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Assessing patient attitudes to computerized screening in primary care: psychometric properties of the computerized
Farah Ahmad1, Sheilah Hogg-Johnson, Harvey A Skinner
1Centre for Research on Inner City Health, St. Michael's Hospital, 30 Bond Street, Toronto, ON M5B 1W8, Canada. ahmadf@smh.toronto.on.ca
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.
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