A comparison of a tablet version of the Quality of Life Systemic Inventory for Children (QLSI-C) to the standard paper version.
Bibliographic record
Abstract
Integration of e-Health technologies for purposes of both assessment and intervention has recently become an interest area in pediatric psychology. The purpose of this study is to present psychometric characteristics of a technology-based (i.e., tablet administration) approach for measuring quality of life (QOL) in children. Eighty children (8-12 years) completed the Quality of Life Systemic Inventory for Children (QLSI-C) twice over a 2-week delay, in a crossover design that used paper and tablet-based modes of administration. Equivalence of scores across methods was examined using intraclass correlation coefficients (ICC), augmented by paired t test and Pearson's correlations. Test-retest reliability was assessed using paired t test and Pearson's correlations while internal consistency was assessed using Cronbach's coefficient. Results showed a good concordance across methods of administration (ICCs = .72 to .91; r = .56 to .83). Paired t test showed no significant differences between the tablet and paper version of the QLSI-C. Internal consistency reliability yielded acceptable Cronbach's alphas for all QLSI-C scores, with all α > .70. Test-retest reliability for the tablet-administered QLSI-C was good (r = .66 to .90). Paired t test showed no significant difference between Time 1 and 2 for the QLSI-C scores, except for the state score. Findings established the reliability of the tablet-administered QLSI-C scores. This technology approach to assessment is more attractive for children, decreases time for administration, and enhances the ease of scoring. These advantages might encourage both clinicians and researchers to consider using e-Health developments in assessment in pediatric psychology. (PsycINFO Database Record
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".