From the Generic to the Condition-specific? Instrument Order Effects in Quality of Life Assessment
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: Generic and condition-specific measures of quality of life are often used in parallel. Despite extensive evidence of question ordering effects in the general survey literature, there is no consensus on which type of measure should be administered first and little previous conclusive research into instrument ordering effects. OBJECTIVES: To investigate the effects of instrument ordering on response rates, speed of response, and response patterns to questions on health-related quality of life. RESEARCH DESIGN: Subjects were randomized to two different versions of a self-completion questionnaire; in the first, condition-specific measures of quality of life preceded generic instruments; in the second version, the relative positions were reversed. SUBJECTS: Adults with asthma or angina from 62 family practices in northeast England. MEASURES: Instruments were the generic Medical Outcomes Study Short Form 36-item questionnaire, the EQ-5D, the Newcastle Asthma Symptoms Questionnaire, the Asthma Quality of Life Questionnaire, and the Seattle Angina Questionnaire. Effects were assessed in terms of questionnaire response rates, speed of response, item nonresponse rates, internal consistency, and domain scores on the quality of life measures. RESULTS: Instrument ordering had no effect on questionnaire response rates or response speed. Only condition affected item nonresponse rates. Some ordering effects in respect of quality of life scores were observed, but these were inconsistent within and between conditions, and none of the differences were clinically significant. CONCLUSIONS: There is little effect of instrument ordering on responses to self-completed measures of quality of life. Further research is required to test whether this finding extends to other methods of administration.
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 | 0.009 | 0.159 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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