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Validation of a brief mental health screening tool for common mental disorders in primary healthcare.

ABSTRACT: 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.

SUBMITTER: Bhana A

PROVIDER: S-EPMC7029170 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature

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Validation of a brief mental health screening tool for common mental disorders in primary healthcare.

Bhana A A Mntambo N N Gigaba S G SG Luvuno Z P B ZPB Grant M M Ackerman D D Ntswe E E Nomathemba M M Petersen I I

South African medical journal = Suid-Afrikaanse tydskrif vir geneeskunde 20190329 4

<h4>Background</h4>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.<h4>Objectives</h4>To establish ...[more]

PMID: 31084695

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Project description:Background: Web-based and mobile mental health applications for the prevention and treatment of common mental disorders (CMDs) are on the rise. Under certain circumstances they have proved to be effective for a range of conditions (e.g., depression). Objective: There is not sufficient evidence regarding the benefits and barriers especially for mobile phone apps and for programs in the field of primary prevention. Studies on the acceptance of potential users of mental health apps yielded mixed outcomes. In a large survey we investigated the attitudes of employees toward mental health apps and various traditional mental health services. Our main research question in this contribution focuses on the acceptance of apps compared to other measures and the moderating influence of individual characteristics. Methods: The standardized survey was completed by members of an online access panel with different job types. A set of 33 self-developed items, including three questions on e-health, captured the perceived relevance of prevention at the (A) occupational, (B) individual, and (C) societal level. On the basis of an exploratory factor analysis, mean scores for mapping seven (sub-)dimensions were constructed and compared using the Wilcoxon test. The influence of potential predictors was analyzed in linear regression models. Results: The data of 610 respondents were analyzed (response rate 75%). Support from mental health applications was rated significantly less important compared to all other dimensions at the levels (A) to (C). Respondents were more likely to use mental health apps if they felt literate with electronic devices, perceived a high relevance of work-related demands as causal factors for CMDs, stated they would be ashamed of having a CMD, and would be willing to begin psychotherapy if recommended. Discussion and Conclusions: The results confirm the critical attitudes of potential mental health app users found in other studies. Since users with a negative attitude toward e-health might have a higher risk for dropout and non-adherence as well as lower intervention effects, well-designed educational strategies should be carried out beforehand.

Project description:BACKGROUND:Mental health (MH) problems have considerable personal and societal implications. Systematic MH screening may raise general practitioners' (GP) awareness of the current need of treatment in their listed patients. The focus of MH screening has so far been on increasing diagnostic rates and treatment of mental disorders, whereas cessation of MH treatment after normal test results has rarely been studied. This study aims to examine the mental healthcare trajectories after MH screening combined with feedback on both positive and negative screening results to the GP. METHODS:This prospective cohort study is based on data from 11,714 randomly selected individuals aged 30-49?years, who were invited to a preventive health check in Denmark during 2012-2015. A total of 5970 (51%) were included. MH status was assessed using the SF-12 Health Survey Mental Component Summary score, and scores were categorised into poor, moderate, and good MH. 'Mental healthcare' within 1 year of follow-up covered the following MH support: psychometric testing by GP, talk therapy by GP, contact to psychologist, contact to psychiatrist, and psychotropic medication. RESULTS:MH was found to be poor in 9%, moderate in 25%, and good in 66% of participants. After 1 year, mental healthcare was initiated in 29% of the participants with poor MH who did not receive mental healthcare at baseline, and mental healthcare was ceased in 44% of the participants with good MH who received mental healthcare at baseline. Odds ratio (OR) for initiation of mental healthcare was associated with worse MH screening status: poor MH: OR 7.1 (5.4-9.4), moderate MH: OR 2.4 (1.9-3.1), compared to those with good MH. OR for cessation of mental healthcare was associated with better MH screening status: good MH: OR 1.6 (1.1-2.6), moderate MH: OR 1.6 (1.0-2.4), compared to those with poor MH. Initiation and cessation of mental healthcare appeared to be time-related to the MH screening. CONCLUSIONS:MH screening combined with feedback on both positive and negative screening results to the GP may contribute to relevant initiation and cessation of mental healthcare. TRIAL REGISTRATION:Registration of the Check Your Health-trial: ClinicalTrials.gov ( NCT02028195 ), 7 March 2014.

Project description:BackgroundAs populations age with increasingly complex chronic conditions, segmenting populations into clinically meaningful categories of healthcare and related service needs can provide healthcare planners with crucial information to optimally meet needs. However, while conventional approaches typically involve electronic medical records (EMRs), such records do not always capture information reliably or accurately.ObjectiveWe describe the inter-rater reliability and predictive validity of a clinician-administered tool, the Simple Segmentation Tool (SST) for categorizing older individuals into one of six Global Impression (GI) segments and eight complicating factors (CFs) indicative of healthcare and related social needs.DesignObservational study ( ClinicalTrials.gov , number NCT02663037).ParticipantsPatients aged 55 years and above.Main measuresEmergency department (ED) subjects (between May and June 2016) had baseline SST assessment by two physicians and a nurse concurrently seeing the same individual. General medical (GM) ward subjects (February 2017) had a SST assessment by their principal physician. Adverse events (ED visits, hospitalizations, and mortality over 90 days from baseline) were determined by a blinded reviewer. Inter-rater reliability was measured using Cohen's kappa. Predictive validity was evaluated using Cox hazard ratios based on time to first adverse event.Key resultsCohen's kappa between physician-physician, service physician-nurse, and physician-nurse pairs for GI were 0.60, 0.71, and 0.68, respectively. Cox analyses demonstrated significant predictive validity of GI and CFs for adverse outcomes.ConclusionsWith modest training, clinicians can complete a brief instrument to segment their patient into clinically meaningful categories of healthcare and related service needs. This approach can complement and overcome current limitations of EMR-based instruments, particularly with respect to whole-patient care.Trial registrationClinicalTrials.gov Identifier: NCT02663037.

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Validation of a brief mental health screening tool for common mental disorders in primary healthcare.

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Validation of a brief mental health screening tool for common mental disorders in primary healthcare.

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