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Measuring the Implementation of Behavioral Intervention Technologies: Recharacterization of Established Outcomes.

ABSTRACT: Behavioral intervention technologies (BITs) are websites, software, mobile apps, and sensors designed to help users address or change behaviors, cognitions, and emotional states. BITs have the potential to transform health care delivery, and early research has produced promising findings of efficacy. BITs also favor new models of health care delivery and provide novel data sources for measurement. However, there are few examples of successful BIT implementation and a lack of consensus on as well as inadequate descriptions of BIT implementation measurement. The aim of this viewpoint paper is to provide an overview and characterization of implementation outcomes for the study of BIT use in routine practice settings. Eight outcomes for the evaluation of implementation have been previously described: acceptability, adoption, appropriateness, feasibility, fidelity, implementation cost, penetration, and sustainability. In a proposed recharacterization of these outcomes with respect to BIT implementation, definitions are clarified, expansions to the level of analysis are identified, and unique measurement characteristics are discussed. Differences between BIT development and implementation, an increased focus on consumer-level outcomes, the expansion of providers who support BIT use, and the blending of BITs with traditional health care services are specifically discussed. BITs have the potential to transform health care delivery. Realizing this potential, however, will hinge on high-quality research that consistently and accurately measures how well such technologies have been integrated into health services. This overview and characterization of implementation outcomes support BIT research by identifying and proposing solutions for key theoretical and practical measurement challenges.

SUBMITTER: Hermes ED

PROVIDER: S-EPMC6367669 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature

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Measuring the Implementation of Behavioral Intervention Technologies: Recharacterization of Established Outcomes.

Hermes Eric DA ED Lyon Aaron R AR Schueller Stephen M SM Glass Joseph E JE

Journal of medical Internet research 20190125 1

Behavioral intervention technologies (BITs) are websites, software, mobile apps, and sensors designed to help users address or change behaviors, cognitions, and emotional states. BITs have the potential to transform health care delivery, and early research has produced promising findings of efficacy. BITs also favor new models of health care delivery and provide novel data sources for measurement. However, there are few examples of successful BIT implementation and a lack of consensus on as well ...[more]

PMID: 30681966

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Project description:BackgroundChanging health behaviors, such as smoking, unhealthy eating, inactivity, and alcohol abuse, may have a greater impact on population health than any curative strategy. One of the suggested strategies is the use of behavioral intervention technologies (BITs). They open up new opportunities in the area of prevention and therapy and have begun to show benefits in the durable change of health behaviors in patients or those at risk. A consensual and international paradigm was adopted by health authorities for drugs 50 years ago. It guides their development from research units to their authorization and surveillance. BITs' generalization brings into question their upstream evaluation before being placed on the market and their downstream monitoring once on the market; this is especially the case in view of the marketing information provided by manufacturers and the scarcity and methodological limits of scientific studies on these tools.ObjectiveThis study aims to identify and categorize the frameworks for the validation and monitoring of BITs proposed in the literature.MethodsWe conducted a narrative literature review using MEDLINE, PsycINFO, and Web of Science. The review items included the following: name, publication year, name of the creator (ie, first author), country, funding organization, health focus, target group, and design (ie, linear, iterative, evolutive, and/or concurrent). The frameworks were then categorized based on (1) translational research thanks to a continuum of steps and (2) the three paradigms that may have inspired the frameworks: biomedical, engineering, and/or behavioral.ResultsWe identified 46 frameworks besides the classic US Food and Drug Administration (FDA) five-phase drug development model. A total of 57% (26/46) of frameworks were created in the 2010s and 61% (28/46) involved the final user in an early and systematic way. A total of 4% (2/46) of frameworks had a linear-only sequence of their phases, 37% (17/46) had a linear and iterative structure, 33% (15/46) added an evolutive structure, and 24% (11/46) were associated with a parallel process. Only 12 out of 46 (26%) frameworks covered the continuum of steps and 12 (26%) relied on the three paradigms.ConclusionsTo date, 46 frameworks of BIT validation and surveillance coexist, besides the classic FDA five-phase drug development model, without the predominance of one of them or convergence in a consensual model. Their number has increased exponentially in the last three decades. Three dangerous scenarios are possible: (1) anarchic continuous development of BITs that depend on companies amalgamating health benefits and usability (ie, user experience, data security, and ergonomics) and limiting implementation to several countries; (2) the movement toward the type of framework for drug evaluation centered on establishing its effectiveness before marketing authorization to guarantee its safety for users, which is heavy and costly; and (3) the implementation of a framework reliant on big data analysis based on a posteriori research and an autoregulation of a market, but that does not address the safety risk for the health user, as the market will not regulate safety or efficacy issues. This paper recommends convergence toward an international validation and surveillance framework based on the specificities of BITs, not equivalent to medical devices, to guarantee their effectiveness and safety for users.

