Project description:BackgroundAudit and feedback (A&F) is a common strategy for helping health providers to implement evidence into practice. Despite being extensively studied, health care A&F interventions remain variably effective, with overall effect sizes that have not improved since 2003. Contributing to this stagnation is the fact that most health care A&F interventions have largely been designed without being informed by theoretical understanding from the behavioral and social sciences. To determine if the trend can be improved, the objective of this study was to develop a list of testable, theory-informed hypotheses about how to design more effective A&F interventions.MethodsUsing purposive sampling, semi-structured 60-90-min telephone interviews were conducted with experts in theories related to A&F from a range of fields (e.g., cognitive, health and organizational psychology, medical decision-making, economics). Guided by detailed descriptions of A&F interventions from the health care literature, interviewees described how they would approach the problem of designing improved A&F interventions. Specific, theory-informed hypotheses about the conditions for effective design and delivery of A&F interventions were elicited from the interviews. The resulting hypotheses were assigned by three coders working independently into themes, and categories of themes, in an iterative process.ResultsWe conducted 28 interviews and identified 313 theory-informed hypotheses, which were placed into 30 themes. The 30 themes included hypotheses related to the following five categories: A&F recipient (seven themes), content of the A&F (ten themes), process of delivery of the A&F (six themes), behavior that was the focus of the A&F (three themes), and other (four themes).ConclusionsWe have identified a set of testable, theory-informed hypotheses from a broad range of behavioral and social science that suggest conditions for more effective A&F interventions. This work demonstrates the breadth of perspectives about A&F from non-healthcare-specific disciplines in a way that yields testable hypotheses for healthcare A&F interventions. These results will serve as the foundation for further work seeking to set research priorities among the A&F research community.

Project description:ObjectiveThis review assesses interventions and their effectiveness in mitigating psychological consequences from pandemic.MethodPublished English literatures were searched from four databases (Medline, PubMed, Embase and PsycINFO) from January 2020 and September 2021. A total of 27 papers with 29 studies (one paper reported three studies) met inclusion criteria. Cochrane risk-of-bias tool is applied to assess the quality of all randomised controlled trials (RCT).ResultsAll studies were recently conducted in 2020. Publications were from high-income (13, 44.8%), upper middle-income (12, 41.4%) and lower middle-income countries (3, 10.3%) and global (1, 3.5%). Half of the studies conducted for general population (51.7%). One-third of studies (8, 27.6%) provided interventions to patients with COVID-19 and 20.7% to healthcare workers. Of the 29 studies, 14 (48.3%) were RCT. All RCTs were assessed for risk of biases; five studies (15, 35.7%) had low risk as measured against all six dimensions reflecting high-quality study.Of these 29 studies, 26 diagnostic or screening measures were applied; 8 (30.9%) for anxiety, 7 (26.9%) for depression, 5 (19.2%) for stress, 5 (19.2%) for insomnia and 1 (3.8%) for suicide. Measures used to assess the baseline and outcomes of interventions were standardised and widely applied by other studies with high level of reliability and validity. Of 11 RCT studies, 10 (90.9%) showed that anxiety interventions significantly lowered anxiety in intervention groups. Five of the six RCT studies (83.3%) had significantly reduced the level of depression. Most interventions for anxiety and stress were mindfulness and meditation based.ConclusionsResults from RCT studies (11%, 78.6%) were effective in mitigating psychological consequences from COVID-19 pandemic when applied to healthcare workers, patients with COVID-19 and general population. These effective interventions can be applied and scaled up in other country settings through adaptation of modes of delivery suitable to country resources, pandemic and health system context.

Project description:Background: Given the worldwide spread of the 2019 Novel Coronavirus (COVID-19), there is an urgent need to identify risk and protective factors and expose areas of insufficient understanding. Emerging tools, such as the Rapid Evidence Map (rEM), are being developed to systematically characterize large collections of scientific literature. We sought to generate an rEM of risk and protective factors to comprehensively inform areas that impact COVID-19 outcomes for different sub-populations in order to better protect the public. Methods: We developed a protocol that includes a study goal, study questions, a PECO statement, and a process for screening literature by combining semi-automated machine learning with the expertise of our review team. We applied this protocol to reports within the COVID-19 Open Research Dataset (CORD-19) that were published in early 2020. SWIFT-Active Screener was used to prioritize records according to pre-defined inclusion criteria. Relevant studies were categorized by risk and protective status; susceptibility category (Behavioral, Physiological, Demographic, and Environmental); and affected sub-populations. Using tagged studies, we created an rEM for COVID-19 susceptibility that reveals: (1) current lines of evidence; (2) knowledge gaps; and (3) areas that may benefit from systematic review. Results: We imported 4,330 titles and abstracts from CORD-19. After screening 3,521 of these to achieve 99% estimated recall, 217 relevant studies were identified. Most included studies concerned the impact of underlying comorbidities (Physiological); age and gender (Demographic); and social factors (Environmental) on COVID-19 outcomes. Among the relevant studies, older males with comorbidities were commonly reported to have the poorest outcomes. We noted a paucity of COVID-19 studies among children and susceptible sub-groups, including pregnant women, racial minorities, refugees/migrants, and healthcare workers, with few studies examining protective factors. Conclusion: Using rEM analysis, we synthesized the recent body of evidence related to COVID-19 risk and protective factors. The results provide a comprehensive tool for rapidly elucidating COVID-19 susceptibility patterns and identifying resource-rich/resource-poor areas of research that may benefit from future investigation as the pandemic evolves.

