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MIDUS Publications Database Search

This search provides access to bibliographies of publications that use MIDUS data.

1. Search by Topic:

Affect Obesity/Weight
Aging Occupation & Employment
Allostatic Load Perceived Discrimination
Altruism Personality
Biomarkers and Neuroscience Physical Health
Cancer Psychological Well-being
Childhood/Early Life Race & Ethnicity
Chronic & Acute Challenges Religion & Spirituality
Cognitive Function Resilience
Culture/Country Sense of Control
Daily Stress Sexuality
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2. List all findings in our MIDUS database

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Number of hits: 969

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Picard, M., Juster, R.-P., Sloan, R. P., & McEwen, B. S. (2017). Mitochondrial nexus to allostatic load biomarkers. Psychosomatic Medicine, 79(1), 114-117 [Commentary on JF Wiley et al. (2016). Modeling multisystem physiological dysregulation.].
View publication via DOI: DOI:10.1097/PSY.0000000000000414
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Pitzer, L. M., & Fingerman, K. L. (2010). Psychosocial resources and associations between childhood physical abuse and adult well-being. The Journals of Gerontology Series B: Psychological Sciences and Social Sciences, 65B(4), 425.
View publication via DOI: DOI:10.1093/geronb/gbq031
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Plaut, V. C., Markus, H. R., & Lachman, M. E. (2002). Place matters: Consensual features and regional variation in American well-being and self. Journal of Personality and Social Psychology, 83(1), 160-184.
View publication via DOI: DOI:10.1037/0022-3514.83.1.160
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Plaut, V. C., Markus, H. R., Treadway, J. R., & Fu, A. S. (2012). The cultural construction of self and well-being: A tale of two cities. Personality and Social Psychology Bulletin, 38(12), 1644-1658.
View publication via DOI: DOI:10.1177/0146167212458125
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Prenda, K. M., & Lachman, M. E. (2001). Planning for the future: A life management strategy for increasing control and life satisfaction in adulthood. Psychology & Aging, 16(2), 206-216.
View publication via DOI: DOI:10.1037/0882-7974.16.2.206
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Priest, J. B. (2017). Examining differentiation of self as a mediator in the biobehavioral family model. Journal of Marital and Family Therapy. Advance online publication.
View publication via DOI: DOI:10.1111/jmft.12301
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Priest, J. B., Roberson, P. N. E., & Woods, S. B. (2018). In our lives and under our skin: An investigation of specific psychobiological mediators linking family relationships and health using the biobehavioral family model. Family Process. Advance online publication.
View publication via DOI: DOI:10.1111/famp.12357
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Priest, J. B., Woods, S. B., Maier, C. A., Parker, E. O., Benoit, J. A., & Roush, T. R. (2015). The biobehavioral family model: Close relationships and allostatic load. Social Science & Medicine, 142, 232-240.
View publication via DOI: DOI:10.1016/j.socscimed.2015.08.026
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Pudrovska, T. (2010). Cancer and mastery: Do age and cohort matter? Social Science & Medicine, 71(7), 1285-1291.
View publication via DOI: DOI:10.1016/j.socscimed.2010.06.029
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Pudrovska, T. (2010). What makes you stronger: Age and cohort differences in personal growth after cancer. Journal of Health and Social Behavior, 51(3), 260-273.
View publication via DOI: DOI:10.1177/0022146510378239
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Pudrovska, T. (2015). Gender and health control beliefs among middle-aged and older adults. Journal of Aging and Health, 27(2), 284-303.
View publication via DOI: DOI:10.1177/0898264314549659
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Pudrovska, T., & Carr, D. (2009). Age at first birth and fathers' subsequent health: Evidence from sibling and twin models. American Journal of Men's Health, 3(2), 104-115.
View publication via DOI: DOI:10.1177/1557988307306424
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Puhl, R. M., Andreyeva, T., & Brownell, K. D. (2008). Perceptions of weight discrimination: Prevalence and comparison to race and gender discrimination in America. International Journal of Obesity, 32(6), 992-1000.
View publication via DOI: DOI:10.1038/ijo.2008.22
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Puterman, E., Weiss, J., Beauchamp, M. R., Mogle, J., & Almeida, D. M. (2017). Physical activity and negative affective reactivity in daily life. Health Psychology, 36(12), 1186-1194.
View publication via DOI: DOI:10.1037/hea0000532
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Putnam, M., Morrow-Howell, N., Inoue, M., Greenfield, J. C., Chen, H., & Lee, Y. (2014). Suitability of public use secondary data sets to study multiple activities. Gerontologist, 54(5), 818-829.
View publication via DOI: DOI:10.1093/geront/gnt074
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Qian, X. L., Yarnal, C. M., & Almeida, D. (2014). Using the dynamic model of affect (DMA) to examine leisure time as a stress coping resource: Taking into account stress severity and gender difference. Journal of Leisure Research, 46(4), 483-505.
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Qian, X. L., Yarnal, C., & Almeida, D. (2013). Does leisure time as a stress coping resource increase affective complexity? Applying the dynamic model of affect (DMA). Journal of Leisure Research, 45(3), 393-414.
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Qian, X. L., Yarnal, C., & Almeida, D. (2014). Is leisure time availability associated with more or less severe daily stressors? An examination using eight-day diary data. Leisure Sciences, 36(1), 35-51.
View publication via DOI: DOI:10.1080/01490400.2014.860782

