Fatalism and knowledge associated to diabetes mellitus type 2 risk perception in Mexican population during COVID-19 confinement

Geu Mendoza-Catalán; Alicia Álvarez Aguirre; Claudia Jennifer Domínguez Chávez; María del Rosario Tolentino Ferrel; Alma Angélica Villa Rueda; Elizabeth Guzmán Ortiz

doi:10.12688/f1000research.134266.1

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Research Article

Fatalism and knowledge associated to diabetes mellitus type 2 risk perception in Mexican population during COVID-19 confinement

[version 1; peer review: 2 not approved]

Geu Mendoza-Catalán¹, Alicia Álvarez Aguirre², Claudia Jennifer Domínguez Chávez¹, María del Rosario Tolentino Ferrel³, Alma Angélica Villa Rueda¹, Elizabeth Guzmán Ortiz ³

Geu Mendoza-Catalán¹, Alicia Álvarez Aguirre², [...] Claudia Jennifer Domínguez Chávez¹, María del Rosario Tolentino Ferrel³, Alma Angélica Villa Rueda¹, Elizabeth Guzmán Ortiz ³

PUBLISHED 03 Jul 2023

Author details Author details

¹ Faculty of Nursing, Universidad Autonoma de Baja California, Mexicali, Baja California, 21280, Mexico
² Department of Clinical Nursing, Universidad de Guanajuato, Celaya, Guanajuato, 38050, Mexico
³ Nursing and Obstetrics, Universidad de Guanajuato, Celaya, Guanajuato, 38050, Mexico

Geu Mendoza-Catalán
Roles: Conceptualization, Investigation, Methodology, Writing – Original Draft Preparation

Alicia Álvarez Aguirre
Roles: Data Curation, Formal Analysis

Claudia Jennifer Domínguez Chávez
Roles: Investigation, Supervision, Writing – Review & Editing

María del Rosario Tolentino Ferrel
Roles: Supervision, Visualization, Writing – Review & Editing

Alma Angélica Villa Rueda
Roles: Resources, Supervision, Writing – Review & Editing

Elizabeth Guzmán Ortiz
Roles: Project Administration, Supervision, Writing – Review & Editing

OPEN PEER REVIEW

REVIEWER STATUS

This article is included in the Sociology of Health gateway.

Abstract

Background: People with fatalistic beliefs and lack of knowledge of healthy lifestyles tend to show conformism and resignation due to their state of health. Even people with fatalism consider that contracting a disease is divine punishment, and this is reflected when they perform in unhealthy behaviours. The relationship between fatalistic beliefs, knowledge about diabetes risk factors, and perception of diabetes risk in Mexican adults during the COVID-19 pandemic were evaluated.
Methods: The study design was cross-sectional and correlational. The study included individuals between 30 and 70 years of age, from a rural community in Guanajuato, Mexico. The data collection was done electronically.
Results: The average age was 29.2 years (SD = 10.5), 55% were women, 52.3% were single, 36.2% had university studies and 57.3% were working. Perceived DMT2 risk was inversely related to fatalistic beliefs. Knowledge level was positively correlated to DMT2 risk perception. In multiple linear regression, pessimism and divine control dimensions were the only predictors of DMT2 risk perception.
Conclusions: In young adults, knowledge increases regarding DMT2 risk perception. But the higher the fatalistic beliefs the lower the level of knowledge and the lower the perception of DMT2 risk.

Keywords

Perception, diabetes mellitus type 2, fatalistic beliefs, knowledge

Corresponding author: Elizabeth Guzmán Ortiz

Competing interests: No competing interests were disclosed.

Grant information: The author(s) declared that no grants were involved in supporting this work.

Copyright: © 2023 Mendoza-Catalán G 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: Mendoza-Catalán G, Álvarez Aguirre A, Domínguez Chávez CJ et al. Fatalism and knowledge associated to diabetes mellitus type 2 risk perception in Mexican population during COVID-19 confinement [version 1; peer review: 2 not approved]. F1000Research 2023, 12:771 (https://doi.org/10.12688/f1000research.134266.1) First published: 03 Jul 2023, 12:771 (https://doi.org/10.12688/f1000research.134266.1) Latest published: 07 Apr 2025, 12:771 (https://doi.org/10.12688/f1000research.134266.2)

Introduction

People with chronic diseases such as type 2 diabetes mellitus (T2DM) are the most vulnerable group of people for hospital incidence and mortality during the COVID-19 pandemic (coronavirus disease 2019).¹^,² Recent studies reported that during emergency care, people with COVID-19 were diagnosed as new cases of T2DM,³^,⁴ suggesting that people were unaware of their disease until admission to the hospital. Therefore, this situation may have generated concern in the general population about their health status and their perceived risk of T2DM.

The perceived risk of T2DM is the individual’s appreciation of the probability of developing the disease in the future. People who perceive a higher T2DM have more intention and adopt healthier lifestyles to prevent the disease.⁵ This type of risk perception increases in women, those who are older, have a family history of diabetes, are overweight/obese, consume sugary drinks, do not consume fruits and vegetables, have a previous diagnosis of hypertension, have knowledge about the risk factors for T2DM and have a poor perception of their health status.⁶^–¹⁰ However, a study conducted in Alemannia, reports that people with prediabetes and undiagnosed T2DM report low risk perception,¹¹ the same as in the Mexican population.¹² The low risk perception of T2DM may be due to different factors such as beliefs that diseases are unpredictable, or fatalistic beliefs.¹³ Fatalistic beliefs are considered as the idea that there is a force superior to the human being that determines the facts of life; this belief is referred to as external locus, luck, fate, destiny, or divine control.¹⁴ People with fatalistic beliefs adopt pessimistic or despair behaviors, whose behavior results in thoughts that death and disease are inevitable.¹⁵ This type of belief is considered an important coping factor when faced with the diagnosis of a chronic disease,¹⁶ that is to say people with higher fatalistic beliefs use health services less, abandon treatments, and show higher mortality rates.¹⁷^,¹⁸

Other studies report that fatalistic beliefs minimize and underestimate health risk because people do not comply with preventive behaviors,¹⁹^–²¹ for example, preventive measures to avoid infection by COVID-19, therefore people with fatalistic beliefs may underestimate the risk of chronic diseases such as T2DM. So far, the association between fatalistic beliefs, knowledge, and perceived risk of T2DM has not been demonstrated. How people perceive themselves and feel vulnerable to developing chronic diseases is a predictor for lifestyle change and disease prevention. However, fatalistic beliefs may be a factor that underestimates knowledge of risk factors and perceived risk of T2DM. Therefore, the aim of this research was to assess the relationship between fatalistic beliefs, knowledge regarding the risk factors of diabetes, and the perception of T2DM in Mexican adults during the COVID-19 pandemic.

Methods

Ethics and consent

The study followed the guidelines of declaration of Helsinki and the General Health Law on health research in Mexico, and it was approved by the Ethics and Research Committee of the University of Guanajuato, Mexico with permit number DCSI-CI 20190308-3. Written informed consent was obtained from participants before their data was collected. Ethics approval was granted in 2019.

Design and participants

The study design was cross-sectional and correlational. We had included adult men and women aged 30 to 70 years, residents of San Miguel Eménguaro, Salvatierra, Guanajuato, Mexico. We had excluded persons with a diagnosis of type 1, type 2, and gestational diabetes. The sample was estimated using the statistical program G*power 3.1.4, with 95% reliability, 90% power and effect size of.08, which gave a sample of 218 people.

Data collection

Participants were invited through online social networks (Facebook, WhatsApp and Instagram). The access link for the survey (hosted on Google Forms) was electronically shared through social networks. The invitation stated the objective of the survey, the declaration of respect for the confidentiality and anonymity of information, as well as that the survey was aimed at residents of San Miguel Eménguaro, Salvatierra, Guanajuato. When the link was opened, the informed consent form with the option to agree to participate in the study was displayed first. Subsequently, information on sociodemographic data was requested and ended with the completion of the questionnaires. We restricted to survey to only allow one entry per person. Data collection was carried out from August to November 2020. The study followed the guidelines of declaration of Helsinki and the General Health Law on health research in Mexico.

Study variables

Independent variables: fatalism and knowledge.

Dependent variable: Perceived risk of Type 2 Diabetes Mellitus.

Questionnaires

A sociodemographic data card was used to collect information such as age, sex, marital status, schooling, and occupation.

