While cognitive impairment is a core feature of psychosis, significant heterogeneity in cognitive and clinical outcomes is observed.

The aim of this study was to identify cognitive and clinical subgroups in first-episode psychosis (FEP) and determine if these profiles were linked to functional outcomes over time.

A total of 323 individuals with FEP were included. Two-step hierarchical and k-means cluster analyses were performed using baseline cognitive and clinical variables. General linear mixed models were used to investigate whether baseline cognitive and clinical clusters were associated with functioning at follow-up time points (6–9, 12 and 15 months).

Three distinct cognitive clusters were identified: a cognitively intact group (N = 59), a moderately impaired group (N= 77) and a more severely impaired group (N= 122). Three distinct clinical clusters were identified: a subgroup characterised by predominant mood symptoms (N = 76), a subgroup characterised by predominant negative symptoms (N= 19) and a subgroup characterised by overall mild symptom severity (N = 94). The subgroup with more severely impaired cognition also had more severe negative symptoms at baseline. Cognitive clusters were significantly associated with later social and occupational function, and associated with changes over time. Clinical clusters were associated with later social functioning but not occupational functioning, and were not associated with changes over time.

Baseline cognitive impairments are predictive of both later social and occupational function and change over time. This suggests that cognitive profiles offer valuable information in terms of prognosis and treatment needs.

Research faculty often experience poor mentoring, low vitality, and burnout. We report on our logic model inputs, activities, measurable outcomes, and impact of a novel mentoring intervention for biomedical research faculty: the C-Change Mentoring & Leadership Institute. We present a) a detailed description of the curriculum and process, b) evaluation of the program’s mentoring effectiveness from the perspective of participants, and c) documentation of mentoring correlated with key positive outcomes.

A yearlong facilitated group peer mentoring program that convened quarterly in person was conducted twice (2020–2022) as part of an NIH-funded randomized controlled study. The culture change intervention aimed to increase faculty vitality, career advancement, and cross-cultural competence through structured career planning and learning of skills essential for advancement and leadership in academic medicine. Participants were 40 midcareer MD and PhD research faculty, half women, and half underrepresented by race or ethnicity from 27 US medical schools.

Participants highly rated their mentoring received at the Institute. Extent of effective mentoring experienced correlated strongly with the measurable outcomes of enhanced vitality, self-efficacy in career advancement, research and work-life integration, feelings of inclusion in the program, valuing diversity, and skills for addressing inequity.

The mentoring model fully included men and women and historically underrepresented persons in medicine and minimized problems of power, gender, race, and ethnicity discordance. The intervention successfully addressed the urgencies of sustaining faculty vitality, developing faculty careers, facilitating cross-cultural engagement and inclusion, and contributing to cultivating cultures of inclusive excellence in academic medicine.

Developing integrated mental health services focused on the needs of children and young people is a key policy goal in England. The THRIVE Framework and its implementation programme, i-THRIVE, are widely used in England. This study examines experiences of staff using i-THRIVE, estimates its effectiveness, and assesses how local system working relationships influence programme success.

This evaluation uses a quasi-experimental design (10 implementation and 10 comparison sites.) Measurements included staff surveys and assessment of ‘THRIVE-like’ features of each site. Additional site-level characteristics were collected from health system reports. The effect of i-THRIVE was evaluated using a four-group propensity-score-weighted difference-in-differences model; the moderating effect of system working relationships was evaluated with a difference-in-difference-in-differences model.

Implementation site staff were more likely to report using THRIVE and more knowledgeable of THRIVE principles than comparison site staff. The mean improvement of fidelity scores among i-THRIVE sites was 16.7, and 8.8 among comparison sites; the weighted model did not find a statistically significant difference. However, results show that strong working relationships in the local system significantly enhance the effectiveness of i-THRIVE. Sites with highly effective working relationships showed a notable improvement in ‘THRIVE-like’ features, with an average increase of 16.41 points (95% confidence interval: 1.69–31.13, P-value: 0.031) over comparison sites. Sites with ineffective working relationships did not benefit from i-THRIVE (−2.76, 95% confidence interval: − 18.25–12.73, P-value: 0.708).