Project description:BackgroundExpanding the use of evidence-based behavioral interventions in community settings has met with limited success in various health outcomes as fidelity and dose of clinical interventions are often diluted when translated to communities. We conducted a pilot implementation study to examine adoption of the rigorously evaluated Healthier Families Program by Parks and Recreation centers in 3 cities across the country (MI, GA, NV) with diverse socio-cultural environments.MethodsUsing the RE-AIM framework, we evaluated the program both quantitatively (pre/post surveys of health behavior change; attendance & fidelity) and qualitatively (interviews with Parks and Recreation staff and participants following the program).ResultsThe 3 partner sites recruited a total of 26 parent-child pairs.ReachAmong the 24 participants who completed pre/post surveys, 62.5% were 25-34 years old, and average child age was 3.6 (SD 0.7) years. The distribution of self-reported race/ethnicity was 54% non-Hispanic White, 38% non-Hispanic Black, and 8% Latino.EffectivenessQualitative interviews with participants demonstrated increased use of the built environment for physical activity and continued use of key strategies for health behavior change.AdoptionThree of five (60%) collaborating sites proceeded with implementation of the program.ImplementationThe average attendance for the 12-week program was 7.6 (SD 3.9) sessions, with 71% attending > 50% of sessions. Average fidelity for the 12 weekly sessions was 25.2 (SD 1.2; possible range 9-27).MaintenanceAll 3 partner sites continued offering the program after grant funding was complete.ConclusionsThis pilot is among the first attempts to scale-out an evidence-based childhood obesity intervention in community Parks and Recreation centers. While this pilot was not intended to confirm the efficacy of the original trial on Body Mass Index (BMI) reduction, the effective and sustained behavior change among a geographically and ethnically diverse population with high attendance and fidelity demonstrates an effective approach on which to base future large-scale implementation efforts to reduce childhood obesity in community settings.

Project description:BackgroundThe Institute for International Internet Interventions for Health at Palo Alto University proposes to develop digital tools specifically to help low-income English- and Spanish-speaking smokers to quit. Individuals from lower-income countries and those with lower social status quit at lower rates than those from high-income countries and those with higher social status.ObjectiveWe plan to launch a project designed to test whether a mobile-based digital intervention designed with systematic input from low-income English- and Spanish-speaking smokers from a public-sector health care system can significantly improve its acceptability, utilization, and effectiveness.MethodsUsing human-centered development methods, we will involve low-income patients in the design of a Web app/text messaging tool. We will also use their input to improve our recruitment and dissemination strategies. We will iteratively develop versions of the digital interventions informed by our human-centered approach. The project involves three specific aims: (1) human-centered development of an English/Spanish smoking cessation web app, (2) improvement of dissemination strategies, and (3) evaluation of resulting smoking cessation web app. We will develop iterative versions of a digital smoking cessation tool that is highly responsive to the needs and preferences of the users. Input from participants will identify effective ways of reaching and encouraging low-income English- and Spanish-speaking smokers to use the digital smoking cessation interventions to be developed. This information will support ongoing dissemination and implementation efforts beyond the grant period. We will evaluate the effectiveness of the successive versions of the resulting stop smoking Web app by an online randomized controlled trial. Increased effectiveness will be defined as increased utilization of the Web app and higher abstinence rates than those obtained by a baseline usual care Web app.ResultsRecruitment will begin January 2016, the study is intended to be completed by summer 2018, and the results should be available by fall 2019.ConclusionsThis study will provide useful knowledge in developing, testing, and disseminating mobile-based interventions for low-income smokers.ClinicaltrialClinicalTrials.gov NCT02666482; https://clinicaltrials.gov/ct2/show/NCT02666482 (Archived by WebCite at http://www.webcitation.org/6gtcwaT28).

