Evaluation and Measurement of Health-Related Quality of Life for Individuals with Diabetes Mellitus by Health Utilities Index Mark 3 (HUI3) System
Bibliographic record
Abstract
The Health Utilities Index Mark 3 (HUI3) is an important indicator when measuring the health-related quality of life (HRQOL) and assessing the burden of disease, especially for chronic conditions such as diabetes mellitus (DM). The objectives of this study were to evaluate the scores of HRQOL for respondents with DM to examine associations between overall HUI3 scores and eight component attributes, and various sociodemographic and lifestyle attributes, and by doing so, provide information to improve the HRQOL of individuals with diabetes. The study was based on the Canadian National Population Survey (NPHS) longitudinal data, from 1994-1995 to 2002-2003. We evaluated overall HUI3 scores and eight attributes (vision, hearing, speech, ambulation, dexterity, emotion, cognition, and pain) between respondents with and without diabetes in relation to demographic characteristics (age, sex, lifestyle, and socioeconomic status using ANCOVA[analysis of covariance]). Awareness of diabetes appeared to affect the HRQOL of older age groups more so than younger age groups (p < 0.01). Diabetes also appeared to have a greater impact on males' quality of life compared to females', and among individuals with single marital status and low socioeconomic status (p < 0.01). These findings add to what is known about cognitive representations and the self-regulation of diabetes as well as the relationships between cognitive representations of diabetes, HRQOL, and behavioral factors. In particular, results from this study suggest the need to address ways of reducing the burden of diabetes associated with health behaviours, and increasing the quality of life for the individuals with diabetes in Canada.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".