Abstract
Previous research suggested the negative implications of fatalism for mental health. The present study addressed more nuanced associations between fatalism and mental health by taking the multidimensionality of fatalism and socioeconomic status (SES) into consideration. Students in an introductory undergraduate course (208 included; mean age: 19.3 [SD = 3.9]) completed an online questionnaire related to demographic characteristics, fatalism, and mental health. Their data was analyzed using sets of regression models to examine whether the five dimensions of fatalism, such as helplessness and (low) internality, mediated the associations of SES with depressive symptoms and perceived stress and whether SES moderated the associations between each fatalism dimension and these mental health outcomes. The mediation was found for helplessness, but not for the other fatalism dimensions, in which lower SES predicted higher helplessness, which in turn predicted greater depressive symptoms and perceived stress. In addition, the moderation of SES was found only for the association between internality and depressive symptoms: internality predicted greater depressive symptoms for those with lower SES. This indicated negative implications of internality contrary to previous findings. The present study also highlighted the importance of specifically addressing helplessness, rather than fatalism in general, as a potential risk factor for mental health.
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The datasets generated and analyzed during the current study are available from the corresponding author upon reasonable request.
Notes
Some other potential factors that may have contributed to having the inconsistent findings for the links between fatalism (or locus of control) and mental health are religiosity and culture. With regard to religiosity, beliefs in divine control have been identified as one dimension of fatalism that is not associated with negative mental health (Esparza et al., 2015). In addition, opposed to the approach of treating fatalism as unitary construct, in their study for religious individuals, Shahid et al. (2020) suggested different forms of fatalism: active fatalism versus passive fatalism. Unlike passive fatalism (i.e., traditionally defined fatalism), active fatalism involves a combination of accepting situations and maintaining individual agency to influence their future outcomes and is actually inversely linked to external locus of control as well as depressive symptoms. With regard to culture, in a meta analysis (C. Cheng et al., 2013b), the associations between external locus of control and anxiety were weaker for those in collectivist societies compared to those in individualist societies. For example, Chinese culture promotes an approach to proactively dealing with life adversities to have better outcomes while acknowledging the uncontrollability of those events, so having fatalistic beliefs may not necessarily have negative implications for mental health among Chinese individuals (T. Cheng et al., 2013b; Lu et al., 2022). Although we acknowledged the importance of taking these factors into consideration in investigating the links of fatalism to mental health, we narrowed our focus by only addressing the multidimensionality of fatalism and SES in the present study.
Our target power was 0.80. Since we analyzed a mediation model consisting of two sets of regression submodels for each mental health outcome, we conducted multiple power analyses. First, using G*Power 3.1 (Faul et al., 2007), we calculated a desired sample size for each regression submodel with the following settings: α = 0.05 (two-tail), f2 = 0.15 (i.e., medium effect), power = 0.90, and the number of predictors = 6 (for the regression submodel that included the largest number of predictors, including SES and five fatalism dimensions, than the other submodels). For this specific analysis, we selected a power of 0.90 considering our focus on indirect effects involving coefficients in combinations of submodels (i.e., 0.90 × 0.90 = 0.81, which would exceed our target power). The analysis indicated the total sample size should be at least 73. In addition, using the MedPower developed by David A. Kenny (https://davidakenny.shinyapps.io/MedPower/), we calculated the sample size with a power of 0.80 to detect an indirect effect a × b (with standardized regression coefficients of 0.30 × 0.30 = 0.09) and obtained the result showing the minimum sample size should be 113. Our sample size (N = 208) exceeded the minimum sizes suggested by these power analyses.
To check the assumptions of linearity, homoscedasticity, and normality, we obtained a scatterplot for standardized predicted values and standardized residuals for the outcome of each regression submodel (i.e., each fatalism dimension predicted by SES or each mental health outcome predicted by SES and/or the five fatalism dimensions) using SPSS. We then conducted visual inspections for the patterns of the residuals in each scatterplot (Tabachnick & Fidell, 2013). For linearity, we inspected whether non-linear or curvilinear patterns were observed (if not, the assumption was met). For homoscedasticity, we inspected whether heteroscedasticity patterns, or uneven spreads of residuals (e.g., the variances of residuals increasing or decreasing with increases in the predicted values), were observed (if not, the assumption was met). For normality, we inspected whether the residuals were spread out asymmetrically from the center of the scatterplot (if not [i.e., if spread out symmetrically], the assumption was met). Additionally, we inspected the P-P plots obtained with SPSS to see whether any major deviations of the data from the reference line for the theoretical distribution (indicating major violations for normality) were observed. In all the visual inspections, we found no major violations for these assumptions. To check potential multicollinearity or the lack thereof, we obtained collinearity statistics, including values of tolerance and variance inflation factor (VIF), for the submodels including multiple predictors (i.e., those with SES and five fatalism dimensions predicting each mental health outcome). We used the criteria of tolerance < 0.10 and VIF > 10 as potential multicollinearity. All the values of tolerance (greater than 0.58) and VIF (between 1 and 2) in the regression submodels did not indicate any concerns of multicollinearity.
