Reviewer 1

This study reports the findings of an experimental study into the relationship between smartphone addiction, defined by cutoffs on the Thai translation of the SAS-SV, and reaction time performance on a dual task paradigm. No differences were found between the SA groups on task performance. I liked the use of an experimental design, and that the data was made publicly available. However, there are a number of issues with the manuscript as it presently stands, outlined below. In particular, I found the lack of hypotheses, issues with some methodological details, and conceptualizations of smartphone addiction affected the overall soundness of the manuscript, but these can be addressed with revisions. My comments are outlined below:

The title includes reference to social media addiction, but this does not appear to be measured in the study. Social media use is included as an inclusion criteria, but the study is not measuring social media addiction.

Answer: Thank you very much for your kind suggestion. The title has been changed to “The Impact of Smartphone Addiction on Reaction Time in Undergraduate Students: An Experimental Study”

There are some points where conceptualizations of behavioral addictions are a bit unclear. For instance, at the bottom of the first paragraph, the references for the claim that individuals with smartphone addiction endure various challenges are two papers on problematic internet use from the late 1990s. I think more specific and relevant evidence could be incorporated here.

Answer: Thank you very much for your kind suggestion. At the first paragraph in the introduction section, we have added some statements for more specific and relevant evidences as follows:

“Prolonged use of smartphones exposes individuals to several detrimental physical and psychological effects. For example, dry eyes, carpal tunnel syndrome, repetitive strain injury, wrist, neck, back, and shoulder pain, migraine headaches, thumb, index, and middle finger pain, and phantom pocket vibration syndrome are physical symptoms associated with smartphone addiction.^{4 ,} ⁵ (AlBarashdi et al., 2016; Sebastian & Jinesh, 2018)."

Similarly in the second paragraph there are number of claims made about the severity of smartphone addiction that are open for debate. There is a critical literature that has highlighted many of the issues with the measurement of smartphone addiction, how it relates to other behavioural addictions (e.g. if somebody is using their phone extensively for social media use, do they have a smartphone, or a social media addiction?), and whether this translates into clinically meaningful levels of harm.

Answer: Thank you very much for your kind suggestion. At the second paragraph, in the introduction section, we have inserted some statements for the issues of smartphone addiction realted to several detrimental psychological impacts as follows:

“It has also been found to have detrimental psychological impacts¹⁶(Kuss & Griffiths, 2011). Excessive use of smartphones negatively affects the quality of students' sleep ^{17 ,} ^{18, 19}^{, 20,} (Ibrahim et al., 2018; Kurugodiyavar et al., 2017; Sahin et al., 2013; Wang et al., 2019) and result in insomnia ²¹(Van Deursen et al., 2015). Many studies have established a correlation between smartphone usage and mental disorders, such as stress and anxiety ²² (Boumosleh & Jaalouk, 2017). Other potential adverse consequences include loss of control ²³(Gupta et al., 2016) and maladaptive behavioral problems ²⁴ (Hwang et al., 2012). Smartphone addiction has a poor correlation with both life satisfaction and performance in school ²⁵(Samaha & Hawi, 2016).”

Again, some of the claims regarding smartphone addiction and adolescence are again debatable. The claim they are inextricably linked, and consider it to be a 'second personality' are particularly questionable. The vast majority of the literature samples adolescents and university students, and so this may be biased by the lack of research compared to other groups.

Answer: We acknowledge the focus of existing research on adolescents and university students, highlighting this as a limitation and noting the potential for selection bias. This sets the stage for why your study is mindful of broader implications. We have inserted several texts to explain those as follows:

“A substantial amount of study has been devoted to the examination of smartphone addiction, with university students and adolescents serving as the primary cohorts for investigation (Kuss & Griffiths, 2011; Sahin et al., 2013). Although the emphasis has resulted in significant findings regarding the trends and repercussions of using smartphones among the youth population, it also presents the possibility of selection bias. The focus on younger age groups and life stages in this analysis of smartphone addiction might not encompass its intricacies (Ibrahim et al., 2018; Kurugodiyavar et al., 2017). In the context of this study's invalidity, this study seeks to contribute by examining the broader consequences associated with smartphone addiction. Through this approach, we aim to contribute to a more holistic comprehension of its ramifications, recognizing that the phenomenon of smartphone addiction transcends the conventional focus on adolescent and university students.”

The final paragraph starts discussing social comparison, but it wasn't entirely clear how this related to the manuscript, and whether it ought to be included.

Answer: Thank you very much for your kind comment. For more accurately related to the manuscript objective, we have revised the final paragraph in the introduction section as follows:

“The increasing significance of smartphones in everyday life, particularly among young adults aged 18 to 22, emphasizes the delicate link between technology use and mental well-being. The objective of this study is to explore the impact of smartphone addiction on cognitive abilities, particularly reaction times, and to analyze the psychosocial repercussions of excessive smartphone usage. This initial investigation primarily examines the direct influence of smartphone addiction on reaction times while also recognizing the potential involvement of several risk factors.”

The introduction didn't introduce the rationale for the use of the dual tasking design, which I thought was a notable oversight that ought to be amended. No hypotheses were presented about the relationship between performance on the dual performance task and smartphone addiction - would one expect people with elevated levels of smartphone addiction severity to be faster or slower on the task?

Answer: Thank you very much for your kind comment. We have added a paragraph for the rationale for the use of the dual tasking in the introduction sectoion as follows:

“Dual-tasking refers to the act of executing two activities simultaneously, whereas multitasking refers to the act of performing more than two tasks simultaneously³⁴(Won et al., 2012). Engaging in activities such as walking or working while simultaneously utilizing various features of a smartphone can be referred to as dual- or multitasking. Nevertheless, engaging in multiple tasks simultaneously can potentially result in a loss of cognitive capacity, hence increasing the risk of experiencing a fall or injury in an unforeseen and unintentional circumstance. The capacity to sustain equilibrium in both stationary and moving scenarios serves as the foundation for executing functional tasks during the course of diverse routine activities ³⁵(Vuillerme et al., 2002). The functional activities requiring dynamic balance are achieved by the coordinated interplay of the ankle joints, knee joints, hip joints, and their respective accompanying muscles, as well as the shoulder joints and their surrounding muscles. Cognitive ability is closely linked to dynamic balance. Engaging in dual-tasking with a smartphone while walking, such as listening to music, sending a message, online surfing, or playing a game, is known to impair the dynamic balance required for functional activities by diminishing cognitive capacity. The act of using a mobile phone while walking is a common scenario known as a dual-task paradigm ³⁶(Plummer et al., 2013). This means that individuals are required to concurrently engage in mobile phone operations and walking duties. The notion of finite capacity scheduling suggests that the outcome of different activities determines the extent to which cognitive or motor performance is affected ^37,38(Coker, 2017; Wickens and Damos, 2020). The mobile phone task involves integrating numerous single activities, such as mathematics, language, memory, and motor skills, while walking, as opposed to doing a single task individually. The demand for cognitive resources in this activity is notably higher compared to other simpler activities ³⁹(Tan et al., 2022). Prior research has demonstrated that engaging in the dual-task paradigm of using a mobile phone while walking is more prone to inducing diminished awareness of the environment, impaired motor function in the lower extremities, and distraction compared to other uncomplicated tasks performed while walking among pedestrians ^40,⁴¹(Kim et al., 2020; Tan et al., 2022).”

The introduction also makes reference to comparing risk variables for smartphone addiction, but this doesn't seem to be reported in the results.

Answer: Thank you very much for you comment. For more correspondly to the main objective of the study that is to examine the effect of smartphone addiction on reaction times, not comparing the risk variable to the smartphone addiction. We have revised the introduction appropriately.

I appreciate that the authors' have conducted a power analysis to justify their sample size. However, my reading of this section is that the study is powered for the experimental effect (i.e. between the control, texting and calling conditions), and not any putative smartphone addiction effect. Therefore, it is not clear whether the data is appropriately powered for the effects the authors are trying to test. I suspect the study is underpowered for the purpose of testing any such effect. This should be included as a limitation.

Answer: Thank you very much for you kind comment. We have added a paragraph of the limitation in study in the last paragraph of the discussion section as follows:

“Although this study utilized a careful methodology, which involved conducting a power analysis to determine the required sample size for detecting variations in reaction times under control, texting, and calling conditions, it is crucial to acknowledge a potential limitation in our examination of the impacts of smartphone addiction. The initial power analysis was primarily intended to ensure an adequate sample size for detecting the experimental effects of dual-tasking conditions. However, it may not have been properly adjusted to accurately identify the more subtle but important influence of different levels of smartphone addiction on these cognitive tasks. After careful consideration, we acknowledge that the study may not have enough statistical power to definitively investigate the subtle impacts that the intensity of smartphone addiction may have on individuals' performance in these activities. This constraint implies that the conclusions on smartphone addiction should be approached with care since the study could not have possessed sufficient statistical strength to identify all significant effects linked to the intensity of smartphone addiction. Subsequent investigations in this field would be enhanced by performing a power analysis particularly designed to evaluate the impact of smartphone addiction. This may involve increasing the sample size or employing a more precise measure of addiction intensity. It is essential to overcome this constraint in order to enhance our comprehension of the cognitive consequences of smartphone addiction and to create specific therapies to reduce its negative impacts. Regarding the results and the original hypotheses of this investigation, further research should explore in greater detail the subtle mechanisms by which extended smartphone usage impacts cognitive functions. Conducting research on auditory reaction times and expanding the study to include various age groups could yield a more comprehensive comprehension of the cognitive consequences associated with smartphone addiction. Furthermore, future research should investigate the possible task-specific cognitive adjustments in those who use smartphones frequently, which could help reduce the anticipated detrimental impacts on dual-task performance.”

The reporting of reaction times could be streamlined, and easier to follow for readers. For instance, I wasn't clear on the need for the distinction between the three different types of RT.

Answer: Thank you very much for your suggestion. For clear understanding to the reader, we have inserted several texts indicating specifically RT’ type in the subsection of Measurement in Methodology section as follows:

“In this study, Choice RT involves multiple stimuli and multiple responses, which directly corresponds to the setup of the study where participants respond to different colored lights with different buttons. The need to recognize the color of the light and choose the correct button to press makes it a choice reaction time task, as there are several stimuli (different colors) and several possible responses (different buttons).
This study focuses on the evaluation of reaction times (RT) as a method for measuring the rate at which an individual reacts to a stimuli. It is crucial to specify that the specific sort of reaction time we are emphasizing is referred to as 'Choice RT.' The relevance of this particular type of reaction time lies in the fact that participants are presented with various stimuli and are required to make a deliberate choice on the appropriate response to carry out.
In further detail, Choice RT scenarios are distinguished by the existence of multiple potential stimuli, each necessitating a separate and specific reaction. Our experimental setup involves presenting participants with lights of varying hues, specifically red, blue, and yellow. Participants are required to hit a designated button for each color. This choice element distinguishes it from 'Simple RT,' which involves a single stimulus and automatic reaction, and from 'Recognition RT,' where the aim is to respond to certain stimuli while ignoring others.

More details regarding of the statistical analysis ought to be reported. To me, the analysis conducted look like 3 sets of addiction vs. non-addiction group analyses for each condition, but this is not clear from the information presented. I think the type of analysis could be reported, as could the test statistics and a measure of error.

