Journal of Clinical and Translational Science最新文献

Introduction: Alleviation of symptom severity for major depressive disorder (MDD) is known to be associated with a lagged improvement of functioning. Pharmacotherapy guidelines support algorithms for MDD treatment. However, it is currently unclear whether concordance with guidelines influences functional recovery. A guideline concordance algorithm (GCA-8) was used to measure this pathway in a naturalistic clinical setting.

Methods: Data from 1403 adults (67% female, 84% non-Hispanic/Latino White, mean age of 43 years) with nonpsychotic MDD from the Penn State Psychiatry Clinical Assessment and Rating Evaluation System registry (visits from 02/01/2015 to 04/13/2021) were evaluated. Multivariable linear regression measured associations between GCA-8 and World Health Organization Disability Assessment Schedule 2.0 (WHODAS) scores. Mediation by MDD symptom severity using the Patient Health Questionnaire depression module (PHQ-9) was also evaluated.

Results: This study found a statistically significant improvement in WHODAS scores (functioning) between baseline and final measures (-2 points, P < .001) within one year. A one standard deviation increase in the GCA-8 score was associated with a 0.48-point reduction in mean disability score (total effect; P = .02) with significant mediation by the change in MDD symptom severity (coefficient = -0.51, P < .001) and a nonsignificant natural direct effect of the GCA-8 independent of PHQ-9 change (coefficient = -0.02, P = .92).

Conclusions: Higher pharmacotherapy guideline concordance is associated with better functioning for MDD patients; this association likely occurs through improvement in MDD symptom severity rather than directly.

Multisector stakeholders, including, community-based organizations, health systems, researchers, policymakers, and commerce, increasingly seek to address health inequities that persist due to structural racism. They require accessible tools to visualize and quantify the prevalence of social drivers of health (SDOH) and correlate them with health to facilitate dialog and action. We developed and deployed a web-based data visualization platform to make health and SDOH data available to the community. We conducted interviews and focus groups among end users of the platform to establish needs and desired platform functionality. The platform displays curated SDOH and de-identified and aggregated local electronic health record data. The resulting Social, Environmental, and Equity Drivers (SEED) Health Atlas integrates SDOH data across multiple constructs, including socioeconomic status, environmental pollution, and built environment. Aggregated health prevalence data on multiple conditions can be visualized in interactive maps. Data can be visualized and downloaded without coding knowledge. Visualizations facilitate an understanding of community health priorities and local health inequities. SEED could facilitate future discussions on improving community health and health equity. SEED provides a promising tool that members of the community and researchers may use in their efforts to improve health equity.

The US biomedical research workforce suffers from systemic barriers causing insufficient diversity and perpetuating inequity. To inform programming enhancing graduate program access, we implemented a formative mixed-method study to identify needed supports for program applications and graduate program success. Overall, results indicate value in added supports for understanding application needs, network development, critical thinking, time management, and reading academic/scientific literature. We find selected differences for underrepresented minority (URM) students compared to others, including in the value of psychosocial supports. This work can inform broader efforts to enhance graduate school access and provides foundation for further understanding of URM students' experiences.

Background: Cervical cancer screening rates in the USA fall behind national targets, requiring innovation to circumvent screening barriers. Cervical cancer screening where human papillomavirus (HPV) testing is performed on vaginal samples collected by the patients themselves (self-sampling) are effective and acceptable, and patient-operated rapid HPV tests (self-testing) are currently under development. It is unclear why there is ambivalence toward HPV self-sampling and self-testing among clinicians, an important stakeholder group. We conducted a mixed convergent quantitative and qualitative study to identify the factors influencing clinicians' attitudes toward self-sampling and self-testing.

Methods: A survey of Midwest clinicians distributed by professional group media and a market research firm between May and November 2021 was analyzed (n = 248) alongside in-depth interviews with Midwest clinicians from professional groups (n = 23). Logistic regression models examined willingness to support self-sampling and self-testing across respondent characteristics.

Results: We report that family practice physicians and those in rural areas were more willing to adopt HPV self-sampling (adjusted OR (aOR) = 3.16 [1.43-6.99]; aOR = 2.17 [1.01-4.68]). Clinician willingness to support self-testing was positively associated with current use of self-testing for other conditions and negatively associated with performing 10 or more monthly cervical cancer screenings (aOR = 2.02 [1.03-3.95], aOR = 0.42 [0.23-0.78]). Qualitative data contextualize how clinical specialty and experience with self-sampling and self-testing for other conditions inform clinician perspectives.

Conclusion: These data suggest clinician populations most accepting of initiatives to implement self-sampling and self-testing for cervical cancer screening and highlight that experience with other forms of self-testing could facilitate more widespread adoption for cervical cancer.