Furthering the reliable and valid measurement of mental health screening, diagnoses, treatment and outcomes through health information technology

A Randomized Evaluation of MoodFX, a Patient-Centred e-Health Tool to Support Outcome Measurement for Depression: Une évaluation randomisée de MoodFX, un outil de santé en ligne centré sur le patient pour soutenir la mesure du résultat dans la dépression

BACKGROUND

e-Health tools using validated questionnaires to assess outcomes may facilitate measurement-based care for psychiatric disorders. MoodFX was created as a free online symptom tracker to support patients for outcome measurement in their depression treatment. We conducted a pilot randomized evaluation to examine its usability, and clinical utility.

METHODS

Patients presenting with a major depressive episode (within a major depressive or bipolar disorder) were randomly assigned to receive either MoodFX or a health information website as the intervention and control condition, respectively, with follow-up assessment surveys conducted online at baseline, 8 weeks and 6 months. The primary usability outcomes included the percentage of patients with self-reported use of MoodFX 3 or more times during follow up (indicating minimally adequate usage) and usability measures based on the System Usability Scale (SUS). Secondary clinical outcomes included the Quick Inventory of Depressive Symptomatology, Self-Rated (QIDS-SR) and Patient Health Questionnaire (PHQ-9).

RESULTS

Forty-nine participants were randomized (24 to MoodFX and 25 to the control condition). Of the 23 participants randomized to MoodFX who completed the user survey, 18 (78%) used MoodFX 3 or more times over the 6 months of the study. The mean SUS score of 72.7 (65th-69th percentile) represents good usability. Compared to the control group, the MoodFX group had significantly better improvement on QIDS-SR and PHQ-9 scores, with large effect sizes and higher response rates at 6 months. There were no differences between conditions on other secondary outcomes such as functioning and quality of life.

CONCLUSION

MoodFX demonstrated good usability and was associated with reduction in depressive symptoms. This pilot study supports the use of digital tools in depression treatment.

Artificial intelligence in perinatal mental health research: A scoping review

The intersection of Artificial Intelligence (AI) and perinatal mental health research presents promising avenues, yet uncovers significant challenges for innovation. This review explicitly focuses on this multidisciplinary field and undertakes a comprehensive exploration of existing research therein. Through a scoping review guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework, we searched relevant literature spanning a decade (2013-2023) and selected fourteen studies for our analysis. We first provide an overview of the main AI techniques and their development, including traditional methods across different categories, as well as recent emerging methods in the field. Then, through our analysis of the literature, we summarize the predominant AI and ML techniques adopted and their applications in perinatal mental health studies, such as identifying risk factors, predicting perinatal mental health disorders, voice assistants, and Q&A chatbots. We also discuss existing limitations and potential challenges that hinder AI technologies from improving perinatal mental health outcomes, and suggest several promising directions for future research to meet real needs in the field and facilitate the translation of research into clinical settings.

Unraveling the interplay of circadian rhythm and sleep deprivation on mood: A Real-World Study on first-year physicians

The interplay between circadian rhythms, time awake, and mood remains poorly understood in the real-world. Individuals in high-stress occupations with irregular schedules or nighttime shifts are particularly vulnerable to depression and other mood disorders. Advances in wearable technology have provided the opportunity to study these interactions outside of a controlled laboratory environment. Here, we examine the effects of circadian rhythms and time awake on mood in first-year physicians using wearables. Continuous heart rate, step count, sleep data, and daily mood scores were collected from 2,602 medical interns across 168,311 days of Fitbit data. Circadian time and time awake were extracted from minute-by-minute wearable heart rate and motion measurements. Linear mixed modeling determined the relationship between mood, circadian rhythm, and time awake. In this cohort, mood was modulated by circadian timekeeping (p<0.001). Furthermore, we show that increasing time awake both deteriorates mood (p<0.001) and amplifies mood's circadian rhythm nonlinearly. These findings demonstrate the contributions of both circadian rhythms and sleep deprivation to underlying mood and show how these factors can be studied in real-world settings using Fitbits. They underscore the promising opportunity to harness wearables in deploying chronotherapies for psychiatric illness.

