Barriers and facilitators to patient and public engagement and recruitment to digital health interventions: protocol of a systematic review of qualitative studies

Strategies for Implementing an Electronic Patient-Reported Outcomes-Based Symptom Management Program Across Six Cancer Centers

Background

Electronic patient-reported outcome (ePRO)-based symptom management improves cancer patients' outcomes. However, implementation of ePROs is challenging, requiring technical resources for integration into clinical systems, substantial buy-in from clinicians and patients, novel workflows to support between-visit symptom management, and institutional investment.

Methods

The SIMPRO Research Consortium developed eSyM, an electronic health record-integrated, ePRO-based symptom management program for medical oncology and surgery patients and deployed it at six cancer centers between August 2019 and April 2022 in a type II hybrid effectiveness-implementation cluster randomized stepped-wedge study. Sites documented implementation strategies monthly using REDCap, itemized them using the Expert Recommendations for Implementation Change (ERIC) list and mapped their target barriers using the Consolidated Framework for Implementation Research (CFIR) to inform eSyM program enhancement, facilitate inter-consortium knowledge sharing and guide future deployment efforts.

Results

We documented 226 implementation strategies: 35 'foundational' strategies were applied consortium-wide by the coordinating center and 191 other strategies were developed by individual sites. We consolidated these 191 site-developed strategies into 64 unique strategies (i.e., removed duplicates) and classified the remainder as either 'universal', consistently used by multiple sites (N=29), or 'adaptive', used only by individual sites (N=35). Universal strategies were perceived as having the highest impact; they addressed eSyM clinical preparation, training, engagement of patients/clinicians, and program evaluation. Across all documented SIMPRO strategies, 44 of the 73 ERIC strategies were addressed and all 5 CFIR barriers were addressed.

Conclusion

Methodical collection of theory-based implementation strategies fostered the identification of universal, high-impact strategies that facilitated adoption of a novel care-delivery intervention by patients, clinicians, and institutions. Attention to the high-impact strategies identified in this project could support implementation of ePROs as a component of routine cancer care at other institutions.

Evaluation of a clinical decision support tool for matching cancer patients to clinical trials using simulation-based research

There is a growing need for alternative methodologies to evaluate digital health solutions in a short timeframe and at relatively low cost. Simulation-based research (SBR) methods have been proposed as an alternative methodology for evaluating digital health solutions; however, few studies have described the applicability of SBR methods to evaluate such solutions. This study used SBR to evaluate the feasibility and user experience of a clinical decision support (CDS) tool used for matching cancer patients to clinical trials. Twenty-five clinicians and research staff were recruited to match 10 synthetic patient cases to clinical trials using both the CDS tool and publicly available online trial databases. Participants were significantly more likely to report having sufficient time (p = 0.020) and to require less mental effort (p = 0.001) to complete trial matching with the CDS tool. Participants required less time for trial matching using the CDS tool, but the difference was not significant (p = 0.093). Most participants reported that they had sufficient guidance to participate in the simulations (96%). This study demonstrates the use of SBR methods is a feasible approach to evaluate digital health solutions and to collect valuable user feedback without the need for implementation in clinical practice. Further research is required to demonstrate the feasibility of using SBR to conduct remote evaluations of digital health solutions.

Mobile Health Technology and Healthcare Providers: Systemic Barriers to Adoption

Objectives

Despite the growing use of mobile health (mHealth), certain barriers seem to be hindering the use of mHealth applications in healthcare. This article presents a systematic review of the literature on barriers associated with mHealth reported by healthcare professionals.

Methods

This systematic review was carried out to identify studies published from January 2015 to December 2019 by searching four electronic databases (PubMed/MEDLINE, Web of Science, Embase, and Google Scholar). Studies were included if they reported perceived barriers to the adoption of mHealth from healthcare providers’ perspectives. Content analysis and categorization of barriers were performed based on a focus group discussion that explored researchers’ knowledge and experiences.

Results

Among the 273 papers retrieved through the search strategy, 18 works were selected and 18 barriers were identified. The relevant barriers were categorized into three main groups: technical, individual, and healthcare system. Security and privacy concerns from the category of technical barriers, knowledge and limited literacy from the category of individual barriers, and economic and financial factors from the category of healthcare system barriers were chosen as three of the most important challenges related to the adoption of mHealth described in the included publications.

Conclusions

mHealth adoption is a complex and multi-dimensional process that is widely implemented to increase access to healthcare services. However, it is influenced by various factors and barriers. Understanding the barriers to adoption of mHealth applications among providers, and engaging them in the adoption process will be important for the successful deployment of these applications.

Recruiting Participants for Population Health Intervention Research: Effectiveness and Costs of Recruitment Methods for a Cohort Study

Background

Public health research studies often rely on population-based participation and draw on various recruitment methods to establish samples. Increasingly, researchers are turning to web-based recruitment tools. However, few studies detail traditional and web-based recruitment efforts in terms of costs and potential biases.