References
Adler, N. E., Epel, E. S., Castellazzo, G., & Ickovics, J. R. (2000). Relationship of subjective and objective social status with psychological and physiological functioning: Preliminary data in healthy, white women. Health Psychology, 19(6), 586–592. https://doi.org/10.1037/0278-6133.19.6.586.
Appalachian Regional Commission (2024). Population and age in Appalachia. Retrieved February 20, 2024, from https://www.arc.gov/about-the-appalachian-region/the-chartbook/appalachias-population/.
Bąk-Sosnowska, M., Gruszczyńska, M., Wyszomirska, J., & Daniel-Sielańczyk, A. (2022). The influence of selected psychological factors on medication adherence in patients with chronic diseases. Healthcare, 10(3), 426. https://doi.org/10.3390/healthcare10030426.
Beeken, R. J., Simon, A. E., von Wagner, C., Whitaker, K. L., & Wardle, J. (2011). Cancer fatalism: Deterring early presentation and increasing social inequalities? Cancer Epidemiology Biomarkers & Prevention, 20(10), 2127–2131. https://doi.org/10.1158/1055-9965.EPI-11-0437.
Braun, M., Hershkovitz, T. A., Melumad, N. M., & Goldzweig, G. (2022). The paradox: Guilt as an antidote to helplessness among oncologists. Supportive Care Cancer, 30(9), 7545–7551. https://doi.org/10.1007/s00520-022-07196-y.
Cheng, C., Cheung, S. F., Chio, J. H., & Chan, M. P. (2013). Cultural meaning of perceived control: A meta-analysis of locus of control and psychological symptoms across 18 cultural regions. Psychological Bulletin, 139(1), 152–188. https://doi.org/10.1037/a0028596.
Cheng, H., Sit, J. W., Twinn, S. F., Cheng, K. K., & Thorne, S. (2013b). Coping with breast cancer survivorship in Chinese women: The role of fatalism or fatalistic voluntarism. Cancer Nursing, 36(3), 236–244. https://doi.org/10.1097/NCC.0b013e31826542b2.
Clark, D. A. (2013). Cognitive restructuring. In S.G. Hofmann (Ed.), The Wiley Handbook of Cognitive Behavioral Therapy (pp. 23–44). https://doi.org/10.1002/9781118528563.wbcbt02.
Cohen, S., & Janicki-Deverts, D. (2012). Who’s stressed? Distributions of psychological stress in the United States in probability samples from 1983, 2006 and 2009. Journal of Applied Social Psychology, 42(6), 1320–1334. https://doi.org/10.1111/j.1559-1816.2012.00900.x.
Cohen, S., Kamarck, T., & Mermelstein, R. (1983). A global measure of perceived stress. Journal of Health and Social Behavior, 24, 385–396. https://doi.org/10.2307/2136404.
Culpin, I., Stapinski, L., Miles, Ö. B., Araya, R., & Joinson, C. (2015). Exposure to socioeconomic adversity in early life and risk of depression at 18 years: The mediating role of locus of control. Journal of Affective Disorders, 183, 269–278. https://doi.org/10.1016/j.jad.2015.05.030.
Dijkstra, M. T., Beersma, B., & Evers, A. (2011). Reducing conflict-related employee strain: The benefits of an internal locus of control and a problem-solving conflict management strategy. Work & Stress, 2(2), 167–184. https://doi.org/10.1080/02678373.2011.593344.
Esparza, O. A., Wiebe, J. S., & Quiñones, J. (2015). Simultaneous development of a multidimensional fatalism measure in English and Spanish. Current Psychology, 34(4), 597–612. https://doi.org/10.1007/s12144-014-9272-z.
Evans, G. W. (2016). Childhood poverty and adult psychological well-being. Psychological and Cognitive Sciences, 113(52), 14949–14952. https://doi.org/10.1073/pnas.1604756114.
Faul, F., Erdfelder, E., Lang, A. G., & Buchner, A. (2007). G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior Research Methods, 39, 175–191.