Replicability and reproducibility of predictive models for diagnosis of depression among young adults using Electronic Health Records

BACKGROUND

Recent advances in machine learning combined with the growing availability of digitized health records offer new opportunities for improving early diagnosis of depression. An emerging body of research shows that Electronic Health Records can be used to accurately predict cases of depression on the basis of individual's primary care records. The successes of these studies are undeniable, but there is a growing concern that their results may not be replicable, which could cast doubt on their clinical usefulness.

METHODS

To address this issue in the present paper, we set out to reproduce and replicate the work by Nichols et al. (2018), who trained predictive models of depression among young adults using Electronic Healthcare Records. Our contribution consists of three parts. First, we attempt to replicate the methodology used by the original authors, acquiring a more up-to-date set of primary health care records to the same specification and reproducing their data processing and analysis. Second, we test models presented in the original paper on our own data, thus providing out-of-sample prediction of the predictive models. Third, we extend past work by considering several novel machine-learning approaches in an attempt to improve the predictive accuracy achieved in the original work.

RESULTS

In summary, our results demonstrate that the work of Nichols et al. is largely reproducible and replicable. This was the case both for the replication of the original model and the out-of-sample replication applying NRCBM coefficients to our new EHRs data. Although alternative predictive models did not improve model performance over standard logistic regression, our results indicate that stepwise variable selection is not stable even in the case of large data sets.

CONCLUSION

We discuss the challenges associated with the research on mental health and Electronic Health Records, including the need to produce interpretable and robust models. We demonstrated some potential issues associated with the reliance on EHRs, including changes in the regulations and guidelines (such as the QOF guidelines in the UK) and reliance on visits to GP as a predictor of specific disorders.

Common mental health problems in medical students and junior doctors - an overview of systematic reviews

BACKGROUND

Common mental health problems (CMHP) are prevalent among junior doctors and medical students, and the COVID-19 pandemic has brought challenging situations with education disruptions, early graduations, and front-line work. CMHPs can have detrimental consequences on clinical safety and healthcare colleagues; thus, it is vital to assess the overall prevalence and available interventions to provide institutional-level support.

AIMS

This overview summarises the prevalence of CMHPs from existing published systematic reviews and informs public health prevention and early intervention practice.

METHODS

Four electronic databases were searched from 2012 to identify systematic reviews on the prevalence of CMHPs and/or interventions to tackle them.

RESULTS

Thirty-six reviews were included: 25 assessing prevalence and 11 assessing interventions. Across systematic reviews, the prevalence of anxiety ranged from 7.04 to 88.30%, burnout from 7.0 to 86.0%, depression from 11.0 to 66.5%, stress from 29.6 to 49.9%, suicidal ideation from 3.0 to 53.9% and one obsessive-compulsive disorder review reported a prevalence of 3.8%. Mindfulness-based interventions were included in all reviews, with mixed findings for each CMHP.

CONCLUSIONS

The prevalence of CMHPs is high among junior doctors and medical students, with anxiety remaining relatively stable and depression slightly increasing during the COVID-19 pandemic. Future research on mindfulness-based interventions is required for a resilient and healthy future workforce.

PRISMA/PROSPERO

the researchers have followed PRISMA guidance. This overview was not registered with PROSPERO as it was conducted as part of an MSc research project.

The relationship between resilience and mental health of undergraduate students: A scoping review

OBJECTIVE

The aim of this scoping review was to examine what is known about the relationship between the resilience and mental health of undergraduate students enrolled in university or college programs, globally.

METHODS

Five electronic databases were searched, yielding a total of 1,498 articles that were screened independently by two researchers. Thirteen articles were eligible for inclusion.

RESULTS

The mental health of undergraduate students in the studies reviewed ranged from low to moderate. Undergraduate students also reported high, moderate, and low levels of resilience. Further, resilience was positively correlated with mental well-being.

CONCLUSION

Findings revealed that the mental health of undergraduate students was poor. Given the established relationship between students' mental health and resilience, evidence-based approaches aimed at strengthening students' resilience, such as providing opportunities for social support, are warranted in order to improve students' mental health. Additional research to rigorously assess this relationship in representative student populations is needed.

Sensitivity and specificity of the Patient Health Questionnaire (PHQ-9, PHQ-8, PHQ-2) and General Anxiety Disorder scale (GAD-7, GAD-2) for depression and anxiety diagnosis: a cross-sectional study in a Peruvian hospital population

OBJECTIVES

The Patient Health Questionnaire (PHQ) and Generalised Anxiety Disorder Scale (GAD) are widely used screening tools, but their sensitivity and specificity in low-income and middle-income countries are lower than in high-income countries. We conducted a study to determine the sensitivity and specificity of different versions of these scales in a Peruvian hospital population.

