Objectives Ecological momentary assessment (EMA) has several advantages in clinical research yet little is known about the feasibility of collecting EMA data with mobile technologies in older adults, particularly those with emotional or cognitive difficulties. The aim of this feasibility study was to assess perceived acceptability, adherence rates, and reasons for non-adherence to smartphone-based EMA. Method At two sites, participants (n=103) aged 65 years or older with a DSM-IV-defined anxiety or depressive disorder and cognitive concerns responded three times daily to smartphone-based EMA questions assessing clinical outcomes for two 10-day periods. Quantitative and qualitative measures assessed acceptability, adherence, and reasons for non-adherence following both 10-day EMA periods. Results Participants were moderately satisfied with and comfortable using smartphone-based EMA. Overall, 76% of participants completed surveys on ≥10 of the 20 assessment days, and 70% of participants completed at least 30% of the total surveys. Reasons for non-adherence included technical (malfunction), logistical (competing demands), physiological (hearing difficulties), and cognitive (forgetting) issues. Discussion Smartphone-based EMA is feasible in older adults with cognitive and emotional difficulties. EMA tools should be responsive to the needs and preferences of participants to ensure adequate acceptability and adherence in this population. Our findings can inform the design, development, and implementation of mobile technologies in older adults in research and clinical contexts.

This study aimed to identify barriers to use of technology for behavioral health care from the perspective of care decision-makers at community behavioral health organizations. As part of a larger survey of technology readiness, 260 care decision-makers completed an open-ended question about perceived barriers to use of technology. Using the Consolidated Framework for Implementation Research (CFIR), qualitative analyses yielded barrier themes related to characteristics of technology (e.g., cost, privacy), potential end-users (e.g., technology literacy, attitudes about technology), organization structure and climate (e.g., budget, infrastructure), and factors external to organizations (e.g., broadband accessibility, reimbursement policies). Number of reported barriers was higher among respondents representing agencies with lower annual budgets and smaller client bases relative to higher budget, larger clientele organizations. Individual barriers were differentially associated with budget, size of client base, and geographic location. Results are discussed in light of implementation science frameworks and proactive strategies to address perceived obstacles to adoption and use of technology-based behavioral health tools.

Background Effective leadership for organizational change is critical to the implementation of evidence-based practices (EBPs). As organizational leaders in behavioral health organizations often are promoted from within the agency for their long-standing, effective work as counselors, they may lack formal training in leadership, management, or practice change. This study assesses a novel implementation leadership training designed to promote leadership skills and successful organizational change specific to EBP implementation. Methods We conducted a pre-post outcome evaluation of the Training in Implementation Practice Leadership (TRIPLE), delivered via three in-person, half-day training sessions, with interim coaching and technical support. Sixteen mid-level leaders (75% female, 94% Caucasian, mean age 37 years) from 8 substance abuse treatment agencies participated. Professional roles included clinical managers, quality improvement coordinators, and program directors. Participants completed surveys prior to the first and following the final session. At both time points, measures included the Implementation Leadership Scale, Implementation Climate Scale, and Organizational Readiness for Implementing Change Scale. At post-test, we added the Training Acceptability and Appropriateness Scale (TAAS), assessing participant satisfaction with the training. Qualitative interviews were conducted 6 to 8 months after the training. Results Most participants (86% and 79%, respectively) reported increased implementation leadership skills and implementation climate; paired samples t tests indicated these pre-post increases were statistically significant. Implementation leadership scores improved most markedly on the Proactive and Knowledgeable subscales. For implementation climate, participants reported the greatest increases in educational support and recognition for using EBP. Post-test scores on the TAAS also indicated that participants found the training program to be highly acceptable and appropriate for their needs. Qualitative results supported positive outcomes of training that resulted in both increased organizational implementation as well as leadership skills of participants. Conclusions This training program represents an innovative, effective, and well-received implementation strategy for emerging behavioral healthcare leaders seeking to adopt or improve the delivery of EBPs. Reported implementation leadership skills and implementation climate improved following the training program, suggesting that TRIPLE may have helped fulfill a critical need for emerging behavioral healthcare leaders. Electronic supplementary material The online version of this article (10.1186/s13012-019-0906-2) contains supplementary material, which is available to authorized users.

