Abstract
Subjective well-being refers to people’s level of satisfaction with life as a whole and with multiple dimensions within it. Interventions that promote subjective well-being are important because there is evidence that physical health, mental health, substance use, and health care costs may be related to subjective well-being. Fun For Wellness (FFW) is a new online universal intervention designed to promote growth in multiple dimensions of subjective well-being. The purpose of this study was to provide an initial evaluation of the efficacy of FFW to increase subjective well-being in multiple dimensions in a universal sample. The study design was a prospective, double-blind, parallel group randomized controlled trial. Data were collected at baseline and 30 and 60 days-post baseline. A total of 479 adult employees at a major university in the southeast of the USA were enrolled. Recruitment, eligibility verification, and data collection were conducted online. Measures of interpersonal, community, occupational, physical, psychological, economic (i.e., I COPPE), and overall subjective well-being were constructed based on responses to the I COPPE Scale. A two-class linear regression model with complier average causal effect estimation was imposed for each dimension of subjective well-being. Participants who complied with the FFW intervention had significantly higher subjective well-being, as compared to potential compliers in the Usual Care group, in the following dimensions: interpersonal at 60 days, community at 30 and 60 days, psychological at 60 days, and economic at 30 and 60 days. Results from this study provide some initial evidence for both the efficacy of, and possible revisions to, the FFW intervention.
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References
Angrist, J., Imbens, G. W., & Rubin, D. B. (1996). Identification of causal effects using instrumental variables. Journal of the American Statistical Association, 91, 444–472. doi:10.2307/2291629.
Bloom, H. S. (1984). Accounting for no-shows in experimental evaluation designs. Evaluation Review, 8, 225–246. doi:10.1177/0193841X8400800205.
Chmiel, M., Brunner, M., Martin, R., & Schalke, D. (2012). Revisiting the structure of subjective well-being in middle-aged adults. Social Indicators Research, 106, 109–116. doi:10.1007/s11205-011-9796-7.
Cobb, N. K., & Poirier, J. (2014). Effectiveness of a multimodal online well-being intervention. American Journal of Preventive Medicine, 46, 41–48. doi:10.1016/j.amepre.2013.08.018.
Conley, C. S., Durlak, J. A., & Kirsch, A. C. (2015). A meta-analysis of universal mental health prevention programs for higher education students. Prevention Science, 16, 487–507. doi:10.1007/s11121-015-0543-1.
Couper, M. P., Alexander, G. L., Maddy, N., Zhang, N., Nowak, M. A., McClure, J. B.,... Cole Johnson, C. (2010). Engagement and retention: Measuring breadth and depth of participant use of an online intervention. Journal of Medical Internet Research, 12, e52. doi:10.2196/jmir.1430
Dolan, P. (2014). Happiness by design. New York, NY: Penguin.
González, M., Coenders, G., Saez, M., & Casas, F. (2010). Non-linearity, complexity and limited measurement in the relationship between satisfaction with specific life domains and satisfaction with life as a whole. Journal of Happiness Studies, 11, 335–352. doi:10.1007/s10902-009-9143-8.
Griffin, K. W., Botvin, G. J., Scheier, L. M., Epstein, J. A., & Doyle, M. M. (2002). Personal competence skills, distress, and well-being as determinants of substance use in a predominantly minority urban adolescent sample. Prevention Science, 3, 23–33. doi:10.1023/A:1014667209130.
Harrison, P. L., Pope, J. E., Coberley, C. R., & Rula, E. Y. (2012). Evaluation of the relationship between individual well-being and future health care utilization and cost. Population Health Management, 15, 325–330. doi:10.1089/pop.2011.0089.
Hays, P. A. (2014). Creating well-being: Four steps to a happier, healthier life. Washington, DC: American Psychological Association.
Irvine, A. B., Gelatt, V. A., Hammond, M., & Seeley, J. R. (2015). A randomized study of internet parent training accessed from community technology centers. Prevention Science, 16, 597–608. doi:10.1007/s11121-014-0521-z.