To evaluate fatalism, the Multidimensional Fatalism Scale in Spanish¹⁵ was used, with 30 statements grouped into five factors: fatalism, pessimism/hopelessness, internal locus, luck, and divine control with a response from 1 to 5, where 1 means frequently disagree and 5 means frequently agree, with a maximum score of 150 points and a minimum of 30 points. The higher the score, the greater the fatalism. Cronbach’s alpha in this study was .88.

In addition, we used of Risk Perception Survey for Developing Diabetes (RPS-DD), which contains 43 items that measures beliefs about one’s risk for developing diabetes. This scale has six subscales: personal control (4 items), worry (2 items), optimistic bias (2 items), personal disease risk (15 items), comparative environment risk (9 items), and knowledge of diabetes risk factors (11 items). The higher the score the higher the perceived risk of T2DM.²²^,²³ To evaluate knowledge of risk factors, a subscale of the same instrument with 11 questions was used. Each question has 4 answers (increases the risk, has no effect on risk, decreases the risk and don’t know). The items are dichotomously scored, correct/incorrect and the total sum of the subscale is from 0 to 11, the higher the score, the greater the knowledge.²³ Cronbach’s alpha in this study was .76.

Statistical analysis

SPSS version 25 was used to capture and assess data. Descriptive statistics were used for the characteristics of the participants, frequencies and percentages for categorical variables and measures of central tendency and dispersion for continuous variables. The variables of fatalistic beliefs (low 30 to 90; high 91 to 150), knowledge (low 0 to 4; high 5 to 9) and perceived risk of T2DM (low 8 to 20; high 21 to 32) were categorized according to the mean of the total score of the questionnaires. For the correlation analysis, Spearman’s coefficient and multiple linear regression were used to explain the perceived risk of T2DM.

Results

Sociodemographic characteristics

In total 222 people participated in the survey, and 218 participants provided complete data. The average age was 29.2 years (SD=10.5), the sample was characterized by being mostly women (55%), single (52.3%), having a university education (36.2%) and having a job (53.7%), see Table 1.

Table 1. Sociodemographic characteristics.

Variable	f (%)
Sex
Female	120 (55)
Male	98 (45)
Marital status
Single	114 (52.3)
Married	59 (27.1)
Common law marriage	30 (13.8)
Other	15 (6.9)
Schooling
Elementary	21 (9.6)
Junior High	51 (23.4)
High School	64 (29.4)
University	82 (37.6)
Occupation
Works	117 (53.7)
Studies	36 (16.5)
Works and studies	44 (20.2)
Unemployed	21 (9.6)

Regarding fatalism, 27.5% report high fatalistic belief scores, 83.5% have high knowledge about T2DM risk factors and 66.1% have high perceived risk of developing T2DM; the measures of central tendency and dispersion of the variables are seen in Table 2.

Table 2. Description of fatalism, knowledge, and perceived risk of T2DM.

Variables	M (SD)
Total fatalism	79.1 (15.2)
Pessimism	15.1 (4.0)
Luck	16.7 (3.8)
Divine control	17.2 (6.1)
Internal locus	11.8 (4.6)
Fatalism	18.1 (4.5)
Knowledge	6.9 (1.9)
T2DM risk perception	27.2 (3.3)

Correlation analysis

According to the correlation analysis, the perceived risk of T2DM was inversely related to fatalism and its dimensions - see Table 3. The level of knowledge was positively correlated with perceived risk of T2DM (r=.178, p<.01). Subsequently, multiple linear regression was performed for perceived risk of T2DM, with fatalism dimensions and knowledge as predictor variables, but only pessimism (β=-.194, p<.01) and divine control (β=-.164, p<.05) were the only predictors, they explained 7.6% of the variance.

Table 3. Correlation between fatalism and perceived risk of diabetes mellitus type 2.

Variables	Fatalism	Pessimism	Locus	Luck	Divine control	Total fatalism
T2DM risk perception	-.160*	-.230**	-.197*	-.171*	-.210**	-.257**
Knowledge	.036	-.055	-.232**	-.139*	-.087	-.133*

* p<.05.

** p<.01.

Discussion

The purpose of this research was to analyze the relationship between fatalistic beliefs, knowledge of T2DM risk factors, and the perceived risk of T2DM in Mexican adults during the COVID-19 pandemic. In Mexico there is a large percentage of the adult population at risk of developing T2DM; according to the results of the 2018 National Health and Nutrition Survey most adults aged 20 years or older have a high prevalence of overweight/obesity, as well as being involved in risky behaviors such as alcohol consumption, smoking, sedentary lifestyle, and food insecurity.²⁴

In this study, it was identified that the perceived risk of T2DM was high in comparison with other studies in the Asian population.²⁵ This may be since the most vulnerable population to complications, hospitalization and death from SARS-Cov-2 was people with chronic diseases.¹^,²^,²⁶ This situation may have generated concern in the population about feeling at risk of developing T2DM and therefore, also feeling vulnerable to the COVID-19 virus. Likewise, even though people with a higher perceived risk of T2DM can make lifestyle changes, it has been reported that during the pandemic, people report an increase in the consumption of alcohol, tobacco and processed foods, emotional problems, and less physical activity.²⁷^,²⁸

Our results identified that a quarter of the respondents had above-average scores on fatalistic beliefs. Cultural beliefs are a key element in health care seeking and chronic disease prevention.²⁹ In several studies it has been reported that people who believe that illness is a result of a supernatural phenomenon do not seek allopathic medical care, but instead seek help from healers or shamans who can help alleviate bad luck, witchcraft or perform prayers.³⁰^,³¹ This is due firstly because of the distrust they have about the negative beliefs held about treatments such as insulin or peritoneal dialysis, and secondly, because they think that allopathic medicine cannot cure or alleviate diseases that are caused by superhuman forces.

The level of knowledge was related to a greater perceived risk of T2DM. These results are consistent with previous studies, in which it has been reported that people who have information on the main risk factors and who have family members with a history of T2DM perceive a greater probability of becoming ill.⁷ In these studies, differences have been found between men and women with the level of knowledge and perceived risk of T2DM. Men have lower level of knowledge about risk factors and lower risk perception but have higher risk of developing T2DM compared to women. Health literacy has been considered as a relevant factor to face health problems and to know that chronic diseases are preventable,¹³ but studies in Latin America have indicated that although people have knowledge about T2DM risk factors, they consider that the disease cannot be prevented, that it is the responsibility of the health professional to prevent it and not of oneself.³²

Finally, we found that people who have high fatalistic beliefs have low perceived risk of developing T2DM. One of the dimensions of fatalistic beliefs that was related to low-risk perception was pessimism. Pessimism has been considered as a negative view, attitude, or idea regarding life events. People with pessimistic ideas have fewer coping strategies, lower self-efficacy, and are carefree³³ considering that positive changes in health cannot be achieved. Thus, people with a pessimistic view have greater problems in making a healthy lifestyle change when they develop chronic diseases.³⁴ Some authors report that these ideas are since they consider disease as something fatal and that death is inevitable, so that any action they take cannot change it.³¹ Another important factor in the perceived risk of T2DM is the belief in divine control. From a religious point of view, beliefs about God are a key element that influences people’s behaviors. On the one hand, people with fatalistic religious beliefs allow them to cope better with health problems.³⁵^–³⁷But, on the other hand, they may consider that diseases are tests or punishments from God, and that only God can cure the disease.³⁸^–⁴⁰ This set of beliefs influences people to consider that it does not matter if they make changes in their way of living, because illness cannot be prevented if God does not want it. Also, people may self-perceive themselves to be at lower risk of developing T2DM by self-evaluating themselves without conflict with God.

The weaknesses of the study include data collection conducted through electronic means and social media on the internet, which resulted in a majority of young adult participants. It is necessary for future studies to collect data through face-to-face interactions in order to include participants from older age groups. The research design was cross-sectional; therefore a cause-and-effect relationship cannot be established. As a result, the findings should be interpreted with caution and extrapolated to similar populations to those in this study.

On the other hand, the strengths of the study include being one of the first investigations to link fatalistic beliefs with knowledge and perceived risk of T2DM. Additionally, it is a study conducted on a population of young adults from a rural community in Mexico, which highlights the relevance of these beliefs and their implications in identifying knowledge and health risks.