DESIGN

Our study has a cross-sectional design.

SETTING

Our participants are hospitalised patients in a Peruvian hospital. The gold standard was a clinical psychiatric interview following ICD-10 criteria for depression (F32.0, F32.1, F32.2 and F32.3) and anxiety (F41.0 and F41.1).

PARTICIPANTS

The sample included 1347 participants. A total of 334 participants (24.8%) were diagnosed with depression, and 28 participants (2.1%) were diagnosed with anxiety.

RESULTS

The PHQ-9's≥7 cut-off point showed the highest simultaneous sensitivity and specificity when contrasted against a psychiatric diagnosis of depression. For a similar contrast against the gold standard, the other optimal cut-off points were: ≥7 for the PHQ-8 and ≥2 for the PHQ-2. In particular, the cut-off point ≥8 had good performance for GAD-7 with sensitivity and specificity, and cut-off point ≥10 had lower levels of sensitivity, but higher levels of specificity, compared with the cut-off point of ≥8. Also, we present the sensitivity and specificity values of each cut-off point in PHQ-9, PHQ-8, PHQ-2, GAD-7 and GAD-2. We confirmed the adequacy of a one-dimensional model for the PHQ-9, PHQ-8 and GAD-7, while all PHQ and GAD scales showed good reliability.

CONCLUSIONS

The PHQ and GAD have adequate measurement properties in their different versions. We present specific cut-offs for each version.

Understanding the Healthy Immigrant Effect in the Context of Mental Health Challenges: A Systematic Critical Review

The "Healthy Immigrant Effect" (HIE) suggests that immigrants have a health advantage over the domestic-born which vanishes with increased length of residency. Most HIE research focuses on physical health, with less attention given to mental health (MH). This systematic review of 58 MH studies examines whether there is a MH advantage among immigrants and explores changes in immigrants' MH, besides critically assessing the use of HIE theory. Inconsistent evidence was detected regarding the presence of MH advantage, whereas consistent, convincing evidence was revealed for a decline in immigrants' MH over years. Although the HIE theory can help reveal MH disparities, this theory alone does not explain the reasons for these disparities nor inform about potential avenues to improve immigrants' MH. A paradigm shift is needed to incorporate other potential theoretical concepts/frameworks, including the "Health Inequalities Action" framework, for a broader understanding of MH issues and to inform effective, culturally-sensitive interventions.

Beyond the Therapist's Office: Merging Measurement-Based Care and Digital Medicine in the Real World

This viewpoint focuses on the ways in which digital medicine and measurement-based care can be utilized in tandem to promote better assessment, patient engagement, and an improved quality of psychiatric care. To date, there has been an underutilization of digital measurement in psychiatry, and there is little discussion of the feedback and patient engagement process in digital medicine. Measurement-based care is a recognized evidence-based strategy that engages patients in an understanding of their outcome data. When implemented as designed, providers review the scores and trends in outcome immediately and then provide feedback to their patients. However, the process is typically confined to office visits, which does not provide a complete picture of a patient's progress and functioning. The process is labor intensive, even with digital feedback systems, but the integration of passive metrics obtained through wearables and apps can supplement office-based observations. This enhanced measurement-based care process can provide a picture of real-world patient functioning through passive metrics (activity, sleep, etc.). This can potentially engage patients more in their health data and involve a critically needed therapeutic alliance component in digital medicine.

Challenges, supports, and postpartum mental health symptoms among non-breastfeeding mothers

Women face a high degree of pressure to breastfeed. However, some women are not able to breastfeed, or choose not to. Few studies have examined the experiences of non-breastfeeding mothers, including their challenges, supports, and mental health sequelae. We sought to identify women's experiences with breastfeeding, specifically their reasons for not breastfeeding, challenges faced, and supports received, and the association between breastfeeding and postpartum mental health. Self-identified postpartum women (N = 70) completed a questionnaire investigating perinatal health. Open-ended responses were analyzed using thematic analysis and quantitative measures were analyzed using descriptive statistics and multivariate analysis of variance (MANOVA). Qualitative analysis identified two main themes reflecting reasons for not breastfeeding (maternal factors and infant factors) and three primary challenges associated with not breastfeeding (emotional health, physical health, and perceived lack of support). Authors identified two main themes categorizing non-breastfeeding mothers' experiences with support (sources of support and type of support). A MANOVA revealed significantly greater levels of distress, anxiety, and depression, and lower levels of social support, among non-breastfeeding, relative to breastfeeding mothers. Findings reveal limitations in the availability of information and resources for non-breastfeeding mothers. It is possible that the pressure women may experience regarding breastfeeding may contribute to increased psychological distress for mothers who cannot or choose not to breastfeed. Based on our findings, future research and applied action should target the development and evaluation of informational resources and supports for non-breastfeeding women.

