Implementing traumatic brain injury screening in behavioral healthcare: protocol for a prospective mixed methods study

Abstract

Background Characteristics of both individuals and innovations are foundational determinants to the adoption of evidenced-based practices (EBPs). However, our understanding about what drives EBP adoption is limited by few studies examining relationships among implementation determinants and implementation outcomes through theory-driven hypothesis testing. Therefore, drawing on the Theory of Planned Behavior and Diffusion of Innovations Theory, this study will disentangle relationships between provider characteristics and innovation factors on the early adoption of the Ohio State University Traumatic Brain Injury Identification Method (OSU TBI-ID) in behavioral health settings. Methods This study will utilize an explanatory sequential mixed methods design. In Phase I (quantitative), Time 1, we will investigate behavioral health providers (N = 200) attitudes, perceived behavioral control, subjective norms, and intentions to screen for TBI upon completion of a video module introducing the OSU TBI-ID. At Time 2, we will examine the number of TBI screens conducted over the previous month, as well as the feasibility, appropriateness, and acceptability of using the OSU TBI-ID in practice. Structural equation modeling will be used to determine whether provider characteristics predict TBI screening intentions, and whether intentions mediate actual TBI screening behaviors. We will then test whether feasibility, appropriateness, and acceptability of the OSU TBI-ID moderates the relationship between intentions and TBI screening behaviors. In Phase II (qualitative), we will develop an interview guide using results from Phase I and will conduct semi-structured interviews with providers (N = 20) to assess contextual determinants of TBI screening adoption. Qualitative data will be thematically analyzed using sensitizing concepts from the Consolidated Framework for Implementation Research and integrated with the quantitative results using a joint display. Discussion This mixed methods study capitalizes on two theory-driven hypotheses bridging proximal (e.g., screening intent) to distal (actual behaviors) implementation outcomes and will contextualize these results qualitatively to advance our understanding about why TBI screening adoption has failed to translate to the behavioral healthcare context. Results of this study will offer insights into what is driving TBI screening adoption so that implementation strategies can be selected with greater precision to improve the adoption, sustainment, and scale-up of TBI screening in behavioral healthcare.

Implementing traumatic brain injury screening in behavioral health treatment settings: results of an explanatory sequential mixed-methods investigation

“…Interventions that address complex physical and mental health comorbidities into behavioral healthcare contexts remain understudied in the implementation science literature [ 32 ]. This study begins to address this gap by illuminating some of the determinants that affect service integration for complex conditions in behavioral healthcare.…”

“…Another possible limitation is desirability bias, which is a potential explanation for discrepancy between some of the quantitative and qualitative results. Finally, because no standard measure exists for the TPB [ 90 ], we had to adapt our TPBQ-TBI measure from prior literature [ 32 ]. Although our CFA determined a strong measurement model, future studies are needed to establish a common measure for research applying this theory.…”

“…This was an explanatory sequential mixed-methods study (QUANT → qual) [ 33 , 34 ]. Details about this mixed-methods design and rationale are published elsewhere [ 32 ]. We use the Journal Article Reporting Standards for Mixed Methods Research for transparency of reporting our research (Supplemental file 1 ) [ 35 ].…”

“…In other words, providers who have more favorable attitudes toward screening for TBI, higher perceived control over TBI screening, and greater social pressures to screen for TBI will have greater intentions to screen and, ultimately, will be more likely to screen for TBI. The TPB has been widely used in other implementation science studies [ 26 , 27 , 29 – 31 ] to guide specification of relationships between proximal indicators (i.e., attitudes, PBC, subjective norms) and mediators (i.e., intentions) on distal implementation outcomes (i.e., EBP use) to help clarify where early-phase implementation succeeds or fails [ 32 ]. However, the extent to which each of these constructs affects EBP adoption is not universal, leading us to investigate the extent to which these provider-level characteristics affect TBI screening adoption so that implementation strategies can be more precisely selected and tailored to steer EBP uptake.…”

“…We present the first sequence of results from our published protocol aimed to investigate the adoption of the OSU TBI-ID in behavioral healthcare settings [ 32 ]. Specifically, the first aim of this study was to examine the relationships between behavioral health providers’ attitudes, PBC, and subjective norms as predictors to TBI screening intentions and to examine whether intentions to adopt TBI screening mediate TBI screening behaviors at a 1-month follow-up.…”