Conclusions

In young adults, knowledge increases the perceived risk of T2DM. But fatalistic beliefs decrease knowledge and perceived risk of T2DM. Fatalistic beliefs should be considered a variable that has to be dealt with by health professionals. It is necessary that health professionals consider fatalistic beliefs for the prevention of chronic diseases and improve through educational programs health literacy about the risk factors of T2DM and the benefit of lifestyle, mainly in young adult populations. It is important to provide more education in those who have low knowledge about T2DM risk factors, so that people become more aware of their risk.

Data availability

Underlying data

figshare: Data.sav. https://doi.org/10.6084/m9.figshare.22773977.v3.⁴¹

This project contains the raw questionnaire responses.

Extended data

figshare: Data.sav. https://doi.org/10.6084/m9.figshare.22773977.v3.⁴¹

This project contains the demographics questionnaire.

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

References

1. Carrillo-Vega MF, Salinas-Escudero G, García-Peña C, et al.: Early estimation of the risk factors for hospitalization and mortality by COVID-19 in Mexico. PLoS One. 2020 Sep [cited 2021 Apr 20]; 15(9): e0238905. PubMed Abstract | Publisher Full Text | Free Full Text
2. Woolcott OO, Castilla-Bancayán JP: The effect of age on the association between dia-betes and mortality in adult patients with COVID-19 in Mexico. Sci. Rep. 2021 Apr [cited 2022 Apr 20]; 11(1): 8386. PubMed Abstract | Publisher Full Text | Free Full Text
3. Sathish T, Chandrika AM: Newly diagnosed diabetes in patients with mild to moderate COVID-19. Diabetes Metab. Syndr. 2021 Mar-Apr [cited 2022 Jan 20]; 15(2): 569–571. PubMed Abstract | Publisher Full Text | Free Full Text
4. Singh AK, Singh R: Hyperglycemia without diabetes and new-onset diabetes are both associated with poorer outcomes in COVID-19. Diabetes Res. Clin. Pract. 2020 Sep [cited 2022 Jan 13]; 167: 108382. PubMed Abstract | Publisher Full Text | Free Full Text
5. Nguyen AP: Risk perception of developing diabetes: A concept analysis. Nurs. Forum. 2020 Nov [cited 2022 Apr 16]; 55(4): 559–568. PubMed Abstract | Publisher Full Text
6. Pelullo CP, Rossiello R, Nappi R, et al.: Diabetes Prevention: Knowledge and Perception of Risk among Italian Population. Biomed. Res. Int. 2019 Oct [cited 2022 Apr 22]; 2019: 1–7. Publisher Full Text Reference Source
7. Khan RK, Misra R, Shawley-Brzoska S, et al.: Predictors of diabetes risk perception among college students. J. Am. Coll. Heal. 2022 Aug-Sep [cited 2022 Nov 20]; 70(6): 1803–1809. PubMed Abstract | Publisher Full Text | Free Full Text
8. Koipuram A, Carroll S, Punthakee Z, et al.: Diabetes knowledge, risk perception, and quality of life among South Asian caregivers in young adulthood. BMJ Open Diabetes Res. Care. 2020 Nov [cited 2021 Aug 20]; 8: 1–7. Publisher Full Text Reference Source
9. Thompson AM, Chad KE: The relationship of pubertal status to body image, social physique anxiety, preoccupation with weight and nutritional status in young females. Can. J. Public Heal. 2000 May-Jun [cited 2021 Aug 20]; 91(3): 207–211. PubMed Abstract | Publisher Full Text | Free Full Text
10. Skøt L, Nielsen JB, Leppin A: Who perceives a higher personal risk of developing type 2 diabetes? A cross-sectional study on associations between personality traits, health-related behaviours and perceptions of susceptibility among university students in Denmark. BMC Public Health. 2018 Aug [cited 2021 Aug 03]; 18(1): 972. PubMed Abstract | Publisher Full Text | Free Full Text
11. Kowall B, Rathmann W, Stang A, et al.: Perceived risk of diabetes seriously underestimates actual diabetes risk: The KORA FF4 study. PLoS One. 2017 Jan [cited 2021 Aug 20]; 12(1): e0171152. PubMed Abstract | Publisher Full Text | Free Full Text
12. Lavielle P, Wacher N: The predictors of glucose screening: the contribution of risk perception. BMC Fam. Pract. 2014 Jun [cited 2021 Aug 20]; 15: 108. PubMed Abstract | Publisher Full Text | Free Full Text
13. Riley KE, Hay JL, Waters EA, et al.: Lay beliefs about risk: relation to risk behaviors and to probabilistic risk perceptions. J. Behav. Med. 2019 Dec [cited 2021 Jun 14]; 42(6): 1062–1072. PubMed Abstract | Publisher Full Text | Free Full Text
14. Straughan PT, Seow A: Fatalism reconceptualized: a concept to predict health screen-ing behavior. J. Gender, Cult. Heal. 1998 [cited 2021 Jun 20]; 3(2): 85–100. Publisher Full Text Reference Source
15. Esparza OA, Wiebe JS, Quiñones J: Simultaneous Development of a Multidimensional Fatalism Measure in English and Spanish. Curr. Psychol. 2015 [cited 2021 Aug 02]; 34(4): 597–612. PubMed Abstract | Publisher Full Text | Free Full Text
16. Imai Y, Onishi C, Bando T: Relationship between Older persons with cancer’ Coping Attitudes and Mental Adjustment. J. Med. Investig. 2020; 67(1.2): 44–50. PubMed Abstract | Publisher Full Text
17. Beeken RJ, Simon AE, von Wagner C , et al.: Cancer fatalism: deter-ring early presentation and increasing social inequalities? Cancer Epidemiol. Biomark. Prev. 2011 Oct [cited 2022 Jun 10]; 20(10): 2127–2131. PubMed Abstract | Publisher Full Text | Free Full Text
18. Valera P, Lian Z, Brotzman L, et al.: Fatalistic Cancer Beliefs and Information Seek-ing in Formerly Incarcerated African-American and Hispanic Men: Implications for Cancer Health Communication and Research. Health Commun. 2018 May; 33(5): 576–584. PubMed Abstract | Publisher Full Text | Free Full Text
19. Anderson AS, Caswell S, Macleod M, et al.: Health Behav-iors and their Relationship with Disease Control in People Attending Genetic Clinics with a Family History of Breast or Colorectal Cancer. J. Genet. Couns. 2017 Feb [cited 2022 May 16]; 26(1): 40–51. PubMed Abstract | Publisher Full Text | Free Full Text
20. Bachem R, Tsur N, Levin Y, et al.: Negative Affect, Fatalism, and Perceived Institutional Betrayal in Times of the Coronavirus Pandemic: A Cross-Cultural Investigation of Control Beliefs. Front. Psychol. 2020 Oct [cited 2022 Feb 18]; 11(1): 40–51. PubMed Abstract | Publisher Full Text | Free Full Text
21. Nordfjaern T, Mehdizadeh M, Fallah ZM: Social Psychology of Coronavirus Disease 2019: Do Fatalism and Comparative Optimism Affect Attitudes and Adherence to Sanitary Protocols? Front. Psychol. 2021 May [cited 2022 Feb 20]; 12. PubMed Abstract | Publisher Full Text | Free Full Text
22. Walker EA, Mertz CK, Kalten MR, et al.: Risk perception for developing diabetes: comparative risk judgments of physicians. Diabetes Care. 2003 Sep [cited 2022 Feb 20]; 26(9): 2543–2548. Publisher Full Text Reference Source
23. Joiner KL, Sternberg RM, Kennedy C, et al.: A Span-ish-Language Risk Perception Survey for Developing Diabetes: Translation Process and As-sessment of Psychometric Properties. J. Nurs. Meas. 2016 Dec [cited 2022 Feb 20]; 24(3): 365–378. PubMed Abstract | Publisher Full Text | Free Full Text
24. Shamah-Levy T, Vielma-Orozco E, Heredia-Hernández O, et al.: Encuesta Nacional de Salud y Nutrición 2018-19: Resul-tados Nacionales. Cuernavaca, México: Instituto Nacional de Salud Pública; 2020.
25. Sulaiman S, Leelavathi M, Norasyikin AW: Risk perception and knowledge regarding diabetes among offspring of type 2 diabetics at a tertiary institution. Med. J. Malaysia. 2020 Nov [cited 2022 Feb 20]; 75(6): 655–659. PubMed Abstract
26. Manrique-espinoza BCD, Salinas-Rodríguez AMC, Moreno-Tamayo KM, et al.: Condiciones de salud y estado funcional de los adultos mayores en México. Salud pública Méx. 2013 Jan [cited 2022 Feb 20]; 55(1): 323–331. Publisher Full Text Reference Source
27. Ammar A, Brach M, Trabelsi K, et al.: Effects of COVID-19 Home Confinement on Eating Behaviour and Physical Activity: Results of the ECLB-COVID19 International Online Survey. Nutrients. 2020 May [cited 2022 Feb 20]; 12(6). PubMed Abstract | Publisher Full Text | Free Full Text
28. Kumar A, Arora A, Sharma P, et al.: Is diabetes mellitus associated with mortality and severity of COVID-19? A meta-analysis. Diabetes Metab. Syndr. 2020 Jul-Aug [cited 2022 Feb 20]; 14(4): 535–545. PubMed Abstract | Publisher Full Text | Free Full Text
29. Keith KD: Cross-cultural psychology: Contemporary themes and perspectives. 2nd ed.John Wiley & Sons; 2019.
30. Zakiawati D, Setiadhi R: Oral manifestations of acute leukemia in children: family supernatural beliefs and its contribution to the prognosis of the disease. Int. J. Med. Dent. Case Rep. 2021 Jul [cited 2022 Oct 20]; 12(6): 1–4. Publisher Full Text
31. Arabiat D, Whitehead L, Al Jabery M, et al.: Beliefs About Illness and Treatment Decision Modelling During Ill-Health in Arabic Fami-lies. J. Multidiscip. Healthc. 2021 Jul [cited 2022 Aug 20]; 14: 1755–1768. PubMed Abstract | Publisher Full Text | Free Full Text
32. Vicente Sánchez B, Bonilla Romero J, Vicente Peña E, et al.: Percepción de riesgo de desarrollar diabetes mellitus en personas no diabéticas. Re-vista Finlay. 2016 [cited 2022 Aug 20]; 6(2): 81–92. Reference Source
33. Fink G: Stress: Concepts, Cognition, Emotion, and Behavior: Handbook of Stress Series. Academic Press; 2016.
34. Helgeson VS, Zajdel M: Adjusting to Chronic Health Conditions. Annu. Rev. Psychol. 2017 Jan [cited 2022 Aug 20]; 68: 545–571. Publisher Full Text Reference Source
35. Han J, Zhou X, Meng Y: The impact of religious beliefs on the health of the resi-dents-Evidence from China. Int. J. Health Plann. Manag. 2020 Jan [cited 2022 Feb 19]; 35(1): 378–393. PubMed Abstract | Publisher Full Text
36. Hill TD, Saenz JL, Rote SM: Religious Participation and Mortality Risk in Mexico. J. Gerontol. B Psychol. Sci. Soc. Sci. 2020 Apr [cited 2022 Feb 19]; 75(5): 1053–1061. PubMed Abstract | Publisher Full Text
37. Borges M, Lucchetti G, Leão FC, et al.: Religious Affiliations Influ-ence Health-Related and General Decision Making: A Brazilian Nationwide Survey. Int. J. Environ. Res. Public Health. 2021 Mar [cited 2022 Feb 19; 18(6): 2873. PubMed Abstract | Publisher Full Text | Free Full Text
38. Jalal Z, Antoniou S, Taylor D, et al.: South Asians living in the UK and adherence to coronary heart disease medication: a mixed- method study. Int. J. Clin. Pharm. 2019 Feb [cited 2022 Apr 19]; 41(1): 122–130. Publisher Full Text Reference Source
39. Ahmedani BK, Peterson EL, Wells KE, et al.: Asthma medication adherence: the role of God and other health locus of control factors. Ann. Allergy Asthma Immunol. 2013 Feb [cited 2022 Apr 19]; 110(2): 75–79.e2. PubMed Abstract | Publisher Full Text | Free Full Text
40. Kilshaw S, Omar N, Major S, et al.: Causal ex-planations of miscarriage amongst Qataris. BMC Pregnancy Childbirth. 2017 Jul [cited 2022 Apr 19]; 17(1): 250. PubMed Abstract | Publisher Full Text | Free Full Text
41. Mendoza Catalan G: Fatalism and risk perception T2DM. [Dataset]. figshare.2023. Publisher Full Text

