Reliability of health-related quality-of-life assessments made by older adults and significant others for health states of increasing cognitive impairment
Bibliographic record
Abstract
BACKGROUND: Older adults are encouraged by many organizations to engage in advance care planning in the event of decisional incapacity. Planning for future health care often involves anticipating health-related quality of life (HRQoL) in states of reduced cognitive functioning. No study has yet examined whether anticipated HRQoL is stable over time. The accuracy with which significant others can predict how an older adult envisions HRQoL in a future state of cognitive impairment is also unknown. We investigated the extent to which health-related quality-of-life ratings made by older adults and designated proxies for health states of increasing cognitive impairment are consistent over time and agree with each other. METHODS: Results are based on HRQoL ratings made on a 5-point Likert scale by 235 community-based elder-proxy dyads on three occasions. Ratings were obtained for the older adult's current health state as well as under the assumption that he/she had a mild to moderate stroke, incurable brain cancer or severe dementia. Data were analyzed using both traditional approaches (e.g., intraclass correlation coefficients, Bland-Altman plots) and the theory of generalizability. RESULTS: We found ratings to be reasonably consistent over time and in good agreement within dyads, even more so as implied cognitive functioning worsened. Across health states, ratings over time or within elder-proxy dyads were no more than one category apart in over 87% of cases. Using the theory of generalizability, we further found that, of the two facets investigated, rater had a greater influence on score variability than occasion. CONCLUSIONS: These findings underscore the importance of discussing health-related quality-of-life issues during advance care planning and involving designated proxies in the discussion to enhance their understanding of the role that HRQoL should play in actual decision-making situations. Medical decision-making may be influenced by healthcare providers' and family members' assessments of an incapacitated patient's health-related quality of life, in addition to that of the designated proxy. Future studies should investigate whether these two groups of individuals share the views of the patient and the designated proxy on anticipated HRQoL.
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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 | 0.022 | 0.057 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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".