Jo, B. (2002a). Estimation of intervention effects with noncompliance: Alternative model specifications. Journal of Educational and Behavioral Statistics, 27, 385–409. doi:10.3102/10769986027004385.
Jo, B. (2002b). Model misspecification sensitivity analysis in estimating causal effects of interventions with non-compliance. Statistics in Medicine, 21, 3161–3181. doi:10.1002/sim.1267.
Jo, B., Ginexi, E. M., & Ialongo, N. S. (2010). Handling missing data in randomized experiments with noncompliance. Prevention Science, 11, 384–396. doi:10.1007/s11121-010-0175-4.
Keyes, C. L. M., & Simoes, E. J. (2012). To flourish or not: Positive mental health and all-cause mortality. American Journal of Public Health, 102, 2164–2172. doi:10.2105/AJPH.2012.300918.
McDonald, R. P. (1970). The theoretical foundations of common factor analysis, principal factor analysis, and alpha factor analysis. British Journal of Mathematical and Statistical Psychology, 23, 1–21. doi:10.1111/j.2044-8317.1970.tb00432.x.
Moessner, M., Minarik, C., Ozer, F., & Bauer, S. (2016). Effectiveness and cost-effectiveness of school-based dissemination strategies of an internet-based program for the prevention and early intervention in eating disorders: A randomized trial. Prevention Science, 17, 306–313. doi:10.1007/s11121-015-0619-y.
Muthén, L. K., & Muthén, B. O. (1998-2012). Mplus user’s guide (7th ed.). Los Angeles: Muthén & Muthén.
Myers, N. D., Prilleltensky, I., Jin, Y., Dietz, S., Rubenstein, C. L., Prilleltensky, O., & McMahon, A. (2014). Empirical contributions of the past in assessing multidimensional well-being. Journal of Community Psychology, 42, 789–798. doi:10.1002/jcop.21653.
Myers, N. D., Park, S. E., Lefevor, G. T., Dietz, S., Prilleltensky, I., & Prado, G. J. (2016). Measuring multidimensional well-being with the I COPPE Scale in a Hispanic sample. Measurement in Physical Education and Exercise Science, 20, 230–243. doi:10.1080/1091367X.2016.1226836.
Norcross, J. C. (2012). Changeology: 5 steps to realizing your goals and resolutions. New York: Simon & Schuster.
Pinker, S. (2014). The village effect: How face-to-face contact can make us healthier and happier. Toronto: Random House.
Portnoy, D. B., Scott-Sheldon, L. A. J., Johnson, B. T., & Carey, M. P. (2008). Computer-delivered interventions for health promotion and behavioral risk reduction: A meta-analysis of 75 randomized controlled trials, 1988–2007. Preventive Medicine, 47, 3–16. doi:10.1016/j.ypmed.2008.02.014.
Prilleltensky, I., Dietz, S., Prilleltensky, O., Myers, N. D., Rubenstein, C. L., Jin, Y., & McMahon, A. (2015). Assessing multidimensional well-being: Development and validation of the I COPPE Scale. Journal of Community Psychology, 43, 199–226. doi:10.1002/jcop.21674.
Primack, B. A., Carroll, M. V., McNamara, M., Klem, M. L., King, B., Rich, M., ... Nayak, S. (2012). Role of video games in improving health-related outcomes: A systematic review. American Journal of Preventive Medicine, 42, 630–638. doi:10.1016/j.amepre.2012.02.023
Prochaska, J. O., Evers, K. E., Castle, P. H., Johnson, J. L., Prochaska, J. M., Rula, E. Y.,. .. Pope, J. E. (2012). Enhancing multiple domains of well-being by decreasing multiple health risk behaviors: A randomized clinical trial. Population Health Management, 15, 276–286. doi:10.1089/pop.2011.0060
Proyer, R. T., Gander, F., Wellenzohn, S., & Ruch, W. (2014). Positive psychology interventions in people aged 50-79 years: Long-term effects of placebo-controlled online interventions on well-being and depression. Aging & Mental Health, 18, 997–1005. doi:10.1080/13607863.2014.899978.
