# Establishing an empirical cut-off on the 12-item Brief Berger HIV Stigma Scale to screen psychosocial vulnerability among PLHIV in Nigeria

## TL;DR

This study establishes a cut-off score for a stigma scale to identify people living with HIV in Nigeria who are at risk for mental health issues.

## Contribution

The paper introduces a data-driven cut-off score for the Brief Berger HIV Stigma Scale in a Nigerian context.

## Key findings

- A cut-off score of ≥30 on the scale has high sensitivity and negative predictive value for identifying psychosocial vulnerability.
- Public attitude concerns are the strongest predictor of psychosocial vulnerability among people living with HIV.
- The scale's optimal cut-off provides a practical tool for mental health screening in resource-limited settings.

## Abstract

This study addresses a key challenge in HIV care the lack of a validated screening tool for psychosocial vulnerability. Although the 12-item Brief Berger HIV Stigma Scale is widely used, no clear threshold exists to identify individuals at high risk for mental health problems. Our research aimed to establish a practical, data-driven cut-off score for the scale in a Nigerian context and to explore which dimensions of stigma are most linked to psychosocial vulnerability. We conducted a cross-sectional study of 285 people living with HIV (PLHIV) at three tertiary centres (May–August 2024). Psychosocial vulnerability was defined as moderate-to-severe depression (Patient Health Questionnaire-9  ≥ 10) or anxiety (Generalised Anxiety Disorder-7 ≥ 10). The Receiver Operating Characteristic (ROC) analysis with the Youden Index identified the optimal cut-off; multivariable logistic regression examined independent associations of stigma subscales with vulnerability. Among 285 participants (mean age 47.1 ± 11.17 years, 72.6% female), 44.9% met vulnerability criteria. The Berger Scale demonstrated acceptable discrimination (AUC = 0.717, 95% CI 0.658–0.777). A cut-off of ≥30 yielded high sensitivity (87.5%) and strong negative predictive value (82.8%). Internal validation confirmed stability (cross-validated AUC 0.703, bootstrap AUC 0.701). Decision curve analysis showed positive net benefit over “screen-none” up to threshold probability 0.45, with peak benefit at 0.30. In multivariable analysis, public attitude concerns were the strongest predictor (adjusted OR 1.68, p < 0.001), while disclosure concerns—despite near-universal prevalence (96.1%)—showed no independent association. The ≥ 30 cut-off provides a practical, sensitive rule-out tool for identifying PLHIV needing psychosocial assessment in resource-limited settings. External validation is essential before widespread adoption. Public attitude concerns outweighing internalised stigma highlights the need for culturally informed interventions addressing societal stigma alongside mental health support.