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Kids with life-threatening illnesses need cutting-edge technology and medical expertise, but families face uneven access and paths to such care.
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Randol Contreras’ drug-robber respondents were not born criminals or torturers, so how did they become "stick-up kids"?
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Indian-American spellers are known for dominance on the national stage and even host regional, culturally specific bees. How did the niche emerge?
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A new movement to drop the word "disorder" from PTSD focuses on stigma.
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How naming a medical malady can be both horrifying for new parents and a key to unlocking resources and care.
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Drawing from cumulative inequality theory, we examine the relationship between childhood disadvantage and health problems in adulthood. Using two waves of data from Midlife Development in the United States, we investigate whether childhood disadvantage is associated with adult disadvantage, including fewer social resources, and the effect of lifelong disadvantage on health problems measured at the baseline survey and a 10-year follow-up.
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Adolescents from poor versus nonpoor neighborhoods are more likely to become obese during the transition to adulthood. It is unclear whether this pertains to all adolescents from poor neighborhoods or only those who remain in disadvantaged settings. Further, it is unknown how neighborhood poverty entries and exits are associated with obesity.
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We use an empirically grounded simulation model to examine how initial smoking prevalence moderates the effectiveness of potential interventions designed to change adolescent smoking behavior. Our model investigates the differences that result when manipulating peer influence and smoker popularity as intervention levers.
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There are concerns about the meaning of self-rated health (SRH) and the factors individuals consider. To illustrate how SRH is contextualized, we examine how the obesity–SRH association varies across age, periods, and cohorts. We decompose SRH into subjective and objective components and use a mechanism-based age–period–cohort model approach with four decades (1970s to 2000s) and five birth cohorts of National Health and Nutrition Examination Survey data (N = 26,184).
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Multiple chronic conditions (i.e., multimorbidity) increase a person’s depressive symptoms more than having one chronic condition. Little is known regarding whether multimorbidity similarly increases the depressive symptoms of one’s spouse and whether this depends on type of condition, gender, or both spouses’ health status. Analysis of multiple waves of the Health and Retirement Study reveals husband’s number of chronic conditions is positively related to wife’s depressive symptoms when both spouses are chronically ill.