Internet-administered Health-related Quality of Life Questionnaires Compared With Pen and Paper in an Adolescent Scoliosis Population: A Randomized Crossover Study
Bibliographic record
Abstract
BACKGROUND: Modern technology puts into question the effectiveness of using pen and paper as a means of collecting information from web-enabled patients. This study aimed to validate and test the reliability of using the Internet as a method of administering health-related quality of life questionnaires in a pediatric spine population. METHODS: A prospective randomized crossover study was conducted. Patients aged 11 to 18 with idiopathic scoliosis were invited to participate, and informed consent was obtained from a scoliosis outpatient clinic setting. Participants were randomized to one of 4 groups determining the method of questionnaire administration [Scoliosis Research Society 30 (SRS-30) and Pediatric Outcomes Data Collection Instrument (PODCI)]. Both questionnaires were completed at 2 separate timepoints and 2 weeks apart to prevent recall bias. Groups included: Paper/Paper, Paper/Internet, Internet/Paper, and Internet/Internet. Paired-samples t tests were used to determine the test-retest reliability of each group. Analysis was stratified for surveys returned within or outside of the allotted 4-week timeframe following enrollment. RESULTS: Of the 96 participants who completed and returned both sets of questionnaires, 26 were allocated to the Paper/Paper group (27%), 20 to the Paper/Internet group (21%), 26 to the Internet/Paper group (27%), and 24 to the Internet/Internet group (25%). The second iteration of questionnaires was returned on time by 69 of the participants (71.2%). Of the late questionnaires, 18 (67%) were paper forms. Overall, no differences were observed between Internet-administered compared with pen and paper-administered questionnaires (P=0.206). No differences were observed within any group individually for either the SRS-30 or PODCI questionnaire. In addition, no significant differences were observed within groups for surveys returned within or outside of the 4-week timeframe. Eighty-four percent of the participants who completed both paper and Internet versions of the questionnaires reported a preference of the Internet. CONCLUSION: Internet administration of both the SRS-30 and PODCI questionnaires is a valid and reliable method of acquiring health-related quality of life information in this population LEVEL OF EVIDENCE:: Level II-therapeutic study.
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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 | 0.011 | 0.010 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".