Impact of COVID-19 on Mobile Technology use in adults in the United States

Instrument

At the pilot testing phase of survey development, responses from 17 female and 16 male respondents were included in the data analysis. None of the participants reported difficulty in accessing or finishing the survey. Ten participants gave positive feedback on the survey content. One participant had minor suggestions on the wording of the survey and added extra response options on questions regarding education level and reasons for adopting MT for the first time. The survey was refined based on the participants’ feedback.

The pilot-tested survey contained both closed-ended and open-ended questions. If the participant agreed to join the study and confirmed they met the inclusion criteria, a paragraph introducing MT was displayed to the participant. For questions about MT use before the pandemic, all participants were asked to answer the questions by recalling their experience before COVID-19.

There were four sections in the survey. Eleven questions collected data on participant characteristics and assessed the impact of COVID-19 on the individual’s life. Twelve questions collected information on participants’ experience with MT use before and during COVID-19; these included questions on the types of MT used, how long the participants had used MT, the main reason for using MTs, the frequency of using MTs each day, the top five most frequently used functions, and the top three factors that influence the decision to engage in MT use. Twenty-two statements (including 16 positive and six negative attitudes measured by a four-point Likert score) collected information about perspectives toward MT; these statements were adopted and modified from the extended Unified Theory of Acceptance and Use of Technology (UTAUT2), and studies aimed to examine MT acceptance and use (Boontarig et al., 2012; Shaw & Sergueeva, 2019; Venkatesh et al., 2012). Finally, two open-ended questions encouraged respondents to comment on their responses in more depth. The list of the questions can be found in the Extended data (Lin, 2023).

Data cleaning

A total of 2,035 responses were recorded on the Qualtrics XM database (a free alternative could be the SoGoSurvey platform). Survey responses that met any of the following conditions were excluded from data analysis: Participants who did not meet the inclusion criteria (n=576), incomplete survey responses (participants who failed to read all the questions or skipped 50% of questions) (n=174), and unreliable survey responses (n=73). The strategies to identify unreliable survey responses included 1) participant spent less than three minutes on the survey; 2) duplicates or responses flagged as spam (when multiple identical responses were submitted from the same IP address within 12 hours) by the Qualtrics XM software; and 3) survey completed by a robot (the Qualtrics XM has adopted Google’s invisible reCaptcha technology for robot detection). After data cleaning, 1,212 usable survey responses were kept for analysis.

Data analysis

Data analyses were completed using IBM SPSS version 28, which involved descriptive statistics demonstrating participant characteristics and Wilcoxon signed-rank test for the paired data that explored differences before and during COVID-19. Quotes collected from open-ended questions were used to support the findings and enrich the discussion and conclusion.

Ethics approval

This study was approved by the University of Kentucky Medical Institutional Review Board (IRB) on Feb 25, 2021 (IRB number: 65430), and was performed in line with the principles of the Declaration of Helsinki.

Participant consent

An IRB-approved electronic informed consent form was presented as the online survey cover letter and obtained from all participants included in the study. Each participant had to read the electronic consent and provide consent by ticking the box that represents agreement.

Change in MT use behavior

MT daily use frequency during COVID-19 was significantly increased (z=-19.740, p<0.001) compared to before (Table 1). Less than half of the participants (43.7%) spent more than 4 hours per day using MT before the pandemic, but this number increased to 68.2% during the pandemic.

All the participants provided information about their five most used MT functions before and during COVID-19 (ranked from most to least used). According to the ranks assigned by the participants to each function, the “text messaging” function was the most used before COVID-19, followed by “emails,” “voice calls/meetings,” “GPS/navigation,” “following breaking news,” and “playing games.” The most used MT functions during COVID-19 were “text messaging,” followed by “emails,” “voice calls/meetings,” “taxi/car service,” “online shopping,” and “video calls/meetings.” There was a significant rise (p<0.001) in the rank of harnessing the following MT functions during COVID-19 compared to before: video calls/meetings (percentage of participants who reported an increased rank: 29.3%, z=-12.160), online education (participants: 9.7%, z=-4.726), grocery/food delivery (participants: 22.0%, z=-11.083), online shopping (participants: 28.9%, z=-5.110), getting information about a health condition (participants: 11.6%, z=-5.652), and ordering taxi/car services (participants: 23.5%, z=-5.531).

In addition to use frequency and choice of functions, more than half of the participants (54.5%) reported experience using a new MT function during the pandemic. These included: online meetings, shopping (including delivery or pickup), health monitoring, receiving news updates, making reservations and checking-in, fitness programs, entertainment, and banking. In the open-ended section of the questionnaire, participants described their experience:

Change in MT use perception

There was a significant increase (z=-20.448, p<0.001) in the feeling of necessity to use MT during COVID-19 compared to before (Table 1). Few participants (7.0%) did not feel the need to use MT in their daily life; this number decreased to 2.7% during the pandemic. One-third of the participants (33.2%) felt a strong need to use MT every day before COVID-19, and the number increased to 73.5% during COVID-19.

