COVID-19 was a collective traumatic event; however, different individuals may have perceived it differently.

This study investigated what older people in a collective culture perceived as stressful during COVID-19 and examined how different stressors related to COVID-19 infection and mental health risks.

Thirty-six participants from diverse backgrounds engaged in a three-round Delphi study to generate items for a COVID-19-related stress scale for older adults (CSS-OA). Subsequently, 4674 people (aged ≥60 years) participated in a cross-sectional telephone survey; interviewers collected their responses to CSS-OA and information about COVID-19 infection, depressive symptoms, anxiety, loneliness and demographics. Exploratory factor analysis and confirmatory factor analysis were conducted on CSS-OA. A multiple indicator multiple cause (MIMIC) model was used to examine associations between CSS-OA and other measures.

The Delphi process generated eight items, all secondary or tertiary stressors related to infection. Exploratory factor analysis revealed a three-factor model, and confirmatory factor analysis confirmed an excellent fit (comparative fit index = 0.99, root mean square error of approximation = 0.06). Pre-existing mental health conditions, having family members/friends infected with COVID-19, loneliness, anxiety and depressive symptoms were associated with higher stress. Conversely, self-infection with COVID-19, older age, being female and living alone were negatively associated with some domains of CSS-OA (all P < 0.05).

The Delphi process enhanced our understanding of what older people perceived as stressful, much of which resulted from certain healthcare strategies and reflected cultural influences. These and the MIMIC results highlight the need to balance public health policies with respect to infectious diseases and older people's mental health and quality of life.

Despite advances in incorporating diversity and structural competency into medical education curriculum, there is limited curriculum for public health research professionals. We developed and implemented a four-part diversity, equity, and inclusion (DEI) training series tailored for academic health research professionals to increase foundational knowledge of core diversity concepts and improve skills.

We analyzed close- and open-ended attendee survey data to evaluate within- and between-session changes in DEI knowledge and perceived skills.

Over the four sessions, workshop attendance ranged from 45 to 82 attendees from our 250-person academic department and represented a mix of staff (64%), faculty (25%), and trainees (11%). Most identified as female (74%), 28% as a member of an underrepresented racial and ethnic minority (URM) group, and 17% as LGBTQI. During all four sessions, attendees increased their level of DEI knowledge, and within sessions two through four, attendees’ perception of DEI skills increased. We observed increased situational DEI awareness as higher proportions of attendees noted disparities in mentoring and opportunities for advancement/promotion. An increase in a perceived lack of DEI in the workplace as a problem was observed; but only statistically significant among URM attendees.

Developing applied curricula yielded measurable improvements in knowledge and skills for a diverse health research department of faculty, staff, and students. Nesting this training within a more extensive program of departmental activities to improve climate and address systematic exclusion likely contributed to the series’ success. Additional research is underway to understand the series’ longer-term impact on applying skills for behavior change.

We tested the ability of our natural language processing (NLP) algorithm to identify delirium episodes in a large-scale study using real-world clinical notes.

We used the Rochester Epidemiology Project to identify persons ≥ 65 years who were hospitalized between 2011 and 2017. We identified all persons with an International Classification of Diseases code for delirium within ±14 days of a hospitalization. We independently applied our NLP algorithm to all clinical notes for this same population. We calculated rates using number of delirium episodes as the numerator and number of hospitalizations as the denominator. Rates were estimated overall, by demographic characteristics, and by year of episode, and differences were tested using Poisson regression.

In total, 14,255 persons had 37,554 hospitalizations between 2011 and 2017. The code-based delirium rate was 3.02 per 100 hospitalizations (95% CI: 2.85, 3.20). The NLP-based rate was 7.36 per 100 (95% CI: 7.09, 7.64). Rates increased with age (both p < 0.0001). Code-based rates were higher in men compared to women (p = 0.03), but NLP-based rates were similar by sex (p = 0.89). Code-based rates were similar by race and ethnicity, but NLP-based rates were higher in the White population compared to the Black and Asian populations (p = 0.001). Both types of rates increased significantly over time (both p values < 0.001).

The NLP algorithm identified more delirium episodes compared to the ICD code method. However, NLP may still underestimate delirium cases because of limitations in real-world clinical notes, including incomplete documentation, practice changes over time, and missing clinical notes in some time periods.