Answer: We acknownledge for the additional statistical analysis. We have added a couple paragraph to report the statistical analysis with descriptive statistical and ANOVA analysis in the results section as follows:

“Analyzing the reaction times under different smartphone usage situations reveals clear trends for persons with and without addiction in Table 4. The non- addiction group exhibited the shortest average reaction time of 0.99 seconds after avoiding from smartphone usage. The results also showed a relatively narrow range of values, as evidenced by the standard deviation of 0.28 seconds. Participating in phone conversations increased response time to an average of 1.22 seconds, while the variation remained similar to the condition when no phone was used. Nevertheless, the texting activity showed the most notable increase, with an average response time of 1.73 seconds and a significantly larger standard deviation, indicating more variation in how texting impacted the reaction times of persons in this particular group. In comparison, the addiction group exhibited a slightly higher initial response time of 1.04 seconds when not using smartphones, while the range of values was narrower. The effect of phone calls was particularly noticeable among those with addiction, as their average response time increased to 1.309 seconds and was accompanied by a higher standard deviation, indicating a larger variation in response times among individuals. The "Addiction" group also saw a comparable impact from texting, with an average reaction time of 1.74 seconds and the largest level of variability across all conditions, as demonstrated by the standard deviation. Reaction times consistently increased in both groups as they transitioned from avoiding smartphones to texting. Although the "Addiction" group had somewhat greater average reaction times in every situation, their reaction times were more consistent under the no-use condition compared to the "No addiction" group. The 95% confidence intervals for the "Addiction" group exhibited higher values, indicating a potential association between addiction and longer reaction times. However, the overlapping intervals of the two groups suggest that the difference in reaction times between the two groups is not significant. In summary, the descriptive statistics reveal a noticeable pattern of longer reaction times linked to the usage of smartphones, particularly for tasks that demand more cognitive effort, such as texting.
The ANOVA analysis in Table 5 showed that those without addiction had an F-statistic of 29.41 and a p-value of roughly < 0.001, which indicates high significance. This result demonstrates a statistically significant difference in response times when comparing the absence of smartphone usage, making phone calls, and sending text messages among individuals in this group. The inference is that the nature of smartphone engagement significantly impacts the response times of non-addicted persons, with certain activities resulting in slower reactions compared to others. Similarly, the analysis conducted for the "Addiction" group yielded an F-statistic of 23.18, along with a significant p-value of roughly < 0.001. This validates that, similar to the "No addiction" group, there are statistically significant disparities in reaction time among those with addiction across the three smartphone-using circumstances. The experimental conditions in which the reaction time was assessed (absence of smartphone usage, during a phone call, or while texting) significantly influenced the recorded reaction times. The notable F-statistics in both groups indicate that the change in reaction times is not consistent across conditions; rather, it fluctuates based on whether individuals were not utilizing their smartphones, were involved in a phone call, or were texting. The p-values, which are significantly lower than the typical alpha level of 0.05, provide strong evidence that the observed changes in reaction times are not a result of random chance but rather indicate a genuine impact of the smartphone use condition. These findings emphasize the significance of the circumstances in which smartphones are used when evaluating their influence on cognitive performance, specifically in terms of reaction time.
In summary, the descriptive statistics and ANOVA analyses provide a thorough understanding of how reaction times are affected by smartphone usage in different situations for persons with and without addiction. The descriptive statistics indicate that reaction times exhibit an upward trend as individuals transition from not using smartphones to making phone calls, and then to sending text messages, for both groups. The heightened fluctuation in reaction times seen while texting, as indicated by the greater standard deviations, implies that this task may necessitate additional cognitive resources, thereby exerting a more pronounced impact on reaction times. This pattern is consistent for both the non-addiction and addiction groups, although individuals with addiction exhibit somewhat faster reaction times overall. The one-way ANOVA results provide additional support for these findings, demonstrating statistically significant variations in reaction times among the three smartphone use circumstances within each group. The "No addiction" group's F-statistic and p-value suggest that various smartphone activities have a differential impact on reaction times. The addiction group likewise has a significant impact of smartphone use circumstances on reaction times, as evidenced by the ANOVA results.”

Hypotheses are only mentioned for the first time at the beginning of the discussion.

Answer: Thank you very much for your suggestion. We have recognized the mention of the hypothesis in the discussion, many texts have been inserted in the discussion section as follows:

“This study aims to investigate the influence of smartphone addiction on visual reaction time (VRT) in several settings, such as control, texting, and chatting situations, as hypothesized. The results of our study did not support our initial hypothesis, which suggested that those with higher degrees of smartphone addiction would have slower VRT due to cognitive overload. Specifically, we found no significant differences in VRT between the group of individuals with smartphone addiction and the control group, regardless of the settings. This result implies a more intricate relationship between smartphone addiction and cognitive performance than originally anticipated.”

“Although we hypothesized that regular smartphone use, which requires higher cognitive capacities, could hinder the ability to perform two tasks simultaneously, resulting in longer reaction times, the findings did not confirm this expectation. One potential reason for this surprising discovery could be attributed to the adaptive capacities of individuals who use smartphones frequently. The study found that social networking was the most popular smartphone application among those with addiction, and they used it for much longer periods of time compared to the control group. The significant involvement with smartphones may have resulted in a type of task-specific cognitive adjustment, allowing these individuals to retain similar VRTs as those who are less involved with smartphones.”

“The lack of significant disparities in VRT among the groups contradicts our initial assumptions and prompts a reassessment of the ways in which smartphone addiction impacts cognitive function. According to capacity theory and bottleneck accounts, we hypothesized that the dual-task interference would be more pronounced in those with smartphone addiction. Nevertheless, the comparable performance observed in both groups indicates that factors such as task prioritization and cognitive resource allocation likely have a substantial influence on moderating the impact of smartphone usage on attention and reaction times.”

The discussion was unclear in places. The second half of the first paragraph starts discussing findings about the amount of smartphone use per session, but this isn't reported elsewhere in the manuscript. This was reported as being collected in the survey included with the data, but the methods talk about a different interview. The methods could be amended to make these passages clearer.

Answer: Thank you very much for your comment. We have inserted many texts to make these passages clearer in the subsection of Procedure in the Methodology section as follows:

“Following the initial evaluation using the SAS-SV-TH, participants were monitored during different experimental sessions intended to replicate their usual smartphone usage. Every session was designed to simulate a practical setting for texting or talking, with a duration that nearly reflected their self-reported typical usage, which was around 30 minutes. In order to obtain a thorough understanding of everyday smartphone usage, participants were involved in multiple sessions of such nature throughout the day. This methodology enabled us to gather detailed information on the potential impact of extended and repetitive smartphone usage within a 24-hour period on reaction speeds.”
Competing Interests: The authors declare no conflicts of interest. Close
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COMMENTS ON THIS REPORT

Author Response 13 Apr 2024

Teerachai Amnuaylojaroen, School of Energy and Environment, University of Phayao, Phayao, 56000, Thailand

13 Apr 2024

Author Response
Dear Reviewer,

We appreciate the opportunity to revise our manuscript entitled " Smartphone used and social media addiction in undergraduate student" and would like to thank the reviewers for ... Continue reading
Dear Reviewer,

We appreciate the opportunity to revise our manuscript entitled " Smartphone used and social media addiction in undergraduate student" and would like to thank the reviewers for their insightful comments and suggestions. We have carefully considered each point and have made substantial revisions to our manuscript (as seen in Track Change). Since many of the texts in the revised manuscript have been edited to cover all comments/suggestion, we have listed the overall changes in the revised version of the manuscript for more understanding in brief as follows:

In the title, it has been changed from " Smartphone used and social media addiction in undergraduate student" to “The Impact of Smartphone Addiction on Reaction Time in Undergraduate Students: An Experimental Study”

In the introduction, we have inserted many of texts in this section for more correspondingly to the point of the objective in study.

In the methodology, we have also inserted and revisde many of texts in this section based on the suggestions/comments from all reviewers such as the flowchart of the study, explanation of the exclusion criteria, type of RT used in this study, as well as additional statistical analysis of this study.

In the result, we have adding the report of the descriptive statistical, and ANOVA analysis based on the suggestion by reviewer.

In the discussion, we have adding the limitation of the study, and mention of hypothesis based on the suggestion by reviewer.

Finally, we appreciate the reviewers' constructive feedback and hope that our revisions adequately address your concerns.

Thank you for considering our revised manuscript. We look forward to hearing from you.

Sincerely,
Authors

Reviewer 1

This study reports the findings of an experimental study into the relationship between smartphone addiction, defined by cutoffs on the Thai translation of the SAS-SV, and reaction time performance on a dual task paradigm. No differences were found between the SA groups on task performance. I liked the use of an experimental design, and that the data was made publicly available. However, there are a number of issues with the manuscript as it presently stands, outlined below. In particular, I found the lack of hypotheses, issues with some methodological details, and conceptualizations of smartphone addiction affected the overall soundness of the manuscript, but these can be addressed with revisions. My comments are outlined below:

The title includes reference to social media addiction, but this does not appear to be measured in the study. Social media use is included as an inclusion criteria, but the study is not measuring social media addiction.

Answer: Thank you very much for your kind suggestion. The title has been changed to “The Impact of Smartphone Addiction on Reaction Time in Undergraduate Students: An Experimental Study”

There are some points where conceptualizations of behavioral addictions are a bit unclear. For instance, at the bottom of the first paragraph, the references for the claim that individuals with smartphone addiction endure various challenges are two papers on problematic internet use from the late 1990s. I think more specific and relevant evidence could be incorporated here.

Answer: Thank you very much for your kind suggestion. At the first paragraph in the introduction section, we have added some statements for more specific and relevant evidences as follows:

“Prolonged use of smartphones exposes individuals to several detrimental physical and psychological effects. For example, dry eyes, carpal tunnel syndrome, repetitive strain injury, wrist, neck, back, and shoulder pain, migraine headaches, thumb, index, and middle finger pain, and phantom pocket vibration syndrome are physical symptoms associated with smartphone addiction.^{4 ,} ⁵ (AlBarashdi et al., 2016; Sebastian & Jinesh, 2018)."

Similarly in the second paragraph there are number of claims made about the severity of smartphone addiction that are open for debate. There is a critical literature that has highlighted many of the issues with the measurement of smartphone addiction, how it relates to other behavioural addictions (e.g. if somebody is using their phone extensively for social media use, do they have a smartphone, or a social media addiction?), and whether this translates into clinically meaningful levels of harm.

Answer: Thank you very much for your kind suggestion. At the second paragraph, in the introduction section, we have inserted some statements for the issues of smartphone addiction realted to several detrimental psychological impacts as follows:

“It has also been found to have detrimental psychological impacts¹⁶(Kuss & Griffiths, 2011). Excessive use of smartphones negatively affects the quality of students' sleep ^{17 ,} ^{18, 19}^{, 20,} (Ibrahim et al., 2018; Kurugodiyavar et al., 2017; Sahin et al., 2013; Wang et al., 2019) and result in insomnia ²¹(Van Deursen et al., 2015). Many studies have established a correlation between smartphone usage and mental disorders, such as stress and anxiety ²² (Boumosleh & Jaalouk, 2017). Other potential adverse consequences include loss of control ²³(Gupta et al., 2016) and maladaptive behavioral problems ²⁴ (Hwang et al., 2012). Smartphone addiction has a poor correlation with both life satisfaction and performance in school ²⁵(Samaha & Hawi, 2016).”

Again, some of the claims regarding smartphone addiction and adolescence are again debatable. The claim they are inextricably linked, and consider it to be a 'second personality' are particularly questionable. The vast majority of the literature samples adolescents and university students, and so this may be biased by the lack of research compared to other groups.

Answer: We acknowledge the focus of existing research on adolescents and university students, highlighting this as a limitation and noting the potential for selection bias. This sets the stage for why your study is mindful of broader implications. We have inserted several texts to explain those as follows:

“A substantial amount of study has been devoted to the examination of smartphone addiction, with university students and adolescents serving as the primary cohorts for investigation (Kuss & Griffiths, 2011; Sahin et al., 2013). Although the emphasis has resulted in significant findings regarding the trends and repercussions of using smartphones among the youth population, it also presents the possibility of selection bias. The focus on younger age groups and life stages in this analysis of smartphone addiction might not encompass its intricacies (Ibrahim et al., 2018; Kurugodiyavar et al., 2017). In the context of this study's invalidity, this study seeks to contribute by examining the broader consequences associated with smartphone addiction. Through this approach, we aim to contribute to a more holistic comprehension of its ramifications, recognizing that the phenomenon of smartphone addiction transcends the conventional focus on adolescent and university students.”

The final paragraph starts discussing social comparison, but it wasn't entirely clear how this related to the manuscript, and whether it ought to be included.

Answer: Thank you very much for your kind comment. For more accurately related to the manuscript objective, we have revised the final paragraph in the introduction section as follows:

“The increasing significance of smartphones in everyday life, particularly among young adults aged 18 to 22, emphasizes the delicate link between technology use and mental well-being. The objective of this study is to explore the impact of smartphone addiction on cognitive abilities, particularly reaction times, and to analyze the psychosocial repercussions of excessive smartphone usage. This initial investigation primarily examines the direct influence of smartphone addiction on reaction times while also recognizing the potential involvement of several risk factors.”

