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Background. Integrating care for common mental disorders (CMDs) such as depression, anxiety and alcohol abuse into primary healthcare (PHC) should assist in reducing South Africa (SA)’s quadruple burden of disease. CMDs compromise treatment adherence, health behaviour change and self-management of illnesses. Appropriate identification of mental disorders in primary care can be facilitated by brief, easy-to-administer screening that promotes high specificity.Objectives. To establish the criterion-based validity of a seven-item Brief Mental Health (BMH) screening tool for assessing positive symptoms of CMDs in primary care patients.Methods. A total of 1 214 participants were recruited from all patients aged ≥18 years visiting 10 clinics as part of routine care in the Newcastle subdistrict of Amajuba District in KwaZulu-Natal Province, SA, over a period of 2 weeks. Consenting patients provided basic biographical information prior to screening with the BMH tool. PHC nurses remained blind to this assessment. PHC nurse-initiated assessment using the Adult Primary Care (APC) guidelines was the gold standard against which the performance of the BMH tool was compared. A specificity standard of 80% was used to establish cut-points. Specificity was favoured over sensitivity to ensure that those who did not have CMD symptoms were excluded, as well as to reduce over-referrals.Results. Of the participants, 72% were female. The AUD-C (alcohol abuse) performed well (area under the curve (AUC) 0.91 (95% confidence interval (CI) 0.88 - 0.95), cut-point ≥4, Cronbach alpha 0.87); PHQ-2 (depression) performed reasonably well (AUC 0.72 (95% CI 0.65 - 0.78), cut-point ≥3, alpha 0.71); and GAD-2 (anxiety) performance was acceptable (AUC 0.69 (95% CI 0.58 - 0.80), cut-point ≥3, alpha 0.62). Using the higher cut-off scores, patients who truly did not have CMD symptoms had negative predictive values (NPVs) of >90%. Overall, 26% of patients had CMD positive symptoms relative to 8% using the APC guidelines.Conclusions. Using a higher specificity index, the positive predictive value and NPV show that at higher cut-point values the BMH not only helps identify individuals with alcohol misuse, depression and anxiety symptoms but also identifies a majority of those who do not have symptoms (true negatives), thus not overburdening nurses with false positives needing assessment. Research is needed to assess whether use of such a short and valid screening tool is generalisable to other clinic contexts as well as how mental health screening should best be introduced into routine clinic functioning and practice.Â

Background: Integrating care for common mental disorders (CMDs) such as depression, anxiety and alcohol abuse into primary healthcare (PHC) should assist in reducing South Africa (SA)'s quadruple burden of disease. CMDs compromise treatment adherence, health behaviour change and self-management of illnesses. Appropriate identification of mental disorders in primary care can be facilitated by brief, easy-to-administer screening that promotes high specificity., Objectives: To establish the criterion-based validity of a seven-item Brief Mental Health (BMH) screening tool for assessing positive symptoms of CMDs in primary care patients., Methods: A total of 1 214 participants were recruited from all patients aged ≥18 years visiting 10 clinics as part of routine care in the Newcastle subdistrict of Amajuba District in KwaZulu-Natal Province, SA, over a period of 2 weeks. Consenting patients provided basic biographical information prior to screening with the BMH tool. PHC nurses remained blind to this assessment. PHC nurse-initiated assessment using the Adult Primary Care (APC) guidelines was the gold standard against which the performance of the BMH tool was compared. A specificity standard of 80% was used to establish cut-points. Specificity was favoured over sensitivity to ensure that those who did not have CMD symptoms were excluded, as well as to reduce over-referrals., Results: Of the participants, 72% were female. The AUD-C (alcohol abuse) performed well (area under the curve (AUC) 0.91 (95% confidence interval (CI) 0.88 - 0.95), cut-point ≥4, Cronbach alpha 0.87); PHQ-2 (depression) performed reasonably well (AUC 0.72 (95% CI 0.65 - 0.78), cut-point ≥3, alpha 0.71); and GAD-2 (anxiety) performance was acceptable (AUC 0.69 (95% CI 0.58 - 0.80), cut-point ≥3, alpha 0.62). Using the higher cut-off scores, patients who truly did not have CMD symptoms had negative predictive values (NPVs) of >90%. Overall, 26% of patients had CMD positive symptoms relative to 8% using the APC guidelines., Conclusions: Using a higher specificity index, the positive predictive value and NPV show that at higher cut-point values the BMH not only helps identify individuals with alcohol misuse, depression and anxiety symptoms but also identifies a majority of those who do not have symptoms (true negatives), thus not overburdening nurses with false positives needing assessment. Research is needed to assess whether use of such a short and valid screening tool is generalisable to other clinic contexts as well as how mental health screening should best be introduced into routine clinic functioning and practice.