Rahmani, E., & Boren, S. A. (2012). Videogames and health improvement: A literature review of randomized controlled trials. Games for Health Journal, 1, 331–341. doi:10.1089/g4h.2012.0031.
Rath, T., & Harter, J. (2010). Well-being: The five essential elements. New York: Gallup Press.
Roepke, A. M., Jaffee, S. R., Riffle, O. M., McGonigal, J., Broome, R., & Maxwell, B. (2015). Randomized controlled trial of SuperBetter, a smartphone-based/internet-based self-help tool to reduce depressive symptoms. Games for Health Journal, 4, 235–246. doi:10.1089/g4h.2014.0046.
Rubenstein, C. L., Duff, J., Prilleltensky, I., Jin, Y., Dietz, S., Myers, N. D., & Prilleltensky, O. (2016). Demographic group differences in domain-specific well-being. Journal of Community Psychology, 44, 499–515. doi:10.1002/jcop.21784.
Rubin, D. B. (1978). Bayesian inference for causal effect: The role of randomization. Annals of Statistics, 6, 34–58. doi:10.1214/aos/1176344064.
Schwinn, T. M., Schinke, S. P., & Di Noia, J. (2010). Preventing drug abuse among adolescent girls: Outcome data from an internet-based intervention. Prevention Science, 11, 24–32. doi:10.1007/s11121-009-0146-9.
Sears, L., Shi, Y., Coberley, C., & Pope, J. (2013). Overall well-being as a predictor of health care, productivity, and retention in a large employer. Population Health Management, 16, 397–405. doi:10.1089/pop.2012.0114.
Seligman, M. (2011). Flourish: A visionary new understanding of happiness and well-being. New York: Simon and Schuster.
Stuart, E. A., Perry, D. F., Le, H.-N., & Ialongo. (2008). Estimating intervention effects of prevention programs: Accounting for noncompliance. Prevention Science, 9, 288–298. doi:10.1007/s11121-008-0104-y.
Watson, D. L., & Tharp, R. G. (2014). Self-directed behavior: Self-modification for personal adjustment (10th ed.). Belmont: Cengage Learning.
Wong, C. F., Schrager, S. M., Holloway, I. W., Meyer, I. H., & Kipke, M. D. (2014). Minority stress experiences and psychological well-being: The impact of support from and connection to social networks within the Los Angeles House and Ball communities. Prevention Science, 15, 44–55. doi:10.1007/s11121-012-0348-4.
World Health Organization. (2009). Global health risks: Mortality and burden of disease attributable to selected major risks. Geneva: World Health Organization.
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Funding
The project described was supported by funds from the Erwin and Barbara Mautner Endowed Chair in Community Well-Being at University of Miami School of Education and Human Development.
Conflict of Interest
Adam McMahon and Isaac Prilleltensky are partners in Wellnuts LLC, which may commercialize the FFW intervention described in this study.
Ethical Approval
All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. The institutional review board at the University of Miami provided necessary permission to conduct this study, IRB no. 20150237.
Informed Consent
Informed consent was obtained from all individual participants included in the study. More specifically, immediately after passing the inclusionary criteria, screened respondents were presented with the IRB-approved consent form to read and sign electronically. Those who clicked “decline to consent” were locked out of the remaining program activities.
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Myers, N.D., Prilleltensky, I., Prilleltensky, O. et al. Efficacy of the Fun For Wellness Online Intervention to Promote Multidimensional Well-Being: a Randomized Controlled Trial. Prev Sci 18, 984–994 (2017). https://doi.org/10.1007/s11121-017-0779-z
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DOI: https://doi.org/10.1007/s11121-017-0779-z