How reliable are self-assessments using mobile technology in healthcare? The effects of technology identity and self-efficacy

Iris Reychav, Roni Beeri, Ali Balapour, Daphne Ruth Raban, Rajiv Sabherwal, Joseph Azuri

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
Pages (from-to)52-61
Number of pages10
JournalComputers in Human Behavior
Volume91
DOIs
StatePublished - Feb 2019

Bibliographical note

Publisher Copyright:
© 2018 Elsevier Ltd

Keywords

  • IT identity
  • Mobile healthcare
  • Quantified self
  • Self-efficacy
  • Self-report reliability

ASJC Scopus subject areas

  • Arts and Humanities (miscellaneous)
  • Human-Computer Interaction
  • Psychology (all)

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