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A Framework for the Study of Complex mHealth Interventions in Diverse Cultural Settings.

ABSTRACT: To facilitate decision-making capacity between options of care under real-life service conditions, clinical trials must be pragmatic to evaluate mobile health (mHealth) interventions under the variable conditions of health care settings with a wide range of participants. The mHealth interventions require changes in the behavior of patients and providers, creating considerable complexity and ambiguity related to causal chains. Process evaluations of the implementation are necessary to shed light on the range of unanticipated effects an intervention may have, what the active ingredients in everyday practice are, how they exert their effect, and how these may vary among recipients or between sites.Building on the CONSORT-EHEALTH (Consolidated Standards of Reporting Trials of Electronic and Mobile HEalth Applications and onLine TeleHealth) statement and participatory evaluation theory, we present a framework for the process evaluations for mHealth interventions in multiple cultural settings. We also describe the application of this evaluation framework to the implementation of DREAM-GLOBAL (Diagnosing hypertension-Engaging Action and Management in Getting Lower BP in Indigenous and LMIC [low- and middle-income countries]), a pragmatic randomized controlled trial (RCT), and mHealth intervention designed to improve hypertension management in low-resource environments. We describe the evaluation questions and the data collection processes developed by us.Our literature review revealed that there is a significant knowledge gap related to the development of a process evaluation framework for mHealth interventions. We used community-based participatory research (CBPR) methods and formative research data to develop a process evaluation framework nested within a pragmatic RCT.Four human organizational levels of participants impacted by the mHealth intervention were identified that included patients, providers, community and organizations actors, and health systems and settings. These four levels represent evaluation domains and became the core focus of the evaluation. In addition, primary implementation themes to explore in each of the domains were identified as follows: (1) the major active components of the intervention, (2) technology of the intervention, (3) cultural congruence, (4) task shifting, and (5) unintended consequences. Using the four organizational domains and their interaction with primary implementation themes, we developed detailed evaluation research questions and identified the data or information sources to best answer our questions.Using DREAM-GLOBAL to illustrate our approach, we succeeded in developing an uncomplicated process evaluation framework for mHealth interventions that provide key information to stakeholders, which can optimize implementation of a pragmatic trial as well as inform scale up. The human organizational level domains used to focus the primary implementation themes in the DREAM-GLOBAL process evaluation framework are sufficiently supported in our research, and the literature and can serve as a valuable tool for other mHealth process evaluations.ClinicalTrials.gov NCT02111226; https://clinicaltrials.gov/ct2/show/NCT02111226 (Archived by WebCite at http://www.webcitation.org/6oxfHXege).

SUBMITTER: Maar MA

PROVIDER: S-EPMC5418524 | biostudies-literature | 2017 Apr

REPOSITORIES: biostudies-literature

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A Framework for the Study of Complex mHealth Interventions in Diverse Cultural Settings.

Maar Marion A MA Yeates Karen K Perkins Nancy N Boesch Lisa L Hua-Stewart Diane D Liu Peter P Sleeth Jessica J Tobe Sheldon W SW

JMIR mHealth and uHealth 20170420 4

<h4>Background</h4>To facilitate decision-making capacity between options of care under real-life service conditions, clinical trials must be pragmatic to evaluate mobile health (mHealth) interventions under the variable conditions of health care settings with a wide range of participants. The mHealth interventions require changes in the behavior of patients and providers, creating considerable complexity and ambiguity related to causal chains. Process evaluations of the implementation are neces ...[more]

