The complex relationship between physical activity and fatigue with socioeconomic status, and mental health factors in individuals with inflammatory bowel disease
Bibliographic record
Abstract
BACKGROUND: We aimed to assess to what extent socioeconomic status (SES) and elevated symptoms of anxiety and depression predict low physical activity (PA) and high fatigue among individuals with inflammatory bowel disease (IBD). METHODS: Participants from the University of Manitoba IBD Research Registry completed a cross-sectional survey pertaining to fatigue, IBD symptoms, PA, and mental health. The International Physical Activity Questionnaire, Modified Fatigue Impact Scale (MFIS), Generalized Anxiety Disorders-7, and Patient Health Questionnaire scales were used. Disease activity was defined by the Inflammatory Bowel Disease Symptom Inventory. RESULTS: Among those who were fatigued (MFIS > 38) more were <63 years of age (63% vs 49%, P < .001), reported education of highschool level or less (34% vs 27%, P = .03), had low household income <$50 000 (24% vs. 16%, P < .01), were not in a relationship (25% vs 18%, P < .001), and were current smokers (16% vs 7%, P < .0001). The odds of low SES were greater for those who participated in low PA (OR = 2.75, 95% CI = 1.8-4.3), low PA and were fatigued (OR = 3.05, 95% CI = 1.7-5.3), and low PA excluding fatigue (OR = 2.28, 95% CI = 1.3-3.9). Low SES was not significantly associated with fatigue (P = .08), particularly after removing PA observations (OR = 1.00, 95% CI = 0.47-1.97). After adjusting for demographic and clinical factors, the odds of being fatigued were greater among those with elevated anxiety (aOR = 14.4, 95% CI = 9.4-22.4), depression (aOR = 39.6, 95% CI = 24.1-67.2), and active disease (aOR = 6.9, 95% CI = 4.8-9.97). The results did not change when removing low PA from the analysis. CONCLUSIONS: Low SES was a main driver of engaging in low PA (and not high fatigue). Anxiety and/or depression and active disease were drivers of high fatigue (and not low PA).
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".