Operationalisation of quality of life for adults with severe disabilities
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: The operationalisation of quality of life for people with more severe disabilities has been acknowledged in the published research for more than two decades. This study aims to contribute to our knowledge and understanding of the quality of life of adults with severe disabilities by developing a set of quality of life indicators appropriate to this population using a Delphi method and the eight-domain conceptual model proposed by Schalock & Verdugo (2002). METHOD: The participating panel in the Delphi method included 12 experts who evaluated each proposed item according to four criteria: suitability, importance, observability and sensitivity. Descriptive analyses were used to select the best items in each of the four rounds of this Delphi study, as well as examining the coefficients of concordance that were calculated for the final pool of items. RESULTS: The four rounds of the Delphi study resulted in a final pool of 118 items (91 that were considered valid in the first round plus 27 items proposed, reformulated or discussed in the following rounds). Importance and sensitivity were the criteria that received the highest and lowest ratings, respectively, but also the ones that had the highest and lowest mean coefficients of concordance. Experts showed the strongest agreement for items related to material well-being, while the weakest was found for items related to personal development. CONCLUSIONS: This study further contributes to our understanding of how to operationalise and measure quality of life in adults with severe disabilities. The item pool generated may prove helpful in the development of instruments for the measurement of quality of life-related outcomes in this population.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.151 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 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 it