Name
Title | ||
|---|---|---|
How reliable are self-assessments using mobile technology in healthcare? The effects of technology identity and self-efficacy. |
Abstract | ||
|---|---|---|
Traditionally in clinics or hospitals, it is the staff (physician, nurses, and so forth) who would check the patient's health status (e.g., blood pressure, height, weight, body temperature, and so forth). However, when mobile apps are used as the point of contact between patients and healthcare providers, the self-monitoring of health status will be exposed to biases due to being done by common people. Therefore ‘self-report reliability’ becomes an essential factor in the mobile healthcare context. Drawing on ‘technology identity’ and ‘technology self-efficacy’ literature, we theorized that perceived mobile technology identity directly affects self-report reliability, and perceived self-efficacy moderates the relationship between the two. A sample of patients from a clinic who completed a survey and self-reported their health status using a mobile health app was collected. The results of the analyses suggest that academic education affects the reliability of self-reports. In addition, patients aged 61 and above were more accurate in reporting their health status. Moreover, we found that self-efficacy improves the accuracy of self-reports and moderates the effect of mobile technology identity on self-report reliability. The findings of this paper contribute to the ongoing research around mobile healthcare application use and issues surrounding this phenomenon. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1016/j.chb.2018.09.024 | Computers in Human Behavior |
Keywords | Field | DocType |
Mobile healthcare,IT identity,Self-efficacy,Self-report reliability,Quantified self | Social psychology,Health care,Mobile technology,Psychology,Self-efficacy,Mobile apps,Applied psychology | Journal |
Volume | ISSN | Citations |
91 | 0747-5632 | 1 |
PageRank | References | Authors |
0.35 | 15 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Iris Reychav | 1 | 94 | 13.43 |
| Roni Beeri | 2 | 1 | 0.35 |
| Ali Balapour | 3 | 2 | 1.06 |
| Daphne Raban | 4 | 418 | 34.57 |
| R. Sabherwal | 5 | 248 | 17.33 |
| Joseph Azuri | 6 | 2 | 0.71 |