Correction: Evaluating the Clinical Feasibility of an Artificial Intelligence-Powered, Web-Based Clinical Decision Support System for the Treatment of Depression in Adults: Longitudinal Feasibility Study.

[This corrects the article DOI: 10.2196/31862.].

Evaluating the Clinical Feasibility of an Artificial Intelligence-Powered, Web-Based Clinical Decision Support System for the Treatment of Depression in Adults: Longitudinal Feasibility Study.

BACKGROUND: Approximately two-thirds of patients with major depressive disorder do not achieve remission during their first treatment. There has been increasing interest in the use of digital, artificial intelligence-powered clinical decision support systems (CDSSs) to assist physicians in their treatment selection and management, improving the personalization and use of best practices such as measurement-based care. Previous literature shows that for digital mental health tools to be successful, the tool must be easy for patients and physicians to use and feasible within existing clinical workflows. OBJECTIVE: This study aims to examine the feasibility of an artificial intelligence-powered CDSS, which combines the operationalized 2016 Canadian Network for Mood and Anxiety Treatments guidelines with a neural network-based individualized treatment remission prediction. METHODS: Owing to the COVID-19 pandemic, the study was adapted to be completed entirely remotely. A total of 7 physicians recruited outpatients diagnosed with major depressive disorder according to the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition criteria. Patients completed a minimum of one visit without the CDSS (baseline) and 2 subsequent visits where the CDSS was used by the physician (visits 1 and 2). The primary outcome of interest was change in appointment length after the introduction of the CDSS as a proxy for feasibility. Feasibility and acceptability data were collected through self-report questionnaires and semistructured interviews. RESULTS: Data were collected between January and November 2020. A total of 17 patients were enrolled in the study; of the 17 patients, 14 (82%) completed the study. There was no significant difference in appointment length between visits (introduction of the tool did not increase appointment length; F2,24=0.805; mean squared error 58.08; P=.46). In total, 92% (12/13) of patients and 71% (5/7) of physicians felt that the tool was easy to use; 62% (8/13) of patients and 71% (5/7) of physicians rated that they trusted the CDSS. Of the 13 patients, 6 (46%) felt that the patient-clinician relationship significantly or somewhat improved, whereas 7 (54%) felt that it did not change. CONCLUSIONS: Our findings confirm that the integration of the tool does not significantly increase appointment length and suggest that the CDSS is easy to use and may have positive effects on the patient-physician relationship for some patients. The CDSS is feasible and ready for effectiveness studies. TRIAL REGISTRATION: ClinicalTrials.gov NCT04061642; http://clinicaltrials.gov/ct2/show/NCT04061642.

An Evaluation of Talent 4 . . . : A Programme to Identify Talent and Skills for Prisoners, Disadvantaged, Unemployed, and Vulnerable Groups.

Previous research suggests that the relationship between employment and recidivism is complex, with more support needed to facilitate employability motivation for sustained change. An arts-based programme designed to facilitate vocational self-determinism among prisoners with evidence of impact across three prisons in the United Kingdom was replicated and delivered to 234 prisoners and long-term unemployed participants from six European countries, to explore whether the findings from the previous evaluation would be replicated on a much larger scale. The research presented in this article found that supporting prisoners and the long-term unemployed to articulate employability goals had a positive effect on personal growth as well as understanding of individual strengths and weaknesses with respect to work, employment, problem solving, and thinking styles. Future research might explore the longer term impact on employment and recidivism.

Hope, optimism and delusion.

Optimism is generally accepted by psychiatrists, psychologists and other caring professionals as a feature of mental health. Interventions typically rely on cognitive-behavioural tools to encourage individuals to 'stop negative thought cycles' and to 'challenge unhelpful thoughts'. However, evidence suggests that most individuals have persistent biases of optimism and that excessive optimism is not conducive to mental health. How helpful is it to facilitate optimism in individuals who are likely to exhibit biases of optimism already? By locating the cause of distress at the individual level and 'unhelpful' cognitions, does this minimise wider systemic social and economic influences on mental health?

A new scale to assess the therapeutic relationship in community mental health care: STAR.

BACKGROUND: No instrument has been developed specifically for assessing the clinician-patient therapeutic relationship (TR) in community psychiatry. This study aimed to develop a measure of the TR with clinician and patient versions using psychometric principles for test construction. METHOD: A four-stage prospective study was undertaken, comprising qualitative semi-structured interviews about TRs with clinicians and patients and their assessment of nine established scales for their applicability to community care, administering an amalgamated scale of more than 100 items, followed by Principal Components Analysis (PCA) of these ratings for preliminary scale construction, test-retest reliability of the scale and administering the scale in a new sample to confirm its factorial structure. The sample consisted of patients with severe mental illness and a designated key worker in the care of 17 community mental health teams in England and Sweden. RESULTS: New items not covered by established scales were identified, including clinician helpfulness in accessing services, patient aggression and family interference. The new patient (STAR-P) and clinician scales (STAR-C) each have 12 items comprising three subscales: positive collaboration and positive clinician input in both versions, non-supportive clinician input in the patient version, and emotional difficulties in the clinician version. Test-retest reliability was r=0.76 for STAR-P and r=0.68 for STAR-C. The factorial structure of the new scale was confirmed with a good fit. CONCLUSIONS: STAR is a specifically developed, brief scale to assess TRs in community psychiatry with good psychometric properties and is suitable for use in research and routine care.