The introduction didn't introduce the rationale for the use of the dual tasking design, which I thought was a notable oversight that ought to be amended. No hypotheses were presented about the relationship between performance on the dual performance task and smartphone addiction - would one expect people with elevated levels of smartphone addiction severity to be faster or slower on the task?

Answer: Thank you very much for your kind comment. We have added a paragraph for the rationale for the use of the dual tasking in the introduction sectoion as follows:

“Dual-tasking refers to the act of executing two activities simultaneously, whereas multitasking refers to the act of performing more than two tasks simultaneously³⁴(Won et al., 2012). Engaging in activities such as walking or working while simultaneously utilizing various features of a smartphone can be referred to as dual- or multitasking. Nevertheless, engaging in multiple tasks simultaneously can potentially result in a loss of cognitive capacity, hence increasing the risk of experiencing a fall or injury in an unforeseen and unintentional circumstance. The capacity to sustain equilibrium in both stationary and moving scenarios serves as the foundation for executing functional tasks during the course of diverse routine activities ³⁵(Vuillerme et al., 2002). The functional activities requiring dynamic balance are achieved by the coordinated interplay of the ankle joints, knee joints, hip joints, and their respective accompanying muscles, as well as the shoulder joints and their surrounding muscles. Cognitive ability is closely linked to dynamic balance. Engaging in dual-tasking with a smartphone while walking, such as listening to music, sending a message, online surfing, or playing a game, is known to impair the dynamic balance required for functional activities by diminishing cognitive capacity. The act of using a mobile phone while walking is a common scenario known as a dual-task paradigm ³⁶(Plummer et al., 2013). This means that individuals are required to concurrently engage in mobile phone operations and walking duties. The notion of finite capacity scheduling suggests that the outcome of different activities determines the extent to which cognitive or motor performance is affected ^37,38(Coker, 2017; Wickens and Damos, 2020). The mobile phone task involves integrating numerous single activities, such as mathematics, language, memory, and motor skills, while walking, as opposed to doing a single task individually. The demand for cognitive resources in this activity is notably higher compared to other simpler activities ³⁹(Tan et al., 2022). Prior research has demonstrated that engaging in the dual-task paradigm of using a mobile phone while walking is more prone to inducing diminished awareness of the environment, impaired motor function in the lower extremities, and distraction compared to other uncomplicated tasks performed while walking among pedestrians ^40,⁴¹(Kim et al., 2020; Tan et al., 2022).”

The introduction also makes reference to comparing risk variables for smartphone addiction, but this doesn't seem to be reported in the results.

Answer: Thank you very much for you comment. For more correspondly to the main objective of the study that is to examine the effect of smartphone addiction on reaction times, not comparing the risk variable to the smartphone addiction. We have revised the introduction appropriately.

I appreciate that the authors' have conducted a power analysis to justify their sample size. However, my reading of this section is that the study is powered for the experimental effect (i.e. between the control, texting and calling conditions), and not any putative smartphone addiction effect. Therefore, it is not clear whether the data is appropriately powered for the effects the authors are trying to test. I suspect the study is underpowered for the purpose of testing any such effect. This should be included as a limitation.

Answer: Thank you very much for you kind comment. We have added a paragraph of the limitation in study in the last paragraph of the discussion section as follows:

“Although this study utilized a careful methodology, which involved conducting a power analysis to determine the required sample size for detecting variations in reaction times under control, texting, and calling conditions, it is crucial to acknowledge a potential limitation in our examination of the impacts of smartphone addiction. The initial power analysis was primarily intended to ensure an adequate sample size for detecting the experimental effects of dual-tasking conditions. However, it may not have been properly adjusted to accurately identify the more subtle but important influence of different levels of smartphone addiction on these cognitive tasks. After careful consideration, we acknowledge that the study may not have enough statistical power to definitively investigate the subtle impacts that the intensity of smartphone addiction may have on individuals' performance in these activities. This constraint implies that the conclusions on smartphone addiction should be approached with care since the study could not have possessed sufficient statistical strength to identify all significant effects linked to the intensity of smartphone addiction. Subsequent investigations in this field would be enhanced by performing a power analysis particularly designed to evaluate the impact of smartphone addiction. This may involve increasing the sample size or employing a more precise measure of addiction intensity. It is essential to overcome this constraint in order to enhance our comprehension of the cognitive consequences of smartphone addiction and to create specific therapies to reduce its negative impacts. Regarding the results and the original hypotheses of this investigation, further research should explore in greater detail the subtle mechanisms by which extended smartphone usage impacts cognitive functions. Conducting research on auditory reaction times and expanding the study to include various age groups could yield a more comprehensive comprehension of the cognitive consequences associated with smartphone addiction. Furthermore, future research should investigate the possible task-specific cognitive adjustments in those who use smartphones frequently, which could help reduce the anticipated detrimental impacts on dual-task performance.”

The reporting of reaction times could be streamlined, and easier to follow for readers. For instance, I wasn't clear on the need for the distinction between the three different types of RT.

Answer: Thank you very much for your suggestion. For clear understanding to the reader, we have inserted several texts indicating specifically RT’ type in the subsection of Measurement in Methodology section as follows:

“In this study, Choice RT involves multiple stimuli and multiple responses, which directly corresponds to the setup of the study where participants respond to different colored lights with different buttons. The need to recognize the color of the light and choose the correct button to press makes it a choice reaction time task, as there are several stimuli (different colors) and several possible responses (different buttons).
This study focuses on the evaluation of reaction times (RT) as a method for measuring the rate at which an individual reacts to a stimuli. It is crucial to specify that the specific sort of reaction time we are emphasizing is referred to as 'Choice RT.' The relevance of this particular type of reaction time lies in the fact that participants are presented with various stimuli and are required to make a deliberate choice on the appropriate response to carry out.
In further detail, Choice RT scenarios are distinguished by the existence of multiple potential stimuli, each necessitating a separate and specific reaction. Our experimental setup involves presenting participants with lights of varying hues, specifically red, blue, and yellow. Participants are required to hit a designated button for each color. This choice element distinguishes it from 'Simple RT,' which involves a single stimulus and automatic reaction, and from 'Recognition RT,' where the aim is to respond to certain stimuli while ignoring others.

More details regarding of the statistical analysis ought to be reported. To me, the analysis conducted look like 3 sets of addiction vs. non-addiction group analyses for each condition, but this is not clear from the information presented. I think the type of analysis could be reported, as could the test statistics and a measure of error.

Answer: We acknownledge for the additional statistical analysis. We have added a couple paragraph to report the statistical analysis with descriptive statistical and ANOVA analysis in the results section as follows:

“Analyzing the reaction times under different smartphone usage situations reveals clear trends for persons with and without addiction in Table 4. The non- addiction group exhibited the shortest average reaction time of 0.99 seconds after avoiding from smartphone usage. The results also showed a relatively narrow range of values, as evidenced by the standard deviation of 0.28 seconds. Participating in phone conversations increased response time to an average of 1.22 seconds, while the variation remained similar to the condition when no phone was used. Nevertheless, the texting activity showed the most notable increase, with an average response time of 1.73 seconds and a significantly larger standard deviation, indicating more variation in how texting impacted the reaction times of persons in this particular group. In comparison, the addiction group exhibited a slightly higher initial response time of 1.04 seconds when not using smartphones, while the range of values was narrower. The effect of phone calls was particularly noticeable among those with addiction, as their average response time increased to 1.309 seconds and was accompanied by a higher standard deviation, indicating a larger variation in response times among individuals. The "Addiction" group also saw a comparable impact from texting, with an average reaction time of 1.74 seconds and the largest level of variability across all conditions, as demonstrated by the standard deviation. Reaction times consistently increased in both groups as they transitioned from avoiding smartphones to texting. Although the "Addiction" group had somewhat greater average reaction times in every situation, their reaction times were more consistent under the no-use condition compared to the "No addiction" group. The 95% confidence intervals for the "Addiction" group exhibited higher values, indicating a potential association between addiction and longer reaction times. However, the overlapping intervals of the two groups suggest that the difference in reaction times between the two groups is not significant. In summary, the descriptive statistics reveal a noticeable pattern of longer reaction times linked to the usage of smartphones, particularly for tasks that demand more cognitive effort, such as texting.
The ANOVA analysis in Table 5 showed that those without addiction had an F-statistic of 29.41 and a p-value of roughly < 0.001, which indicates high significance. This result demonstrates a statistically significant difference in response times when comparing the absence of smartphone usage, making phone calls, and sending text messages among individuals in this group. The inference is that the nature of smartphone engagement significantly impacts the response times of non-addicted persons, with certain activities resulting in slower reactions compared to others. Similarly, the analysis conducted for the "Addiction" group yielded an F-statistic of 23.18, along with a significant p-value of roughly < 0.001. This validates that, similar to the "No addiction" group, there are statistically significant disparities in reaction time among those with addiction across the three smartphone-using circumstances. The experimental conditions in which the reaction time was assessed (absence of smartphone usage, during a phone call, or while texting) significantly influenced the recorded reaction times. The notable F-statistics in both groups indicate that the change in reaction times is not consistent across conditions; rather, it fluctuates based on whether individuals were not utilizing their smartphones, were involved in a phone call, or were texting. The p-values, which are significantly lower than the typical alpha level of 0.05, provide strong evidence that the observed changes in reaction times are not a result of random chance but rather indicate a genuine impact of the smartphone use condition. These findings emphasize the significance of the circumstances in which smartphones are used when evaluating their influence on cognitive performance, specifically in terms of reaction time.
In summary, the descriptive statistics and ANOVA analyses provide a thorough understanding of how reaction times are affected by smartphone usage in different situations for persons with and without addiction. The descriptive statistics indicate that reaction times exhibit an upward trend as individuals transition from not using smartphones to making phone calls, and then to sending text messages, for both groups. The heightened fluctuation in reaction times seen while texting, as indicated by the greater standard deviations, implies that this task may necessitate additional cognitive resources, thereby exerting a more pronounced impact on reaction times. This pattern is consistent for both the non-addiction and addiction groups, although individuals with addiction exhibit somewhat faster reaction times overall. The one-way ANOVA results provide additional support for these findings, demonstrating statistically significant variations in reaction times among the three smartphone use circumstances within each group. The "No addiction" group's F-statistic and p-value suggest that various smartphone activities have a differential impact on reaction times. The addiction group likewise has a significant impact of smartphone use circumstances on reaction times, as evidenced by the ANOVA results.”

Hypotheses are only mentioned for the first time at the beginning of the discussion.

Answer: Thank you very much for your suggestion. We have recognized the mention of the hypothesis in the discussion, many texts have been inserted in the discussion section as follows:

“This study aims to investigate the influence of smartphone addiction on visual reaction time (VRT) in several settings, such as control, texting, and chatting situations, as hypothesized. The results of our study did not support our initial hypothesis, which suggested that those with higher degrees of smartphone addiction would have slower VRT due to cognitive overload. Specifically, we found no significant differences in VRT between the group of individuals with smartphone addiction and the control group, regardless of the settings. This result implies a more intricate relationship between smartphone addiction and cognitive performance than originally anticipated.”

“Although we hypothesized that regular smartphone use, which requires higher cognitive capacities, could hinder the ability to perform two tasks simultaneously, resulting in longer reaction times, the findings did not confirm this expectation. One potential reason for this surprising discovery could be attributed to the adaptive capacities of individuals who use smartphones frequently. The study found that social networking was the most popular smartphone application among those with addiction, and they used it for much longer periods of time compared to the control group. The significant involvement with smartphones may have resulted in a type of task-specific cognitive adjustment, allowing these individuals to retain similar VRTs as those who are less involved with smartphones.”

“The lack of significant disparities in VRT among the groups contradicts our initial assumptions and prompts a reassessment of the ways in which smartphone addiction impacts cognitive function. According to capacity theory and bottleneck accounts, we hypothesized that the dual-task interference would be more pronounced in those with smartphone addiction. Nevertheless, the comparable performance observed in both groups indicates that factors such as task prioritization and cognitive resource allocation likely have a substantial influence on moderating the impact of smartphone usage on attention and reaction times.”