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Version 2

VERSION 2 PUBLISHED 03 Jul 2023

Author details Author details

Geu Mendoza-Catalán
Roles: Conceptualization, Investigation, Methodology, Writing – Original Draft Preparation

Alicia Álvarez Aguirre
Roles: Data Curation, Formal Analysis

Claudia Jennifer Domínguez Chávez
Roles: Investigation, Supervision, Writing – Review & Editing

María del Rosario Tolentino Ferrel
Roles: Supervision, Visualization, Writing – Review & Editing

Alma Angélica Villa Rueda
Roles: Resources, Supervision, Writing – Review & Editing

Elizabeth Guzmán Ortiz
Roles: Project Administration, Supervision, Writing – Review & Editing

Competing interests

No competing interests were disclosed.

Grant information

The author(s) declared that no grants were involved in supporting this work.

Article Versions (2)

version 2

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Published: 07 Apr 2025, 12:771

https://doi.org/10.12688/f1000research.134266.2

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Published: 03 Jul 2023, 12:771

https://doi.org/10.12688/f1000research.134266.1

© 2023 Mendoza-Catalán G 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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Mendoza-Catalán G, Álvarez Aguirre A, Domínguez Chávez CJ et al. Fatalism and knowledge associated to diabetes mellitus type 2 risk perception in Mexican population during COVID-19 confinement [version 1; peer review: 2 not approved]. F1000Research 2023, 12:771 (https://doi.org/10.12688/f1000research.134266.1)

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Reviewer Report 28 Oct 2024

Sanisah Binti Saidi, International Islamic University Malaysia, Kuala Lumpur, Federal Territory of Kuala Lumpur, Malaysia

Not Approved

https://doi.org/10.5256/f1000research.147307.r335082

Abstract: The problem statement is missing within the abstract. Furthermore, methods of analysis and the total number of samples are missing.
Introduction: The concept of fatalism, i.e., the fatalistic perception of diabetes vs. fatalism due to COVID-19, is not clearly discussed. Fatalism might be viewed differently based on these situations, which would affect patients' perceptions of diabetes and the perceived risk that they may have. Furthermore, further discussion on the hypothesised relationship between knowledge about diabetes, fatalistic behaviour related to diabetes and perceived risk of Type 2 diabetes is required to justify the current study.
Methods: Did the authors exclude people with type 2 diabetes? Have the samples been infected with and recovered from COVID-19? This might affect their fatalistic beliefs.
Findings: Further interpretation of the statistical findings is needed.
Discussion: In the first paragraph, the authors do not have to repeat the prevalence of obesity/diabetes but brief the reader about the research objectives and summarize the findings. The primary variable introduced to the reader was fatalism; therefore, it would be more apparent if the authors discussed the findings of fatalism in more detail and provided a clear view to the reader about the fatalistic beliefs of the samples within this study. The influence of culture on fatalistic beliefs was not discussed earlier; therefore, it would be more beneficial if the authors could inform the reader how they have included this aspect within the questionnaires or if it is a new component that has been identified, as it was contained within the discussion.

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?

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

I cannot comment. A qualified statistician is required.
Are all the source data underlying the results available to ensure full reproducibility?

No
Are the conclusions drawn adequately supported by the results?

Partly

Competing Interests: No competing interests were disclosed.

Reviewer Expertise: Diabetes self-care/self-management, fatalism, spiritual care, qualitative research

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.

