Colombian Rasch validation of KIDSCREEN-27 quality of life questionnaire
Bibliographic record
Abstract
BACKGROUND: The family of KIDSCREEN instruments is the only one with trans-cultural adaptation and validation in Colombia. These validations have been performed from the classical test theory approach, which has evidenced satisfactory psychometric properties. The aim of this study was to evaluate psychometric properties of KIDSCREEN-27 children and parent-proxy versions, through Rasch analysis. METHODS: The participants in the present study were two different sets of populations, 321 kids with a mean age of 12.3 (SD 2.6), 41 % 8 to 11 years old and 59 % 12 to 18 years old; and 1150 parent-proxy with an average age of 45.5 (SD 18.9). Psychometric properties were assessed using the partial credits model in the Rasch approach. Unidimensionality, fitting of person and item, response form, and differential item functioning (DIF) were measured. RESULTS: The Infit MNSQ in child self-reported version that ranges between 0.71-1.76, and 0.69-1.31 in the parent-proxy version. Scores gathered on Likert forms of 5-response options, person separation was 2.08 for child self-reported version and 2.40 for parent-proxy; reliability was 0.81 and 0.85, respectively. Items reliability was 0.99 on both versions, with separations of 11.92 for child self-reported and 10.83 for parent-proxy. There was not DIF according to the variables sex and age but was present according to socioeconomic status. CONCLUSION: There was a good fit for items and individuals to the Rasch model. Item separation was adecuate, and person separation improved when the response form was re-codified to four options. The presence of DIF according to socioeconomic status implies a scale's bias in the measure of HRQoL of Colombian children.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".