Project description:BackgroundAccumulating evidence suggests the COVID-19 pandemic has negative effects on public mental health. Digital interventions that have been developed and evaluated in recent years may be used to mitigate the negative consequences of the pandemic. However, evidence-based recommendations on the use of existing telemedicine and internet-based (eHealth) and app-based mobile health (mHealth) interventions are lacking.ObjectiveThe aim of this study was to investigate the theoretical and empirical base, user perspective, safety, effectiveness, and cost-effectiveness of digital interventions related to public mental health provision (ie, mental health promotion, prevention, and treatment of mental disorders) that may help to reduce the consequences of the COVID-19 pandemic.MethodsA rapid meta-review was conducted. The MEDLINE, PsycINFO, and CENTRAL databases were searched on May 11, 2020. Study inclusion criteria were broad and considered systematic reviews and meta-analyses that investigated digital tools for health promotion, prevention, or treatment of mental health conditions and determinants likely affected by the COVID-19 pandemic.ResultsOverall, 815 peer-reviewed systematic reviews and meta-analyses were identified, of which 83 met the inclusion criteria. Our findings suggest that there is good evidence on the usability, safety, acceptance/satisfaction, and effectiveness of eHealth interventions. Evidence on mHealth apps is promising, especially if social components (eg, blended care) and strategies to promote adherence are incorporated. Although most digital interventions focus on the prevention or treatment of mental disorders, there is some evidence on mental health promotion. However, evidence on process quality, cost-effectiveness, and long-term effects is very limited.ConclusionsThere is evidence that digital interventions are particularly suited to mitigating psychosocial consequences at the population level. In times of physical distancing, quarantine, and restrictions on social contacts, decision makers should develop digital strategies for continued mental health care and invest time and efforts in the development and implementation of mental health promotion and prevention programs.

Project description:IntroductionThe global spread of COVID-19 has raised concerns about its possible impact on mental health. People living with multiple sclerosis (PwMS) are considered potentially vulnerable to the mental health effects of the pandemic, as they may be subject to increased social isolation.AimTo systematically review the current evidence on the impact of the COVID-19 pandemic on mental health outcomes among PwMS.MethodWe searched four major databases (Medline, EMBASE, PsychInfo and Scopus) and the WHO Global Health COVID-19 research database. We included peer-reviewed primary research studies using validated health-related quality of life (HRQOL) and psychometric screening tools to evaluate mental health outcomes among PwMS during the COVID-19 pandemic. Studies reporting data on the prevalence of mental health disorders, severity of psychological symptoms and contributing demographic and clinical factors for PwMS during the COVID-19 pandemic were included.ResultsOur initial search yielded 268 records; 19 studies (13 cross-sectional, 6 longitudinal) were included. Most were conducted during a peak in the pandemic in the host country via an online platform. The main mental health outcomes were depression, anxiety, stress, sleep quality and HRQOL. The included studies used a variety of outcome assessment tools and study designs. The prevalence of mental health issues such as depression, anxiety and stress were high among PwMS during the pandemic. In addition, compared to control populations, PwMS experienced more severe symptoms of depression and stress during the COVID-19 outbreak. However, results from longitudinal studies demonstrate that the severity of mental health symptoms among PwMS during the pandemic were not significantly different compared with the pre-pandemic period.ConclusionAlthough mental health issues such as anxiety and depression were common among PwMS during the pandemic, current evidence suggests that mental health among PwMS has not been significantly affected by pandemic-related restrictive measures. Instead, the observed differences may be the result of pre-pandemic differences in prevalence and severity. Where possible, future studies should seek to address the methodological issues identified in the included studies to ensure that data collected during the pandemic can be synthesized into recommendations for policy and practice.

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Identifying evidence informed psychological interventions during the COVID-19 pandemic: Rapid review of the literature.

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