CITE

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Author Response 07 Apr 2025

Elizabeth Guzman, Nursing and Obstetrics, Universidad de Guanajuato, Celaya, 38050, Mexico

07 Apr 2025

Author Response

We appreciate the valuable comments and suggestions on the manuscript.
Abstract: we add aim, statistical analyses, sample size and questionnaires used
Introduction: Fatalism is widespread in risk perception and preventive ... Continue reading We appreciate the valuable comments and suggestions on the manuscript.
Abstract: we add aim, statistical analyses, sample size and questionnaires used
Introduction: Fatalism is widespread in risk perception and preventive or risk behaviors, and fatalism is associated with the perception of diabetes risk.
Methods: COVID-19 was included as a temporal factor since data collection was carried out during the pandemic.
Data collection took place at the beginning of the pandemic when the risk of contagion was low, so it was not evaluated.
Findings: We added a table for linear regression and its interpretation.
Discussion: The first paragraph was deleted
Some Mexicans believe that illness results from supernatural phenomena, leading them to seek help from healers or shamans rather than allopathic medical care. These healers are believed to alleviate bad luck, counteract witchcraft, or perform prayers.
We appreciate the valuable comments and suggestions on the manuscript.
Abstract: we add aim, statistical analyses, sample size and questionnaires used
Introduction: Fatalism is widespread in risk perception and preventive or risk behaviors, and fatalism is associated with the perception of diabetes risk.
Methods: COVID-19 was included as a temporal factor since data collection was carried out during the pandemic.
Data collection took place at the beginning of the pandemic when the risk of contagion was low, so it was not evaluated.
Findings: We added a table for linear regression and its interpretation.
Discussion: The first paragraph was deleted
Some Mexicans believe that illness results from supernatural phenomena, leading them to seek help from healers or shamans rather than allopathic medical care. These healers are believed to alleviate bad luck, counteract witchcraft, or perform prayers.
Competing Interests: No competing interests were disclosed. Close
Report a concern
Respond or Comment

COMMENTS ON THIS REPORT

Author Response 07 Apr 2025

Elizabeth Guzman, Nursing and Obstetrics, Universidad de Guanajuato, Celaya, 38050, Mexico

07 Apr 2025

Author Response

We appreciate the valuable comments and suggestions on the manuscript.
Abstract: we add aim, statistical analyses, sample size and questionnaires used
Introduction: Fatalism is widespread in risk perception and preventive ... Continue reading We appreciate the valuable comments and suggestions on the manuscript.
Abstract: we add aim, statistical analyses, sample size and questionnaires used
Introduction: Fatalism is widespread in risk perception and preventive or risk behaviors, and fatalism is associated with the perception of diabetes risk.
Methods: COVID-19 was included as a temporal factor since data collection was carried out during the pandemic.
Data collection took place at the beginning of the pandemic when the risk of contagion was low, so it was not evaluated.
Findings: We added a table for linear regression and its interpretation.
Discussion: The first paragraph was deleted
Some Mexicans believe that illness results from supernatural phenomena, leading them to seek help from healers or shamans rather than allopathic medical care. These healers are believed to alleviate bad luck, counteract witchcraft, or perform prayers.
We appreciate the valuable comments and suggestions on the manuscript.
Abstract: we add aim, statistical analyses, sample size and questionnaires used
Introduction: Fatalism is widespread in risk perception and preventive or risk behaviors, and fatalism is associated with the perception of diabetes risk.
Methods: COVID-19 was included as a temporal factor since data collection was carried out during the pandemic.
Data collection took place at the beginning of the pandemic when the risk of contagion was low, so it was not evaluated.
Findings: We added a table for linear regression and its interpretation.
Discussion: The first paragraph was deleted
Some Mexicans believe that illness results from supernatural phenomena, leading them to seek help from healers or shamans rather than allopathic medical care. These healers are believed to alleviate bad luck, counteract witchcraft, or perform prayers.
Competing Interests: No competing interests were disclosed. Close
Report a concern

Views

Reviewer Report 04 Sep 2023

Ola Sukkarieh, Hariri School of Nursing, American University of Beirut, Beirut, Beirut Governorate, Lebanon

Not Approved

https://doi.org/10.5256/f1000research.147307.r196704

The purpose of this study was to analyze the relationship between fatalistic beliefs, knowledge of T2DM risk factors, and the perceived risk of T2DM in Mexican adults during the COVID-19 pandemic. The authors could not present clearly the relationship between the three variables of interest. It was hard to follow.

Abstract: missing aim, statistical analyses, sample size and questionnaires used

Manuscript:

Introduction: the focus of the introduction is not clear specifically with context of COVID 19. If the main goal is to study fatalism, why is COVID 19 introduced and how does it matter or affect the relationship?

Methods:

inclusion criteria: what about excluding pre-diabetes since it's a major risk factor to develop T2DM and might affect participants' perceptions. what about criteria related to COVID 19 since the time frame seems to be influenced with COVID pandemic.

Results:

Why were the scores categorized instead of being used as continuous variables when the latter yields stronger data analyses?

Descriptive data can be combined in one table for ease of following (T1and T2)

There needs to be T4 for multiple linear regression.

Discussion:

needs to start with brief summary of the findings
in 1st paragraph, authors cannot introduce new concepts of risky behaviors when it is out of the scope of the paper.
presentation of findings are not aligned with T3, i.e. there is no reflection on negative or positive existing relationships.
Additionally, the variables are not well identified in the discussion as to what is the outcome of interest which is according to the methods section: Dependent variable: Perceived risk of Type 2 Diabetes Mellitus.
regression analysis is missed from the discussion.

Weakness: need to acknowledge limitations of self-report which affects biases in responses and lack of generalizability due to research design..

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?

No
Are sufficient details of methods and analysis provided to allow replication by others?

No
If applicable, is the statistical analysis and its interpretation appropriate?

No
Are all the source data underlying the results available to ensure full reproducibility?

No
Are the conclusions drawn adequately supported by the results?

No

Competing Interests: No competing interests were disclosed.

Reviewer Expertise: My areas of expertise is diabetes self-management, fatalism in diabetes, social determinants of health

CITE

Report a concern

Author Response 07 Apr 2025

Elizabeth Guzman, Nursing and Obstetrics, Universidad de Guanajuato, Celaya, 38050, Mexico

07 Apr 2025

Author Response
We appreciate the valuable comments and suggestions on the manuscript.
Abstract: We added the aim, statistical analyses, sample size and questionnaires used.
Introduction: COVID-19 was added as a temporal factor since ... Continue reading
We appreciate the valuable comments and suggestions on the manuscript.
Abstract: We added the aim, statistical analyses, sample size and questionnaires used.
Introduction: COVID-19 was added as a temporal factor since data collection was carried out during the pandemic.
Results: The scores categorized for sociodemographic data were used for descriptive statistics; however, continuous variables were used for inferential analysis.
Table 1 is extensive, which limits the possibility of adding more information on a single page.
An additional table was included for multiple linear regression.
Discussion:

A summary of the findings is written.

Some information has been deleted.

Adjustments have been made to the table, and the results are presented according to the main objective of the study. Information on the direction of the relationship between fatalism and risk perception (dependent variable) has been added.

A negative relationship was found between fatalism and risk perception for diabetes mellitus. This contrasts with a recent sample of university students, which showed that fatalistic beliefs are negatively related to risk behaviors for diabetes mellitus. These findings also align with the results of another study conducted on health professionals, which demonstrated that fatalistic beliefs negatively affect perceptions of occupational health.

In the sixth paragraph, we discuss the findings of the regression analysis.

Weakness:
Our findings are only generalizable to a rural community in Mexico. However, future studies are recommended in diverse cultural settings to replicate our findings and further explore the influence of fatalistic beliefs and perceived risk of T2DM. Additionally, qualitative studies are needed to provide a deeper understanding of fatalistic beliefs.
We appreciate the valuable comments and suggestions on the manuscript.
Abstract: We added the aim, statistical analyses, sample size and questionnaires used.
Introduction: COVID-19 was added as a temporal factor since data collection was carried out during the pandemic.
Results: The scores categorized for sociodemographic data were used for descriptive statistics; however, continuous variables were used for inferential analysis.
Table 1 is extensive, which limits the possibility of adding more information on a single page.
An additional table was included for multiple linear regression.
Discussion:

A summary of the findings is written.

Some information has been deleted.

Adjustments have been made to the table, and the results are presented according to the main objective of the study. Information on the direction of the relationship between fatalism and risk perception (dependent variable) has been added.

A negative relationship was found between fatalism and risk perception for diabetes mellitus. This contrasts with a recent sample of university students, which showed that fatalistic beliefs are negatively related to risk behaviors for diabetes mellitus. These findings also align with the results of another study conducted on health professionals, which demonstrated that fatalistic beliefs negatively affect perceptions of occupational health.

In the sixth paragraph, we discuss the findings of the regression analysis.

