A systematic review of qualitative studies exploring the factors influencing the physical activity levels of Arab migrants
Bibliographic record
Abstract
BACKGROUND: Evidence suggests that Arab migrant populations engage in low levels of physical activity. To our knowledge, there are no reviews that explore the perspectives of Arab migrant populations on the factors influencing physical activity. The aim of this systematic review was to thematically synthesise qualitative literature on the factors influencing physical activity among Arab migrant populations. METHODS: Five electronic databases (CINAHL, SPORTDiscus, PsychoInfo, MEDLINE, Embase) were searched in July 2018 and searched again in April 2020. A manual search in Google Scholar was also performed using keywords and the reference lists of included studies were also screened to identify further articles. The eligibility criteria for inclusion were studies that sampled adult (≥18 years) Arab migrant populations, used qualitative methodology, explored the factors influencing physical activity as a primary aim, and were published in English. The 10-item Critical Appraisal Skills Programme (CASP) checklist was used to assess methodological quality of individual studies. The results of the studies were thematically synthesised using the qualitative software Quirkos v1.6. RESULTS: A total of 15 studies were included, with the largest proportion of studies conducted in Australia, followed by the United States, Netherlands, Sweden, and then Canada. Five studies exclusively sampled Arab migrant populations in their study. A total of 7 major themes influencing physical activity among Arab migrants emerged from the synthesis: culture and religion, competing commitments and time, social factors, health-related influences, accessibility issues, outdoor environment, and the migratory experience. CONCLUSIONS: The findings of this review highlighted the various factors influencing the physical activity levels of Arab migrant adults. While many of the factors influencing physical activity are shared with those experienced by other populations (e.g., time constraints), for Arab migrant populations there are other more unique factors closely associated with culture and religion that appear to influence their levels of physical activity. The findings of this review could be used to inform the design of physical activity interventions targeting Arab migrant populations.
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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 | 0.053 | 0.132 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.018 | 0.017 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".