PMID: 28428165

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Project description:AIMS: This study aimed to document and compare the nature of clinical pharmacists' interventions made in different practice settings within a children's hospital. METHODS: The primary investigator observed and documented all clinical interventions performed by clinical pharmacists for between 35-37 days on each of the five study wards from the three practice settings, namely general medical, general surgical and hematology-oncology. The rates, types and significance of the pharmacists' interventions in the different settings were compared. RESULTS: A total of 982 interventions were documented, related to the 16,700 medication orders reviewed on the five wards in the three practice settings over the duration of the study. Taking medication histories and/or patient counselling were the most common pharmacists' interventions in the general settings; constituting more than half of all interventions. On the Hematology-Oncology Ward the pattern was different with drug therapy changes being the most common interventions (n = 73/195, 37.4% of all interventions). Active interventions (pharmacists' activities leading to a change in drug therapy) constituted less than a quarter of all interventions on the general medical and surgical wards compared to nearly half on the specialty Hematology-Oncology Ward. The majority (n = 37/42, 88.1%) of a random sample of the active interventions reviewed were rated as clinically significant. Dose adjustment was the most frequent active interventions in the general settings, whilst drug addition constituted the most common active interventions on the Hematology-Oncology Ward. The degree of acceptance of pharmacists' active interventions by prescribers was high (n = 223/244, 91.4%). CONCLUSIONS: The rate of pharmacists' active interventions differed across different practice settings, being most frequent in the specialty hematology-oncology setting. The nature and type of the interventions documented in the hematology-oncology were also different compared to those in the general medical and surgical settings.

Project description:Background Failing to account for the resources required to successfully implement public health interventions can lead to an underestimation of costs and budget impact, optimistic cost-effectiveness estimates, and ultimately a disconnect between published evidence and public health decision-making. Methods We developed a conceptual framework for assessing implementation costs. We illustrate the use of this framework with case studies involving interventions for tuberculosis and HIV/AIDS in resource-limited settings. Results Costs of implementing public health interventions may be conceptualized as occurring across three phases: design, initiation, and maintenance. In the design phase, activities include developing intervention components and establishing necessary infrastructure (e.g., technology, standard operating procedures). Initiation phase activities include training, initiation of supply chains and quality assurance procedures, and installation of equipment. Implementation costs in the maintenance phase include ongoing technical support, monitoring and evaluation, and troubleshooting unexpected obstacles. Within each phase, implementation costs can be incurred at the site of delivery (“site-specific” costs) or more centrally (“above-service” or “central” costs). For interventions evaluated in the context of research studies, implementation costs should be classified as programmatic, research-related, or shared research/program costs. Purely research-related costs are often excluded from analysis of programmatic implementation. Conclusions In evaluating public health interventions in resource-limited settings, accounting for implementation costs enables more realistic estimates of budget impact and cost-effectiveness and provides important insights into program feasibility, scale-up, and sustainability. Assessment of implementation costs should be planned prospectively and performed in a standardized manner to ensure generalizability.

Project description:BackgroundMedication adherence is an important but highly complex set of behaviors, which for life-threatening and infectious diseases such as HIV carry critical consequences for individual and public health. There is growing evidence that mobile phone text messaging interventions (mHealth) connecting providers with patients positively impact medication adherence, particularly two-way engagement platforms that require bidirectional communication versus one-way in which responses are not mandatory. However, mechanisms of action have not been well defined. The Behavior Change Wheel is a comprehensive framework for behavior change that includes an all-encompassing model of behavior known as Capability Opportunity Motivation-Behavior and is complemented by a taxonomy of behavior change techniques. Evaluating mHealth interventions for medication adherence using these tools could provide useful insights that may contribute to optimizing their integration into the healthcare system and successful scaling-up.ObjectiveThis study aimed to help address the current knowledge gap regarding how two-way mHealth interventions for medication adherence may work by applying the Behavior Change Wheel to characterize WelTel: an interactive digital health outreach platform with robust evidence for improving adherence to antiretroviral therapy.MethodsTo characterize how WelTel may promote medication adherence, we applied the Behavior Change Wheel to systematically (1) generate a behavioral diagnosis through mapping known antiretroviral therapy adherence barriers onto the Capability Opportunity Motivation-Behavior model of behavior, (2) specify the behavior change techniques that WelTel delivers, (3) link identified behavior change techniques to corresponding intervention functions of the Behavior Change Wheel, and (4) connect these behavior change techniques and intervention functions to respective Capability Opportunity Motivation-Behavior influences on behavior to determine potential mechanisms of action.ResultsOur evaluation of WelTel using the Behavior Change Wheel suggests that most of its impact is delivered primarily through its personalized communication component, in which 8 different behavior change techniques were identified and linked with 5 intervention functions (environmental restructuring, enablement, education, persuasion, and training). Its mechanisms of action in promoting antiretroviral therapy adherence may involve addressing all Capability Opportunity Motivation-Behavior influences on behavior (physical and psychological capability, physical and social opportunity, reflective and automatic motivation).ConclusionsSystematically unpacking the potential active ingredients of effective interventions facilitates the creation and implementation of more parsimonious, tailored, and targeted approaches. Evaluating WelTel using the Behavior Change Wheel has provided valuable insights into how and why such interactive two-way mHealth interventions may produce greater impact than one-way in addressing both nonintentional and intentional forms of nonadherence. The application of the Behavior Change Wheel for evidence synthesis across mHealth interventions targeting various conditions would contribute to strengthening the knowledge base regarding how they may work to impact medication adherence behavior.

