Consumer Risk Perceptions in Mobile Health Services Adoption: Do They Matter?
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
The purpose of this study is to investigate empirically the role of consumer perceived risks in the adoption of mobile health services. A theoretical model including the perceived risk associated with the activity targeted by a mobile health service and the perceived risk associated with the mobile service itself was developed and tested empirically in the context of an application supporting smoking cessation. The model was validated in a cross-sectional experiment conducted with 422 consumers in the UK and Canada. Findings show that while risk triggered by the nature of a health promotion activity is a strong driver of the adoption of the supporting mobile health service, risk related to the actual application targeting that activity is a comparatively weaker obstacle. The two contrasting risk perspectives are highly significant as they together explain over 31% of the variance in consumer intention to use the mobile health service, independently from other adoption factors. Overall, this study demonstrates that consumer risk perceptions alone are a multifaceted and meaningful component in mobile health services adoption, and that this element should not be overlooked in more complex research models.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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