BACKGROUND

The Opening Minds Stigma Scale for Health Care Providers (OMS-HC) is a widely used questionnaire to measure the stigmatising attitudes of healthcare providers towards patients with mental health problems. The psychometric properties of the scale; however, have never been investigated in Hungary. We aimed to thoroughly explore the factor structure of the OMS-HC and examine the key psychometric properties of the Hungarian version.

METHODS

The OMS-HC is a self-report questionnaire that measures the overall stigmatising attitude by a total score, and three subscales can be calculated: Attitude, Disclosure and Help-seeking, and Social Distance. Our study population included specialists and trainees in adult and child psychiatry (n = 211). Exploratory and confirmatory factor analyses were performed, and higher-order factors were tested. We calculated the test-retest reliability on a subgroup of our sample (n = 31) with a follow-up period of 1 month. The concurrent validity of the scale was measured with the Mental Illness: Clinician's Attitudes-4 scale (MICA-4).

RESULTS

Three factors were extracted based on a parallel-analysis. A bifactor solution (a general factor and three specific factors) showed an excellent model-fit (root mean square error of approximation = 0.025, comparative fit index = 0.961, and Tucker-Lewis index = 0.944). The model-based reliability was low; however, the general factor showed acceptable reliability (coefficient omega hierarchical = 0.56). The scale demonstrated a good concurrent validity with the MICA-4 [intraclass correlation coefficient (ICC) = 0.77]. The test-retest reliability was excellent for the general factor (ICC = 0.95) and good for the specific factors (ICC = 0.90, 0.88, and 0.84, respectively).

CONCLUSIONS

The three dimensions of the OMS-HC was confirmed, and the scale was found to be an adequate measure of the stigmatising attitude in Hungary. The bifactor model is more favourable as compared to the three correlated factor model; however, despite the excellent internal structure, its model-based reliability was low.