Qian, X., Yarnal, C., & Almeida, D. (2014). Does leisure time moderate or mediate the effect of daily stress on positive affect? An examination using eight-day diary data. Journal of Leisure Research, 46(1), 106-124.
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Quoidbach, J., Gilbert, D. T., & Wilson, T. D. (2013). The end of history illusion. Science, 339(6115), 96-98.
View publication via DOI: DOI:10.1126/science.1229294
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Radler, B. (2015). Making the most of data. International Innovation, 184, 28-30.
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Radler, B. T. (2014). The Midlife in the United States (MIDUS) series: A national longitudinal study of health and well-being. Open Health Data, 2(1), e3.
View publication via DOI: DOI:10.5334/ohd.ai
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Radler, B. T., & Ryff, C. D. (2010). Who participates? Accounting for longitudinal retention in the MIDUS National Study of Health and Well-Being. Journal of Aging and Health, 22(3), 307-331.
View publication via DOI: DOI:10.1177/0898264309358617
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Radler, B. T., Rigotti, A., & Ryff, C. D. (2018). Persistently high psychological well-being predicts better HDL cholesterol and triglyceride levels: Findings from the Midlife in the U.S. (MIDUS) longitudinal study Lipids in Health and Disease, 17(1), 1.
View publication via DOI: DOI:10.1186/s12944-017-0646-8
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Ransome, Y., Slopen, N., Karlsson, O., & Williams, D. R. (2017). The association between alcohol abuse and neuroendocrine system dysregulation: Race differences in a national sample. Brain, Behavior, and Immunity, 66, 313-321.
View publication via DOI: DOI:10.1016/j.bbi.2017.07.154
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Ransome, Y., Slopen, N., Karlsson, O., & Williams, D. R. (2017). Elevated inflammation in association with alcohol abuse among blacks but not whites: Results from the midus biomarker study. Journal of Behavioral Medicine. Advance online publication.
View publication via DOI: DOI:10.1007/s10865-017-9905-4
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Ready, R. E., Akerstedt, A. M., & Mroczek, D. K. (2012). Emotional complexity and emotional well-being in older adults: Risks of high neuroticism. Aging & Mental Health, 16(1), 17-26.
View publication via DOI: DOI:10.1080/13607863.2011.602961
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Reisinger Walker, E., & Druss, B. G. (2015). Rate and predictors of persistent major depressive disorder in a nationally representative sample. Community Mental Health Journal, 51(6), 701-707.
View publication via DOI: DOI:10.1007/s10597-014-9793-9
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Relton, C., Cooper, K., Viksveen, P., Fibert, P., & Thomas, K. (2017). Prevalence of homeopathy use by the general population worldwide: A systematic review. Homeopathy, 106(2), 69-78.
View publication via DOI: DOI:10.1016/j.homp.2017.03.002
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Rendina, D. N., Ryff, C. D., & Coe, C. L. (2017). Precipitous dehydroepiandrosterone declines reflect decreased physical vitality and function. he Journals of Gerontology Series A: Biological Sciences and Medical Sciences, 72(6), 747-753.
View publication via DOI: DOI:10.1093/gerona/glw135
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