Physical and Psychosocial Health in Older Women with Chronic Pain: Comparing Clusters of Clinical and Nonclinical Samples

This investigation examined why some elderly women with severe pain symptoms and impairment in health status were not seen in a tertiary care pain center.Three groups of older (≥60 years) women were included in the study: women seeking chronic pain treatment at a multidisciplinary pain center (N = 49), and research volunteers from the same institution with (N = 28) and without (N = 27) chronic pain. A clustering classification technique was used to identify clusters of older women with similar physical and mental health status.We found three clusters: 1) a healthy cluster (cluster 1: mostly nonclinical women); 2) a cluster with very poor physical and mental health status (cluster 3); and 3) a cluster with low physical health but average mental health (cluster 2). Although only cluster 1 had significantly higher physical health ( P  < 0.001), all three clusters had different mental health ( P  < 0.001). Within cluster 2, clinical women had more pain than nonclinical women, but within cluster 3, this was not so, indicating that mental health issues may create an obstacle to women having their pain appropriately assessed and treated.Our findings support that while disability and pain severity contribute to specialized pain services usage among older women, there is a subgroup of people not receiving pain care for whom these pain symptoms are similar. Further studies are needed to assess the role of health-seeking behavior, coping preferences, referral patterns, and patient–physician communication on access to tertiary pain care for older women.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/79094/1/j.1526-4637.2010.00803.x.pd

Possible selves as roadmaps

Possible selves, expectations, and concerns about the coming year, can promote feeling good (‘‘I may not be doing well in school this year, but I will next year.’’) or can promote regulating for oneself (‘‘I may not be doing well in school this year, but to make sure I do better next year, I have signed up for summer tutoring.’’). We hypothesized that improved academic outcomes were likely only when a possible self could plausibly be a self-regulator. Hierarchical regression analyses supported this conclusion, with more support for the influence of self-regulation on change in behavior and academic outcomes than on affect regulation. N ¼ 160 low-income eighth graders improved grades, spent more time doing homework, participated in class more, and were referred less to summer school (controlling for fall grades and the dependent variable of interest) when academic possible selves were plausibly self-regulatory.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/64253/1/Possible_selves_as_roadmaps.pd

When mothers have serious mental health problems: Parenting as a proximal mediator

Maternal mental health (MMH) problems are associated with lack of confidence in one’s parenting, overly lax or too harsh discipline, and child academic underperformance. We asked if parenting mediates the effect of MMH problems on academic outcomes even among mothers with serious mental illness (n ¼ 164). Structural equation analyses show a significant association between MMH problems and permissive (lack of parenting confidence, lack of follow through) parenting and verbal hostility as well as worse academic outcomes (school recorded grades, teacher reported behaviour). Permissive parenting completely mediated the direct effect of MMH on academic outcomes. Further analyses showed that the mediation effect was attributed to a single component of permissive parenting—lack of parenting confidence.http://deepblue.lib.umich.edu/bitstream/2027.42/64256/1/When_mothers_have_serious_mental_health_problems.pd

Diversity of outcomes among adolescent children of mothers with mental illness

Children of parents with mental illness are an at-risk population according to research on psychiatric outcomes using white, middle-class samples of depressed parents and infants and preschool children. The current study expands this evidence by exploring within-group heterogeneity across psychosocial outcomes, in a racially diverse, low-income sample of adolescent children of mothers with mental illness (N = 166). Using measures of mental health, academics, behavior problems, and social relationships--and employing cluster analysis methodology--we identified five meaningful subgroups of these youth. Two of five identified clusters evidenced mental health symptoms (15%) or possible behavioral problems (27%). The largest cluster (30%) appeared quite socially and academically competent; another cluster (22%) presented as average in their functioning but adult-oriented. A final small cluster (4.8%) was distinguished by members' social isolation. Cluster membership related to maternal substance abuse history, father's relationship to youth, and social support available to mothers. Implication for planning preventative intervention are discussed.http://deepblue.lib.umich.edu/bitstream/2027.42/64262/1/Diversity_of_outcomes_among_children_of_mothers_with_mental_illness.pd

Racial-Ethnic Self-Schemas

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/89951/1/oyserman_et_al__2003.pd

Considerations for using race and ethnicity as quantitative variables in medical education research

Abstract Throughout history, race and ethnicity have been used as key descriptors to categorize and label individuals. The use of these concepts as variables can impact resources, policy, and perceptions in medical education. Despite the pervasive use of race and ethnicity as quantitative variables, it is unclear whether researchers use them in their proper context. In this Eye Opener, we present the following seven considerations with corresponding recommendations, for using race and ethnicity as variables in medical education research: 1) Ensure race and ethnicity variables are used to address questions directly related to these concepts. 2) Use race and ethnicity to represent social experiences, not biological facts, to explain the phenomenon under study. 3) Allow study participants to define their preferred racial and ethnic identity. 4) Collect complete and accurate race and ethnicity data that maximizes data richness and minimizes opportunities for researchers’ assumptions about participants’ identity. 5) Follow evidence-based practices to describe and collapse individual-level race and ethnicity data into broader categories. 6) Align statistical analyses with the study’s conceptualization and operationalization of race and ethnicity. 7) Provide thorough interpretation of results beyond simple reporting of statistical significance. By following these recommendations, medical education researchers can avoid major pitfalls associated with the use of race and ethnicity and make informed decisions around some of the most challenging race and ethnicity topics in medical education.http://deepblue.lib.umich.edu/bitstream/2027.42/173951/1/40037_2020_Article_602.pd