Technology-delivered adaptations of motivational interviewing for the prevention and management of chronic diseases: Scoping review

BACKGROUND: Motivational interviewing (MI) can increase health-promoting behaviors and decrease health-damaging behaviors. However, MI is often resource intensive, precluding its use with people with limited financial or time resources. Mobile health-based versions of MI interventions or technology-delivered adaptations of MI (TAMIs) might increase reach. OBJECTIVE: We aimed to understand the characteristics of existing TAMIs. We were particularly interested in the inclusion of people from marginalized sociodemographic groups, whether the TAMI addressed sociocontextual factors, and how behavioral and health outcomes were reported. METHODS: We employed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines for scoping reviews to conduct our scoping review. We searched PubMed, CINAHL, and PsycInfo from January 1, 1996, to April 6, 2022, to identify studies that described interventions incorporating MI into a mobile or electronic health platform. For inclusion, the study was required to (1) describe methods/outcomes of an MI intervention, (2) feature an intervention delivered automatically via a mobile or electronic health platform, and (3) report a behavioral or health outcome. The exclusion criteria were (1) publication in a language other than English and (2) description of only in-person intervention delivery (ie, no TAMI). We charted results using Excel (Microsoft Corp). RESULTS: Thirty-four studies reported the use of TAMIs. Sample sizes ranged from 10 to 2069 participants aged 13 to 70 years. Most studies (n=27) directed interventions toward individuals engaging in behaviors that increased chronic disease risk. Most studies (n=22) oversampled individuals from marginalized sociodemographic groups, but few (n=3) were designed specifically with marginalized groups in mind. TAMIs used text messaging (n=8), web-based intervention (n=22), app + text messaging (n=1), and web-based intervention + text messaging (n=3) as delivery platforms. Of the 34 studies, 30 (88%) were randomized controlled trials reporting behavioral and health-related outcomes, 23 of which reported statistically significant improvements in targeted behaviors with TAMI use. TAMIs improved targeted health behaviors in the remaining 4 studies. Moreover, 11 (32%) studies assessed TAMI feasibility, acceptability, or satisfaction, and all rated TAMIs highly in this regard. Among 20 studies with a disproportionately high number of people from marginalized racial or ethnic groups compared with the general US population, 16 (80%) reported increased engagement in health behaviors or better health outcomes. However, no TAMIs included elements that addressed sociocontextual influences on behavior or health outcomes. CONCLUSIONS: Our findings suggest that TAMIs may improve some health promotion and disease management behaviors. However, few TAMIs were designed specifically for people from marginalized sociodemographic groups, and none included elements to help address sociocontextual challenges. Research is needed to determine how TAMIs affect individual health outcomes and how to incorporate elements that address sociocontextual factors, and to identify the best practices for implementing TAMIs into clinical practice

Meeting the Needs of Emerging Adults With Type 1 Diabetes Living in a Rural Area With Mobile Health Interventions: Focus Group Study

