Healthcare professional acceptance of telemonitoring for chronic care patients in primary care
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: A pilot experimentation of a telemonitoring system for chronic care patients is conducted in the Bilbao Primary Care Health Region (Basque Country, Spain). It seems important to understand the factors related to healthcare professionals' acceptance of this new technology in order to inform its extension to the whole healthcare system.This study aims to examine the psychosocial factors related to telemonitoring acceptance among healthcare professionals and to apply a theory-based instrument. METHODS: A validated questionnaire, based on an extension of the Technology Acceptance Model (TAM), was distributed to a total of 605 nurses, general practitioners and paediatricians. Logistic regression analysis was performed to test the theoretical model. Adjusted odds ratios (OR) and their 95% confidence intervals (CI) were computed. RESULTS: A response rate of 44.3% was achieved. The original TAM model was good at predicting intention to use the telemonitoring system. However, the extended model, that included other theoretical variables, was more powerful. Perceived Usefulness, Compatibility, and Facilitators were the significant predictors of intention. A detailed analysis showed that intention to use telemonitoring was best predicted by healthcare professionals' beliefs that they would obtain adequate training and technical support and that telemonitoring would require important changes in their practice. CONCLUSION: The extended TAM explained a significant portion of the variance in healthcare professionals' intention to use a telemonitoring system for chronic care patients in primary care. The perception of facilitators in the organisational context is the most important variable to consider for increasing healthcare professionals' intention to use the new technology.
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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 | 0.000 | 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 | 0.000 | 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 it