The discussion was unclear in places. The second half of the first paragraph starts discussing findings about the amount of smartphone use per session, but this isn't reported elsewhere in the manuscript. This was reported as being collected in the survey included with the data, but the methods talk about a different interview. The methods could be amended to make these passages clearer.

Answer: Thank you very much for your comment. We have inserted many texts to make these passages clearer in the subsection of Procedure in the Methodology section as follows:

“Following the initial evaluation using the SAS-SV-TH, participants were monitored during different experimental sessions intended to replicate their usual smartphone usage. Every session was designed to simulate a practical setting for texting or talking, with a duration that nearly reflected their self-reported typical usage, which was around 30 minutes. In order to obtain a thorough understanding of everyday smartphone usage, participants were involved in multiple sessions of such nature throughout the day. This methodology enabled us to gather detailed information on the potential impact of extended and repetitive smartphone usage within a 24-hour period on reaction speeds.”
Dear Reviewer,

We appreciate the opportunity to revise our manuscript entitled " Smartphone used and social media addiction in undergraduate student" and would like to thank the reviewers for their insightful comments and suggestions. We have carefully considered each point and have made substantial revisions to our manuscript (as seen in Track Change). Since many of the texts in the revised manuscript have been edited to cover all comments/suggestion, we have listed the overall changes in the revised version of the manuscript for more understanding in brief as follows:

In the title, it has been changed from " Smartphone used and social media addiction in undergraduate student" to “The Impact of Smartphone Addiction on Reaction Time in Undergraduate Students: An Experimental Study”

In the introduction, we have inserted many of texts in this section for more correspondingly to the point of the objective in study.

In the methodology, we have also inserted and revisde many of texts in this section based on the suggestions/comments from all reviewers such as the flowchart of the study, explanation of the exclusion criteria, type of RT used in this study, as well as additional statistical analysis of this study.

In the result, we have adding the report of the descriptive statistical, and ANOVA analysis based on the suggestion by reviewer.

In the discussion, we have adding the limitation of the study, and mention of hypothesis based on the suggestion by reviewer.

Finally, we appreciate the reviewers' constructive feedback and hope that our revisions adequately address your concerns.

Thank you for considering our revised manuscript. We look forward to hearing from you.

Sincerely,
Authors

Reviewer 1

This study reports the findings of an experimental study into the relationship between smartphone addiction, defined by cutoffs on the Thai translation of the SAS-SV, and reaction time performance on a dual task paradigm. No differences were found between the SA groups on task performance. I liked the use of an experimental design, and that the data was made publicly available. However, there are a number of issues with the manuscript as it presently stands, outlined below. In particular, I found the lack of hypotheses, issues with some methodological details, and conceptualizations of smartphone addiction affected the overall soundness of the manuscript, but these can be addressed with revisions. My comments are outlined below:

The title includes reference to social media addiction, but this does not appear to be measured in the study. Social media use is included as an inclusion criteria, but the study is not measuring social media addiction.

Answer: Thank you very much for your kind suggestion. The title has been changed to “The Impact of Smartphone Addiction on Reaction Time in Undergraduate Students: An Experimental Study”

There are some points where conceptualizations of behavioral addictions are a bit unclear. For instance, at the bottom of the first paragraph, the references for the claim that individuals with smartphone addiction endure various challenges are two papers on problematic internet use from the late 1990s. I think more specific and relevant evidence could be incorporated here.

Answer: Thank you very much for your kind suggestion. At the first paragraph in the introduction section, we have added some statements for more specific and relevant evidences as follows:

“Prolonged use of smartphones exposes individuals to several detrimental physical and psychological effects. For example, dry eyes, carpal tunnel syndrome, repetitive strain injury, wrist, neck, back, and shoulder pain, migraine headaches, thumb, index, and middle finger pain, and phantom pocket vibration syndrome are physical symptoms associated with smartphone addiction.^{4 ,} ⁵ (AlBarashdi et al., 2016; Sebastian & Jinesh, 2018)."

Similarly in the second paragraph there are number of claims made about the severity of smartphone addiction that are open for debate. There is a critical literature that has highlighted many of the issues with the measurement of smartphone addiction, how it relates to other behavioural addictions (e.g. if somebody is using their phone extensively for social media use, do they have a smartphone, or a social media addiction?), and whether this translates into clinically meaningful levels of harm.

Answer: Thank you very much for your kind suggestion. At the second paragraph, in the introduction section, we have inserted some statements for the issues of smartphone addiction realted to several detrimental psychological impacts as follows:

“It has also been found to have detrimental psychological impacts¹⁶(Kuss & Griffiths, 2011). Excessive use of smartphones negatively affects the quality of students' sleep ^{17 ,} ^{18, 19}^{, 20,} (Ibrahim et al., 2018; Kurugodiyavar et al., 2017; Sahin et al., 2013; Wang et al., 2019) and result in insomnia ²¹(Van Deursen et al., 2015). Many studies have established a correlation between smartphone usage and mental disorders, such as stress and anxiety ²² (Boumosleh & Jaalouk, 2017). Other potential adverse consequences include loss of control ²³(Gupta et al., 2016) and maladaptive behavioral problems ²⁴ (Hwang et al., 2012). Smartphone addiction has a poor correlation with both life satisfaction and performance in school ²⁵(Samaha & Hawi, 2016).”

Again, some of the claims regarding smartphone addiction and adolescence are again debatable. The claim they are inextricably linked, and consider it to be a 'second personality' are particularly questionable. The vast majority of the literature samples adolescents and university students, and so this may be biased by the lack of research compared to other groups.

Answer: We acknowledge the focus of existing research on adolescents and university students, highlighting this as a limitation and noting the potential for selection bias. This sets the stage for why your study is mindful of broader implications. We have inserted several texts to explain those as follows:

“A substantial amount of study has been devoted to the examination of smartphone addiction, with university students and adolescents serving as the primary cohorts for investigation (Kuss & Griffiths, 2011; Sahin et al., 2013). Although the emphasis has resulted in significant findings regarding the trends and repercussions of using smartphones among the youth population, it also presents the possibility of selection bias. The focus on younger age groups and life stages in this analysis of smartphone addiction might not encompass its intricacies (Ibrahim et al., 2018; Kurugodiyavar et al., 2017). In the context of this study's invalidity, this study seeks to contribute by examining the broader consequences associated with smartphone addiction. Through this approach, we aim to contribute to a more holistic comprehension of its ramifications, recognizing that the phenomenon of smartphone addiction transcends the conventional focus on adolescent and university students.”

The final paragraph starts discussing social comparison, but it wasn't entirely clear how this related to the manuscript, and whether it ought to be included.

Answer: Thank you very much for your kind comment. For more accurately related to the manuscript objective, we have revised the final paragraph in the introduction section as follows:

“The increasing significance of smartphones in everyday life, particularly among young adults aged 18 to 22, emphasizes the delicate link between technology use and mental well-being. The objective of this study is to explore the impact of smartphone addiction on cognitive abilities, particularly reaction times, and to analyze the psychosocial repercussions of excessive smartphone usage. This initial investigation primarily examines the direct influence of smartphone addiction on reaction times while also recognizing the potential involvement of several risk factors.”

The introduction didn't introduce the rationale for the use of the dual tasking design, which I thought was a notable oversight that ought to be amended. No hypotheses were presented about the relationship between performance on the dual performance task and smartphone addiction - would one expect people with elevated levels of smartphone addiction severity to be faster or slower on the task?

Answer: Thank you very much for your kind comment. We have added a paragraph for the rationale for the use of the dual tasking in the introduction sectoion as follows:

“Dual-tasking refers to the act of executing two activities simultaneously, whereas multitasking refers to the act of performing more than two tasks simultaneously³⁴(Won et al., 2012). Engaging in activities such as walking or working while simultaneously utilizing various features of a smartphone can be referred to as dual- or multitasking. Nevertheless, engaging in multiple tasks simultaneously can potentially result in a loss of cognitive capacity, hence increasing the risk of experiencing a fall or injury in an unforeseen and unintentional circumstance. The capacity to sustain equilibrium in both stationary and moving scenarios serves as the foundation for executing functional tasks during the course of diverse routine activities ³⁵(Vuillerme et al., 2002). The functional activities requiring dynamic balance are achieved by the coordinated interplay of the ankle joints, knee joints, hip joints, and their respective accompanying muscles, as well as the shoulder joints and their surrounding muscles. Cognitive ability is closely linked to dynamic balance. Engaging in dual-tasking with a smartphone while walking, such as listening to music, sending a message, online surfing, or playing a game, is known to impair the dynamic balance required for functional activities by diminishing cognitive capacity. The act of using a mobile phone while walking is a common scenario known as a dual-task paradigm ³⁶(Plummer et al., 2013). This means that individuals are required to concurrently engage in mobile phone operations and walking duties. The notion of finite capacity scheduling suggests that the outcome of different activities determines the extent to which cognitive or motor performance is affected ^37,38(Coker, 2017; Wickens and Damos, 2020). The mobile phone task involves integrating numerous single activities, such as mathematics, language, memory, and motor skills, while walking, as opposed to doing a single task individually. The demand for cognitive resources in this activity is notably higher compared to other simpler activities ³⁹(Tan et al., 2022). Prior research has demonstrated that engaging in the dual-task paradigm of using a mobile phone while walking is more prone to inducing diminished awareness of the environment, impaired motor function in the lower extremities, and distraction compared to other uncomplicated tasks performed while walking among pedestrians ^40,⁴¹(Kim et al., 2020; Tan et al., 2022).”

The introduction also makes reference to comparing risk variables for smartphone addiction, but this doesn't seem to be reported in the results.

Answer: Thank you very much for you comment. For more correspondly to the main objective of the study that is to examine the effect of smartphone addiction on reaction times, not comparing the risk variable to the smartphone addiction. We have revised the introduction appropriately.

I appreciate that the authors' have conducted a power analysis to justify their sample size. However, my reading of this section is that the study is powered for the experimental effect (i.e. between the control, texting and calling conditions), and not any putative smartphone addiction effect. Therefore, it is not clear whether the data is appropriately powered for the effects the authors are trying to test. I suspect the study is underpowered for the purpose of testing any such effect. This should be included as a limitation.

Answer: Thank you very much for you kind comment. We have added a paragraph of the limitation in study in the last paragraph of the discussion section as follows:

“Although this study utilized a careful methodology, which involved conducting a power analysis to determine the required sample size for detecting variations in reaction times under control, texting, and calling conditions, it is crucial to acknowledge a potential limitation in our examination of the impacts of smartphone addiction. The initial power analysis was primarily intended to ensure an adequate sample size for detecting the experimental effects of dual-tasking conditions. However, it may not have been properly adjusted to accurately identify the more subtle but important influence of different levels of smartphone addiction on these cognitive tasks. After careful consideration, we acknowledge that the study may not have enough statistical power to definitively investigate the subtle impacts that the intensity of smartphone addiction may have on individuals' performance in these activities. This constraint implies that the conclusions on smartphone addiction should be approached with care since the study could not have possessed sufficient statistical strength to identify all significant effects linked to the intensity of smartphone addiction. Subsequent investigations in this field would be enhanced by performing a power analysis particularly designed to evaluate the impact of smartphone addiction. This may involve increasing the sample size or employing a more precise measure of addiction intensity. It is essential to overcome this constraint in order to enhance our comprehension of the cognitive consequences of smartphone addiction and to create specific therapies to reduce its negative impacts. Regarding the results and the original hypotheses of this investigation, further research should explore in greater detail the subtle mechanisms by which extended smartphone usage impacts cognitive functions. Conducting research on auditory reaction times and expanding the study to include various age groups could yield a more comprehensive comprehension of the cognitive consequences associated with smartphone addiction. Furthermore, future research should investigate the possible task-specific cognitive adjustments in those who use smartphones frequently, which could help reduce the anticipated detrimental impacts on dual-task performance.”

The reporting of reaction times could be streamlined, and easier to follow for readers. For instance, I wasn't clear on the need for the distinction between the three different types of RT.