Weakness:
Our findings are only generalizable to a rural community in Mexico. However, future studies are recommended in diverse cultural settings to replicate our findings and further explore the influence of fatalistic beliefs and perceived risk of T2DM. Additionally, qualitative studies are needed to provide a deeper understanding of fatalistic beliefs.
Competing Interests: No competing interests were disclosed. Close
Report a concern
Respond or Comment

COMMENTS ON THIS REPORT

Author Response 07 Apr 2025

Elizabeth Guzman, Nursing and Obstetrics, Universidad de Guanajuato, Celaya, 38050, Mexico

07 Apr 2025

Author Response
We appreciate the valuable comments and suggestions on the manuscript.
Abstract: We added the aim, statistical analyses, sample size and questionnaires used.
Introduction: COVID-19 was added as a temporal factor since ... Continue reading
We appreciate the valuable comments and suggestions on the manuscript.
Abstract: We added the aim, statistical analyses, sample size and questionnaires used.
Introduction: COVID-19 was added as a temporal factor since data collection was carried out during the pandemic.
Results: The scores categorized for sociodemographic data were used for descriptive statistics; however, continuous variables were used for inferential analysis.
Table 1 is extensive, which limits the possibility of adding more information on a single page.
An additional table was included for multiple linear regression.
Discussion:

A summary of the findings is written.

Some information has been deleted.

Adjustments have been made to the table, and the results are presented according to the main objective of the study. Information on the direction of the relationship between fatalism and risk perception (dependent variable) has been added.

A negative relationship was found between fatalism and risk perception for diabetes mellitus. This contrasts with a recent sample of university students, which showed that fatalistic beliefs are negatively related to risk behaviors for diabetes mellitus. These findings also align with the results of another study conducted on health professionals, which demonstrated that fatalistic beliefs negatively affect perceptions of occupational health.

In the sixth paragraph, we discuss the findings of the regression analysis.

Weakness:
Our findings are only generalizable to a rural community in Mexico. However, future studies are recommended in diverse cultural settings to replicate our findings and further explore the influence of fatalistic beliefs and perceived risk of T2DM. Additionally, qualitative studies are needed to provide a deeper understanding of fatalistic beliefs.
We appreciate the valuable comments and suggestions on the manuscript.
Abstract: We added the aim, statistical analyses, sample size and questionnaires used.
Introduction: COVID-19 was added as a temporal factor since data collection was carried out during the pandemic.
Results: The scores categorized for sociodemographic data were used for descriptive statistics; however, continuous variables were used for inferential analysis.
Table 1 is extensive, which limits the possibility of adding more information on a single page.
An additional table was included for multiple linear regression.
Discussion:

A summary of the findings is written.

Some information has been deleted.

Adjustments have been made to the table, and the results are presented according to the main objective of the study. Information on the direction of the relationship between fatalism and risk perception (dependent variable) has been added.

A negative relationship was found between fatalism and risk perception for diabetes mellitus. This contrasts with a recent sample of university students, which showed that fatalistic beliefs are negatively related to risk behaviors for diabetes mellitus. These findings also align with the results of another study conducted on health professionals, which demonstrated that fatalistic beliefs negatively affect perceptions of occupational health.

In the sixth paragraph, we discuss the findings of the regression analysis.

Weakness:
Our findings are only generalizable to a rural community in Mexico. However, future studies are recommended in diverse cultural settings to replicate our findings and further explore the influence of fatalistic beliefs and perceived risk of T2DM. Additionally, qualitative studies are needed to provide a deeper understanding of fatalistic beliefs.
Competing Interests: No competing interests were disclosed. Close
Report a concern

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Version 2

VERSION 2 PUBLISHED 03 Jul 2023

Open Peer Review

Reviewer Status

Reviewer Reports

	Invited Reviewers
	1	2	3	4
Version 2 (revision) 07 Apr 25			read	read
Version 1 03 Jul 23	read	read

Ola Sukkarieh, American University of Beirut, Beirut, Lebanon
Sanisah Binti Saidi, International Islamic University Malaysia, Kuala Lumpur, Malaysia
Masoud Mohammadnezhad, Birmingham City University, Birmingham, UK
Nodirjon Ruzimurodov, Institute of Immunology and Human Genomics, Tashkent, Uzbekistan

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Reviewer Report

2 Views

08 Aug 2025 | for Version 2

Nodirjon Ruzimurodov, Institute of Immunology and Human Genomics, Tashkent, Uzbekistan

2 Views Cite this report Responses(0)

Approved With Reservations

Brief overview
I enjoyed reading this paper. The authors surveyed 222 adults from a rural community in Guanajuato during the 2020 lockdown to see whether two things—fatalistic beliefs about health and factual knowledge about diabetes—shape how people judge their own risk of developing type 2 diabetes. They used the Spanish versions of the Multidimensional Fatalism Scale (MFS-ES) and the Risk Perception Survey for Developing Diabetes (RPS-DD). Correlations and a multiple-linear model told a consistent story: people who know more about diabetes feel more vulnerable to it, whereas those who see health as ruled by pessimism or divine control feel less at risk. Together those factors explain only about eight percent of the variance, but the signal is unmistakable.
What must be fixed before I can give full approval

Age mismatch. In the methods you promise to include adults aged 30–70, yet the results show a mean age of 29.2 ± 10.5 years. Either the age cut-off was different in practice or younger respondents slipped in. Please clear this up and, if necessary, rerun the analysis without the under-30s (or defend keeping them).
Who is really represented? Recruiting through Facebook, WhatsApp and Instagram in a self-described “rural” population almost certainly filters out residents with poor connectivity. A short paragraph comparing your sample’s demographics with local census data would help readers judge external validity.
Cutting continuous scales in half. Splitting fatalism, knowledge and risk-perception scores at the sample mean costs statistical power and hides nuance. I would strongly prefer to see the main regression with continuous predictors (you already have the correlations), or at least a sensitivity analysis showing the results are stable.
Show us the diagnostics. The final model explains 7.6 % of risk-perception variance. That is fine, but please give the adjusted R², check the usual assumptions (linearity, homoscedasticity, multicollinearity, normal residuals) and tone down the wording of your conclusions if any assumption is shaky.
Are the instruments fully appropriate? Have the MFS-ES and RPS-DD been formally validated in rural Mexican adults? If not, note this as a limitation and report Cronbach’s α for each sub-scale so that readers can judge internal consistency.
Reproducibility basics. Thank you for sharing the raw .sav file on Figshare. To make the study truly reproducible, please add (i) a variable dictionary and (ii) the analysis code—SPSS syntax or an R script—so that any reader can walk from data to tables without guessing.

Smaller but worthwhile tweaks

Bring the literature review up to 2025: a handful of recent papers on diabetes-related fatalism in Latino populations are missing.
Fix the handful of typos (“rick” → “risk”; subject–verb agreement) and align the Table 3 header.
A simple flow diagram (invited → completed → analysed) would make the sample easier to follow.
Cite the ethics approval number once (it appears twice).
Including a STROBE checklist as supplementary material would tick one more transparency box.

Final word
The research question is timely, the core analyses are sound and the results are worth sharing. Addressing the points above—especially the age-range confusion, the scale dichotomisation and the missing code/metadata—will strengthen both the credibility and the reproducibility of the work. Once those items are sorted, I’ll be happy to mark the manuscript Approved.

Conflicts of Interest: None declared.

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?

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

Partly
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

Clinical immunology; endocrinology and metabolic disorders (diabetes); immunogenetics; maternal-fetal medicine; population health/epidemiology

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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Reviewer Report

2 Views

03 Jun 2025 | for Version 2

Masoud Mohammadnezhad, Birmingham City University, Birmingham, England, UK

2 Views Cite this report Responses(0)

Approved With Reservations

Thank you for the opportunity to review this paper. This study is important and employs a rigorous methodology. However, I have a few comments and questions:
First, could you please clarify the version of the questionnaire used in this study? Specifically, was it in Mexican or another language? If it was in Mexican, how was it translated, and who was involved in the translation process?
Second, I would like to inquire about the validity and reliability of the tools used in this study. Did you conduct a pilot study, or did you use the original version and report the Cronbach's alpha for reliability?

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?

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?

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

Yes
Are the conclusions drawn adequately supported by the results?

Yes

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

Public Health

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Reviewer Report

22 Views

28 Oct 2024 | for Version 1

Sanisah Binti Saidi, International Islamic University Malaysia, Kuala Lumpur, Federal Territory of Kuala Lumpur, Malaysia

22 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?

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

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

I cannot comment. A qualified statistician is required.
Are all the source data underlying the results available to ensure full reproducibility?