Association between sensory impairment and suicidal ideation and attempt: a cross-sectional analysis of nationally representative English household data

OBJECTIVES

Sensory impairments are associated with worse mental health and poorer quality of life, but few studies have investigated whether sensory impairment is associated with suicidal behaviour in a population sample. We investigated whether visual and hearing impairments were associated with suicidal ideation and attempt.

DESIGN

National cross-sectional study.

SETTING

Households in England.

PARTICIPANTS

We analysed data for 7546 household residents in England, aged 16 and over from the 2014 Adult Psychiatric Morbidity Survey.

EXPOSURES

Sensory impairment (either visual or hearing), Dual sensory impairment (visual and hearing), visual impairment, hearing impairment.

PRIMARY OUTCOME

Suicidal ideation and suicide attempt in the past year.

RESULTS

People with visual or hearing sensory impairments had twice the odds of past-year suicidal ideation (OR 2.06; 95% CI 1.17 to 2.73; p<0.001), and over three times the odds of reporting past-year suicide attempt (OR 3.12; 95% CI 1.57 to 6.20; p=0.001) compared with people without these impairments. Similar results were found for hearing and visual impairments separately and co-occurring.

CONCLUSIONS

We found evidence that individuals with sensory impairments are more likely to have thought about or attempted suicide in the past year than individuals without.

Psychometric properties of burnout measures: a systematic review

AIMS

Occupational Burnout (OB) is currently measured through several Patient-Reported Outcome Measures (PROMs) and some of them have become widely used in occupational health research and practice. We, therefore, aimed to review and grade the psychometric validity of the five OB PROMs considered as valid for OB measure in mental health professionals (the Maslach Burnout Inventory (MBI), the Pines' Burnout Measure (BM), the Psychologist Burnout Inventory (PBI), the OLdenburg Burnout Inventory (OLBI) and the Copenhagen Burnout Inventory (CBI)).

METHODS

We conducted systematic literature searches in MEDLINE, PsycINFO and EMBASE databases. We reviewed studies published between January 1980 and September 2018 following a methodological framework, in which each step of PROM validation, the reference method, analytical technics and result interpretation criteria were assessed. Using the COnsensus-based Standards for the selection of health Measurement Instruments we evaluated the risk of bias in studies assessing content and criterion validity, structural validity, internal consistency, reliability, measurement error, hypotheses testing and responsiveness of each PROM. Finally, we assessed the level of evidence for the validity of each PROM using the GRADE approach.

RESULTS

We identified 6541 studies, 19 of which were included for review. Fifteen studies dealt with MBI whereas BM, PBI, OLBI and CBI were each examined in only one study. OLBI had the most complete validation, followed by CBI, MBI, BM and PBI, respectively. When examining the result interpretation correctness, the strongest disagreement was observed for MBI (27% of results), BM (25%) and CBI (17%). There was no disagreement regarding PBI and OLBI. For OLBI and CBI, the quality of evidence for sufficient content validity, the crucial psychometric property, was moderate; for MBI, BM and PBI, it was very low.

CONCLUSION

To be validly and reliably used in medical research and practice, PROM should exhibit robust psychometric properties. Among the five PROMs reviewed, CBI and, to a lesser extent, OLBI meet this prerequisite. The cross-cultural validity of these PROMs was beyond the scope of our work and should be addressed in the future. Moreover, the development of a diagnostic standard for OB would be helpful to assess the sensitivity and specificity of the PROMs and further reexamine their validity.The study protocol was registered in PROSPERO (CRD 42019124621).