Project description:BackgroundA behavioural medicine approach in physiotherapy has shown positive effects on increased and sustained activities and participation, including reduced sick leave for patients with persistent musculoskeletal pain. The aim of this study was to explore the health outcomes of patients with persistent musculoskeletal pain treated by physiotherapists who had received active compared with passive support when implementing a behavioural medicine approach.MethodsAn explorative and comparative pre-/post-test trial was conducted. A total of 155 patients with musculoskeletal pain ≥4 weeks were consecutively recruited by physiotherapists in primary healthcare who had received active or passive support when implementing a behavioural medicine approach. Data concerning health outcomes for patients were collected using questionnaires before and after the physiotherapy treatment and at half-, one- and two-year follow-ups. Descriptive, non-parametric and parametric bi- and multivariate statistics were used.ResultsThere were no differences over time between the patients treated by physiotherapists who had received active compared to passive implementation support regarding pain-related disability, pain intensity, self-rated health, self-efficacy in performing daily activities, catastrophic thinking related to pain, and fear of movement. Significant improvements over time were identified in both groups regarding all variables and the effect sizes were large. The percentage of patients on sick leave significantly decreased in the patient group treated by physiotherapists who had received active implementation support.ConclusionIt is very important to include patient outcomes when evaluating the implementation of multicomponent interventions. It seems that the implementation method did not play a major role for the patients' outcomes in this study. Most of the patients' health outcomes improved regardless of whether they were treated by physiotherapists who had received active or passive support when implementing a behavioural medicine approach. This was likely because the active implementation support was not extensive enough to enable the physiotherapists to sustain the behavioural medicine approach.Trial registrationThe study protocol was retrospectively registered in ClinicalTrials.gov . ID NCT03118453 , March 20, 2017.

Project description:BackgroundImplementation science comprises a large set of theories suggesting interacting factors at different organisational levels. Development of literature syntheses and frameworks for implementation have contributed to comprehensive descriptions of implementation. However, corresponding instruments for measuring these comprehensive descriptions are currently lacking. The present study aimed to develop an instrument measuring care providers' perceptions of an implementation effort, and to explore the instrument's psychometric properties.MethodsBased on existing implementation literature, a questionnaire was designed with items on individual and team factors and on stages of change in an implementation process. The instrument was tested in a Norwegian study on implementation of evidence based practices for psychosis. Item analysis, factor structure, and internal consistency at baseline were examined.ResultsThe 27-item Implementation Process Assessment Tool (IPAT) revealed large variation between mean score of the items. The total scale scores were widely dispersed across respondents. Internal consistency for the total scale was high (Cronbach's alpha: .962), and all but one item contributed positively to the construct. The results indicated four underlying constructs: individual stages for behavioural change, individual activities and perceived support, collective readiness and support, and individual perceptions of the intervention.ConclusionsThe IPAT appears to be a feasible instrument for investigating the implementation process from the perspective of those making the change. It can enable examination of the relative importance of factors thought to be essential for implementation outcomes. It may also provide ongoing feedback for leaders tailoring support for teams to improve implementation. However, further research is needed to detect the instrument's properties later in the implementation process and in different contexts.Trial registrationClinicalTrials.gov code NCT03271242 (retrospective registered September 5, 2017).

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Measuring the Implementation of Behavioral Intervention Technologies: Recharacterization of Established Outcomes.

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Measuring the Implementation of Behavioral Intervention Technologies: Recharacterization of Established Outcomes.

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