Answer: Thank you very much for your suggestion. For clear understanding to the reader, we have inserted several texts indicating specifically RT’ type in the subsection of Measurement in Methodology section as follows:

“In this study, Choice RT involves multiple stimuli and multiple responses, which directly corresponds to the setup of the study where participants respond to different colored lights with different buttons. The need to recognize the color of the light and choose the correct button to press makes it a choice reaction time task, as there are several stimuli (different colors) and several possible responses (different buttons).
This study focuses on the evaluation of reaction times (RT) as a method for measuring the rate at which an individual reacts to a stimuli. It is crucial to specify that the specific sort of reaction time we are emphasizing is referred to as 'Choice RT.' The relevance of this particular type of reaction time lies in the fact that participants are presented with various stimuli and are required to make a deliberate choice on the appropriate response to carry out.
In further detail, Choice RT scenarios are distinguished by the existence of multiple potential stimuli, each necessitating a separate and specific reaction. Our experimental setup involves presenting participants with lights of varying hues, specifically red, blue, and yellow. Participants are required to hit a designated button for each color. This choice element distinguishes it from 'Simple RT,' which involves a single stimulus and automatic reaction, and from 'Recognition RT,' where the aim is to respond to certain stimuli while ignoring others.

More details regarding of the statistical analysis ought to be reported. To me, the analysis conducted look like 3 sets of addiction vs. non-addiction group analyses for each condition, but this is not clear from the information presented. I think the type of analysis could be reported, as could the test statistics and a measure of error.

Answer: We acknownledge for the additional statistical analysis. We have added a couple paragraph to report the statistical analysis with descriptive statistical and ANOVA analysis in the results section as follows:

“Analyzing the reaction times under different smartphone usage situations reveals clear trends for persons with and without addiction in Table 4. The non- addiction group exhibited the shortest average reaction time of 0.99 seconds after avoiding from smartphone usage. The results also showed a relatively narrow range of values, as evidenced by the standard deviation of 0.28 seconds. Participating in phone conversations increased response time to an average of 1.22 seconds, while the variation remained similar to the condition when no phone was used. Nevertheless, the texting activity showed the most notable increase, with an average response time of 1.73 seconds and a significantly larger standard deviation, indicating more variation in how texting impacted the reaction times of persons in this particular group. In comparison, the addiction group exhibited a slightly higher initial response time of 1.04 seconds when not using smartphones, while the range of values was narrower. The effect of phone calls was particularly noticeable among those with addiction, as their average response time increased to 1.309 seconds and was accompanied by a higher standard deviation, indicating a larger variation in response times among individuals. The "Addiction" group also saw a comparable impact from texting, with an average reaction time of 1.74 seconds and the largest level of variability across all conditions, as demonstrated by the standard deviation. Reaction times consistently increased in both groups as they transitioned from avoiding smartphones to texting. Although the "Addiction" group had somewhat greater average reaction times in every situation, their reaction times were more consistent under the no-use condition compared to the "No addiction" group. The 95% confidence intervals for the "Addiction" group exhibited higher values, indicating a potential association between addiction and longer reaction times. However, the overlapping intervals of the two groups suggest that the difference in reaction times between the two groups is not significant. In summary, the descriptive statistics reveal a noticeable pattern of longer reaction times linked to the usage of smartphones, particularly for tasks that demand more cognitive effort, such as texting.
The ANOVA analysis in Table 5 showed that those without addiction had an F-statistic of 29.41 and a p-value of roughly < 0.001, which indicates high significance. This result demonstrates a statistically significant difference in response times when comparing the absence of smartphone usage, making phone calls, and sending text messages among individuals in this group. The inference is that the nature of smartphone engagement significantly impacts the response times of non-addicted persons, with certain activities resulting in slower reactions compared to others. Similarly, the analysis conducted for the "Addiction" group yielded an F-statistic of 23.18, along with a significant p-value of roughly < 0.001. This validates that, similar to the "No addiction" group, there are statistically significant disparities in reaction time among those with addiction across the three smartphone-using circumstances. The experimental conditions in which the reaction time was assessed (absence of smartphone usage, during a phone call, or while texting) significantly influenced the recorded reaction times. The notable F-statistics in both groups indicate that the change in reaction times is not consistent across conditions; rather, it fluctuates based on whether individuals were not utilizing their smartphones, were involved in a phone call, or were texting. The p-values, which are significantly lower than the typical alpha level of 0.05, provide strong evidence that the observed changes in reaction times are not a result of random chance but rather indicate a genuine impact of the smartphone use condition. These findings emphasize the significance of the circumstances in which smartphones are used when evaluating their influence on cognitive performance, specifically in terms of reaction time.
In summary, the descriptive statistics and ANOVA analyses provide a thorough understanding of how reaction times are affected by smartphone usage in different situations for persons with and without addiction. The descriptive statistics indicate that reaction times exhibit an upward trend as individuals transition from not using smartphones to making phone calls, and then to sending text messages, for both groups. The heightened fluctuation in reaction times seen while texting, as indicated by the greater standard deviations, implies that this task may necessitate additional cognitive resources, thereby exerting a more pronounced impact on reaction times. This pattern is consistent for both the non-addiction and addiction groups, although individuals with addiction exhibit somewhat faster reaction times overall. The one-way ANOVA results provide additional support for these findings, demonstrating statistically significant variations in reaction times among the three smartphone use circumstances within each group. The "No addiction" group's F-statistic and p-value suggest that various smartphone activities have a differential impact on reaction times. The addiction group likewise has a significant impact of smartphone use circumstances on reaction times, as evidenced by the ANOVA results.”

Hypotheses are only mentioned for the first time at the beginning of the discussion.

Answer: Thank you very much for your suggestion. We have recognized the mention of the hypothesis in the discussion, many texts have been inserted in the discussion section as follows:

“This study aims to investigate the influence of smartphone addiction on visual reaction time (VRT) in several settings, such as control, texting, and chatting situations, as hypothesized. The results of our study did not support our initial hypothesis, which suggested that those with higher degrees of smartphone addiction would have slower VRT due to cognitive overload. Specifically, we found no significant differences in VRT between the group of individuals with smartphone addiction and the control group, regardless of the settings. This result implies a more intricate relationship between smartphone addiction and cognitive performance than originally anticipated.”

“Although we hypothesized that regular smartphone use, which requires higher cognitive capacities, could hinder the ability to perform two tasks simultaneously, resulting in longer reaction times, the findings did not confirm this expectation. One potential reason for this surprising discovery could be attributed to the adaptive capacities of individuals who use smartphones frequently. The study found that social networking was the most popular smartphone application among those with addiction, and they used it for much longer periods of time compared to the control group. The significant involvement with smartphones may have resulted in a type of task-specific cognitive adjustment, allowing these individuals to retain similar VRTs as those who are less involved with smartphones.”

“The lack of significant disparities in VRT among the groups contradicts our initial assumptions and prompts a reassessment of the ways in which smartphone addiction impacts cognitive function. According to capacity theory and bottleneck accounts, we hypothesized that the dual-task interference would be more pronounced in those with smartphone addiction. Nevertheless, the comparable performance observed in both groups indicates that factors such as task prioritization and cognitive resource allocation likely have a substantial influence on moderating the impact of smartphone usage on attention and reaction times.”

The discussion was unclear in places. The second half of the first paragraph starts discussing findings about the amount of smartphone use per session, but this isn't reported elsewhere in the manuscript. This was reported as being collected in the survey included with the data, but the methods talk about a different interview. The methods could be amended to make these passages clearer.

Answer: Thank you very much for your comment. We have inserted many texts to make these passages clearer in the subsection of Procedure in the Methodology section as follows:

“Following the initial evaluation using the SAS-SV-TH, participants were monitored during different experimental sessions intended to replicate their usual smartphone usage. Every session was designed to simulate a practical setting for texting or talking, with a duration that nearly reflected their self-reported typical usage, which was around 30 minutes. In order to obtain a thorough understanding of everyday smartphone usage, participants were involved in multiple sessions of such nature throughout the day. This methodology enabled us to gather detailed information on the potential impact of extended and repetitive smartphone usage within a 24-hour period on reaction speeds.”
Competing Interests: The authors declare no conflicts of interest. Close
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Version 3

VERSION 3 PUBLISHED 15 Dec 2022

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Richard J. E. James, University of Nottingham, Nottingham, UK
Hariom K. Solanki, Maulana Azad Medical College, Delhi, New Delhi, India
Tarık Talan, Gaziantep Islam Science and Technology University, Gaziantep, Turkey
Andres Chamarro, Universitat Autònoma de Barcelona, Barcelona, Spain

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8 Views

22 Mar 2025 | for Version 3

Andres Chamarro, Universitat Autònoma de Barcelona, Barcelona, Spain

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Not Approved

The manuscript addresses the relationship between smartphone addiction and reaction time. A priori the topic is interesting, since the literature with experimental methods in the field is not very frequent. However, the study suffers from limitations that do not allow me to recommend its approval for indexing.

1. First of all, the title unfortunately fails to reflect the objective of the study.
2. The background of the abstract focuses on the use of social media in children, when the sample of the study is university students.
3. The manuscript uses smartphone addiction, measured with the SAS-SV, which is not a measure of addiction, but of problematic use (see Lopez-Fernandez O et al. [2017 (Ref-1)] https://doi.org/10.1016/j.addbeh.2015.11.013), nothing to do with it.
4. The introduction is disorganized, presenting evidence of smartphone addiction, social media addiction or prolonged smartphone use and screen time use. The authors should unify the terminology and use the appropriate literature, all terms are not comparable and are related to the objectives of the study. In addition, the negative consequences are repeated in the paragraphs on pages 3 and 4, with a significant bias in the negative consequences.
5. In the justification of the objective (page 5), the risk posed by the use of smartphones in daily life and its effect on well-being is mentioned, which does not correspond to the objective of the study. In short, the authors should focus the review of the literature on attentional effects, which is what the study is about. In addition, no hypotheses are formulated, which are then assumed to be true in the discussion.
6. The SAS-SV is not described in the measures section.
7. On page 8 I find it unnecessary to insert the formulas of the SD and the Kolmogorox-Smirnoff test, widely known by academics.
8. On page 11 I do not consider the summary of results necessary.
9. Tables 3, 4 and 5 can be perfectly merged, given that it is not necessary to show the sum of squares and add the statistics and p values to the table of descriptions is something common in the literature.
10. In the discussion, my major concern has to do with the presence of hypotheses that have not been presented or justified in the method section, as well as the new formulation of the study objective (relationship between addiction and VRT in different situations). I disagree with the authors' conclusion that the results are not inconsistent with the hypothesis that smartphone addicts should show lower VRT (page 11) nor that it is consistent with the Yu and Huang study (page 12), since the results do not show this result (as expressed in the abstract). On page 12 (first paragraph) another hypothesis is formulated again.
In short, the discussion does not start from the fact that the results contradict the hypotheses raised and are not in line with the cited literature. That is why the authors do not present a clear discussion of why smartphone users do not increase VRT in a dual task. Perhaps the task is not well designed?, apart from the sample size and the power of the analysis.
11. Therefore. the conclusion of the study is not correct, nor is it clearly expressed in the abstract and the conclusions of the study.

Is the work clearly and accurately presented and does it cite the current literature?

Partly
Is the study design appropriate and is the work technically sound?

Yes
Are sufficient details of methods and analysis provided to allow replication by others?

Yes
If applicable, is the statistical analysis and its interpretation appropriate?

Partly
Are all the source data underlying the results available to ensure full reproducibility?

Yes
Are the conclusions drawn adequately supported by the results?

No

References

1. Lopez-Fernandez O: Short version of the Smartphone Addiction Scale adapted to Spanish and French: Towards a cross-cultural research in problematic mobile phone use.Addict Behav. 2017; 64: 275-280 PubMed Abstract | Publisher Full Text

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No competing interests were disclosed.

Reviewer Expertise

Gaming Disorder, Cyberpsychology, PIU

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6 Views

04 Oct 2024 | for Version 3

Tarık Talan, Gaziantep Islam Science and Technology University, Gaziantep, Turkey

6 Views Cite this report Responses(0)

Approved

The researchers have made the requested corrections. I have no further comments regarding the study.

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

social media addiction

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.

