Open Access
Assessing Patient Attitudes to Computerized Screening in Primary Care: Psychometric Properties of the Computerized Lifestyle Assessment Scale
Author(s) -
Farah Ahmad,
Sheilah HoggJohnson,
Harvey A. Skinner
Publication year - 2008
Publication title -
jmir. journal of medical internet research/journal of medical internet research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.446
H-Index - 142
eISSN - 1439-4456
pISSN - 1438-8871
DOI - 10.2196/jmir.955
Subject(s) - intraclass correlation , scale (ratio) , construct validity , reliability (semiconductor) , popularity , psychology , medicine , psychometrics , clinical psychology , construct (python library) , family medicine , social psychology , computer science , physics , quantum mechanics , power (physics) , programming language
Background Computer-based health-risk assessments are electronic surveys which can be completed by patients privately, for example during their waiting time in a clinic, generating a risk report for the clinician and a recommendation sheet for the patient at the point of care. Despite increasing popularity of such computer-based health-risk assessments, patient attitudes toward such tools are rarely evaluated by reliable and valid scales. The lack of psychometric appraisal of appropriate scales is an obstacle to advancing the field. Objective This study evaluated the psychometric properties of a 14-item Computerized Lifestyle Assessment Scale (CLAS). Methods Out of 212 female patients receiving the study information at a family practice clinic, 202 completed a paper questionnaire, for a response rate of 97.6%. After 2 weeks, 52 patients completed the scale a second time. Results Principal component analysis revealed that CLAS is a multidimensional scale consisting of four subscales (factors): (1) Benefits: patient-perceived benefits toward the quality of medical consultation and means of achieving them, (2) Privacy-Barrier: concerns about information privacy, (3) Interaction-Barrier: concerns about potential interference in their interaction with the physician, and (4) Interest: patient interest in computer-assisted health assessments. Each subscale had good internal consistency reliability ranging from .50 (2-item scale) to .85 (6-item scale). The study also provided evidence of scale stability over time with intraclass correlation coefficients of .91, .82, .86, and .67 for the four subscales, respectively. Construct validity was supported by concurrent hypotheses testing. Conclusions The CLAS is a promising approach for evaluating patients’ attitudes toward computer-based health-risk assessments.