Precision clinical trials: a framework for getting to precision medicine for neurobehavioural disorders

The goal of precision medicine (individually tailored treatments) is not being achieved for neurobehavioural conditions such as psychiatric disorders. Traditional randomized clinical trial methods are insufficient for advancing precision medicine because of the dynamic complexity of these conditions. We present a pragmatic solution: the precision clinical trial framework, encompassing methods for individually tailored treatments. This framework includes the following: (1) treatment-targeted enrichment, which involves measuring patients' response after a brief bout of an intervention, and then randomizing patients to a full course of treatment, using the acute response to predict long-term outcomes; (2) adaptive treatments, which involve adjusting treatment parameters during the trial to individually optimize the treatment; and (3) precise measurement, which involves measuring predictor and outcome variables with high accuracy and reliability using techniques such as ecological momentary assessment. This review summarizes precision clinical trials and provides a research agenda, including new biomarkers such as precision neuroimaging, transcranial magnetic stimulation-electroencephalogram digital phenotyping and advances in statistical and machine-learning models. Validation of these approaches - and then widespread incorporation of the precision clinical trial framework - could help achieve the vision of precision medicine for neurobehavioural conditions.

Who comes to a self-help depression prevention website? Characteristics of Spanish- and English-speaking visitors

OBJECTIVE

To describe demographic and clinical characteristics of Spanish- and English-speaking visitors to a "Healthy Mood" website.

METHODS

An online study intended to prevent depression by teaching users mood management skills recruited participants globally using primarily Google Ads. Those who consented responded to the Patient Health Questionnaire (PHQ-9) and the MDE Screener (Muñoz, 1998) upon entry into the study.

RESULTS

1423 participants consented, 437 English speakers and 986 Spanish speakers. Of the 1271 participants with sufficient depression symptom data, 65% screened positive for a current major depressive episode, 30% were at high risk for onset of a major depressive episode, and 5% were in the low-risk category.

CONCLUSION

Websites intended to be preventive appear to attract primarily individuals who are currently experiencing enough symptoms to screen positive for a major depressive episode. Only 30% of participants were appropriate for a depression prevention intervention. Therefore, such sites must be ready to encourage those with current depression to obtain professional help as well as ensure that the online self-help interventions are appropriate for participants who could benefit from both preventive and treatment interventions.

How Do Physical Therapists Measure Treatment Outcomes in Adults With Chronic Low Back Pain? A Systematic Review

BACKGROUND

There is an increasing recognition of the importance of using a conceptual framework covering the full range of relevant health domains and outcome measures addressed by physical therapy modalities in patients with chronic low back pain (CLBP). However, little is known about what outcome domains have been measured and through what measures in physical therapy research.

OBJECTIVE

The purpose of this review was to synthesize outcome domains, instruments, and cutoff values reported in published randomized controlled trials and their compliance with the original Patient-Reported Outcomes Measurement Information System (PROMIS) framework.

DATA SOURCES

Embase, MEDLINE, Cochrane Library, and Physiotherapy Evidence Database electronic databases were systematically searched from January 2008 to April 2019.

STUDY SELECTION

Randomized controlled trials that compared physical therapy with any other intervention for adults with CLBP were included.

DATA EXTRACTION

Study characteristics, outcome domains, instruments, and cutoff values were extracted by 2 reviewers. The PROMIS framework was used for domain categorization.

DATA SYNTHESIS

One hundred ninety-five studies were included, with 52 outcome domains and 45 cutoff values identified from 182 instruments reported. Only 14 of 195 studies assessed all PROMIS health core areas, whereas the PROMIS physical health core area was assessed in all included studies. Pain intensity and disability were the most frequently used domains.

LIMITATIONS

Only studies for which full texts were available in English were included.

CONCLUSIONS

This review identified a poor overlap between the PROMIS framework and outcome domains used to define the effectiveness of physical therapy in adults with CLBP. This finding suggests that other potential benefits resulting from physical therapy modalities are not being measured. Furthermore, a large diversity in the outcome domains and instruments was found.

European Psychiatric Association (EPA) guidance on quality assurance in mental healthcare

Purpose:

To advance the quality of mental healthcare in Europe by developing guidance on implementing quality assurance.

Methods:

We performed a systematic literature search on quality assurance in mental healthcare and the 522 retrieved documents were evaluated by two independent reviewers (B.J. and J.Z.). Based on these evaluations, evidence tables were generated. As it was found that these did not cover all areas of mental healthcare, supplementary hand searches were performed for selected additional areas. Based on these findings, fifteen graded recommendations were developed and consented by the authors. Review by the EPA Guidance Committee and EPA Board led to two additional recommendations (on immigrant mental healthcare and parity of mental and physical healthcare funding).