Fu, J., Zhao, Y., Feng, X., Wang, Y., Yu, Z., Hua, L., & Li, J. (2021). How is fatalistic determinism linked to depression? The mediating role of self-control and resilience. Personality and Individual Differences, 180, 110992.
Galvin, B. M., Randel, A. E., Collins, B. J., & Johnson, R. E. (2018). Changing the focus of locus (of control): A targeted review of the locus of control literature and agenda for future research. Journal of Organizational Behavior, 39(7), 820–833. https://doi.org/10.1002/job.2275.
Garza, J. R., Glenn, B. A., Mistry, R. S., Ponce, N. A., & Zimmerman, F. J. (2017). Subjective social status and self-reported health among US-born and immigrant latinos. Journal of Immigrant and Minority Health, 19(1), 108–119. https://doi.org/10.1007/s10903-016-0346-x.
Gore, J. S., Griffin, D. P., & McNierney, D. (2016). Does internal or external locus of control have a stronger link to mental and physical health? Psychological Studies, 61, 181–196. https://doi.org/10.1007/s12646-016-0361-y.
Haushofer, J., & Fehr, E. (2014). On the psychology of poverty. Science, 344(6186), 862–867. https://doi.org/10.1126/science.1232491.
Hayes, A. F. (2018). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach (2nd ed.). Guilford.
Henrich, J., Heine, S. J., & Norenzayan, A. (2010). The weirdest people in the world? Behavioral and Brain Sciences, 33(2–3), 61–83. https://doi.org/10.1017/S0140525X0999152X.
Kausmann, C., Cohrdes, C., & RKI-SOEP-2-study group. (2022). What factors contribute to maintaining mental well-being during the COVID-19 pandemic? European Journal of Public Health, 32(3). https://doi.org/10.1093/eurpub/ckac131.067.
Krause, E. D., Vélez, C. E., Woo, R., Hoffmann, B., Freres, D. R., Abenavoli, R. M., & Gillham, J. E. (2018). Rumination, depression, and gender in early adolescence: A longitudinal study of a bidirectional model. The Journal of Early Adolescence, 38(7), 923–946. https://doi.org/10.1177/0272431617704956.
Kroenke, K., Spitzer, R. L., & Williams, J. B. (2001). The PHQ-9: Validity of a brief depression severity measure. Journal of General Internal Medicine, 16(9), 606–613.
Lachman, M. E., Neupert, S. D., & Agrigoroaei, S. (2011). The relevance of control beliefs for health and aging. In K. W. Schaie & S. L. Willis (Eds.), Handbook of the psychology of aging (pp. 175–190). Academic Press. https://doi.org/10.1016/C2009-0-01966-7.
Lassi, G., Taylor, A. E., Mahedy, L., Heron, J., Eisen, T., & Munafò, M. R. (2019). Locus of control is associated with tobacco and alcohol consumption in young adults of the Avon Longitudinal Study of parents and children. Royal Society Open Science, 6(3), 181133. https://doi.org/10.1098/rsos.181133.
Lu, L., Liu, J., & Yuan, Y. C. (2022). Cultural differences in cancer information acquisition: cancer risk perceptions, fatalistic beliefs, and worry as predictors of cancer information seeking and avoidance in the US and China. Health Communication, 37(11), 1442–1451. https://doi.org/10.1080/10410236.2021.1901422.
Maercker, A., Ben-Ezra, M., Esparza, O. A., & Augsburger, M. (2019). Fatalism as a traditional cultural belief potentially relevant to trauma sequelae: Measurement equivalence, extent and associations in six countries. European Journal of Psychotraumatology, 10(1), 1657371. https://doi.org/10.1080/20008198.2019.1657371.
Operario, D., Adler, N. E., & Williams, D. R. (2004). Subjective social status: Reliability and predictive utility for global health. Psychology & Health, 19(2), 237–246. https://doi.org/10.1080/08870440310001638098.
Peterson, C., Seligman, M. E., & Vaillant, G. E. (1988). Pessimistic explanatory style is a risk factor for physical illness: A thirty-five-year longitudinal study. Journal of Personality and Social Psychology, 55(1), 23–27. https://doi.org/10.1037//0022-3514.55.1.23.
Powe, B. D. (1997). Cancer fatalism—spiritual perspectives. Journal of Religion and Health, 36, 135–144.
Ridley, M., Rao, G., Schilbach, F., & Patel, V. (2020). Poverty, depression, and anxiety: Causal evidence and mechanisms. Science, 370(6522). https://doi.org/10.1126/science.aay0214.
