Psychometric Performance of Fatigue Scales in Inflammatory Bowel Disease
Bibliographic record
Abstract
BACKGROUND: Fatigue is highly prevalent in people with inflammatory bowel disease (IBD). Fatigue scales are important for studies testing fatigue interventions, but information about psychometric properties of many scales is insufficient in IBD. We compared the psychometric properties of multiple generic fatigue scales in participants with IBD. METHODS: Individuals with IBD (N = 216) completed the Daily Fatigue Impact Scale (DFIS), the vitality subscale of the RAND-36, and the Patient Health Questionnaire-9 (PHQ-9) fatigue item twice. A subgroup (n = 84) also completed the Fatigue Impact Scale (FIS) once, from which we also scored the 21 items from the Modified Fatigue Impact Scale (MFIS-IBD). We assessed floor/ceiling effects, construct validity, and internal consistency reliability. Using relative efficiency (RE), we compared discriminating ability and comparative responsiveness of the measures regarding disease activity and employment status and changes. RESULTS: The FIS, MFIS, and RAND-36-vitality scales did not exhibit floor or ceiling effects. The DFIS showed mild floor effects (19.4%), and the PHQ-9 fatigue item showed floor (18.1%) and ceiling (20.8%) effects. Internal consistency reliability exceeded 0.93 for FIS, MFIS-IBD, and DFIS and was 0.81 for the RAND-36-vitality scale. In the subgroup analysis, the FIS, MFIS-IBD, and DFIS were strongly correlated with each other (r ≥ 0.90). The ability to discriminate between disease activity groups was highest for the FIS and MFIS-IBD, followed by the DFIS. The FIS, MFIS-IBD, and DFIS were responsive to changes in work impairment. CONCLUSIONS: The FIS, MFIS-IBDs and DFIS had adequate validity and reliability for assessing fatigue in IBD.
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 | 0.014 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".