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14 Views

23 Sep 2024 | for Version 2

Tarık Talan, Gaziantep Islam Science and Technology University, Gaziantep, Turkey

14 Views Cite this report Responses(1)

Approved With Reservations

Information can be provided regarding why the study was conducted, its significance, and its unique aspects in comparison to other studies.
In the introduction section of the study, briefly mentioning the recent studies on the subject will help broaden the scope of the research. For instance, the following studies could be briefly referenced:
* Social media addiction and poor mental health: examining the mediating roles of internet addiction and phubbing. Ergün N et al. (2023 [Ref - 1])
* Psychological Balances in the Digital World: Dynamic Relationships Among Social Media Addiction, Depression, Anxiety, Academic Self-Efficacy, General Belongingness, and Life Satisfaction. Kalınkara Y et al (2024 [Ref - 2])
* Effects of Smartphone Addiction, Social Media Addiction and Fear of Missing Out on University Students’ Phubbing: A Structural Equation Model. Talan T et al. (2024 [Ref-3]).
* Problematic smartphone use and social media fatigue: The mediating role of self-control. Świątek AH et al. (2023 [Ref - 4]).

Following the discussion of the study's limitations, it may be beneficial to provide concise recommendations for researchers interested in pursuing future work on this subject.

Is the work clearly and accurately presented and does it cite the current literature?

Yes
Is the study design appropriate and is the work technically sound?

Partly
Are sufficient details of methods and analysis provided to allow replication by others?

Yes
If applicable, is the statistical analysis and its interpretation appropriate?

Yes
Are all the source data underlying the results available to ensure full reproducibility?

Yes
Are the conclusions drawn adequately supported by the results?

Partly

References

1. Ergün N, Özkan Z, Griffiths MD: Social Media Addiction and Poor Mental Health: Examining the Mediating Roles of Internet Addiction and Phubbing.Psychol Rep. 2023. 332941231166609 PubMed Abstract | Publisher Full Text
2. Kalınkara Y, Talan T: Psychological Balances in the Digital World: Dynamic Relationships Among Social Media Addiction, Depression, Anxiety, Academic Self-Efficacy, General Belongingness, and Life Satisfaction.J Genet Psychol. 2024. 1-29 PubMed Abstract | Publisher Full Text
3. Talan T, Doğan Y, Kalinkara Y: Effects of Smartphone Addiction, Social Media Addiction and Fear of Missing Out on University Students’ Phubbing: A Structural Equation Model. Deviant Behavior. 2024; 45 (1): 1-14 Publisher Full Text
4. Świątek AH, Szcześniak M, Aleksandrowicz B, Zaczkowska D, et al.: Problematic Smartphone Use and Social Media Fatigue: The Mediating Role of Self-Control.Psychol Res Behav Manag. 2023; 16: 211-222 PubMed Abstract | Publisher Full Text

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

social media addiction

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.

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Author Response

30 Sep 2024

Teerachai Amnuaylojaroen, School of Energy and Environment, University of Phayao, Phayao, 56000, Thailand

Dear Reviewer,
We sincerely appreciate your thorough review of our manuscript and the valuable feedback provided. Your insights have been instrumental in improving the quality and clarity of our work. We have carefully considered each of your comments and have made significant revisions to address them. Below, we outline our responses and the corresponding changes made to the manuscript.

In the introduction section of the study, briefly mentioning the recent studies on the subject will help broaden the scope of the research. For instance, the following studies could be briefly referenced:
* Social media addiction and poor mental health: examining the mediating roles of internet addiction and phubbing. Ergün N et al. (2023 [Ref - 1])
* Psychological Balances in the Digital World: Dynamic Relationships Among Social Media Addiction, Depression, Anxiety, Academic Self-Efficacy, General Belongingness, and Life Satisfaction. Kalınkara Y et al (2024 [Ref - 2])
* Effects of Smartphone Addiction, Social Media Addiction and Fear of Missing Out on University Students’ Phubbing: A Structural Equation Model. Talan T et al. (2024 [Ref-3]).
* Problematic smartphone use and social media fatigue: The mediating role of self-control. Świątek AH et al. (2023 [Ref - 4]).

Response: We thank you for your suggestion to broaden the scope of our research by incorporating recent studies. As per your recommendation, we have revised the introduction to include the following studies as follows:

“Recent studies have further illuminated the complex relationship between smartphone use, social media addiction, and mental health. Ergün et al¹⁴ examined how social media addiction is associated with poor mental health, finding that this relationship is mediated by internet addiction and phubbing. Similarly, Kalınkara et al¹⁵explored the dynamic relationships among social media addiction, depression, anxiety, academic self-efficacy, general belongingness, and life satisfaction, highlighting the multifaceted nature of technology's impact on psychological well-being. The phenomenon of phubbing - the act of snubbing someone in a social setting by focusing on one's phone instead of the person - has also gained attention. Talan et al¹⁶investigated the effects of smartphone addiction, social media addiction, and fear of missing out (FoMO) on university students' phubbing behavior, revealing significant influences of smartphone and social media addiction on this phenomenon. Furthermore, Świątek et al¹⁷ explored the relationship between problematic smartphone use and social media fatigue, identifying self-control as a crucial mediating factor. This finding underscores the importance of considering psychological factors in understanding and addressing technology-related issues.”

2. Following the discussion of the study's limitations, it may be beneficial to provide concise recommendations for researchers interested in pursuing future work on this subject.
Response: We appreciate your comment on the need for a more comprehensive discussion of the study's limitations and suggestions for future research. We have expanded this in discussion section as follows:
“Secondly, the study's focus on a specific age group limits the generalizability of our findings to other age groups or populations. The cognitive effects of smartphone addiction may manifest differently across various life stages and demographic groups. Thirdly, our study primarily examined visual reaction times. While this provides valuable insights, it does not capture the full spectrum of cognitive functions that may be affected by smartphone addiction. Auditory reaction times and other cognitive domains, such as attention, memory, and executive functions, warrant further investigation. Lastly, the cross-sectional nature of our study limits our ability to establish causal relationships between smartphone addiction and cognitive performance. Longitudinal studies would be better suited to tracking the development and progression of smartphone addiction and its cognitive impacts over time. To address these limitations, subsequent investigations in this field would be enhanced by several key improvements. Firstly, performing a power analysis specifically designed to evaluate the impact of smartphone addiction would be crucial. This may involve increasing the sample size or employing a more precise measure of addiction intensity. Additionally, expanding the study to include various age groups and populations would yield a more comprehensive understanding of the cognitive consequences associated with smartphone addiction. Future research should also explore auditory reaction times and other cognitive domains to provide a more holistic picture of the cognitive effects of smartphone addiction. Conducting longitudinal studies would be valuable in tracking changes in smartphone usage patterns and their effects on cognitive function over time. Lastly, investigating the possible task-specific cognitive adjustments in those who use smartphones frequently could help explain any unexpected findings or reduced detrimental impacts on dual-task performance. By implementing these enhancements, future studies can provide more robust and generalizable insights into the complex relationship between smartphone addiction and cognitive functioning. It is essential to overcome these constraints in order to enhance our comprehension of the cognitive consequences of smartphone addiction and to create specific therapies to mitigate its negative impacts. Regarding the results and the original hypotheses of this investigation, further research should explore in greater detail the subtle mechanisms by which extended smartphone usage impacts cognitive functions across various domains and populations.”

We believe these revisions have substantially improved the quality and rigor of our manuscript. We appreciate your valuable input and hope that these changes address your concerns satisfactorily.

Sincerely yours,
Authors

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Reviewer Report

20 Views

07 Feb 2024 | for Version 1

Hariom K. Solanki, Department of Community Medicine, Maulana Azad Medical College, Delhi, New Delhi, Uttar Pradesh, India

20 Views Cite this report Responses(1)

Not Approved

Is the work clearly and accurately presented and does it cite the current literature?

Partly
Is the study design appropriate and is the work technically sound?

Partly
Are sufficient details of methods and analysis provided to allow replication by others?

Yes
If applicable, is the statistical analysis and its interpretation appropriate?

Yes
Are all the source data underlying the results available to ensure full reproducibility?

Partly
Are the conclusions drawn adequately supported by the results?

Partly

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

Public Health, Epidemiology, Primary Health Care

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Author Response

13 Apr 2024

Teerachai Amnuaylojaroen, School of Energy and Environment, University of Phayao, Phayao, 56000, Thailand

Dear Reviewer,

We appreciate the opportunity to revise our manuscript entitled " Smartphone used and social media addiction in undergraduate student" and would like to thank the reviewers for their insightful comments and suggestions. We have carefully considered each point and have made substantial revisions to our manuscript (as seen in Track Change). Since many of the texts in the revised manuscript have been edited to cover all comments/suggestion, we have listed the overall changes in the revised version of the manuscript for more understanding in brief as follows:

In the title, it has been changed from " Smartphone used and social media addiction in undergraduate student" to “The Impact of Smartphone Addiction on Reaction Time in Undergraduate Students: An Experimental Study”
In the introduction, we have inserted many of texts in this section for more correspondingly to the point of the objective in study.
In the methodology, we have also inserted and revisde many of texts in this section based on the suggestions/comments from all reviewers such as the flowchart of the study, explanation of the exclusion criteria, type of RT used in this study, as well as additional statistical analysis of this study.
In the result, we have adding the report of the descriptive statistical, and ANOVA analysis based on the suggestion by reviewer.
In the discussion, we have adding the limitation of the study, and mention of hypothesis based on the suggestion by reviewer.

Finally, we appreciate the reviewers' constructive feedback and hope that our revisions adequately address your concerns.

Thank you for considering our revised manuscript. We look forward to hearing from you.

Sincerely,
Authors

Reviewer 2

Dear Authors
There are certain comments/ queries / suggestions with respect to this manuscript. Please address them to improve upon the manuscript.

The title of the manuscript does not reflect the main objective and results presented in the manuscript.

Answer: Thank you very much for your kind suggestion. The title has been changed to “The Impact of Smartphone Addiction on Reaction Time in Undergraduate Students: An Experimental Study”

"In this study, we examined the features of smartphone addiction in adolescents aged 18 to 22 years" - there is no result presented with respect to this objective in the study. Also, adolescent age group does not include people 20 or above as per the World Health Organization definition. If some other operational definition has been used, please cite the source.

Answer: Thank you very much for your kind comment. For more accurately in the word “adolescent” used in this study, we have explained the definition of the word “adolescent” and “undergraduate”, as well as the overlappint in the age of both words in the introduction section as follows:

“Meanwhile some of the individuals who are predominant smartphone users are adolescents. Adolescence, as delineated by developmental psychology and esteemed organizations such as the World Health Organization (WHO), covers from early adolescence to late adolescence. In many definitions, it may also comprise young adults up to the age of 19 or even stretch into the early 20s. Undergraduates, in contrast, refer to those who are actively pursuing a bachelor's degree at a college or university. The terms 'undergraduate' and 'adolescent' refer to separate facets of an individual's existence. Although there are variations, there is a significant convergence in the normal age range linked to each. Adolescence, as per developmental psychology and organizations such the World Health Organization (WHO), refers to the period from early to late teens and may even include young adults up to the age of 19 or even early 20s in certain definitions. Most undergraduates commence their tertiary studies promptly after finishing secondary education, usually at approximately 18 or 19 years old. As a result, a significant proportion of college students are in the late adolescent stage.”

For more accuraltely understandble, we have edited the objective in this study with a word of “undergraduate” instead of “adolescent” as follows:

“The increasing significance of smartphones in everyday life, particularly among undergraduate student aged 18 to 22, emphasizes the delicate link between technology use and mental well-being. The objective of this study is to explore the impact of smartphone addiction on cognitive abilities, particularly reaction times, and to analyze the psychosocial repercussions of excessive smartphone usage. This initial investigation primarily examines the direct influence of smartphone addiction on reaction times while also recognizing the potential involvement of several risk factors.”

Fig 1 does not correspond to flowchart as the claim is made in the text in results section. In any case participant recruitment flowchart should be included in the methods section (when you put the correct figure in the manuscript).

Answer: Thank you very much for your comment. We have added the new flow chart figure in the manuscript as follows:

Figure 1 Flowchart of inclusion participants

The number of exclusions seems to be too large. What were the reasons to exclude all participants for myopia, impaired vision - were they still excluded if they were either corrected with glasses or were only of mild degree in nature?