Project description:BackgroundDespite the widely recognised importance of cultural adaptation to increase the effectiveness of psychological interventions, there is little guidance on its process. Developed based on existing theory, we applied a four-step process to culturally adapt a low-intensity psychological intervention for use in humanitarian settings.MethodsThe four-step process was applied to adapt a WHO low-intensity psychological intervention (i.e. Problem Management Plus, or PM+) for use with displaced Venezuelans and Colombians in Colombia. First, a rapid desk review was used as an (1) information gathering tool to identify local population characteristics. Next, the results were taken forward for the (2) formulation of adaptation hypotheses, whereby PM+ protocols were screened to identify components for adaptation, drawing on the Ecological Validity Model. Third, the elements flagged for adaptation were taken forward for (3) local consultation to firstly, verify the components identified for adaptation, to identify other areas in need of adaptation, and thirdly, to adapt the intervention protocols. Finally, the adapted intervention protocols were reviewed through (4) external evaluations with local experts.ResultsThe information gathering phase yielded key information on the socioeconomic aspects of the groups targeted for intervention, the availability and need for mental health and psychosocial support, and existing barriers to accessing care. The adaptation hypotheses phase further identified the need for clearer explanations of key concepts, the need for sensitive topics to match local attitudes (e.g., domestic violence, thoughts of suicide), and the identification of culturally appropriate social supports. Building on these first two phases, local consultation subsequently resulted in revised PM+ protocols. The adapted protocols differed from the original format in their focus on the problems unique to these population groups, the way that psychological distress is expressed in this context, and the inclusion of locally available supports. The results of the external evaluation supported the adaptations made to the protocols.ConclusionThe proposed four-step process offers a useful guide for how to adapt low-intensity psychological intervention within humanitarian settings. Despite some limitations, we show that even when time and resources are scarce it is possible and necessary to culturally adapt psychological interventions. We invite further testing, replication, and improvements to this methodology.

Project description:Longitudinal targeted maximum likelihood estimation (LTMLE) has very rarely been used to estimate dynamic treatment effects in the context of time-dependent confounding affected by prior treatment when faced with long follow-up times, multiple time-varying confounders, and complex associational relationships simultaneously. Reasons for this include the potential computational burden, technical challenges, restricted modeling options for long follow-up times, and limited practical guidance in the literature. However, LTMLE has desirable asymptotic properties, ie, it is doubly robust, and can yield valid inference when used in conjunction with machine learning. It also has the advantage of easy-to-calculate analytic standard errors in contrast to the g-formula, which requires bootstrapping. We use a topical and sophisticated question from HIV treatment research to show that LTMLE can be used successfully in complex realistic settings, and we compare results to competing estimators. Our example illustrates the following practical challenges common to many epidemiological studies: (1) long follow-up time (30 months); (2) gradually declining sample size; (3) limited support for some intervention rules of interest; (4) a high-dimensional set of potential adjustment variables, increasing both the need and the challenge of integrating appropriate machine learning methods; and (5) consideration of collider bias. Our analyses, as well as simulations, shed new light on the application of LTMLE in complex and realistic settings: We show that (1) LTMLE can yield stable and good estimates, even when confronted with small samples and limited modeling options; (2) machine learning utilized with a small set of simple learners (if more complex ones cannot be fitted) can outperform a single, complex model, which is tailored to incorporate prior clinical knowledge; and (3) performance can vary considerably depending on interventions and their support in the data, and therefore critical quality checks should accompany every LTMLE analysis. We provide guidance for the practical application of LTMLE.