The findings underscore the importance of working relationship effectiveness in the successful adoption and implementation of multi-agency health policies like i-THRIVE.

The primary purpose of this study was to assess perceived burdens and benefits of participating in implementation research among staff employed in resource-constrained healthcare settings. Another objective was to use findings to generate considerations for engaging staff in research across different phases of implementation research.

This qualitative focus group and consensus building study involved researchers affiliated with the National Cancer Institute Implementation Science Centers in Cancer Control program and nine Community Health Centers (CHCs) in Massachusetts. Six focus groups (n = 3 with CHC staff; n = 3 with researchers) assessed barriers and facilitators to staff participation in implementation research. During consensus discussions, we used findings to develop considerations for engaging staff as participants and partners throughout phases of implementation research.

Sixteen researchers and 14 staff participated in separate focus groups; nine researchers and seven staff participated in separate consensus discussions. Themes emerged across participant groups in three domains: (1) influences on research participation; (2) research burdens and benefits; and (3) ways to facilitate staff participation in research. Practical considerations included: (a) aligning research with organizational and staff values and priorities; (b) applying user-centered design to research methods; (c) building organizational and individual research capacity; and (d) offering equitable incentives for staff participation.

Engaging staff as participants and partners across different phases of implementation research requires knowledge about what contributes to research burden and benefits and addressing context-specific burdens and benefits.

Medicare claims are frequently used to study Clostridioides difficile infection (CDI) epidemiology. However, they lack specimen collection and diagnosis dates to assign location of onset. Algorithms to classify CDI onset location using claims data have been published, but the degree of misclassification is unknown.

We linked patients with laboratory-confirmed CDI reported to four Emerging Infections Program (EIP) sites from 2016–2021 to Medicare beneficiaries with fee-for-service Part A/B coverage. We calculated sensitivity of ICD-10-CM codes in claims within ±28 days of EIP specimen collection. CDI was categorized as hospital, long-term care facility, or community-onset using three different Medicare claims-based algorithms based on claim type, ICD-10-CM code position, duration of hospitalization, and ICD-10-CM diagnosis code presence-on-admission indicators. We assessed concordance of EIP case classifications, based on chart review and specimen collection date, with claims case classifications using Cohen’s kappa statistic.

Of 12,671 CDI cases eligible for linkage, 9,032 (71%) were linked to a single, unique Medicare beneficiary. Compared to EIP, sensitivity of CDI ICD-10-CM codes was 81%; codes were more likely to be present for hospitalized patients (93.0%) than those who were not (56.2%). Concordance between EIP and Medicare claims algorithms ranged from 68% to 75%, depending on the algorithm used (κ = 0.56–0.66).

ICD-10-CM codes in Medicare claims data had high sensitivity compared to laboratory-confirmed CDI reported to EIP. Claims-based epidemiologic classification algorithms had moderate concordance with EIP classification of onset location. Misclassification of CDI onset location using Medicare algorithms may bias findings of claims-based CDI studies.

Cost-effectiveness models fully informed by real-world epidemiological parameters yield the best results, but they are costly to obtain. Model calibration using real-world data/evidence (RWD/E) on routine health indicators can provide an alternative to improve the validity and acceptability of the results. We calibrated the transition probabilities of the reference chemotherapy treatment using RWE on patient overall survival (OS) to model the survival benefit of adjuvant trastuzumab in Indonesia.

A Markov model comprising four health states was initially parameterized using the reference-treatment transition probabilities, obtained from published international evidence. We then calibrated these probabilities, targeting a 2-year OS of 86.11 percent from the RWE sourced from hospital registries. We compared projected OS duration and life-years gained (LYG) before and after calibration for the Nelder–Mead, Bound Optimization BY Quadratic Approximation, and generalized reduced gradient (GRG) nonlinear optimization methods.

The pre-calibrated transition probabilities overestimated the 2-year OS (92.25 percent). GRG nonlinear performed best and had the smallest difference with the RWD/E OS. After calibration, the projected OS duration was significantly lower than their pre-calibrated estimates across all optimization methods for both standard chemotherapy (~7.50 vs. 11.00 years) and adjuvant trastuzumab (~9.50 vs. 12.94 years). LYG measures were, however, similar (~2 years) for the pre-calibrated and calibrated models.