Answer: Thank you very much for your comment. In this study, participants with myopia and impaired vision from certain studies, especially those focusing on cognitive tasks, reaction times, or visual processing, were excluded for several reasons. Firstly, we need to control our visual acuity. Since this study relies heavily on visual stimuli aims to ensure that all participants have a similar baseline for visual acuity to reduce variability in response times or accuracy that could be attributed to differences in vision rather than the cognitive or behavioral variable being studied. This issue was discussed by Bach (1996) who revealed the importance of accurately measuring visual acuity in research settings and how variations in acuity can affect the reliability of visual assessments. At the same time, we are concerned about the impact on reaction times. Since this study measures reaction times to visual stimuli, variations in vision clarity could introduce significant confounders, as those with uncorrected visual impairments might inherently respond more slowly or inaccurately. This issue was reported by Strang et al., (1999) who illustrate that even mild visual impairments can significantly impact the speed and accuracy of visual processing, thereby supporting the rationale for controlling visual acuity in studies where reaction time is a critical measure.

We have also added this explaination in the subsection of Participant in the Methodology section.

Ref:

Strang, N. C., Atchison, D. A., & Woods, R. L. (1999). Effects of defocus and pupil size on human reaction time. Journal of the Optical Society of America A, 16(3), 412-418.
Bach, M. (1996). The Freiburg Visual Acuity test-automatic measurement of visual acuity. Optometry and Vision Science, 73(1), 49-53.

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Reviewer Report

43 Views

12 Jul 2023 | for Version 1

Richard J. E. James, University of Nottingham, Nottingham, England, UK

43 Views Cite this report Responses(1)

Not Approved

The title includes reference to social media addiction, but this does not appear to be measured in the study. Social media use is included as an inclusion criteria, but the study is not measuring social media addiction.
There are some points where conceptualizations of behavioral addictions are a bit unclear. For instance, at the bottom of the first paragraph, the references for the claim that individuals with smartphone addiction endure various challenges are two papers on problematic internet use from the late 1990s. I think more specific and relevant evidence could be incorporated here.
Similarly in the second paragraph there are number of claims made about the severity of smartphone addiction that are open for debate. There is a critical literature that has highlighted many of the issues with the measurement of smartphone addiction, how it relates to other behavioural addictions (e.g. if somebody is using their phone extensively for social media use, do they have a smartphone, or a social media addiction?), and whether this translates into clinically meaningful levels of harm.
Again, some of the claims regarding smartphone addiction and adolescence are again debatable. The claim they are inextricably linked, and consider it to be a 'second personality' are particularly questionable. The vast majority of the literature samples adolescents and university students, and so this may be biased by the lack of research compared to other groups.
The final paragraph starts discussing social comparison, but it wasn't entirely clear how this related to the manuscript, and whether it ought to be included.
The introduction didn't introduce the rationale for the use of the dual tasking design, which I thought was a notable oversight that ought to be amended. No hypotheses were presented about the relationship between performance on the dual performance task and smartphone addiction - would one expect people with elevated levels of smartphone addiction severity to be faster or slower on the task?
The introduction also makes reference to comparing risk variables for smartphone addiction, but this doesn't seem to be reported in the results.
I appreciate that the authors' have conducted a power analysis to justify their sample size. However, my reading of this section is that the study is powered for the experimental effect (i.e. between the control, texting and calling conditions), and not any putative smartphone addiction effect. Therefore, it is not clear whether the data is appropriately powered for the effects the authors are trying to test. I suspect the study is underpowered for the purpose of testing any such effect. This should be included as a limitation.
The reporting of reaction times could be streamlined, and easier to follow for readers. For instance, I wasn't clear on the need for the distinction between the three different types of RT.
More details regarding of the statistical analysis ought to be reported. To me, the analysis conducted look like 3 sets of addiction vs. non-addiction group analyses for each condition, but this is not clear from the information presented. I think the type of analysis could be reported, as could the test statistics and a measure of error.
Hypotheses are only mentioned for the first time at the beginning of the discussion.
The discussion was unclear in places. The second half of the first paragraph starts discussing findings about the amount of smartphone use per session, but this isn't reported elsewhere in the manuscript. This was reported as being collected in the survey included with the data, but the methods talk about a different interview. The methods could be amended to make these passages clearer.

Is the work clearly and accurately presented and does it cite the current literature?

Partly
Is the study design appropriate and is the work technically sound?

Partly
Are sufficient details of methods and analysis provided to allow replication by others?

Yes
If applicable, is the statistical analysis and its interpretation appropriate?

Partly
Are all the source data underlying the results available to ensure full reproducibility?

Yes
Are the conclusions drawn adequately supported by the results?

Partly

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

Gambling, behavioural addiction, smartphone addiction

Respond to this report

Responses (1)

Author Response

13 Apr 2024

Teerachai Amnuaylojaroen, School of Energy and Environment, University of Phayao, Phayao, 56000, Thailand

In the title, it has been changed from " Smartphone used and social media addiction in undergraduate student" to “The Impact of Smartphone Addiction on Reaction Time in Undergraduate Students: An Experimental Study”
In the introduction, we have inserted many of texts in this section for more correspondingly to the point of the objective in study.
In the methodology, we have also inserted and revisde many of texts in this section based on the suggestions/comments from all reviewers such as the flowchart of the study, explanation of the exclusion criteria, type of RT used in this study, as well as additional statistical analysis of this study.
In the result, we have adding the report of the descriptive statistical, and ANOVA analysis based on the suggestion by reviewer.
In the discussion, we have adding the limitation of the study, and mention of hypothesis based on the suggestion by reviewer.

Finally, we appreciate the reviewers' constructive feedback and hope that our revisions adequately address your concerns.

Thank you for considering our revised manuscript. We look forward to hearing from you.

Sincerely,
Authors

Reviewer 1

This study reports the findings of an experimental study into the relationship between smartphone addiction, defined by cutoffs on the Thai translation of the SAS-SV, and reaction time performance on a dual task paradigm. No differences were found between the SA groups on task performance. I liked the use of an experimental design, and that the data was made publicly available. However, there are a number of issues with the manuscript as it presently stands, outlined below. In particular, I found the lack of hypotheses, issues with some methodological details, and conceptualizations of smartphone addiction affected the overall soundness of the manuscript, but these can be addressed with revisions. My comments are outlined below:

The title includes reference to social media addiction, but this does not appear to be measured in the study. Social media use is included as an inclusion criteria, but the study is not measuring social media addiction.

Answer: Thank you very much for your kind suggestion. The title has been changed to “The Impact of Smartphone Addiction on Reaction Time in Undergraduate Students: An Experimental Study”

There are some points where conceptualizations of behavioral addictions are a bit unclear. For instance, at the bottom of the first paragraph, the references for the claim that individuals with smartphone addiction endure various challenges are two papers on problematic internet use from the late 1990s. I think more specific and relevant evidence could be incorporated here.

Answer: Thank you very much for your kind suggestion. At the first paragraph in the introduction section, we have added some statements for more specific and relevant evidences as follows:

“Prolonged use of smartphones exposes individuals to several detrimental physical and psychological effects. For example, dry eyes, carpal tunnel syndrome, repetitive strain injury, wrist, neck, back, and shoulder pain, migraine headaches, thumb, index, and middle finger pain, and phantom pocket vibration syndrome are physical symptoms associated with smartphone addiction.^{4 ,} ⁵ (AlBarashdi et al., 2016; Sebastian & Jinesh, 2018)."

Similarly in the second paragraph there are number of claims made about the severity of smartphone addiction that are open for debate. There is a critical literature that has highlighted many of the issues with the measurement of smartphone addiction, how it relates to other behavioural addictions (e.g. if somebody is using their phone extensively for social media use, do they have a smartphone, or a social media addiction?), and whether this translates into clinically meaningful levels of harm.

Answer: Thank you very much for your kind suggestion. At the second paragraph, in the introduction section, we have inserted some statements for the issues of smartphone addiction realted to several detrimental psychological impacts as follows:

“It has also been found to have detrimental psychological impacts¹⁶(Kuss & Griffiths, 2011). Excessive use of smartphones negatively affects the quality of students' sleep ^{17 ,} ^{18, 19}^{, 20,} (Ibrahim et al., 2018; Kurugodiyavar et al., 2017; Sahin et al., 2013; Wang et al., 2019) and result in insomnia ²¹(Van Deursen et al., 2015). Many studies have established a correlation between smartphone usage and mental disorders, such as stress and anxiety ²² (Boumosleh & Jaalouk, 2017). Other potential adverse consequences include loss of control ²³(Gupta et al., 2016) and maladaptive behavioral problems ²⁴ (Hwang et al., 2012). Smartphone addiction has a poor correlation with both life satisfaction and performance in school ²⁵(Samaha & Hawi, 2016).”

Again, some of the claims regarding smartphone addiction and adolescence are again debatable. The claim they are inextricably linked, and consider it to be a 'second personality' are particularly questionable. The vast majority of the literature samples adolescents and university students, and so this may be biased by the lack of research compared to other groups.

Answer: We acknowledge the focus of existing research on adolescents and university students, highlighting this as a limitation and noting the potential for selection bias. This sets the stage for why your study is mindful of broader implications. We have inserted several texts to explain those as follows:

“A substantial amount of study has been devoted to the examination of smartphone addiction, with university students and adolescents serving as the primary cohorts for investigation (Kuss & Griffiths, 2011; Sahin et al., 2013). Although the emphasis has resulted in significant findings regarding the trends and repercussions of using smartphones among the youth population, it also presents the possibility of selection bias. The focus on younger age groups and life stages in this analysis of smartphone addiction might not encompass its intricacies (Ibrahim et al., 2018; Kurugodiyavar et al., 2017). In the context of this study's invalidity, this study seeks to contribute by examining the broader consequences associated with smartphone addiction. Through this approach, we aim to contribute to a more holistic comprehension of its ramifications, recognizing that the phenomenon of smartphone addiction transcends the conventional focus on adolescent and university students.”

The final paragraph starts discussing social comparison, but it wasn't entirely clear how this related to the manuscript, and whether it ought to be included.

Answer: Thank you very much for your kind comment. For more accurately related to the manuscript objective, we have revised the final paragraph in the introduction section as follows:

“The increasing significance of smartphones in everyday life, particularly among young adults aged 18 to 22, emphasizes the delicate link between technology use and mental well-being. The objective of this study is to explore the impact of smartphone addiction on cognitive abilities, particularly reaction times, and to analyze the psychosocial repercussions of excessive smartphone usage. This initial investigation primarily examines the direct influence of smartphone addiction on reaction times while also recognizing the potential involvement of several risk factors.”

The introduction didn't introduce the rationale for the use of the dual tasking design, which I thought was a notable oversight that ought to be amended. No hypotheses were presented about the relationship between performance on the dual performance task and smartphone addiction - would one expect people with elevated levels of smartphone addiction severity to be faster or slower on the task?

Answer: Thank you very much for your kind comment. We have added a paragraph for the rationale for the use of the dual tasking in the introduction sectoion as follows:

“Dual-tasking refers to the act of executing two activities simultaneously, whereas multitasking refers to the act of performing more than two tasks simultaneously³⁴(Won et al., 2012). Engaging in activities such as walking or working while simultaneously utilizing various features of a smartphone can be referred to as dual- or multitasking. Nevertheless, engaging in multiple tasks simultaneously can potentially result in a loss of cognitive capacity, hence increasing the risk of experiencing a fall or injury in an unforeseen and unintentional circumstance. The capacity to sustain equilibrium in both stationary and moving scenarios serves as the foundation for executing functional tasks during the course of diverse routine activities ³⁵(Vuillerme et al., 2002). The functional activities requiring dynamic balance are achieved by the coordinated interplay of the ankle joints, knee joints, hip joints, and their respective accompanying muscles, as well as the shoulder joints and their surrounding muscles. Cognitive ability is closely linked to dynamic balance. Engaging in dual-tasking with a smartphone while walking, such as listening to music, sending a message, online surfing, or playing a game, is known to impair the dynamic balance required for functional activities by diminishing cognitive capacity. The act of using a mobile phone while walking is a common scenario known as a dual-task paradigm ³⁶(Plummer et al., 2013). This means that individuals are required to concurrently engage in mobile phone operations and walking duties. The notion of finite capacity scheduling suggests that the outcome of different activities determines the extent to which cognitive or motor performance is affected ^37,38(Coker, 2017; Wickens and Damos, 2020). The mobile phone task involves integrating numerous single activities, such as mathematics, language, memory, and motor skills, while walking, as opposed to doing a single task individually. The demand for cognitive resources in this activity is notably higher compared to other simpler activities ³⁹(Tan et al., 2022). Prior research has demonstrated that engaging in the dual-task paradigm of using a mobile phone while walking is more prone to inducing diminished awareness of the environment, impaired motor function in the lower extremities, and distraction compared to other uncomplicated tasks performed while walking among pedestrians ^40,⁴¹(Kim et al., 2020; Tan et al., 2022).”