Roberts, R. E., Roberts, C. R., & Chen, I. G. (2000). Fatalism and risk of adolescent depression. Psychiatry, 63(3), 239–252. https://doi.org/10.1080/00332747.2000.11024917.
Robinson, S. A., & Lachman, M. E. (2017). Perceived control and aging: A mini-review and directions for future research. Gerontology, 63(5), 435–442.
Ross, C. E., Mirowsky, J., & Cockerham, W. C. (1983). Social class, Mexican culture, and fatalism: Their effects on psychological distress. American Journal of Community Psychology, 11(4), 383–399.
Rotter, J. B. (1966). Generalized expectancies for internal versus external control of reinforcement. Psychological Monographs: General and Applied, 80(1), 1–28.
Sagone, E., & De Caroli, M. E. (2014). A correlational study on dispositional resilience, psychological well-being, and coping strategies in university students. American Journal of Educational Research, 2(7), 463–471.
Saleh, T. J., Shahab, S., & Mehmood, M. T. (2022). Role of locus of control in satisfaction with work-life balance in the life of working women. Pakistan Journal of International Affairs, 5(3), 529–540. https://doi.org/10.52337/pjia.v5i3.614.
Seligman, M. E. (1972). Learned helplessness. Annual Review of Medicine, 23(1), 407–412.
Shahid, F., Beshai, S., & Del Rosario, N. (2020). Fatalism and depressive symptoms: Active and passive forms of fatalism differentially predict depression. Journal of Religion and Health, 59, 3211–3226. https://doi.org/10.1007/s10943-020-01024-5.
Singh-Manoux, A., Marmot, M. G., & Adler, N. E. (2005). Does subjective social status predict health and change in health status better than objective status? Psychosomatic Medicine, 67(6), 855–861. https://doi.org/10.1097/01.psy.0000188434.52941.a0.
Sullivan, S., Yamasaki, S., Ando, S., Endo, K., Kasai, K., Culpin, I., & Nishida, A. (2021). The association between locus of control and psychopathology: A cross-cohort comparison between a UK (Avon Longitudinal Study of Parents and Children) and a Japanese (Tokyo Teen Cohort) cohort. Frontiers in Psychology, 12, 600941. https://doi.org/10.3389/fpsyg.2021.600941.
Tabachnick, B. G., & Fidell, L. S. (2013). Using multivariate statistics (6th ed.). Pearson.
Tan, J. J. X., Kraus, M. W., Carpenter, N. C., & Adler, N. E. (2020). The association between objective and subjective socioeconomic status and subjective well-being: A meta-analytic review. Psychological Bulletin, 146(11), 970–1020. https://doi.org/10.1037/bul0000258.
Trindade, I. A., Mendes, A. L., & Ferreira, N. B. (2020). The moderating effect of psychological flexibility on the link between learned helplessness and depression symptomatology: A preliminary study. Journal of Contextual Behavioral Science, 15, 68–72. https://doi.org/10.1016/j.jcbs.2019.12.001.
Tsai, W., & Wang, J. H. Y. (2022). Fatalism and psychological distress among Chinese-American breast cancer survivors: Mediating role of perceived self-control and fear of cancer recurrence. International Journal of Behavioral Medicine. Advanced online publication. https://doi.org/10.1007/s12529-022-10136-z.
Valenti, G. D., & Faraci, P. (2022). Instruments measuring fatalism: A systematic review. Psychological Assessment, 34(2), 159–175. https://doi.org/10.1037/pas0001076.
Welch, W. (2011). Self control, fatalism, and health in Appalachia. Journal of Appalachian Studies, 17(1–2), 108–122. https://doi.org/10.2307/41446937.
Wepf, H., Joseph, S., & Leu, A. (2021). Pathways to mental well-being in young carers: The role of benefit finding, coping, helplessness, and caring tasks. Journal of Youth and Adolescence, 50(9), 1911–1924. https://doi.org/10.1007/s10964-021-01478-0.
Wiersma, J. E., van Oppen, P., van Schaik, D. J., van der Does, A. J., Beekman, A. T., & Penninx, B. W. (2011). Psychological characteristics of chronic depression: A longitudinal cohort study. The Journal of Clinical Psychiatry, 72(3), 288–294. https://doi.org/10.4088/JCP.09m05735blu.
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Toyama, M., Morris, K.L. Nuanced associations among fatalism, socioeconomic status, and mental health among undergraduate students. Curr Psychol 43, 19906–19917 (2024). https://doi.org/10.1007/s12144-024-05812-0
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DOI: https://doi.org/10.1007/s12144-024-05812-0