Research Appraisals
Evidence-based critical appraisals of the latest medical research, systematically evaluated using Oxford CEBM methodology.
Showing 4 appraisals
Journal of medical Internet research
Using Ultra-Abridged Individual Difference Scales for Personalization in Digital Mental Health to Improve Uptake, Engagement, and Experiences: Three-Tiered Decision Framework for Scale Shortening
Given the diversity of human characteristics and experiences, personalization in nudges, messages, choice presentations, interventions, and overall product design has been increasingly adopted in digital health to promote engagement. Past studies on moderators and personalization in digital health and mental health services generally focused on demographic and symptom variables, with generally inconsistent findings or null findings. Cognitive, motivational, and decisional psychological attributes are largely overlooked. Psychology often uses long self-report scales to measure various psychological attributes. Although they are useful in tapping into individuals' psychological profiles, when applied in real-life, everyday settings to assess individual differences, people are most likely unwilling to complete them. With the pressing need to personalize digital health platforms to enhance uptake, retention, and engagement, ultrashort versions of these psychological scales may be considered to allow assessment of multiple attributes at the same time. Scale shortening can be achieved through regression analyses of each item, factor analyses, item response theory, ant colony optimization, and machine learning methods, with each method having advantages, disadvantages, and conditions required to make it suitable. To illustrate, we provided examples of regression analyses of each item and factor analyses, with potential implications for personalizing narrative versus research-based messages in digital mental health contexts. We present a 3-tiered decision framework for scale shortening method selection depending on goals and possible constraints, with guidelines on validation methods for ultrashort scales. Moving forward, more validation studies and field studies in digital health platforms are needed to evaluate the ecological validity, reliability, and generalizability of these methods, bearing in mind the limitations and conditions where such shortening methods may not work well. Researchers may compare the effectiveness and limitations of personalization using ultrashort scales with other commonly adopted personalization methods (eg, based on longer scales, behavioral data, and large language models). Ethical concerns need to be considered and mitigated carefully, respecting diverse preferences, informed choices, and the privacy of service users. Our viewpoint piece is primarily intended for digital mental health researchers and practitioners, but may also be informative for the fields of digital health and medicine as well as personalization (eg, personalized health care, personalized nudging, and message matching) more broadly, given the common goal of boosting uptake and engagement as well as improving service users' experiences.
10 June 2026
Read appraisal →JMIR mental health
Adoption of Digital Mental Health Interventions in National Health Service England, Scotland, and Wales: Freedom of Information Questionnaire Study
BACKGROUND: Digital mental health interventions (DMHIs) have been widely promoted to improve access to mental health care within the UK National Health Service (NHS), particularly following the COVID-19 pandemic. In 2015, a total of 48 technologies were reportedly used in NHS services in England, but over the past decade, substantial changes to regulatory requirements, evidence standards, and procurement processes have reshaped the digital mental health landscape. There is limited clarity regarding which DMHIs are currently being formally procured and funded by NHS mental health services across the United Kingdom. OBJECTIVE: This study aimed to identify and describe the DMHIs currently procured, contracted, or paid for by NHS mental health service providers in England, Scotland, and Wales for adult common mental health problems and to compare current procurement practices with findings reported in 2015. METHODS: Freedom of Information requests were submitted to all NHS mental health trusts in England and all health boards in Scotland and Wales. Responses were collated and screened to provide an updated and extended record of which technologies are reportedly procured or paid for by services. RESULTS: In total, 19 different DMHIs were identified as being procured across mental health service providers for adult common mental health problems at the time of data collection. This demonstrates a substantial reduction in the number of technologies being adopted into practice compared to the 48 reported in England in 2015. The findings reveal several key insights, including that only 2 technologies have remained in use for a decade, and they shed light on the types of technologies being selected and the variations in procurement practices among the 3 national health services. CONCLUSIONS: Despite the expansion of the digital mental health marketplace, the number of DMHIs formally procured by NHS mental health services has markedly decreased over the past decade. This consolidation may reflect increased selectivity and the adoption of higher-quality products, driven by strengthened regulatory oversight, evidence standards, and national guidance. Although these developments may enhance safety and quality assurance, they also raise important questions about innovation, market sustainability, and equitable access to digital mental health care. Ongoing monitoring of procurement practices is needed to inform policy, service design, and the future development of DMHIs.
16 May 2026
Read appraisal →The British journal of psychiatry : the journal of mental science
Characterisation of serious mental illness trajectories through transdiagnostic clinical features
BACKGROUND: Electronic health records (EHRs), increasingly available in low- and middle-income countries (LMICs), provide an opportunity to study transdiagnostic features of serious mental illness (SMI) and its trajectories. AIMS: Characterise transdiagnostic features and diagnostic trajectories of SMI using an EHR database in an LMIC institution. METHOD: We conducted a retrospective cohort study using EHRs from 2005-2022 at Clínica San Juan de Dios Manizales, a specialised mental health facility in Colombia, including 22 447 patients with schizophrenia (SCZ), bipolar disorder (BPD) or severe/recurrent major depressive disorder (MDD). Using diagnostic codes and clinical notes, we analysed the frequency of suicidality and psychosis across diagnoses, patterns of diagnostic switching and the accumulation of comorbidities. Mixed-effect logistic regression was used to identify factors influencing diagnostic stability. RESULTS: High frequencies of suicidality and psychosis were observed across diagnoses of SCZ, BPD and MDD. Most patients (64%) received multiple diagnoses over time, including switches between primary SMI diagnoses (19%), diagnostic comorbidities (30%) or both (15%). Predictors of diagnostic switching included mentions of delusions (odds ratio = 1.47, 95% CI 1.34-1.61), prior diagnostic switching (odds ratio = 4.01, 95% CI 3.7-4.34) and time in treatment, independent of age (log of visit number; odds ratio = 0.57, 95% CI 0.54-0.61). Over 80% of patients reached diagnostic stability within 6 years of their first record. CONCLUSIONS: Integrating structured and unstructured EHR data reveals transdiagnostic patterns in SMI and predictors of disease trajectories, highlighting the potential of EHR-based tools for research and precision psychiatry in LMICs.
9 May 2026
Read appraisal →Social science & medicine (1982)
Imaginaries of digital health: Unpacking the platformization of mental health through users' practices
The platformization of healthcare is reshaping the organization of mental health services, redefining access, relationships, and meanings of care. This paper examines how users experience and negotiate the platformization of mental health through the case of Unobravo, an Italian digital platform offering online psychotherapy. Drawing on Science and Technology Studies and digital health literature, the study explores how platform imaginaries of efficiency, accessibility, and personalization are enacted and contested in everyday practices. Adopting a mixed-methods design, the research combines qualitative interviews (N = 12) with a quantitative survey (N = 3870) to analyse users' narratives and patterns of engagement. Findings reveal a persistent tension between the promise of algorithmic efficiency and the realities of situated practice. While users value the flexibility and accessibility provided by digital infrastructures, they also encounter infrastructural misalignments, such as unstable connections and opaque algorithmic matching processes. These challenges are addressed through practices of domestication that reconfigure the therapeutic setting, integrating care into mobile and domestic environments. By analysing user practices, the paper investigates how mental health is domesticated through digital platforms and shaped by platform imaginaries, reconfiguring the therapeutic setting as a datafied and everyday space.
4 May 2026
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