System Service Quality Factors and Their Impact on User Satisfaction and Continuance Intention to Use M-Health: The Moderating Influence of Monetary Cost
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
Mobile health (M-health) is widely recognized as a powerful technological driver for developing health systems.Service quality factors have been identified as critical indicators of user satisfaction and the intention to continue using M-health.However, the relationship between these factors varies across studies, leaving a research gap, particularly in the Middle Eastern region where limited studies have been conducted.This study aimed to investigate the impact of quality system factors on user satisfaction and the continuance intention to use Mhealth.A survey was conducted among 292 diabetes patients in the UAE.The results revealed that both interaction quality (ITQ) and system quality (SQ) significantly influenced user satisfaction and the intention to continue using M-health.In contrast, information quality (IFQ) had a significant impact on user satisfaction but not on continuance intention.Additionally, the study found that the relationship between user satisfaction and the intention to continue using M-health was moderated by monetary cost.These findings extend the information system model by offering new insights into the role of the IS success model in predicting Mhealth continuance intention.
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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 | 0.002 | 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 | 0.001 |
| 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 it