No
Are the conclusions drawn adequately supported by the results?

Partly

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

Diabetes self-care/self-management, fatalism, spiritual care, qualitative research

Respond to this report

Responses (1)

Author Response

07 Apr 2025

Elizabeth Guzman, Nursing and Obstetrics, Universidad de Guanajuato, Celaya, 38050, Mexico

We appreciate the valuable comments and suggestions on the manuscript.
Abstract: we add aim, statistical analyses, sample size and questionnaires used
Introduction: Fatalism is widespread in risk perception and preventive or risk behaviors, and fatalism is associated with the perception of diabetes risk.
Methods: COVID-19 was included as a temporal factor since data collection was carried out during the pandemic.
Data collection took place at the beginning of the pandemic when the risk of contagion was low, so it was not evaluated.
Findings: We added a table for linear regression and its interpretation.
Discussion: The first paragraph was deleted
Some Mexicans believe that illness results from supernatural phenomena, leading them to seek help from healers or shamans rather than allopathic medical care. These healers are believed to alleviate bad luck, counteract witchcraft, or perform prayers.

View more View less

Competing Interests

No competing interests were disclosed.

Back to all reports

Reviewer Report

23 Views

04 Sep 2023 | for Version 1

Ola Sukkarieh, Hariri School of Nursing, American University of Beirut, Beirut, Beirut Governorate, Lebanon

23 Views Cite this report Responses(1)

Not Approved

needs to start with brief summary of the findings
in 1st paragraph, authors cannot introduce new concepts of risky behaviors when it is out of the scope of the paper.
presentation of findings are not aligned with T3, i.e. there is no reflection on negative or positive existing relationships.
Additionally, the variables are not well identified in the discussion as to what is the outcome of interest which is according to the methods section: Dependent variable: Perceived risk of Type 2 Diabetes Mellitus.
regression analysis is missed from the discussion.

Weakness: need to acknowledge limitations of self-report which affects biases in responses and lack of generalizability due to research design..

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?

No
Are sufficient details of methods and analysis provided to allow replication by others?

No
If applicable, is the statistical analysis and its interpretation appropriate?

No
Are all the source data underlying the results available to ensure full reproducibility?

No
Are the conclusions drawn adequately supported by the results?

No

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

My areas of expertise is diabetes self-management, fatalism in diabetes, social determinants of health

Respond to this report

Responses (1)

Author Response

07 Apr 2025

Elizabeth Guzman, Nursing and Obstetrics, Universidad de Guanajuato, Celaya, 38050, Mexico

We appreciate the valuable comments and suggestions on the manuscript.
Abstract: We added the aim, statistical analyses, sample size and questionnaires used.
Introduction: COVID-19 was added as a temporal factor since data collection was carried out during the pandemic.
Results: The scores categorized for sociodemographic data were used for descriptive statistics; however, continuous variables were used for inferential analysis.
Table 1 is extensive, which limits the possibility of adding more information on a single page.
An additional table was included for multiple linear regression.
Discussion:

A summary of the findings is written.
Some information has been deleted.
Adjustments have been made to the table, and the results are presented according to the main objective of the study. Information on the direction of the relationship between fatalism and risk perception (dependent variable) has been added.
A negative relationship was found between fatalism and risk perception for diabetes mellitus. This contrasts with a recent sample of university students, which showed that fatalistic beliefs are negatively related to risk behaviors for diabetes mellitus. These findings also align with the results of another study conducted on health professionals, which demonstrated that fatalistic beliefs negatively affect perceptions of occupational health.
In the sixth paragraph, we discuss the findings of the regression analysis.

Weakness:
Our findings are only generalizable to a rural community in Mexico. However, future studies are recommended in diverse cultural settings to replicate our findings and further explore the influence of fatalistic beliefs and perceived risk of T2DM. Additionally, qualitative studies are needed to provide a deeper understanding of fatalistic beliefs.

View more View less

Competing Interests

No competing interests were disclosed.

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

[1] 1. Carrillo-Vega MF, Salinas-Escudero G, García-Peña C, et al.: Early estimation of the risk factors for hospitalization and mortality by COVID-19 in Mexico. PLoS One. 2020 Sep [cited 2021 Apr 20]; 15(9): e0238905. PubMed Abstract | Publisher Full Text | Free Full Text

[2] 2. Woolcott OO, Castilla-Bancayán JP: The effect of age on the association between dia-betes and mortality in adult patients with COVID-19 in Mexico. Sci. Rep. 2021 Apr [cited 2022 Apr 20]; 11(1): 8386. PubMed Abstract | Publisher Full Text | Free Full Text

[3] 3. Sathish T, Chandrika AM: Newly diagnosed diabetes in patients with mild to moderate COVID-19. Diabetes Metab. Syndr. 2021 Mar-Apr [cited 2022 Jan 20]; 15(2): 569–571. PubMed Abstract | Publisher Full Text | Free Full Text

[4] 4. Singh AK, Singh R: Hyperglycemia without diabetes and new-onset diabetes are both associated with poorer outcomes in COVID-19. Diabetes Res. Clin. Pract. 2020 Sep [cited 2022 Jan 13]; 167: 108382. PubMed Abstract | Publisher Full Text | Free Full Text

[5] 5. Nguyen AP: Risk perception of developing diabetes: A concept analysis. Nurs. Forum. 2020 Nov [cited 2022 Apr 16]; 55(4): 559–568. PubMed Abstract | Publisher Full Text

[6] 6. Pelullo CP, Rossiello R, Nappi R, et al.: Diabetes Prevention: Knowledge and Perception of Risk among Italian Population. Biomed. Res. Int. 2019 Oct [cited 2022 Apr 22]; 2019: 1–7. Publisher Full Text Reference Source

[7] 7. Khan RK, Misra R, Shawley-Brzoska S, et al.: Predictors of diabetes risk perception among college students. J. Am. Coll. Heal. 2022 Aug-Sep [cited 2022 Nov 20]; 70(6): 1803–1809. PubMed Abstract | Publisher Full Text | Free Full Text

[8] 8. Koipuram A, Carroll S, Punthakee Z, et al.: Diabetes knowledge, risk perception, and quality of life among South Asian caregivers in young adulthood. BMJ Open Diabetes Res. Care. 2020 Nov [cited 2021 Aug 20]; 8: 1–7. Publisher Full Text Reference Source

[9] 9. Thompson AM, Chad KE: The relationship of pubertal status to body image, social physique anxiety, preoccupation with weight and nutritional status in young females. Can. J. Public Heal. 2000 May-Jun [cited 2021 Aug 20]; 91(3): 207–211. PubMed Abstract | Publisher Full Text | Free Full Text

[10] 10. Skøt L, Nielsen JB, Leppin A: Who perceives a higher personal risk of developing type 2 diabetes? A cross-sectional study on associations between personality traits, health-related behaviours and perceptions of susceptibility among university students in Denmark. BMC Public Health. 2018 Aug [cited 2021 Aug 03]; 18(1): 972. PubMed Abstract | Publisher Full Text | Free Full Text

[11] 11. Kowall B, Rathmann W, Stang A, et al.: Perceived risk of diabetes seriously underestimates actual diabetes risk: The KORA FF4 study. PLoS One. 2017 Jan [cited 2021 Aug 20]; 12(1): e0171152. PubMed Abstract | Publisher Full Text | Free Full Text

[12] 12. Lavielle P, Wacher N: The predictors of glucose screening: the contribution of risk perception. BMC Fam. Pract. 2014 Jun [cited 2021 Aug 20]; 15: 108. PubMed Abstract | Publisher Full Text | Free Full Text

[13] 13. Riley KE, Hay JL, Waters EA, et al.: Lay beliefs about risk: relation to risk behaviors and to probabilistic risk perceptions. J. Behav. Med. 2019 Dec [cited 2021 Jun 14]; 42(6): 1062–1072. PubMed Abstract | Publisher Full Text | Free Full Text

[14] 14. Straughan PT, Seow A: Fatalism reconceptualized: a concept to predict health screen-ing behavior. J. Gender, Cult. Heal. 1998 [cited 2021 Jun 20]; 3(2): 85–100. Publisher Full Text Reference Source

[15] 15. Esparza OA, Wiebe JS, Quiñones J: Simultaneous Development of a Multidimensional Fatalism Measure in English and Spanish. Curr. Psychol. 2015 [cited 2021 Aug 02]; 34(4): 597–612. PubMed Abstract | Publisher Full Text | Free Full Text

