An instrument to assess quality of life in relation to nutrition: item generation, item reduction and initial validation
Bibliographic record
Abstract
BACKGROUND: It is arguable that modification of diet, given its potential for positive health outcomes, should be widely advocated and adopted. However, food intake, as a basic human need, and its modification may be accompanied by sensations of both pleasure and despondency and may consequently affect to quality of life (QoL). Thus, the feasibility and success of dietary changes will depend, at least partly, on whether potential negative influences on QoL can be avoided. This is of particular importance in the context of dietary intervention studies and in the development of new food products to improve health and well being. Instruments to measure the impact of nutrition on quality of life in the general population, however, are few and far between. Therefore, the aim of this project was to develop an instrument for measuring QoL related to nutrition in the general population. METHODS AND RESULTS: We recruited participants from the general population and followed standard methodology for quality of life instrument development (identification of population, item selection, n = 24; item reduction, n = 81; item presentation, n = 12; pretesting of questionnaire and initial validation, n = 2576; construct validation n = 128; and test-retest reliability n = 20). Of 187 initial items, 29 were selected for final presentation. Factor analysis revealed an instrument with 5 domains. The instrument demonstrated good cross-sectional divergent and convergent construct validity when correlated with scores of the 8 domains of the SF-36 (ranging from -0.078 to 0.562, 19 out of 40 tested correlations were statistically significant and 24 correlations were predicted correctly) and good test-retest reliability (intra-class correlation coefficients from 0.71 for symptoms to 0.90). CONCLUSIONS: We developed and validated an instrument with 29 items across 5 domains to assess quality of life related to nutrition and other aspects of food intake. The instrument demonstrated good face and construct validity as well as good reliability. Future work will focus on the evaluation of longitudinal construct validity and responsiveness.
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 | 0.031 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".