Evaluating the Development, Reliability, and Validation of the Tele-Primary Care Oral Health Clinical Information System Questionnaire: Cross-Sectional Questionnaire Study
Bibliographic record
Abstract
BACKGROUND: Evaluating digital health service delivery in primary health care requires a validated questionnaire to comprehensively assess users' ability to implement tasks customized to the program's needs. OBJECTIVE: This study aimed to develop, test the reliability of, and validate the Tele-Primary Care Oral Health Clinical Information System (TPC-OHCIS) questionnaire for evaluating the implementation of maternal and child digital health information systems. METHODS: A cross-sectional study was conducted in 2 phases. The first phase focused on content item development and was validated by a group of 10 experts using the content validity index. The second phase was to assess its psychometric testing for reliability and validity. RESULTS: A structured questionnaire of 65 items was constructed to assess the TPC-OHCIS delivery for primary health care use based on literature and has been validated by 10 experts, and 319 respondents answered the 65-item TPC-OHCIS questionnaire, with mean item scores ranging from 1.99 (SD 0.67) to 2.85 (SD 1.019). The content validity, reliability, and face validity showed a scale-level content validity index of 0.90, scale-level content validation ratio of 0.90, and item-level face validity index of 0.76, respectively. The internal reliability was calculated as a Cronbach α value of 0.90, with an intraclass correlation coefficient of 0.91. Scales were determined by the scree plot with eigenvalues >1, and 13 subscales were identified based on principal component analysis. The Kaiser-Meyer-Olkin value was 0.90 (P<.049). The total variance explained was 76.07%, and factor loading scores for all variables were >0.7. The Bartlett test of sphericity, determining construct validity, was found to be significant (P<.049). CONCLUSIONS: The TPC-OHCIS questionnaire is valid to be used at the primary health care level to evaluate the TPC-OHCIS implementation. It can assess health care workers' work performance and job acceptance and improve the quality of care.
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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 | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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".