BackgroundEmerging adults (EAs; age 18-30 years) with type 1 diabetes (T1D) have more challenges with diabetes management and glycemic control than other age groups. Living in a rural community introduces additional unique diabetes care challenges due to limited access to specialty care and ancillary support services. Yet, few interventions have been developed to improve diabetes management in rural-dwelling EAs with T1D. ObjectiveThis study aimed to understand the diabetes management experiences of older adolescents and EAs (age 16-25 years) with T1D living in a rural area and to assess their perceptions of the acceptability of 4 fully automated mobile health (mHealth) interventions to support diabetes management. MethodsEAs were identified by clinical staff through convenience sampling. In total, 8 EAs participated in 1 focus group and 1 EA completed an individual interview; all data were collected over Zoom. Facilitators explored EAs’ experiences living in a rural community with T1D and discussed EAs’ impressions of, feedback on, and recommendations for improving 4 mHealth interventions to meet the specific needs of EAs with T1D living in rural communities. Discussions were transcribed and analyzed using conventional content analysis. ResultsIn total, 9 EAs (aged 18.8, SD 2.7 years; 5, 56% men; 8, 89% White) with a duration of diabetes of 8.6 (SD 4.3) years participated. They described experiences with diabetes stigma (attributing diabetes to poor lifestyle choices) and feelings of self-consciousness (hyperawareness) in their rural communities. They attributed these experiences to the small size of their communities (“everyone knows”) and community members’ lack of knowledge about diabetes (unable to differentiate between type 1 and type 2 diabetes). In contrast, EAs reported high levels of social support for diabetes and diabetes care from family, friends, and other community members, but low support for medical needs. The location of their diabetes care providers and the limited accessibility of diabetes-specific and general medical care services in their local community created a challenging medical care context. Overall, EAs found mHealth interventions appealing due to their digital delivery and highlighted features that increased accessibility (voiceovers and simple, jargon-free language), individualization (ability to tailor intervention content and delivery), and applicability to their own lives and other EAs with T1D (relatability of vignettes and other content). EAs suggestions for improving the interventions included more opportunities to tailor the interventions to their preferences (greater frequency and duration, ability to adapt content to emerging needs), increasing opportunities for peer support within the interventions (friend and significant other as identified support person, connecting with peers beyond their local community), and making the tone of intervention components more casual and engaging. ConclusionsmHealth interventions aligned with EAs’ needs and preferences are a promising strategy to support EAs in communities where social support and resources might be limited. Trial RegistrationN/A, not a clinical tria

Influence of provider openness and leadership behaviors on adherence to motivational interviewing training implementation strategies: Considerations for evidence-based practice delivery

BackgroundAdherence to intervention training implementation strategies is at the foundation of fidelity; however, few studies have linked training adherence to trainee attitudes and leadership behaviors to identify what practically matters for the adoption and dissemination of evidence-based practices. Through the conduct of this hybrid type 3 effectiveness-implementation cluster randomized controlled trial, we collected Exploration, Preparation, Implementation, and Sustainment (EPIS) data and merged it with tailored motivational interviewing training adherence data, to elucidate the relationship between provider attitudes toward evidence-based practices, leadership behaviors, and training implementation strategy (e.g., workshop attendance and participation in one-on-one coaching) adherence.MethodOur sample included data from providers who completed baseline (pre-intervention) surveys that captured inner and outer contexts affecting implementation and participated in tailored motivational interviewing training, producing a dataset that included training implementation strategies adherence and barriers and facilitators to implementation (N = 77). Leadership was assessed by two scales: the director leadership scale and implementation leadership scale. Attitudes were measured with the evidence-based practice attitude scale (EBPAS-50). Adherence to training implementation strategies was modeled as a continuous outcome with a Gaussian distribution. Analyses were conducted in SPSS.ResultsOf the nine general attitudes toward evidence-based practice, openness was associated with training adherence (estimate [EST] = 0.096, p < .001; 95% CI = [0.040, 0.151]). Provider general (EST = 0.054, 95% CI = [0.007, 0.102]) and motivational interviewing-specific (EST = 0.044, 95% CI = [0.002, 0.086]) leadership behaviors were positively associated with training adherence (p < .05). Of the four motivational interviewing-specific leadership domains, knowledge and perseverant were associated with training adherence (p < .05). As these leadership behaviors increased, knowledge (EST = 0.042, 95% CI = [0.001, 0.083]) and perseverant (EST = 0.039, 95% CI = [0.004, 0.075]), so did provider adherence to training implementation strategies.ConclusionsAs implementation science places more emphasis on assessing readiness prior to delivering evidence-based practices by evaluating organizational climate, funding streams, and change culture, consideration should also be given to metrics of leadership. A potential mechanism to overcome resistance is via the implementation of training strategies focused on addressing leadership prior to conducting training for the evidence-based practice of interest