Fatigue in the General Population of Colombia - Normative Values for the Multidimensional Fatigue Inventory MFI-20
Bibliographic record
Abstract
BACKGROUND: Fatigue is a frequent symptom in cancer patients. In Europe and Northern America fatigue questionnaires were developed and tested, but their generalizability to other cultural contexts is largely unknown. The aim of this study is to provide normative values for the Multidimensional Fatigue Inventory (MFI-20) based on a representative sample of the general population in Colombia and to test psychometric properties. METHODS: 1,500 individuals completed a questionnaire that contained the MFI-20, as well as other questionnaires, and questions on sociodemographic variables and chronic diseases. RESULTS: The mean values of the scales were marginally higher than those for 2 European samples. The mean value of the total score was 44.3 ± 14.1. Women were affected by fatigue more than men, and there was an almost linear age trend, with higher mean scores for older subjects. People with chronic diseases were affected by fatigue more than people without chronic conditions. The best psychometric properties were obtained for the total scale (sum score) of the MFI-20. CONCLUSION: The normative values presented here can help us to assess the individual burden of fatigue in a Latin American context. Psychometric properties of the MFI-20 in Colombia are similar to those obtained in Europe.
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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 | 0.001 | 0.003 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".