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1.
J Biol Rhythms ; 37(4): 358-384, 2022 Aug.
Article in English | MEDLINE | ID: covidwho-1916809

ABSTRACT

The COVID-19 pandemic has negatively impacted the well-being of healthcare workers (HCWs). HCWs are highly exposed to shift work and their work schedules have been subject to increasing unpredictability since the start of the pandemic. This review aims to: (1) map the studies providing information about factors associated with sleep characteristics in HCWs working in the context of the COVID-19 pandemic during the first and second waves and (2) examine the state of the evidence base in terms of the availability of information on the influence of atypical work schedules. A literature search was performed in PubMed. Studies containing information about factors (demographic; psychological; occupational; COVID-19-specific; work schedule; lifestyle; medical; or other) associated with various sleep characteristics among HCWs working in the context of the COVID-19 pandemic were included. Particular attention was paid to the availability of information on the role of atypical work schedules on HCW sleep. Fifty-seven articles met the inclusion criteria. Most studies were reports of quantitative cross-sectional surveys using self-report measures. Associations between female sex, frontline HCW status, psychological factors, and poorer sleep were observed. Six studies included a measure of shift work in their analyses, 5 of which reported an association between shift work status and sleep. A wide range of factors were investigated, with female sex, frontline HCW status, and psychological factors repeatedly demonstrating associations with poorer sleep. Sleep was predominantly measured in terms of self-reported sleep quality or insomnia symptoms. Few studies investigated the influence of atypical work schedules on HCW sleep in the context of the COVID-19 pandemic. Research on this topic is lacking in terms of reliable and consistent measurements of sleep outcomes, longitudinal data, and knowledge about the influence of covariates such atypical work schedules, comorbidity, and medical history on HCW sleep.


Subject(s)
COVID-19 , Sleep Initiation and Maintenance Disorders , COVID-19/epidemiology , Circadian Rhythm , Cross-Sectional Studies , Female , Health Personnel/psychology , Humans , Pandemics , Personnel Staffing and Scheduling , SARS-CoV-2 , Sleep , Sleep Initiation and Maintenance Disorders/epidemiology
2.
Front Digit Health ; 4: 814248, 2022.
Article in English | MEDLINE | ID: covidwho-1809364

ABSTRACT

Nearly all young people use the internet daily. Many youth with mental health concerns, especially since the Covid-19 pandemic, are using this route to seek help, whether through digital mental health treatment, illness prevention tools, or supports for mental wellbeing. Videogames also have wide appeal among young people, including those who receive mental health services. This review identifies the literature on videogame interventions for young people, ages 12-29, and maps the data on game use by those with mental health and substance use problems, focusing on evidence for the capacity of games to support treatment in youth mental health services; how stakeholders are involved in developing or evaluating games; and any potential harms and ethical remedies identified. A systematic scoping review methodology was used to identify and assess relevant studies. A search of multiple databases identified a total of 8,733 articles. They were screened, and 49 studies testing 32 digital games retained. An adapted stepped care model, including four levels, or steps, based on illness manifestation and severity, was used as a conceptual framework for organizing target populations, mental health conditions and corresponding digital games, and study results. The 49 selected studies included: 10 studies (20.4%) on mental health promotion/prevention or education for undiagnosed youth (Step 0: 7 games); 6 studies (12.2%) on at-risk groups or suspected mental problems (Step 1: 5 games); 24 studies (49.0%) on mild to moderate mental conditions (Steps 2-3: 16 games); and 9 studies (18.4%) focused on severe and complex mental conditions (Step 4: 7 games). Two interventions were played by youth at more than one level of illness severity: the SPARX game (Steps 1, 2-3, 4) and Dojo (Steps 2-3 and 4), bringing the total game count to 35 with these repetitions. Findings support the potential integration of digital games in youth services based on study outcomes, user satisfaction, relatively high program retention rates and the potential usefulness of most games for mental health treatment or promotion/prevention. Most studies included stakeholder feedback, and involvement ratings were very high for seven games. Potential harms were not addressed in this body of research. This review provides an important initial repository and evaluation of videogames for use in clinical settings concerned with youth mental health.

3.
2021.
Preprint in English | Other preprints | ID: ppcovidwho-295743

ABSTRACT

Objective We examine the feasibility of an Artificial Intelligence (AI)-powered clinical decision support system (CDSS), which combines the operationalized 2016 Canadian Network for Mood and Anxiety Treatments guidelines with a neural-network based individualized treatment remission prediction. Methods Due to COVID-19, the study was adapted to be completed entirely at a distance. Seven physicians recruited outpatients diagnosed with major depressive disorder (MDD) as per DSM-V criteria. Patients completed a minimum of one visit without the CDSS (baseline) and two subsequent visits where the CDSS was used by the physician (visit 1 and 2). The primary outcome of interest was change in session length after CDSS introduction, as a proxy for feasibility. Feasibility and acceptability data were collected through self-report questionnaires and semi-structured interviews. Results Seventeen patients enrolled in the study;14 completed. There was no significant difference between appointment length between visits (introduction of the tool did not increase session length). 92.31% of patients and 71.43% of physicians felt that the tool was easy to use. 61.54% of the patients and 71.43% of the physicians rated that they trusted the CDSS. 46.15% of patients felt that the patient-clinician relationship significantly or somewhat improved, while the other 53.85% felt that it did not change. Conclusions Our results confirm the primary hypothesis that the integration of the tool does not increase appointment length. Findings suggest the CDSS is easy to use and may have some positive effects on the patient-physician relationship. The CDSS is feasible and ready for effectiveness studies.

4.
JMIR Form Res ; 5(10): e31862, 2021 Oct 25.
Article in English | MEDLINE | ID: covidwho-1484964

ABSTRACT

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.

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