BackgroundAcceptability of digital mental health interventions is a significant predictor of treatment-seeking behavior and engagement. However, acceptability has been conceptualized and operationalized in various ways, which decreases measurement precision and leads to heterogeneous conclusions aboutacceptability. Standardized self-report measures of acceptability have been developed, which have the potential to ameliorate these problems, but none have demonstrated evidence for validation among Black communities, which limits our understanding of attitudes toward these interventions among racially minoritized groups with well-documented barriers to mental health treatment.ObjectiveThis study aims to examine the psychometric validity and reliability of one of the first and most widely used measures of acceptability, the Attitudes Towards Psychological Online Interventions Questionnaire, among a Black American sample.MethodsParticipants (N=254) were recruited from a large southeastern university and the surrounding metropolitan area and completed the self-report measure via a web-based survey. A confirmatory factor analysis using mean and variance adjusted weighted least squares estimation was conducted to examine the validity of the underlying hierarchical 4-factor structure proposed by the original authors of the scale. An alternative, hierarchical 2-factor structure model and bifactor model were examined for comparative fit.ResultsThe findings indicated that the bifactor model demonstrated a superior fit (comparative fit index=0.96, Tucker-Lewis index=0.94, standardized root mean squared residual=0.03, and root mean square error of approximation=0.09) compared with both 2- and 4-factor hierarchical structure models.ConclusionsThe findings suggest that, within a Black American sample, there may be greater utility in interpreting the Attitudes Towards Psychological Online Interventions Questionnaire subscales as attitudinal constructs that are distinct from the globalacceptabilityfactor. The theoretical and practical implications for culturally responsive measurements were explored.