A rapid review of home-based activities that can promote mental wellness during the COVID-19 pandemic
Bibliographic record
Abstract
BACKGROUND: During the COVID-19 pandemic, public health measures such as isolation, quarantine, and social distancing are needed. Some of these measures can adversely affect mental health. Activities that can be performed at home may mitigate these consequences and improve overall mental well-being. In this study, home-based activities that have potential beneficial effects on mental health were examined. METHODS: A rapid review was conducted based on a search of the following databases: MEDLINE, EMBASE, CINAHL, PyscINFO, Global Health, epistemonikos.org, covid19reviews.org, and eppi.ioe.ac.uk/covid19_map_v13.html. Eligible studies include randomized controlled trials and non-randomized studies published between 1/1/2000 and 28/05/2020 and that examined the impact of various activities on mental health outcomes in low-resource settings and contexts that lead to social isolation. Studies of activities that require mental health professionals or that could not be done at home were excluded. Two review authors performed title/abstract screening. At the full-text review stage, 25% of the potentially eligible studies were reviewed in full by two review authors; the rest were reviewed by one review author. Risk of bias assessment and data extraction were performed by one review author and checked by a second review author. The main outcome assessed was change or differences in mental health as expressed in Cohen's d; analysis was conducted following the synthesis without meta-analysis guidelines (SWiM). PROSPERO registration: CRD42020186082. RESULTS: Of 1,236 unique records identified, 160 were reviewed in full, resulting in 16 included studies. The included studies reported on the beneficial effects of exercise, yoga, progressive muscle relaxation, and listening to relaxing music. One study reported on the association between solitary religious activities and post traumatic stress disorder symptoms. While most of the included studies examined activities in group settings, particularly among individuals in prisons, the activities were described as something that can be performed at home and alone. All included studies were assessed to be at risk of bias in one or more of the bias domains examined. CONCLUSIONS: There is some evidence that certain home-based activities can promote mental wellness during the COVID-19 pandemic. Guidelines are needed to help optimize benefits while minimizing potential risks when performing these activities.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.058 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.005 |
| Bibliometrics | 0.020 | 0.019 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".