Post-traumatic stress disorder (PTSD) is associated with cognitive impairments. It is unclear whether problems persist after PTSD symptoms remit.

Data came from 12 270 trauma-exposed women in the Nurses' Health Study II. Trauma and PTSD symptoms were assessed using validated scales to determine PTSD status as of 2008 (trauma/no PTSD, remitted PTSD, unresolved PTSD) and symptom severity (lifetime and past-month). Starting in 2014, cognitive function was assessed using the Cogstate Brief Battery every 6 or 12 months for up to 24 months. PTSD associations with baseline cognition and longitudinal cognitive changes were estimated by covariate-adjusted linear regression and linear mixed-effects models, respectively.

Compared to women with trauma/no PTSD, women with remitted PTSD symptoms had a similar cognitive function at baseline, while women with unresolved PTSD symptoms had worse psychomotor speed/attention and learning/working memory. In women with unresolved PTSD symptoms, past-month PTSD symptom severity was inversely associated with baseline cognition. Over follow-up, both women with remitted and unresolved PTSD symptoms in 2008, especially those with high levels of symptoms, had a faster decline in learning/working memory than women with trauma/no PTSD. In women with remitted PTSD symptoms, higher lifetime PTSD symptom severity was associated with a faster decline in learning/working memory. Results were robust to the adjustment for sociodemographic, biobehavioral, and health factors and were partially attenuated when adjusted for depression.

Unresolved but not remitted PTSD was associated with worse cognitive function assessed six years later. Accelerated cognitive decline was observed among women with either unresolved or remitted PTSD symptoms.

To estimate the impact of opting into the community eligibility provision (CEP) on school meal participation among students in Texas.

A quasi-experimental design using a two-way fixed effects panel difference-in-difference model and the variation in adoption timing to estimate the impact of opting into CEP on student breakfast and lunch participation in eligible, ever-adopting schools.

All public and charter K-12 schools in Texas participating in national school meals (breakfast and/or lunch) from 2013 to 2019 who are eligible for the CEP program in at least 1 year and choose to opt into the program in at least 1 year (n 2797 unique schools and 16 103 school-years).

School-level administrative data from the Texas Department of Agriculture on meal counts, enrollment and summary characteristics of students merged with district-level educational and socio-demographic data from the Texas Education Authority.

We find opting into CEP increased school breakfast participation by 4·59 percentage points (P < 0·001) and lunch participation by 4·32 percentage points (P < 0·001), on average. The effect is slightly larger (4·64 and 4·61, respectively) and still statistically significant when excluding summer months.

Our findings suggest that opting into CEP modestly increases school meal participation in Texas, with a similar impact on breakfast and lunch.

Interdisciplinary academic teams perform better when competent in teamwork; however, there is a lack of best practices of how to introduce and facilitate the development of effective learning and functioning within these teams in academic environments.

To close this gap, we tailored, implemented, and evaluated team science training in the year-long Engineering Innovation in Health (EIH) program at the University of Washington (UW), a project-based course in which engineering students across several disciplines partner with health professionals to develop technical solutions to clinical and translational health challenges. EIH faculty from the UW College of Engineering and the Institute of Translational Health Sciences’ (ITHS) Team Science Core codeveloped and delivered team science training sessions and evaluated their impact with biannual surveys. A student cohort was surveyed prior to the implementation of the team science trainings, which served as a baseline.

Survey responses were compared within and between both cohorts (approximately 55 students each Fall Quarter and 30 students each Spring Quarter). Statistically significant improvements in measures of self-efficacy and interpersonal team climate (i.e., psychological safety) were observed within and between teams.

Tailored team science training provided to student-professional teams resulted in measurable improvements in self-efficacy and interpersonal climate both of which are crucial for teamwork and intellectual risk taking. Future research is needed to determine long-term impacts of course participation on individual and team outcomes (e.g., patents, start-ups). Additionally, adaptability of this model to clinical and translational research teams in alternate formats and settings should be tested.

Late-life depression has substantial impacts on individuals, families and society. Knowledge gaps remain in estimating the economic impacts associated with late-life depression by symptom severity, which has implications for resource prioritisation and research design (such as in modelling). This study examined the incremental health and social care expenditure of depressive symptoms by severity.