RWD/E calibration resulted in realistically lower survival estimates. Despite the little difference in LYG, calibration is useful to adapt external evidence commonly used to derive transition probabilities to the policy context, thereby enhancing the validity and acceptability of the modeling results.

Limited studies have examined the association between the whole range of parental psychopathology and offspring major depression (MD). No previous study has examined this association by age of onset of offspring MD, or restricting to parental psychiatric diagnoses before offspring birth.

This nested case–control study included 37,677 cases of MD and 145,068 controls, identified from Finnish national registers. Conditional logistic regression models examined the association between parental psychopathology and MD, adjusting for potential confounders.

Increased risk of MD, expressed as adjusted odds ratio and 95% confidence interval (aOR [95% CI]) were most strongly observed for maternal diagnoses of schizophrenia and schizoaffective disorders (2.51 [2.24–2.82]) and depression (2.19 [2.11–2.28]), and paternal diagnoses of schizophrenia and schizoaffective disorders (2.0 [1.75–2.29]) and conduct disorders (1.90 [1.40–2.59]). The aORs for any psychiatric diagnosis were (2.66 [2.54–2.78]) for mothers, (1.95 [1.86–2.04]) for fathers, and (4.50 [4.24–4.79]) for both parents. When both parents had any psychiatric diagnosis, the highest risk was for MD diagnosed at the age of 5–12 years (7.66 [6.60–8.89]); versus at 13–18 years (4.13 [3.85–4.44]) or 19–25 years (3.37 [2.78–4.07]). A stronger association with parental psychopathology and offspring MD was seen among boys than girls, especially among 13–19 years and 19–25 years.

Parental psychiatric disorders, including those diagnosed before offspring birth, were associated with offspring MD, indicating potential genetic and environmental factors in the development of the disorder.

Mental health problems in adolescence are increasingly prevalent and have tremendous impacts on life-long health and mortality. Although household poverty is a known risk factor for adolescent mental health, evidence of the timing hypothesis is scarce. We aimed to examine the longitudinal associations of poverty across childhood with mental health in adolescence, focusing on the timing of exposure.

We used the data of 5,671 children from a Japanese population-based longitudinal cohort, which recruited the first graders (aged 6–7 years) and followed biannually until eighth grade (aged 13–14 years) in Adachi, Tokyo. Household poverty was defined as households having any of the following experiences: annual income less than Japanese yen 3 million, payment difficulties and material deprivations, measured in first, second, fourth, sixth and eighth grades. Adolescent mental health included parent-report internalizing and externalizing problems (the Strengths and Difficulties Questionnaire), self-report depression (the Patient Health Questionnaire-9) and self-esteem (the Japanese version Children’s Perceived Competence Scale) in eighth grade. We applied g-estimation of structural nested mean modelling to account for time-varying confounders.

If adolescents were exposed to household poverty at any grade across childhood, on average, they would report more severe depressive symptoms (ψ = 0.32 [95% CI 0.13; 0.51]) and lower self-esteem (ψ = −0.41 [−0.62; −0.21]) in eighth grade. There were also average associations of household poverty at any grade with more internalizing (ψ = 0.19 [0.10; 0.29]) and externalizing problems (ψ = 0.10 [0.002; 0.19]). Although the associations between household poverty and mental health were stronger in younger ages (e.g., poverty in the second grade → depression: ψ = 0.54 [−0.12; 1.19] vs. poverty in the eighth grade → depression: ψ = −0.01 [−0.66; 0.64]), overlapping 95% CIs indicated no statistically significantly different associations by the timing of exposure.

We found the average effect of exposure to household poverty at any grade on mental health outcomes in eighth grade, failing to support the timing hypothesis. The findings indicate that the effects of household poverty accumulate over time in childhood and impact adolescent mental health (cumulative hypothesis) rather than the effects differ by the timing of exposure. While cumulative effects suggest a persistent intervention in poor households across childhood, we highlight intervention at any timing in childhood may be effective in alleviating adolescent mental health problems.