The indirect effects of basic psychological needs on the relationship between physical activity and mental health in adults with disabilities: A cross-sectional study
Bibliographic record
Abstract
Abstract Introduction Poor mental health is a common secondary health condition for adults with disabilities. The mental health benefits of moderate-to-vigorous intensity physical activity (MVPA) are well-documented. Few studies have empirically tested the relationship between MVPA and mental health among persons with disabilities. Additionally, theoretically-informed factors that may mediate the relationship are not commonly tested among persons with disabilities. The primary aim of this study was to examine the cross-sectional relationship between MVPA and mental health in adults with disabilities. A secondary aim was to explore the indirect effects of the three psychological needs (autonomy, competence, relatedness) on the MVPA-mental health relationship. Material and methods Participants (n = 100; mean age = 36.61; 54% women; 84% physical disability) completed an online questionnaire to assess MVPA, mental health, autonomy, competence, and relatedness. The associations between MVPA, psychological needs, and mental health were explored descriptively and in a multiple mediation regression model. Results The bivariate association between MVPA and mental health was significant ( r s = 0.34, p = 0.01), as were the associations between the three psychological needs and MVPA ( r s = 0.24–0.43) and mental health ( r s = 0.61–0.82). MVPA had a significant indirect effect on mental health through autonomy (β = 0.05, 95% CI = 0.00–0.12), competence (β = 0.16, 95% CI = 0.08–0.25) and relatedness (β = 0.08, 95% CI = 0.02–0.17). Conclusions The results of this study add to limited research documenting the relationship between MVPA and mental health in adults with disabilities by highlighting the potential benefits of autonomy, competence, and relatedness. Future prospective research is needed to investigate the mediating effects of autonomy, competence and relatedness on the relationship between MVPA and mental health in adults with disabilities.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".