Development of a Video Consultation Patient-Satisfaction Questionnaire (vCare-PSQ): A Cross-Sectional Explorative Study
Bibliographic record
Abstract
BACKGROUND: Since the COVID-19 pandemic, the use of video consultation (VC) in primary care has expanded considerably in many countries. VC and other telehealth formats are often touted as a solution to improved health care access, with numerous studies showing high satisfaction with this care format among health professionals and patients. However, operationalization and measurement of patient satisfaction with VC varies across studies and often lacks consideration of dynamic contextual factors (eg, convenience, ease-of-use, or privacy) and doctor-patient relational variables that may influence patient satisfaction. OBJECTIVE: We aim to develop a comprehensive and evidence-based questionnaire for assessing patient satisfaction with VC in general practice. METHODS: The vCare Patient-Satisfaction Questionnaire (the vCare-PSQ) was developed according to the COSMIN (Consensus-Based Standards for the Selection of Health Measurement Instruments) guidelines. To achieve our overall objective, we pursued three aims: (1) a validation analysis of an existing patient-satisfaction scale (the PS-14), (2) an assessment of extrinsic contextual factors that may impact patient satisfaction, and (3) an assessment of pertinent intrinsic and relational satisfaction correlates (eg, health anxiety, information technology literacy, trust in the general practitioner, or convenience). For validation purposes, the questionnaire was filled out by a convenience sample of 188 Danish adults who had attended at least 1 VC. RESULTS: Our validation analysis of the PS-14 in a Danish population produced reliable results, indicating that the PS-14 is an appropriate measure of patient satisfaction with VC in Danish patient populations. Regressing situational and doctor-patient relational factors onto patient satisfaction further suggested that patient satisfaction is contingent on several factors not measured by the PS-14. These include information technology literacy and patient trust in the general practitioner, as well as several contextual pros and cons. CONCLUSIONS: Supplementing the PS-14 with dynamic measures of situational and doctor-patient relational factors may provide a more comprehensive understanding of patient satisfaction with VC. The vCare-PSQ may thus contribute to an enhanced methodological approach to assessing patient satisfaction with VC. We hope that the vCare-PSQ format may be useful for future research and implementation efforts regarding VC in a general practice setting.
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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 | 0.009 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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 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".