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TUScholarShare is a service to support the needs of the Temple University community around sharing, promoting, and archiving the wide range of scholarly works created in the course of research and teaching. The repository aims to make Temple scholarship freely available online to a global audience, with the goal of advancing knowledge and learning.
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Enhancing the Cardiovascular Health Construct With a Psychological Health Metric for Predicting Mortality RiskBACKGROUND: The American Heart Association’s Life’s Essential 8 (LE8) Presidential Advisory deemed psychological health foundational for cardiovascular health (CVH) but did not include it as a CVH metric. OBJECTIVES: The purpose of this study was to evaluate associations of a CVH construct enhanced with a ninth metric for psychological health based on readily administered depression screening with mortality risk in U.S. adults. METHODS: Participants were 21,183 adults (mean age: 48y, 51% female, 11% Black, 15% Hispanic, 65% White) from the 2011 to 2018 National Health and Nutrition Examination Survey. The LE8 algorithm was used to assess CVH. Two enhanced CVH constructs that include a ninth psychological health metric based on depression screening using the Patient Health Questionnaires (PHQ-2 and PHQ-9) were computed. Multivariable Cox proportional hazards models compared all-cause and cause-specific mortality risk across CVH score tertiles and a priori defined categories (high: 80-100, moderate: 50-79, low: 0-49) in the overall sample and by sex and race and ethnicity. RESULTS: There were 1,397 deaths (414 cardiovascular and 329 cancer deaths). High vs low CVH scores, enhanced with PHQ-2 and PHQ-9, were associated with 69% and 70% lower mortality risk, while a high vs low LE8 score was associated with 65% lower risk (p-trend<0.001). Higher LE8 and enhanced CVH scores predicted lower mortality risk in both sexes and in Black and White but not Hispanic adults and were also associated with lower cardiovascular and cancer mortality. Both enhanced CVH scores had excellent performance for predicting mortality, similar to the LE8 score (C-statistic ¼ 0.843 vs 0.842, P < 0.001). CONCLUSIONS: A CVH construct enhanced with psychological health strongly predicts mortality. Inclusion of psychological health as a ninth CVH metric, with depression screening as a feasible proxy in clinical and public health settings, should be considered. (JACC Adv. 2024;3:101112)
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Prevalence of pain and use of prescription opioids among older adults: results from the Brazilian Longitudinal Study of Aging (ELSI-Brazil)Background: Pain has a significant impact on people’s quality of life. The use of prescription opioids to treat pain is associated with an increased risk of opioid use disorders and overdose death. We measured the prevalence of recurrent pain, prescription opioid use, and associations between chronic conditions and prescription opioid use among Brazilian older adults. Methods: We used data from the first population-based longitudinal study of aging in Brazil (ELSI-Brazil), 2019–2020 (mean age = 63.3; 54.4% female). Outcomes were: (1) experience of recurrent pain and (2) use of opioid analgesics in the past three months among those who experience pain. Exposures included selected health conditions, history of falls, and hospitalizations. Findings: Prevalence of pain (n = 9234) was 36.9% (95% CI: 32.6–41.1). Pain was reported more frequently by female participants, low-income individuals, and those with a previous diagnosis of arthritis, chronic back pain, depressive symptoms, history of falls, and hospitalizations. Prevalence of opioid use among those reporting pain (n = 3350) was 30% (95% CI: 23.1–38.0). Prevalence of opioid use was higher among female and single individuals. In adjusted models, arthritis, chronic back pain, and presence of depressive symptoms were associated with prescription opioid use. Interpretation: Prescription opioid use was reported by a sizable portion of the older adults who suffer from pain in Brazil. In a context of growing consumption of prescription opioids, opioid misuse has the potential to increase in the future. Surveillance of prescription opioid use is critical to prevent their harmful consequences.
