Implementation drivers scale: a new implementation measure to reduce mental health gaps
Implementation drivers scale: a new implementation measure to reduce mental health gaps

Implementation drivers scale: a new implementation measure to reduce mental health gaps

Prim Health Care Res Dev. 2025 Jul 15;26:e57. doi: 10.1017/S146342362510025X.

ABSTRACT

AIM: The objectives of this study were to study the psychometric properties of the Implementation Drivers Scale (IDS), for the mhGAP programme, both clinical and community; to test its structural validity, and to propose an instrument to accompany the implementation of the mhGAP in similar contexts. For this purpose, a cross-sectional quantitative methodology study was conducted.

BACKGROUND: Mental health programmes proposed in low- and middle-income countries to address gaps in care have implementation problems.

METHODS: A cross-sectional quantitative methodology study was conducted. During 2022 and 2023, the instrument was administered to 204 individuals, including primary care professionals (50%), national administrative leaders (19.11%), and community strategy leaders. Three departments of Colombia participated, two with low levels of implementation in mental health programmes and one with high levels of implementation of programmes and services.

FINDINGS: The Kaiser-Meyer-Olkin factor analysis resulted in 0.861, which indicated the suitability of the data for a factor analysis. Bartlett’s Test of Sphericity had a value of 2480.907 (153 degrees of freedom, p <.001). The exploratory factor analysis explained variance of 66.781%. The four factors proposed in the AIF model (System enablers for implementation, Accessibility of the strategy, Adaptability and acceptability, and Strategy training and supervision) were confirmed, with all items with loadings greater than 0.4. For the entire instrument, a Cronbach’s alpha was 0.907. The IDS could contribute to the monitoring of some components of mhGAP implementation, both clinical and community-based, in low- and middle-income settings through appropriate validation processes.

PMID:40660904 | DOI:10.1017/S146342362510025X