Psychometric Development of the Iceland-Expressive Family Functioning Questionnaire (ICE-EFFQ)
Bibliographic record
Abstract
Instruments that are able to capture changes related to an intervention are of great value to the scientific as well as to the clinical community. The Iceland-Expressive Family Functioning Questionnaire (ICE-EFFQ) measures expressive emotions, collaboration, problem solving, communication, and behavior in families experiencing a chronic or an acute illness. The conceptual framework of the Calgary Family Assessment Model (Wright & Leahey, 2009) was used to construct the original questionnaire of 45 items and 10 subcategories. A total of 557 family members with a recent illness experience of a close relative answered the ICE-EFFQ in three different studies. Principal component factor analysis reduced the original questionnaire to 22 items with five factors emerging and a total Cronbach's alpha coefficient of α = 0.912 accounting for 60.3% of the total variability. Confirmatory factor analysis from two studies produced the final version of the questionnaire consisting of 17 items and four factors.
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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 | 0.008 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".