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Facilitating treatment engagement for early psychosis through peer-delivered decision support: intervention development and protocol for pilot evaluationBackground: Emerging adults with early psychosis demonstrate high rates of service disengagement from critical early intervention services. Decision support interventions and peer support have both been shown to enhance service engagement but are understudied in this population. The purposes of this article are to describe the development of a novel peer-delivered decision coaching intervention for this population and to report plans for a pilot study designed to gather preliminary data about its feasibility, acceptability, and potential impact. Methods: The intervention was developed based on formative qualitative data and in collaboration with a diverse team of researchers, key stakeholders, and expert consultants. The pilot trial will utilize a single-group (N = 20), pre-post, convergent mixed-methods design to explore whether and how the intervention addresses decision-making needs (the primary intervention target). The impact of the intervention on secondary outcomes (e.g., engagement in the program) will also be assessed. Additionally, through observation and feedback from the peer decision coach and study participants, we will evaluate the feasibility of research and intervention procedures, and the acceptability of information and support from the peer decision coach. Discussion: The peer-delivered decision coaching intervention holds promise for assisting young people with making informed and values-consistent decisions about their care, and potentially enhancing service engagement within this traditionally difcult-to-engage population. If the intervention demonstrates feasibility and acceptability, and pilot data show its potential for improving treatment decision-making, our work will also lay the foundation for a new evidence base regarding roles for peer specialists on early intervention teams.
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Do Patient Preferences Align With Value Frameworks? A Discrete-Choice Experiment of Patients With Breast CancerPurpose. Assess patient preferences for aspects of breast cancer treatments to evaluate and inform the usual assumptions in scoring rubrics for value frameworks. Methods. A discrete-choice experiment (DCE) was designed and implemented to collect quantitative evidence on references from 100 adult female patients with a self-reported physician diagnosis of stage 3 or stage 4 breast cancer. Respondents were asked to evaluate some of the treatment aspects currently considered in value frameworks. Respondents’ choices were analyzed using logit-based regression models that produced preference weights for each treatment aspect considered. Aggregate- and individual-level preferences were used to assess the relative importance of treatment aspects and their variability across respondents. Results. As expected, better clinical outcomes were associated with higher preference weights. While life extensions with treatment were considered to be most important, respondents assigned great value to out-of-pocket cost of treatment, treatment route of administration, and the availability of reliable tests to help gauge treatment efficacy. Two respondent classes were identified in the sample. Differences in class-specific preferences were primarily associated with route of administration, out-of-pocket treatment cost, and the availability of a test to gauge treatment efficacy. Only patient cancer stage was found to be correlated with class assignment (P = 0.035). Given the distribution of individual-level preference estimates, preference for survival benefits are unlikely to be adequately described with two sets of preference weights. Conclusions. Although value frameworks are an important step in the systematic evaluation of medications in the context of a complex treatment landscape, the frameworks are still largely driven by expert judgment. Our results illustrate issues with this approach as patient preferences can be heterogeneous and different from the scoring weights currently provided by the frameworks.
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Do people have difering motivations for participating in a stated-preference study? Results from a latent-class analysisBackground: Researchers and policy makers have long suspected that people have differing, and potentially nefarious, motivations for participating in stated-preference studies such as discrete-choice experiments (DCE). While anecdotes and theories exist on why people participate in surveys, there is a paucity of evidence exploring variation in preferences for participating in stated-preference studies. Methods: We used a DCE to estimate preferences for participating in preference research among an online survey panel sample. Preferences for the characteristics of a study to be conducted at a local hospital were assessed across five attributes (validity, relevance, bias, burden, time and payment) and described across three levels using a starring system. A D-efficient experimental design was used to construct three blocks of 12 choice tasks with two profiles each. Respondents were also asked about factors that motivated their choices. Mixed logistic regression was used to analyze the aggregate sample and latent class analysis identified segments of respondents. Results: 629 respondents completed the experiment. In aggregate “study validity” was most important. Latent class results identified two segments based on underlying motivations: a quality-focused segment (76%) who focused most on validity, relevance, and bias and a convenience-focused segment (24%) who focused most on reimbursement and time. Quality-focused respondents spent more time completing the survey (p < 0.001) and were more likely to identify data quality (p < 0.01) and societal well-being (p < 0.01) as motivations to participate. Conclusions: This information can be used to better understand variability in motivations to participate in stated-preference surveys and the impact of motivations on response quality.