Tobacco smoking is an important risk factor for cancer incidence, an effect modifier for cancer treatment, and a negative prognostic factor for disease outcomes. Inadequate implementation of evidence-based smoking cessation treatment in cancer centers, a consequence of numerous patient-, provider-, and system-level barriers, contributes to tobacco-related morbidity and mortality. This study provides data for a paradigm shift from a frequently used specialist referral model to a point-of-care treatment model for tobacco use assessment and cessation treatment for outpatients at a large cancer center. The point-of-care model is enabled by a low-burden strategy, the Electronic Health Record-Enabled Evidence-Based Smoking Cessation Treatment program, which was implemented in the cancer center clinics on June 2, 2018. Five-month pre- and post-implementation data from the electronic health record (EHR) were analyzed. The percentage of cancer patients assessed for tobacco use significantly increased from 48% to 90% (z = 126.57, p < .001), the percentage of smokers referred for cessation counseling increased from 0.72% to 1.91% (z = 3.81, p < .001), and the percentage of smokers with cessation medication significantly increased from 3% to 17% (z = 17.20, p < .001). EHR functionalities may significantly address barriers to point-of-care treatment delivery, improving its consistent implementation and thereby increasing access to and quality of smoking cessation care for cancer center patients.

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Background Although effective treatments exist, alcohol use disorder (AUD) is undertreated. We used a cascade of care framework to understand gaps in care for persons with AUD. Methods Using 2015–2019 National Survey on Drug Use and Health data, we evaluated the following steps in the cascade of care: (1) adult prevalence of AUD; (2) proportion of adults with AUD who utilized health care in the past 12 months; (3) proportion with AUD screened about their alcohol use; (4) proportion with AUD who received a brief intervention about their alcohol misuse; (5) proportion with AUD who received information about treatment for alcohol misuse; and (6) proportion with AUD who received treatment. Analyses were stratified by AUD severity. Results Of the 214,505 persons included in the sample, the weighted prevalence of AUD was 7.8% (95% CI 7.6–8.0%). Cascades of care showed the majority of individuals with AUD utilized health care in the past 12 months [81.4% (95% CI 80.7–82.1%)] and were screened about alcohol use [69.9% (95% CI 68.9–70.8%)]. However, only a minority of individuals received subsequent steps of care, including 11.6% (95% CI 11.0–12.2%) who reported receiving a brief intervention, 5.1% (95% CI 4.6–5.6%) who were referred to treatment, and 5.8% (95% CI 5.4–6.3%) who received treatment. Similar patterns were observed when cascades of care were stratified by AUD severity. Conclusions Persons with AUD commonly utilize health care and are often screened about alcohol use, but few receive treatment. Healthcare settings—particularly primary care settings—represent a prime opportunity to implement AUD treatment to improve outcomes in this high‐risk population.

BackgroundResearch supports the effectiveness of technology-based treatment approaches for substance use disorders. These approaches have the potential to broaden the reach of evidence-based care. Yet, there is limited understanding of factors associated with implementation of technology-based care approaches in different service settings.ObjectivesIn this study, we explored provider and staff perceptions of facilitators and barriers to implementation of a mobile phone substance use recovery support app with clients in 4 service settings.MethodsInterviews were conducted with leadership and provider stakeholders (N=12) from 4 agencies in the first year of an implementation trial of the mobile phone app. We used the Consolidated Framework for Implementation Research as the conceptual foundation for identifying facilitators and barriers to implementation.ResultsImplementation process facilitators included careful planning of all aspects of implementation before launch, engaging a dedicated team to implement and foster motivation, working collaboratively with the app development team to address technical barriers and adapt the app to meet client and agency needs, and consistently reviewing app usage data to inform progress. Implementation support strategies included training all staff to promote organization awareness about the recovery support app and emphasize its priority as a clinical care tool, encouraging clients to try the technology before committing to use, scaling rollout to clients, setting clear expectations with clients about use of the app, and using peer coaches and consistent client-centered messaging to promote engagement. Perceived compatibility of the mobile phone app with agency and client needs and readiness to implement emerged as salient agency-level implementation facilitators. Facilitating characteristics of the recovery support app itself included evidence of its impact for recovery support, perceived relative advantage of the app over usual care, the ability to adapt the app to improve client use, and its ease of use. The mobile phone itself was a strong motivation for clients to opt in to use the app in settings that provided phones. App access was limited in settings that did not provide phones owing to lack of mobile phone ownership or incompatibility of the app with clients’ mobile phones. Individual differences in technology literacy and provider beliefs about substance use care either facilitated or challenged implementation. Awareness of patient needs and resources facilitated implementation, whereas external policies and regulations regarding technology use introduced barriers to implementation.ConclusionsThe conceptually grounded facilitators and barriers identified in this study can guide systematic targeting of strategies to improve implementation of mobile phone interventions in community treatment settings. Results also inform the design of technology-based therapeutic tools. This study highlights directions for research with regard to implementation of technology-based behavio...

Despite concerns around the use of technology-based interventions, they are increasingly being employed by social workers as a direct practice methodology to address the mental health needs of vulnerable clients. Researchers have highlighted the importance of using innovative technologies within social work practice, yet little has been done to summarize the evidence and collectively assess findings. In this systematic review, we describe accounts of technology-based mental health interventions delivered by social workers over the past 10 years. Results highlight the impacts of these tools and summarize advantages and disadvantages to utilizing technologies as a method for delivering or facilitating interventions.