It remains unclear which individuals with subthreshold depression benefit most from psychological intervention, and what long-term effects this has on symptom deterioration, response and remission.

To synthesise psychological intervention benefits in adults with subthreshold depression up to 2 years, and explore participant-level effect-modifiers.

Randomised trials comparing psychological intervention with inactive control were identified via systematic search. Authors were contacted to obtain individual participant data (IPD), analysed using Bayesian one-stage meta-analysis. Treatment–covariate interactions were added to examine moderators. Hierarchical-additive models were used to explore treatment benefits conditional on baseline Patient Health Questionnaire 9 (PHQ-9) values.

IPD of 10 671 individuals (50 studies) could be included. We found significant effects on depressive symptom severity up to 12 months (standardised mean-difference [s.m.d.] = −0.48 to −0.27). Effects could not be ascertained up to 24 months (s.m.d. = −0.18). Similar findings emerged for 50% symptom reduction (relative risk = 1.27–2.79), reliable improvement (relative risk = 1.38–3.17), deterioration (relative risk = 0.67–0.54) and close-to-symptom-free status (relative risk = 1.41–2.80). Among participant-level moderators, only initial depression and anxiety severity were highly credible (P > 0.99). Predicted treatment benefits decreased with lower symptom severity but remained minimally important even for very mild symptoms (s.m.d. = −0.33 for PHQ-9 = 5).

Psychological intervention reduces the symptom burden in individuals with subthreshold depression up to 1 year, and protects against symptom deterioration. Benefits up to 2 years are less certain. We find strong support for intervention in subthreshold depression, particularly with PHQ-9 scores ≥ 10. For very mild symptoms, scalable treatments could be an attractive option.

Negative symptoms are a key feature of several psychiatric disorders. Difficulty identifying common neurobiological mechanisms that cut across diagnostic boundaries might result from equifinality (i.e., multiple mechanistic pathways to the same clinical profile), both within and across disorders. This study used a data-driven approach to identify unique subgroups of participants with distinct reward processing profiles to determine which profiles predicted negative symptoms.

Participants were a transdiagnostic sample of youth from a multisite study of psychosis risk, including 110 individuals at clinical high-risk for psychosis (CHR; meeting psychosis-risk syndrome criteria), 88 help-seeking participants who failed to meet CHR criteria and/or who presented with other psychiatric diagnoses, and a reference group of 66 healthy controls. Participants completed clinical interviews and behavioral tasks assessing four reward processing constructs indexed by the RDoC Positive Valence Systems: hedonic reactivity, reinforcement learning, value representation, and effort–cost computation.

k-means cluster analysis of clinical participants identified three subgroups with distinct reward processing profiles, primarily characterized by: a value representation deficit (54%), a generalized reward processing deficit (17%), and a hedonic reactivity deficit (29%). Clusters did not differ in rates of clinical group membership or psychiatric diagnoses. Elevated negative symptoms were only present in the generalized deficit cluster, which also displayed greater functional impairment and higher psychosis conversion probability scores.

Contrary to the equifinality hypothesis, results suggested one global reward processing deficit pathway to negative symptoms independent of diagnostic classification. Assessment of reward processing profiles may have utility for individualized clinical prediction and treatment.

The ability to remotely monitor cognitive skills is increasing with the ubiquity of smartphones. The Mobile Toolbox (MTB) is a new measurement system that includes measures assessing Executive Functioning (EF) and Processing Speed (PS): Arrow Matching, Shape-Color Sorting, and Number-Symbol Match. The purpose of this study was to assess their psychometric properties.

MTB measures were developed for smartphone administration based on constructs measured in the NIH Toolbox® (NIHTB). Psychometric properties of the resulting measures were evaluated in three studies with participants ages 18 to 90. In Study 1 (N = 92), participants completed MTB measures in the lab and were administered both equivalent NIH TB measures and other external measures of similar cognitive constructs. In Study 2 (N = 1,021), participants completed the equivalent NIHTB measures in the lab and then took the MTB measures on their own, remotely. In Study 3 (N = 168), participants completed MTB measures twice remotely, two weeks apart.

All three measures exhibited very high internal consistency and strong test-retest reliability, as well as moderately high correlations with comparable NIHTB tests and moderate correlations with external measures of similar constructs. Phone operating system (iOS vs. Android) had a significant impact on performance for Arrow Matching and Shape-Color Sorting, but no impact on either validity or reliability.