All the participants identified the top three factors (ranked from most to least important) that affected their decision to use MT before and during COVID-19. According to the ranks assigned by participants, the most crucial factor affecting the decision to use MT before COVID-19 was the “availability of functions that support daily life,” followed by the “necessity of using MT,” “ease of use,” and “pleasure of using MT.” On the other hand, the most crucial factor that affected the decision to use MT during COVID-19 was the “availability of functions that support daily life,” followed by the “necessity of using MT,” “social benefits of using MT,” and “ease of use.” There was a significant rise (p≤0.001) in considering the following factors essential in deciding to use MT during COVID-19 compared to before: physical benefits (percentage of participants who reported an increased rank: 14.9%, z=-4.440), social benefits (participants: 23.1%, z=-3.238), emotional benefits (participants: 18.3%, z=-6.343), the availability of functions that support daily life (participants: 29.3%, z=-4.265), and necessity (participants: 27.3%, z=-4.902).

Change in perspectives toward MT

Participants’ agreement level to fifteen statements regarding positive perspectives toward MT significantly increased (p<0.001) during COVID-19 compared to before (Table 2). These statements reflected participants’ views about ease of use, the pleasure to use, and the benefits of using MT. Participants’ agreement level to one statement regarding positive view did not reach a significant difference (p>0.05) compared between the time before and during COVID-19; the statement was “MTs are reasonably priced.”

Participants’ agreement level with two statements regarding negative perspectives toward MT significantly decreased (p<0.001) during COVID-19 compared to before. These statements reflected pleasure to use and emotional benefits, which were 1) “Using the MT is annoying;” and 2) “I have fear of using MT.” Two statements regarding negative views significantly increased (p<0.001) during COVID-19 compared to before. These statements reflected perceived risk and perceived sacrifice of using MT, which were 1) “I am worried that my privacy could be threatened due to the use of MT;” and 2) “Using MT limits my human interaction in daily life.” Two statements regarding negative attitudes did not reach a significant difference (p>0.05) between the time before and during COVID-19. These statements reflected the perceived sacrifice and perceived price value of MT, which were 1) “Using MT prevents me from developing other habits;” and 2) “MTs are too expensive for me to use.”

Strengths and limitations

This study included the responses from participants of each region of the United States, which made our findings representative and reflected the MT use phenomenon in the United States. Our data cleaning process was strict and included multiple criteria to exclude unreliable data. Our study identified a shift of values regarding factors that affect MT use decisions, which offers the potential for developing strategies to increase MT adoption. The increase in MT adoption would provide a vast platform for delivering services to fulfill the variety of needs of MT users. Moreover, the findings of this study indicated a decrease in the variation of perspectives toward MT. We discovered substantial growth of acceptance toward MT during COVID-19; this is thus an excellent time to educate people about technology use and encourage teleservices development. Although the pandemic is less severe compared to the beginning of the outbreak and the COVID-19 restrictions are mostly lifted, the knowledge from this study in MT use during COVID-19 may serve to understand technology needs in this population better and to better plan for implementing new technologies.

Our study had several limitations—first, the lack of diversity in participants and recruitment methods. The data was collected during the severe period of the pandemic; thus, the recruitment method was extremely limited. Second, adding additional questions such as participants’ household arrangements, employment information, and the impact of COVID-19 on participants’ health would enrich the findings. Third, the survey study required participants to recall their experience with MT before COVID-19, which may lead to memory recall bias. Fourth, the survey question design could not consider personal factors (such as personality, intelligence, emotional state, and learning ability) that are more complex to measure. Fifth, this study might have response bias since the data was self-reported. Although the self-reported data had the advantage of revealing participants’ actual thoughts, participants’ concerns with social desirability might influence the data unconsciously.

Finally, it is essential to acknowledge that a shift in MT use behavior might already have occurred prior to the pandemic; COVID-19 might have simply provided a convenient excuse or trigger in accelerating behavior change. The data in this study do not allow us to explore MT use behavior changes before the pandemic, but such changes certainly occurred during the pandemic. More details about participant information and data on behavioral decisions during COVID-19 with respect to MT use would provide deeper insight.

Future directions

This study could help design future studies to examine the relationships between health, technology implementations, acceptance, and adoption among middle-aged and older adults in the United States during the continuous waves of pandemic and post-pandemic. Comprehensive knowledge regarding the associations between MT use behavior, physical health, and mental health warrant longitudinal studies in the future. MT use could become even more critical in maintaining the quality of life; thus, future studies could consider recruiting diverse participant groups, including non-technology users, to explore MT use and adoption. Providers working on service delivery via mobile devices should explore strategies for increasing learning motivation. Developing strategies to give people a comfortable experience while embracing technology and making people in diverse situations learn fast will be more critical than ever. A 56-year-old female participant in the study explained, “I worry that as I get older, the world will depend more on mobile technology, and my ability to use it will decline.” A 63-year-old female who described her experience of using MT noted, “The technologies change so quickly, that I gave up on trying to keep up with all of them.” Technology use is supposed to bring convenience and efficiency to human beings; it is essential to reduce the burden of people trying to use it. Following the rapid steps of technology evolution, the question of how to provide a friendly interface or strategy for human-machine interaction demands immediate attention.