Project description:BACKGROUND:In low-resource settings, there are numerous socioeconomic challenges such as poverty, inadequate facilities, shortage of skilled health workers, illiteracy and cultural barriers that contribute to high maternal and newborn deaths. To address these challenges, there are several mHealth projects particularly in Sub-Sahara Africa seeking to exploit opportunities provided by over 90% rate of mobile penetration. However, most of these interventions have failed to justify their value proposition to inspire utilization in low-resource settings. METHODS:This study proposes a theoretical model named Technology, Individual, Process-Fit (TIPFit) suitable for user-centred evaluation of intervention designs to predict utilization of mHealth products in low-resource settings. To investigate the predictive power of TIPFit model, we operationalized its latent constructs into variables used to predict utilization of an mHealth prototype called mamacare. The study employed single-group repeated measures quasi-experiment in which a random sample of 79 antenatal and postnatal patients were recruited from a rural hospital. During the study conducted between May and October 2014, the treatment involved sending and receiving SMS alerts on vital signs, appointments, safe delivery, danger signs, nutrition, preventive care and adherence to medication. RESULTS:Measurements taken during the study were cleaned and coded for analysis using statistical models like Partial Least Squares (PLS), Repeated Measures Analysis of Variance (RM-ANOVA), and Bonferroni tests. After analyzing 73 pretest responses, the model predicted 80.2% fit, and 63.9% likelihood of utilization. However, results obtained from initial post-test taken after three months demonstrated 69.1% fit, and utilization of 50.5%. The variation between prediction and the actual outcome necessitated improvement of mamacare based on feedback obtained from users. Three months later, we conducted the second post-test that recorded further drop in fit from 69.1 to 60.3% but utilization marginally improved from 50.5 to 53.7%. CONCLUSIONS:Despite variations between the pretest and post-test outcomes, the study demonstrates that predictive approach to user-centred design offers greater flexibility in aligning design attributes of an mHealth intervention to fulfill user needs and expectations. These findings provide a unique contribution for decision makers because it is possible to prioritize investments among competing digital health projects.

Project description:BackgroundRandomized trials of complex, non-pharmacologic interventions implemented in home and community settings, such as the University of Southern California (USC)-Rancho Los Amigos National Rehabilitation Center (RLANRC) Pressure Ulcer Prevention Study (PUPS), present unique challenges with respect to (1) participant recruitment and retention, (2) intervention delivery and fidelity, (3) randomization and assessment, and (4) potential inadvertent treatment effects.PurposeWe describe the methods employed to address the challenges confronted in implementing PUPS. In this randomized controlled trial, we are assessing the efficacy of a complex, preventive intervention in reducing the incidence of, and costs associated with, the development of medically serious pressure ulcers in people with spinal cord injury.MethodsIndividuals with spinal cord injury recruited from RLANRC were assigned to either a 12-month preventive intervention group or a standard care control group. The primary outcome is the incidence of serious pressure ulcers with secondary endpoints including ulcer-related surgeries, medical treatment costs, and quality of life. These outcomes are assessed at 12 and 24 months after randomization. Additionally, we are studying the mediating mechanisms that account for intervention outcomes.ResultsPUPS has been successfully implemented, including recruitment of the target sample size of 170 participants, assurance of the integrity of intervention protocol delivery with an average 90% treatment adherence rate, and enactment of the assessment plan. However, implementation has been replete with challenges. To meet recruitment goals, we instituted a five-pronged approach customized for an underserved, ethnically diverse population. In intervention delivery, we increased staff time to overcome economic and cultural barriers to retention and adherence. To ensure treatment fidelity and replicability, we monitored intervention protocol delivery in accordance with a rigorous plan. Finally, we have overcome unanticipated assessment and design concerns related to (1) determining pressure ulcer incidence/severity, (2) randomization imbalance, and (3) inadvertent potential control group contamination.LimitationsWe have addressed the most daunting challenges encountered in the recruitment, assessment, and intervention phases of PUPS. Some challenges and solutions may not apply to trials conducted in other settings.ConclusionsOvercoming challenges has required a multifaceted approach incorporating individualization, flexibility, and persistence, as well as the ability to implement needed mid-course corrections.