[16] 16. Imai Y, Onishi C, Bando T: Relationship between Older persons with cancer’ Coping Attitudes and Mental Adjustment. J. Med. Investig. 2020; 67(1.2): 44–50. PubMed Abstract | Publisher Full Text

[17] 17. Beeken RJ, Simon AE, von Wagner C , et al.: Cancer fatalism: deter-ring early presentation and increasing social inequalities? Cancer Epidemiol. Biomark. Prev. 2011 Oct [cited 2022 Jun 10]; 20(10): 2127–2131. PubMed Abstract | Publisher Full Text | Free Full Text

[18] 18. Valera P, Lian Z, Brotzman L, et al.: Fatalistic Cancer Beliefs and Information Seek-ing in Formerly Incarcerated African-American and Hispanic Men: Implications for Cancer Health Communication and Research. Health Commun. 2018 May; 33(5): 576–584. PubMed Abstract | Publisher Full Text | Free Full Text

[19] 19. Anderson AS, Caswell S, Macleod M, et al.: Health Behav-iors and their Relationship with Disease Control in People Attending Genetic Clinics with a Family History of Breast or Colorectal Cancer. J. Genet. Couns. 2017 Feb [cited 2022 May 16]; 26(1): 40–51. PubMed Abstract | Publisher Full Text | Free Full Text

[20] 20. Bachem R, Tsur N, Levin Y, et al.: Negative Affect, Fatalism, and Perceived Institutional Betrayal in Times of the Coronavirus Pandemic: A Cross-Cultural Investigation of Control Beliefs. Front. Psychol. 2020 Oct [cited 2022 Feb 18]; 11(1): 40–51. PubMed Abstract | Publisher Full Text | Free Full Text

[21] 21. Nordfjaern T, Mehdizadeh M, Fallah ZM: Social Psychology of Coronavirus Disease 2019: Do Fatalism and Comparative Optimism Affect Attitudes and Adherence to Sanitary Protocols? Front. Psychol. 2021 May [cited 2022 Feb 20]; 12. PubMed Abstract | Publisher Full Text | Free Full Text

[22] 22. Walker EA, Mertz CK, Kalten MR, et al.: Risk perception for developing diabetes: comparative risk judgments of physicians. Diabetes Care. 2003 Sep [cited 2022 Feb 20]; 26(9): 2543–2548. Publisher Full Text Reference Source

[23] 23. Joiner KL, Sternberg RM, Kennedy C, et al.: A Span-ish-Language Risk Perception Survey for Developing Diabetes: Translation Process and As-sessment of Psychometric Properties. J. Nurs. Meas. 2016 Dec [cited 2022 Feb 20]; 24(3): 365–378. PubMed Abstract | Publisher Full Text | Free Full Text

[24] 24. Shamah-Levy T, Vielma-Orozco E, Heredia-Hernández O, et al.: Encuesta Nacional de Salud y Nutrición 2018-19: Resul-tados Nacionales. Cuernavaca, México: Instituto Nacional de Salud Pública; 2020.

[25] 25. Sulaiman S, Leelavathi M, Norasyikin AW: Risk perception and knowledge regarding diabetes among offspring of type 2 diabetics at a tertiary institution. Med. J. Malaysia. 2020 Nov [cited 2022 Feb 20]; 75(6): 655–659. PubMed Abstract

[26] 26. Manrique-espinoza BCD, Salinas-Rodríguez AMC, Moreno-Tamayo KM, et al.: Condiciones de salud y estado funcional de los adultos mayores en México. Salud pública Méx. 2013 Jan [cited 2022 Feb 20]; 55(1): 323–331. Publisher Full Text Reference Source

[27] 27. Ammar A, Brach M, Trabelsi K, et al.: Effects of COVID-19 Home Confinement on Eating Behaviour and Physical Activity: Results of the ECLB-COVID19 International Online Survey. Nutrients. 2020 May [cited 2022 Feb 20]; 12(6). PubMed Abstract | Publisher Full Text | Free Full Text

[28] 28. Kumar A, Arora A, Sharma P, et al.: Is diabetes mellitus associated with mortality and severity of COVID-19? A meta-analysis. Diabetes Metab. Syndr. 2020 Jul-Aug [cited 2022 Feb 20]; 14(4): 535–545. PubMed Abstract | Publisher Full Text | Free Full Text

[29] 29. Keith KD: Cross-cultural psychology: Contemporary themes and perspectives. 2nd ed.John Wiley & Sons; 2019.

[30] 30. Zakiawati D, Setiadhi R: Oral manifestations of acute leukemia in children: family supernatural beliefs and its contribution to the prognosis of the disease. Int. J. Med. Dent. Case Rep. 2021 Jul [cited 2022 Oct 20]; 12(6): 1–4. Publisher Full Text

[31] 31. Arabiat D, Whitehead L, Al Jabery M, et al.: Beliefs About Illness and Treatment Decision Modelling During Ill-Health in Arabic Fami-lies. J. Multidiscip. Healthc. 2021 Jul [cited 2022 Aug 20]; 14: 1755–1768. PubMed Abstract | Publisher Full Text | Free Full Text

[32] 32. Vicente Sánchez B, Bonilla Romero J, Vicente Peña E, et al.: Percepción de riesgo de desarrollar diabetes mellitus en personas no diabéticas. Re-vista Finlay. 2016 [cited 2022 Aug 20]; 6(2): 81–92. Reference Source

[33] 33. Fink G: Stress: Concepts, Cognition, Emotion, and Behavior: Handbook of Stress Series. Academic Press; 2016.

[34] 34. Helgeson VS, Zajdel M: Adjusting to Chronic Health Conditions. Annu. Rev. Psychol. 2017 Jan [cited 2022 Aug 20]; 68: 545–571. Publisher Full Text Reference Source

[35] 35. Han J, Zhou X, Meng Y: The impact of religious beliefs on the health of the resi-dents-Evidence from China. Int. J. Health Plann. Manag. 2020 Jan [cited 2022 Feb 19]; 35(1): 378–393. PubMed Abstract | Publisher Full Text

[36] 36. Hill TD, Saenz JL, Rote SM: Religious Participation and Mortality Risk in Mexico. J. Gerontol. B Psychol. Sci. Soc. Sci. 2020 Apr [cited 2022 Feb 19]; 75(5): 1053–1061. PubMed Abstract | Publisher Full Text

[37] 37. Borges M, Lucchetti G, Leão FC, et al.: Religious Affiliations Influ-ence Health-Related and General Decision Making: A Brazilian Nationwide Survey. Int. J. Environ. Res. Public Health. 2021 Mar [cited 2022 Feb 19; 18(6): 2873. PubMed Abstract | Publisher Full Text | Free Full Text

[38] 38. Jalal Z, Antoniou S, Taylor D, et al.: South Asians living in the UK and adherence to coronary heart disease medication: a mixed- method study. Int. J. Clin. Pharm. 2019 Feb [cited 2022 Apr 19]; 41(1): 122–130. Publisher Full Text Reference Source

[39] 39. Ahmedani BK, Peterson EL, Wells KE, et al.: Asthma medication adherence: the role of God and other health locus of control factors. Ann. Allergy Asthma Immunol. 2013 Feb [cited 2022 Apr 19]; 110(2): 75–79.e2. PubMed Abstract | Publisher Full Text | Free Full Text

[40] 40. Kilshaw S, Omar N, Major S, et al.: Causal ex-planations of miscarriage amongst Qataris. BMC Pregnancy Childbirth. 2017 Jul [cited 2022 Apr 19]; 17(1): 250. PubMed Abstract | Publisher Full Text | Free Full Text

[41] 41. Mendoza Catalan G: Fatalism and risk perception T2DM. [Dataset]. figshare.2023. Publisher Full Text

Fatalism and knowledge associated to diabetes mellitus type 2 risk perception in Mexican population during COVID-19 confinement

Abstract

Keywords

Introduction

Methods

Ethics and consent

Design and participants

Data collection

Study variables

Questionnaires

Statistical analysis

Results

Sociodemographic characteristics

Table 1. Sociodemographic characteristics.

Table 2. Description of fatalism, knowledge, and perceived risk of T2DM.

Correlation analysis

Table 3. Correlation between fatalism and perceived risk of diabetes mellitus type 2.

Discussion

Conclusions

Data availability

Underlying data

Extended data

References

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