Impacts of Physical Activity Interventions on Psychiatric Symptom Severity in Adults with Severe Mental illness: A Systematic Review
Bibliographic record
Abstract
Abstract Background There is a well-established relationship between physical activity (PA) and improved mental and physical health. However, the focus has been on mild to moderate anxiety and depression, while there has been a paucity in the literature regarding the impacts of PA on psychiatric symptoms in individuals with severe mental illness (SMI), and the potential utility of PA as an adjunctive treatment for these conditions. The purpose of this narrative analysis was to examine the effects of PA interventions on psychiatric symptoms among individuals with SMI, which we defined as schizophrenia spectrum disorders, bipolar disorders, and major depressive disorders. Methods A search was conducted in MEDLINE PsycInfo, and SPORTDiscus databases concluding in January 2023 that included studies published in an English peer-reviewed journal, with a PA intervention, conducted with adults (≥ 18yrs) diagnosed with a schizophrenia spectrum disorder, bipolar disorder, or major depressive disorder. The search returned 119 articles, and 10 met eligibility criteria. Results Results clearly showed that PA caused no harm and that a small improvement in psychiatric symptom severity was achieved, with effect sizes ranging from 0.013 to 0.712. Conclusions Physical activity interventions can decrease psychiatric symptom severity in persons with severe mental illness and may be an efficacious adjuvant treatment to pharmacological management of schizophrenia, bipolar and major depressive disorders. Physical activity interventions did not have any adverse effects on individuals with severe mental illness. However, the current literature is heterogeneous in terms of PA types, frequency, duration, and intensity, and further research is needed before specific PA recommendations can be made as an adjunctive treatment for individuals with SMI.
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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 | 0.005 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.007 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".