Project description:BackgroundThe mass availability and use of mobile health (mHealth) technologies offers the potential for these technologies to support or substitute medical advice. However, it is worrisome that most assessment initiatives are still not able to successfully evaluate all aspects of mHealth solutions. As a result, multiple strategies to assess mHealth solutions are being proposed by medical regulatory bodies and similar organizations.ObjectiveWe aim to offer a collective description of a universally applicable description of mHealth assessment initiatives, given their current and, as we see it, potential impact. In doing so, we recommend a common foundation for the development or update of assessment initiatives by addressing the multistakeholder issues that mHealth technology adds to the traditional medical environment.MethodsOrganized by the Mobile World Capital Barcelona Foundation, we represent a workgroup consisting of patient associations, developers, and health authority representatives, including medical practitioners, within Europe. Contributions from each group's diverse competencies has allowed us to create an overview of the complex yet similar approaches to mHealth evaluation that are being developed today, including common gaps in concepts and perspectives. In response, we summarize commonalities of existing initiatives and exemplify additional characteristics that we believe will strengthen and unify these efforts.ResultsAs opposed to a universal standard or protocol in evaluating mHealth solutions, assessment frameworks should respect the needs and capacity of each medical system or country. Therefore, we expect that the medical system will specify the content, resources, and workflow of assessment protocols in order to ensure a sustainable plan for mHealth solutions within their respective countries.ConclusionsA common framework for all mHealth initiatives around the world will be useful in order to assess whatever mHealth solution is desirable in different areas, adapting it to the specifics of each context, to bridge the gap between health authorities, patients, and mHealth developers. We aim to foster a more trusting and collaborative environment to safeguard the well-being of patients and citizens while encouraging innovation of technology and policy.

Project description:BackgroundMobile health (mHealth) has the potential to improve access to healthcare, especially in developing countries. The proliferation of mHealth has not been accompanied by a corresponding growth in design guidelines for mHealth applications. This paper proposes a framework for mHealth application design that combines the Information Systems Research (ISR) framework and design thinking. We demonstrate a use case for the proposed framework in the form of an app to read the result of the tuberculin skin test (TST), which is used to screen for latent tuberculosis infection. The framework was used in the re-design of the TST reading app but could also be used in earlier stages of mHealth app design.MethodsThe ISR framework and design thinking were merged based on how the modes of design thinking integrate with the cycles of the ISR framework. Using the combined framework, we re-designed an mHealth app for TST reading, intended to be used primarily in a developing context by healthcare workers. Using the proposed framework, the app was iterated upon and developed with the aid of personas, observations, prototyping and questionnaires.ResultThe combined framework was applied through engagement with end-users, namely ten healthcare workers and ten graduate students. Through review of the literature and iterations of the app prototype, we identified various usability requirements and limitations. These included challenges related to image capture and a misunderstanding of instructions. These insights influenced the development and improvement of the app.ConclusionThe combined framework allowed for engagement with end-users and for low-cost, rapid development of the app while addressing contextual challenges and needs. The integration of design thinking modes with the ISR cycles was effective in achieving the objectives of each approach. The combined framework acknowledges the importance of engaging users when implementing mHealth technologies, especially in developing and under-resourced contexts. Findings from this study support the use of this framework as a guide in the design of user-centred mHealth interventions.

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A Framework for the Study of Complex mHealth Interventions in Diverse Cultural Settings.

Publications

A Framework for the Study of Complex mHealth Interventions in Diverse Cultural Settings.

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