Results support the reliability and convergent validity of MTB EF and PS measures for use across the adult lifespan in remote, self-administered designs.

Pediatric medical devices lag behind adult devices due to economic barriers, smaller patient populations, changing anatomy and physiology of patients, regulatory hurdles, and especially difficulties in executing clinical trials. We investigated the requirements, challenges, associated timeline, and costs of conducting a multi-site pivotal clinical trial for a Class II pediatric physiologic monitoring device.

This case study focused on the negotiation of clinical trial agreements (CTAs), budgets, and Institutional Review Board (IRB) processing times for a pediatric device trial. We identified key factors contributing to delays in clinical trial execution and potential best practices to expedite the process while maintaining safety, ethics, and efficacy.

The total time from site contact to first patient enrollment averaged 14 months. CTA and budget negotiations were the most time-consuming processes, averaging nearly 10 and 9 months, respectively. Reliance and local IRB processing also contributed significantly to the timeline, overall adding an average of 6.5 months across institutions. Nearly half of all costs were devoted to regulatory oversight. The COVID-19 pandemic caused significant slowdowns and delays at multiple institutions during study enrollment. Despite these pandemic-induced delays, it is important to note that the issues and themes highlighted remain relevant and have post-pandemic applicability.

Our case study results underscore the importance of establishing efficient and standardized processing of CTAs, budget negotiations, and use of reliance IRBs to expedite clinical trial execution for pediatric devices. The findings also highlight the need for a national clinical trials network to streamline the clinical trial process.

A critical need in the neuropsychology field is development and validation of efficient, scalable assessments of cognition. The Mobile Toolbox (MTB), a novel suite of mobile device-compatible, app-based cognitive assessments, was developed to address this need. The goals of this study were (1) To collect longitudinal normative data for the MTB assessments in a large, ethnoculturally and educationally diverse cohort; (2) To assess the feasibility and usability of remote assessment using MTB.

Participants were recruited from the UCSF Brain Health Registry (BHR), an online cohort (N>100,000) that collects longitudinal cognitive, functional, behavioral, and health data using online neuropsychological tests and self- and study-partner report surveys. BHR participants who opted to learning about additional research opportunities were sent automated email invitations to enroll in the MTB study. Those who indicated study interest were provided instructions within the BHR online portal for downloading the MTB app. All participants had the opportunity to complete a single baseline administration of MTB (Word Meaning, Sequences, Spelling, Arranging Pictures, Arrow Matching, Faces and Names, Shape-Color Sorting, Number Match). Those who completed the baseline assessment within three days were invited to continue into the longitudinal study, where they complete MTB assessments at a single, short-term timepoint (day 7, 14, or 21; study arms sequentially assigned), and then at 6-month intervals. Enrollment across demographic groups was monitored, and study invitations were sent to specific demographic groups, with the goal of enrolling a sample of 800 participants in the longitudinal study: equal distribution across eight, 10-year age bands (ages 18-80+); 60% with <16 years of education; 10% non-Latinx Black, 15% Latinx, and 5% non-White other ethnocultural identity.

Between January-June 2022, 48,110 BHR participants were invited to the MTB study. Of those, 8294 (17%) expressed interest, 3401 (7%) completed the baseline assessment, 850 (1.8%) were assigned to the longitudinal study, and 782 (1.6%) completed a short-term longitudinal assessment. Study staff received 797 help tickets submitted by participants asking for email support to complete MTB. The baseline cohort had and average age of 64 years and an average of 16.6 years of education, 76.2% female, 2.1% non-Latinx Black, 7.1% Latinx, 86.8% non-Latinx White, and 4% from other ethnocultural groups. The longitudinal cohort had an average age of 62.3 years and an average of 16.1 years of education, 80% female, 2.8% non-Latinx Black, 8.5% Latinx, 83.5% non-Latinx White; and 5% other ethnocultural group. Compared to those invited to the study, those who enrolled in the longitudinal study were older, had higher educational attainment, and were more likely to be female and self-identify as non-Latinx White (p<0.05 for all).

Efficient enrollment and task completion of a large cohort in a novel, app-based mobile cognitive assessment is feasible in a completely remote setting. Most participants were able to complete MTB without individual support, indicating good usability. This approach can be scaled up to efficiently assess cognition in many research and healthcare settings. A remaining challenge is achieving robust ethnocultural and educational diversity.

