The Psychometric Properties of The Revised-Depression Attitude Questionnaire Among Primary Healthcare Physicians in Oman
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Abstract
Objective: The revised-depression attitude questionnaire (R-DAQ) is one of the most widely used instruments to evaluate the attitudes of healthcare workers toward depression. This study aimed to assess the psychometric properties of the R-DAQ and validate its use among primary healthcare physicians in Oman.
Materials and Methods: This assessment is part of a cross-sectional study conducted using the R-DAQ distributed as a self-administered online questionnaire to a convenient sample of primary healthcare physicians working under the Ministry of Health in 2022 to evaluate their attitudes toward depression. The exploratory factor analysis was conducted using two types of software to assess the robustness of the factor solution based on different correlation matrices and across different extraction methods. Further evaluation of the factor solution was verified by computing different indices, assessing internal replicability, and known-group validity.
Results: The analyses resulted in a 16-item scale summarized by a three-factor solution. The first factor was saliently loaded by six items representing "the professional confidence in providing care for people with depression”. The second factor was saliently loaded by six items representing “the optimistic view on recognizing depression as a health condition”. The third factor was saliently loaded by four items representing “the general perspective on integrating depression care into health practice”. Overall, the total three-factor solution demonstrated internal consistency, simplicity, goodness-of-fit, and internal replicability, as well as known-group validity.
Conclusion: The validation of using the R-DAQ among primary healthcare physicians in Oman uncovered a three-factor solution with adequate psychometric properties. In addition, the factor solution was conceptually consistent with the theoretical model of planned behavior.
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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Accepted 2023-12-26
Published 2024-01-01
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