Perinatal depression screening and intervention: enhancing health provider involvement

Abstract

Objective: The authors of this study collaborated in the analysis of public health survey data in order to inform future statewide interventions that could systematically enhance depression screening and mental health service use for women of reproductive age. The primary objective of the study was to empirically inform and test the program theory components of a motivational interviewing intervention that we anticipate will guide statewide practice and policy priorities.

Methods: Data were examined from a survey of healthcare practitioners statewide (n=1498) regarding their practices with and perceptions of perinatal depression care for women. Confirmatory factor analysis (CFA) was used to measure two latent constructs: health provider confidence in the ability to diagnose and treat and the importance placed on screening and treatment. Structural equation modeling (SEM) was used to test a program theory supporting motivational interviewing using a model implied relationship between confidence and importance on screening and treatment/referral practices.

Results: The data fit the model; the model provisionally supports motivational interviewing as an intervention influencing provider attitudes and practices surrounding perinatal depression screening and treatment/referral.

Conclusions: Ultimately, study findings support statewide public health efforts to expand the role of health providers in recognizing and responding to perinatal depression and suggest that motivational interviewing techniques that augment importance and confidence may lead to enhanced screening and referral/treatment outcomes for pregnant and postpartum women.

FIG. 1.

Confirmatory factor analysis (CFA) models for latent variables (standardized factor loadings).

FIG. 2.

Program theory structural equation model: Motivational interviewing components informing key outcomes (standardized factor loadings and parameter estimates). RMSEA, Root Mean Square Error of Approximation; CFI, Comparative Fit Index; TLI, Tucker-Lewis Index.