The introduction also makes reference to comparing risk variables for smartphone addiction, but this doesn't seem to be reported in the results.

Answer: Thank you very much for you comment. For more correspondly to the main objective of the study that is to examine the effect of smartphone addiction on reaction times, not comparing the risk variable to the smartphone addiction. We have revised the introduction appropriately.

I appreciate that the authors' have conducted a power analysis to justify their sample size. However, my reading of this section is that the study is powered for the experimental effect (i.e. between the control, texting and calling conditions), and not any putative smartphone addiction effect. Therefore, it is not clear whether the data is appropriately powered for the effects the authors are trying to test. I suspect the study is underpowered for the purpose of testing any such effect. This should be included as a limitation.

Answer: Thank you very much for you kind comment. We have added a paragraph of the limitation in study in the last paragraph of the discussion section as follows:

“Although this study utilized a careful methodology, which involved conducting a power analysis to determine the required sample size for detecting variations in reaction times under control, texting, and calling conditions, it is crucial to acknowledge a potential limitation in our examination of the impacts of smartphone addiction. The initial power analysis was primarily intended to ensure an adequate sample size for detecting the experimental effects of dual-tasking conditions. However, it may not have been properly adjusted to accurately identify the more subtle but important influence of different levels of smartphone addiction on these cognitive tasks. After careful consideration, we acknowledge that the study may not have enough statistical power to definitively investigate the subtle impacts that the intensity of smartphone addiction may have on individuals' performance in these activities. This constraint implies that the conclusions on smartphone addiction should be approached with care since the study could not have possessed sufficient statistical strength to identify all significant effects linked to the intensity of smartphone addiction. Subsequent investigations in this field would be enhanced by performing a power analysis particularly designed to evaluate the impact of smartphone addiction. This may involve increasing the sample size or employing a more precise measure of addiction intensity. It is essential to overcome this constraint in order to enhance our comprehension of the cognitive consequences of smartphone addiction and to create specific therapies to reduce its negative impacts. Regarding the results and the original hypotheses of this investigation, further research should explore in greater detail the subtle mechanisms by which extended smartphone usage impacts cognitive functions. Conducting research on auditory reaction times and expanding the study to include various age groups could yield a more comprehensive comprehension of the cognitive consequences associated with smartphone addiction. Furthermore, future research should investigate the possible task-specific cognitive adjustments in those who use smartphones frequently, which could help reduce the anticipated detrimental impacts on dual-task performance.”

The reporting of reaction times could be streamlined, and easier to follow for readers. For instance, I wasn't clear on the need for the distinction between the three different types of RT.

Answer: Thank you very much for your suggestion. For clear understanding to the reader, we have inserted several texts indicating specifically RT’ type in the subsection of Measurement in Methodology section as follows:

“In this study, Choice RT involves multiple stimuli and multiple responses, which directly corresponds to the setup of the study where participants respond to different colored lights with different buttons. The need to recognize the color of the light and choose the correct button to press makes it a choice reaction time task, as there are several stimuli (different colors) and several possible responses (different buttons).
This study focuses on the evaluation of reaction times (RT) as a method for measuring the rate at which an individual reacts to a stimuli. It is crucial to specify that the specific sort of reaction time we are emphasizing is referred to as 'Choice RT.' The relevance of this particular type of reaction time lies in the fact that participants are presented with various stimuli and are required to make a deliberate choice on the appropriate response to carry out.
In further detail, Choice RT scenarios are distinguished by the existence of multiple potential stimuli, each necessitating a separate and specific reaction. Our experimental setup involves presenting participants with lights of varying hues, specifically red, blue, and yellow. Participants are required to hit a designated button for each color. This choice element distinguishes it from 'Simple RT,' which involves a single stimulus and automatic reaction, and from 'Recognition RT,' where the aim is to respond to certain stimuli while ignoring others.

More details regarding of the statistical analysis ought to be reported. To me, the analysis conducted look like 3 sets of addiction vs. non-addiction group analyses for each condition, but this is not clear from the information presented. I think the type of analysis could be reported, as could the test statistics and a measure of error.

Answer: We acknownledge for the additional statistical analysis. We have added a couple paragraph to report the statistical analysis with descriptive statistical and ANOVA analysis in the results section as follows:

“Analyzing the reaction times under different smartphone usage situations reveals clear trends for persons with and without addiction in Table 4. The non- addiction group exhibited the shortest average reaction time of 0.99 seconds after avoiding from smartphone usage. The results also showed a relatively narrow range of values, as evidenced by the standard deviation of 0.28 seconds. Participating in phone conversations increased response time to an average of 1.22 seconds, while the variation remained similar to the condition when no phone was used. Nevertheless, the texting activity showed the most notable increase, with an average response time of 1.73 seconds and a significantly larger standard deviation, indicating more variation in how texting impacted the reaction times of persons in this particular group. In comparison, the addiction group exhibited a slightly higher initial response time of 1.04 seconds when not using smartphones, while the range of values was narrower. The effect of phone calls was particularly noticeable among those with addiction, as their average response time increased to 1.309 seconds and was accompanied by a higher standard deviation, indicating a larger variation in response times among individuals. The "Addiction" group also saw a comparable impact from texting, with an average reaction time of 1.74 seconds and the largest level of variability across all conditions, as demonstrated by the standard deviation. Reaction times consistently increased in both groups as they transitioned from avoiding smartphones to texting. Although the "Addiction" group had somewhat greater average reaction times in every situation, their reaction times were more consistent under the no-use condition compared to the "No addiction" group. The 95% confidence intervals for the "Addiction" group exhibited higher values, indicating a potential association between addiction and longer reaction times. However, the overlapping intervals of the two groups suggest that the difference in reaction times between the two groups is not significant. In summary, the descriptive statistics reveal a noticeable pattern of longer reaction times linked to the usage of smartphones, particularly for tasks that demand more cognitive effort, such as texting.
The ANOVA analysis in Table 5 showed that those without addiction had an F-statistic of 29.41 and a p-value of roughly < 0.001, which indicates high significance. This result demonstrates a statistically significant difference in response times when comparing the absence of smartphone usage, making phone calls, and sending text messages among individuals in this group. The inference is that the nature of smartphone engagement significantly impacts the response times of non-addicted persons, with certain activities resulting in slower reactions compared to others. Similarly, the analysis conducted for the "Addiction" group yielded an F-statistic of 23.18, along with a significant p-value of roughly < 0.001. This validates that, similar to the "No addiction" group, there are statistically significant disparities in reaction time among those with addiction across the three smartphone-using circumstances. The experimental conditions in which the reaction time was assessed (absence of smartphone usage, during a phone call, or while texting) significantly influenced the recorded reaction times. The notable F-statistics in both groups indicate that the change in reaction times is not consistent across conditions; rather, it fluctuates based on whether individuals were not utilizing their smartphones, were involved in a phone call, or were texting. The p-values, which are significantly lower than the typical alpha level of 0.05, provide strong evidence that the observed changes in reaction times are not a result of random chance but rather indicate a genuine impact of the smartphone use condition. These findings emphasize the significance of the circumstances in which smartphones are used when evaluating their influence on cognitive performance, specifically in terms of reaction time.
In summary, the descriptive statistics and ANOVA analyses provide a thorough understanding of how reaction times are affected by smartphone usage in different situations for persons with and without addiction. The descriptive statistics indicate that reaction times exhibit an upward trend as individuals transition from not using smartphones to making phone calls, and then to sending text messages, for both groups. The heightened fluctuation in reaction times seen while texting, as indicated by the greater standard deviations, implies that this task may necessitate additional cognitive resources, thereby exerting a more pronounced impact on reaction times. This pattern is consistent for both the non-addiction and addiction groups, although individuals with addiction exhibit somewhat faster reaction times overall. The one-way ANOVA results provide additional support for these findings, demonstrating statistically significant variations in reaction times among the three smartphone use circumstances within each group. The "No addiction" group's F-statistic and p-value suggest that various smartphone activities have a differential impact on reaction times. The addiction group likewise has a significant impact of smartphone use circumstances on reaction times, as evidenced by the ANOVA results.”

Hypotheses are only mentioned for the first time at the beginning of the discussion.

Answer: Thank you very much for your suggestion. We have recognized the mention of the hypothesis in the discussion, many texts have been inserted in the discussion section as follows:

“This study aims to investigate the influence of smartphone addiction on visual reaction time (VRT) in several settings, such as control, texting, and chatting situations, as hypothesized. The results of our study did not support our initial hypothesis, which suggested that those with higher degrees of smartphone addiction would have slower VRT due to cognitive overload. Specifically, we found no significant differences in VRT between the group of individuals with smartphone addiction and the control group, regardless of the settings. This result implies a more intricate relationship between smartphone addiction and cognitive performance than originally anticipated.”

“Although we hypothesized that regular smartphone use, which requires higher cognitive capacities, could hinder the ability to perform two tasks simultaneously, resulting in longer reaction times, the findings did not confirm this expectation. One potential reason for this surprising discovery could be attributed to the adaptive capacities of individuals who use smartphones frequently. The study found that social networking was the most popular smartphone application among those with addiction, and they used it for much longer periods of time compared to the control group. The significant involvement with smartphones may have resulted in a type of task-specific cognitive adjustment, allowing these individuals to retain similar VRTs as those who are less involved with smartphones.”

“The lack of significant disparities in VRT among the groups contradicts our initial assumptions and prompts a reassessment of the ways in which smartphone addiction impacts cognitive function. According to capacity theory and bottleneck accounts, we hypothesized that the dual-task interference would be more pronounced in those with smartphone addiction. Nevertheless, the comparable performance observed in both groups indicates that factors such as task prioritization and cognitive resource allocation likely have a substantial influence on moderating the impact of smartphone usage on attention and reaction times.”

The discussion was unclear in places. The second half of the first paragraph starts discussing findings about the amount of smartphone use per session, but this isn't reported elsewhere in the manuscript. This was reported as being collected in the survey included with the data, but the methods talk about a different interview. The methods could be amended to make these passages clearer.

Answer: Thank you very much for your comment. We have inserted many texts to make these passages clearer in the subsection of Procedure in the Methodology section as follows:

“Following the initial evaluation using the SAS-SV-TH, participants were monitored during different experimental sessions intended to replicate their usual smartphone usage. Every session was designed to simulate a practical setting for texting or talking, with a duration that nearly reflected their self-reported typical usage, which was around 30 minutes. In order to obtain a thorough understanding of everyday smartphone usage, participants were involved in multiple sessions of such nature throughout the day. This methodology enabled us to gather detailed information on the potential impact of extended and repetitive smartphone usage within a 24-hour period on reaction speeds.”

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Competing Interests

The authors declare no conflicts of interest.

Alongside their report, reviewers assign a status to the article:

Approved - the paper is scientifically sound in its current form and only minor, if any, improvements are suggested

Approved with reservations - A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.

Not approved - fundamental flaws in the paper seriously undermine the findings and conclusions

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Smartphone use and social media addiction in undergraduate students

Abstract

Keywords

Introduction

Methods

Study design and setting

Participants

(1)

Ethical considerations

Measurement

Figure 1. Flowchart of the Study.

Procedure

Table 1. Questionnaire for interview.

Statistical analysis

(1)

(2)

Results

Table 2. Demographic Information.

Table 3. Average Reaction Times of both groups across all condition of smartphone use.

Figure 2. Reaction time in the difference conditions of the smartphone use.

Discussion

Conclusions

Data availability

Underlying data

Acknowledgments

References

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