Insufficient recruitment of groups underrepresented in medical research threatens the generalizability of research findings and compounds inequity in research and medicine. In the present study, we examined barriers and facilitators to recruitment of underrepresented research participants from the perspective of clinical research coordinators (CRCs).

CRCs from one adult and one pediatric academic medical centers completed an online survey in April-May 2022. Survey topics included: participant language and translations, cultural competency training, incentives for research participation, study location, and participant research literacy. CRCs also reported their success in recruiting individuals from various backgrounds and completed an implicit bias measure.

Surveys were completed by 220 CRCs. CRCs indicated that recruitment is improved by having translated study materials, providing incentives to compensate participants, and reducing the number of in-person study visits. Most CRCs had completed some form of cultural competency training, but most also felt that the training either had no effect or made them feel less confident in approaching prospective participants from backgrounds different than their own. In general, CRCs reported having greater success in recruiting prospective participants from groups that are not underrepresented in research. Results of the implicit bias measure did not indicate that bias was associated with intentions to approach a prospective participant.

CRCs identified several strategies to improve recruitment of underrepresented research participants, and CRC insights aligned with insights from research participants in previous work. Further research is needed to understand the impact of cultural competency training on recruitment of underrepresented research participants.

Current psychiatric diagnoses, although heritable, have not been clearly mapped onto distinct underlying pathogenic processes. The same symptoms often occur in multiple disorders, and a substantial proportion of both genetic and environmental risk factors are shared across disorders. However, the relationship between shared symptoms and shared genetic liability is still poorly understood.

Well-characterised, cross-disorder samples are needed to investigate this matter, but few currently exist. Our aim is to develop procedures to purposely curate and aggregate genotypic and phenotypic data in psychiatric research.

As part of the Cardiff MRC Mental Health Data Pathfinder initiative, we have curated and harmonised phenotypic and genetic information from 15 studies to create a new data repository, DRAGON-Data. To date, DRAGON-Data includes over 45 000 individuals: adults and children with neurodevelopmental or psychiatric diagnoses, affected probands within collected families and individuals who carry a known neurodevelopmental risk copy number variant.

We have processed the available phenotype information to derive core variables that can be reliably analysed across groups. In addition, all data-sets with genotype information have undergone rigorous quality control, imputation, copy number variant calling and polygenic score generation.

DRAGON-Data combines genetic and non-genetic information, and is available as a resource for research across traditional psychiatric diagnostic categories. Algorithms and pipelines used for data harmonisation are currently publicly available for the scientific community, and an appropriate data-sharing protocol will be developed as part of ongoing projects (DATAMIND) in partnership with Health Data Research UK.

Depressive symptoms, such as depressed mood, are common in older adults and associated with an increased risk for morbidity and mortality. Given the evidence that sleep disturbance and alterations in interferon (IFN)-γ biology are associated with depression risk, this study examines the separate and joint contributions of poor sleep maintenance and IFN-γ to depressed mood in older adults.

Community-dwelling, non-depressed older adults (n = 36, 72.1 ± 6.8 years) underwent a night of polysomnography to assess sleep maintenance [i.e. wake time after sleep onset (WASO)]. The morning after polysomnography, plasma levels of IFN-γ were evaluated along with self-reported depressed mood throughout the day. Multivariate linear regression tested associations of WASO and IFN-γ with the severity of depressed mood. In addition, moderation and mediation models examined the role of IFN-γ for the relationship between WASO and depressed mood.

A greater amount of WASO (p < 0.05) and higher levels of IFN-γ (p < 0.01) were both associated with the severity of depressed mood. Moreover, IFN-γ moderated the relationship between WASO and depressed mood (p < 0.01), such that WASO was more strongly related to the depressed mood among those with higher IFN-γ, than among those with lower IFN-γ. However, IFN-γ did not mediate the relationship between WASO and depressed mood.

In this study of older adults, poor sleep maintenance and higher levels of IFN-γ were both related to depressed mood. Moreover, IFN-γ moderated the relationship between poor sleep maintenance and depressed mood. Together, these findings suggest that older adults with higher IFN-γ are at heightened risk for depressive symptoms following sleep disturbance.