We analysed data collected from 2707 older adults aged 60 years and over in Hong Kong. The Patient Health Questionnaire-9 (PHQ-9) and the Client Service Receipt Inventory were used, respectively, to measure depressive symptoms and service utilisation as a basis for calculating care expenditure. Two-part models were used to estimate the incremental expenditure associated with symptom severity over 1 year.

The average PHQ-9 score was 6.3 (standard deviation, s.d. = 4.0). The percentages of respondents with mild, moderate and moderately severe symptoms and non-depressed were 51.8%, 13.5%, 3.7% and 31.0%, respectively. Overall, the moderately severe group generated the largest average incremental expenditure (US$5886; 95% CI 1126–10 647 or a 272% increase), followed by the mild group (US$3849; 95% CI 2520–5177 or a 176% increase) and the moderate group (US$1843; 95% CI 854–2831, or 85% increase). Non-psychiatric healthcare was the main cost component in a mild symptom group, after controlling for other chronic conditions and covariates. The average incremental association between PHQ-9 score and overall care expenditure peaked at PHQ-9 score of 4 (US$691; 95% CI 444–939), then gradually fell to negative between scores of 12 (US$ - 35; 95% CI - 530 to 460) and 19 (US$ -171; 95% CI - 417 to 76) and soared to positive and rebounded at the score of 23 (US$601; 95% CI -1652 to 2854).

The association between depressive symptoms and care expenditure is stronger among older adults with mild and moderately severe symptoms. Older adults with the same symptom severity have different care utilisation and expenditure patterns. Non-psychiatric healthcare is the major cost element. These findings inform ways to optimise policy efforts to improve the financial sustainability of health and long-term care systems, including the involvement of primary care physicians and other geriatric healthcare providers in preventing and treating depression among older adults and related budgeting and accounting issues across services.

Disabilities in physical activity and functional independence affect the early rehabilitation of stroke survivors. Moreover, a good instrument for assessing activity disability allows accurate assessment of physical disability and assists in prognosis determination.

To compare three assessment tools for physical activity in acute-phase stroke survivors.

We conducted this prospective observational study at an affiliated hospital of a Medical University in Shanghai, China, from June 2018 to November 2019. We administered three instruments to all patients during post-stroke days 5–7, including the Modified Barthel Index (MBI), Instrumental Activities of Daily Living (IADL), and modified Rankin scale (mRs). We analyzed correlations among the aforementioned scales and the National Institutes of Health Stroke Scale (NIHSS) using Spearman’s rank-order correlations test. Univariate analyses were performed using the Mann–Whitney U test. We used a binary logistic regression model to assess the association between the NIHSS (30 days) and patient-related variables. Finally, we used receiver operating characteristic (ROC) curves to assess the predictive value of the multivariate regression models.

There was a high correlation among the three instruments; furthermore, the MBI had a higher correlation with the NIHSS (days 5–7). The NIHSS (day 30) was correlated with thrombolysis. ROC analysis revealed that the mRs-measured disability level had the highest predictive value of short-term stroke severity (30 days).

The MBI was the best scale for measuring disability in physical activity, whereas the mRs showed better accuracy in short-term prediction of stroke severity.

Over the past several years there has been considerable interest in the relation between emotion dysregulation and non-suicidal self-injury (NSSI), particularly given that rates of NSSI have been increasing and NSSI is a critical risk factor for suicidal behavior. To date, however, no synthesis of empirical findings exists.

The present study presents a comprehensive meta-analytic review of the literature on the association between NSSI and emotion dysregulation. A total of 48 publications, including 49 independent samples, were included in this analysis.

Overall, a significant association was found between emotion dysregulation and NSSI (pooled OR = 3.03 [95% CI = 2.56–3.59]). This association was reduced but remained significant (OR = 2.40 [95% CI = 2.01–2.86]) after adjustment for publication bias. Emotion dysregulation subscales most strongly associated with NSSI included limited access to regulation strategies, non-acceptance of emotional responses, impulse control difficulties, and difficulties engaging goal-directed behavior. Lack of emotional awareness/clarity and cognitive aspects of dysregulation yielded weaker, yet significant, positive associations with NSSI.

Findings support the notion that greater emotion dysregulation is associated with higher risk for NSSI among individuals across settings, regardless of age or sex. Furthermore, findings reveal facets of dysregulation that may have unique implications for NSSI. This meta-analysis highlights the importance of better understanding emotion dysregulation as a treatment target for preventing NSSI.