Results:

Although quality assurance (measures to keep a certain degree of quality), quality control and monitoring (applying quality indicators to the current degree of quality), and quality management (coordinated measures and activities with regard to quality) are conceptually distinct, in practice they are frequently used as if identical and hardly separable. There is a dearth of controlled trials addressing ways to optimize quality assurance in mental healthcare. Altogether, seventeen recommendations were developed addressing a range of aspects of quality assurance in mental healthcare, which appear usable across Europe. These were divided into recommendations about structures, processes and outcomes. Each recommendation was assigned to a hierarchical level of analysis (macro-, meso- and micro-level).

Discussion:

There was a lack of evidence retrievable by a systematic literature search about quality assurance of mental healthcare. Therefore, only after further topics and search had been added it was possible to develop recommendations with mostly medium evidence levels.

Conclusion:

Evidence-based graded recommendations for quality assurance in mental healthcare were developed which should next be implemented and evaluated for feasibility and validity in some European countries. Due to the small evidence base identified corresponding to the practical obscurity of the concept and methods, a European research initiative is called for by the stakeholders represented in this Guidance to improve the educational, methodological and empirical basis for a future broad implementation of measures for quality assurance in European mental healthcare.

Safety Evaluation of an Automated Remote Monitoring System for Heart Failure in an Urban, Indigent Population

Heart Failure (HF) is the most expensive preventable condition, regardless of patient ethnicity, race, socioeconomic status, sex, and insurance status. Remote telemonitoring with timely outpatient care can significantly reduce avoidable HF hospitalizations. Human outreach, the traditional method used for remote monitoring, is effective but costly. Automated systems can potentially provide positive clinical, fiscal, and satisfaction outcomes in chronic disease monitoring. The authors implemented a telephonic HF automated remote monitoring system that utilizes deterministic decision tree logic to identify patients who are at risk of clinical decompensation. This safety study evaluated the degree of clinical concordance between the automated system and traditional human monitoring. This study focused on a broad underserved population and demonstrated a safe, reliable, and inexpensive method of monitoring patients with HF.

Demographic, clinical and psychosocial factors identify a high-risk group for depression screening among predominantly Hispanic patients with Type 2 diabetes in safety net care

OBJECTIVE

Identify biopsychosocial factors associated with depression for patients with Type 2 diabetes.

METHOD

A quasi-experimental clinical trial of 1293 patients was predominantly Hispanic (91%) female (62%), mean age 53 and average diabetes duration 10 years; 373 (29%) patients were depressed and assessed by Patient Health Questionnaire-9. Demographic, baseline clinical and psychosocial variables were compared between depressed and nondepressed patients.

RESULTS

Bivariate analyses found depression significantly associated (p<0.05) with female gender, diabetes emotional burden and regimen distress, BMI ≥ 30, lack of an A1C test, diabetes duration, poor self-care, number of diabetes symptoms and complications, functional and physical characteristics (pain, self-rated health condition, Short-Form Health Survey SF-physical, disability score and comorbid illnesses), as well as higher number of ICD-9 diagnoses and emergency room use. A multivariable regression model with stepwise selection identified six key risk factors: greater disability, diabetes symptoms and regimen distress, female gender, less diabetes self-care and lack of A1C. In addition, after controlling for identified six factors, the number of psychosocial stressors significantly associated with increased risk of depression (adjusted odds ratio=1.37, 95% confidence intervals: 1.18-1.58, p<.0001).

CONCLUSION

Knowing biopsychosocial factors could help primary care physicians and endocrinologists identify a high-risk group of patients needing depression screening.

Psychosocial rehabilitation for severe mental illnesses in general hospital psychiatric settings in South Asia

In South Asia, general hospital psychiatric units (GHPUs) have developed as an alternative to mental hospitals for the provision of comprehensive mental health services, training and research. GHPUs provide clinical care for all types of patients, including those with severe mental illnesses (SMIs). However, psychosocial rehabilitation is often neglected in GHPUs, partly because of the predominance of the medical model in routine clinical care and a lack of resources. This paper discusses the challenges in the management of SMIs in GHPUs and proposes a model of psychosocial rehabilitation which could be used in such settings.