Objective

This study aims to report on and evaluate the cost-effectiveness, time effectiveness, and sociodemographic representation of diverse recruitment methods used to enroll participants in 3 cities of the Interventions, Research, and Action in Cities Team (INTERACT) study, a cohort study conducted in Canadian cities.

Methods

Over 2017 and 2018 in Vancouver, Saskatoon, and Montreal, the INTERACT study used the following recruitment methods: mailed letters, social media (including sponsored Facebook advertisements), news media, partner communications, snowball recruitment, in-person recruitment, and posters. Participation in the study involved answering web-based questionnaires (at minimum), activating a smartphone app to share sensor data, and wearing a device for mobility and physical activity monitoring. We describe sociodemographic characteristics by the recruitment method and analyze performance indicators, including cost, completion rate, and time effectiveness. Effectiveness included calculating cost per completer (ie, a participant who completed at least one questionnaire), the completion rate of a health questionnaire, and the delay between completion of eligibility and health questionnaires. Cost included producing materials (ie, printing costs), transmitting recruitment messages (ie, mailing list rental, postage, and sponsored Facebook posts charges), and staff time. In Montreal, the largest INTERACT sample, we modeled the number of daily recruits through generalized linear models accounting for the distributed lagged effects of recruitment campaigns.

Results

Overall, 1791 participants were recruited from 3 cities and completed at least one questionnaire: 318 in Vancouver, 315 in Saskatoon, and 1158 in Montreal. In all cities, most participants chose to participate fully (questionnaires, apps, and devices). The costs associated with a completed participant varied across recruitment methods and by city. Facebook advertisements generated the most recruits (n=687), at a cost of CAD $15.04 (US $11.57; including staff time) per completer. Mailed letters were the costliest, at CAD $108.30 (US $83.3) per completer but served to reach older participants. All methods resulted in a gender imbalance, with women participating more, specifically with social media. Partner newsletters resulted in the participation of younger adults and were cost-efficient (CAD $5.16 [US $3.97] per completer). A generalized linear model for daily Montreal recruitment identified 2-day lag effects on most recruitment methods, except for the snowball campaign (4 days), letters (15 days), and reminder cards (5 days).

Conclusions

This study presents comprehensive data on the costs, effectiveness, and bias of population recruitment in a cohort study in 3 Canadian cities. More comprehensive documentation and reporting of recruitment efforts across studies are needed to improve our capacity to conduct inclusive intervention research.

Effectiveness of mobile applications in diabetic patients' healthy lifestyles: A review of systematic reviews

OBJECTIVE

(1) Examine the mobile applications that address lifestyles to improve the metabolic control of adult patients with diabetes mellitus. (2) Describe the characteristics of the used mobile applications, identify the healthy lifestyles they target, and describe any of their adverse effects.

METHODS

Review systematic reviews. We included studies that used any mobile application to help patients improve diabetes mellitus self-management by focusing on healthy lifestyles. Studies needed to include a control group receiving regular care with no mobile devices. In May 2018, Medline, Embase, Cochrane, LILACS, PsychINFO, Cinahl and Science Direct were searched, updated in June 2021. The methodological quality of the studies was assessed by the Amstar-2 tool.

RESULTS

First 804 articles were analyzed to select 17 systematic reviews, of which the methodological quality of seven was high or moderate. Interventions lasted 1-12 months. Twenty-three different mobile applications were identified that were all related to eating and physical activity. Significant changes were noted in HbA1c values. No clear improvement was observed for weight/BMI, lipid profile, quality of life or blood pressure. No adverse effects were found.

CONCLUSIONS

Managing the lifestyle of patients with diabetes using mobile applications improves short-term glycemic control, but the long-term results are not conclusive. The identified mobile applications focus on food and physical activity. Most are free. No adverse effects caused by using them were identified.

PROSPERO REGISTER

CRD42019133685.

A Text Messaging Intervention for Coping With Social Distancing During COVID-19 (StayWell at Home): Protocol for a Randomized Controlled Trial

BACKGROUND

Social distancing is a crucial intervention to slow down person-to-person transmission of COVID-19. However, social distancing has negative consequences, including increases in depression and anxiety. Digital interventions, such as text messaging, can provide accessible support on a population-wide scale. We developed text messages in English and Spanish to help individuals manage their depressive mood and anxiety during the COVID-19 pandemic.

OBJECTIVE

In a two-arm randomized controlled trial, we aim to examine the effect of our 60-day text messaging intervention. Additionally, we aim to assess whether the use of machine learning to adapt the messaging frequency and content improves the effectiveness of the intervention. Finally, we will examine the differences in daily mood ratings between the message categories and time windows.

METHODS

The messages were designed within two different categories: behavioral activation and coping skills. Participants will be randomized into (1) a random messaging arm, where message category and timing will be chosen with equal probabilities, and (2) a reinforcement learning arm, with a learned decision mechanism for choosing the messages. Participants in both arms will receive one message per day within three different time windows and will be asked to provide their mood rating 3 hours later. We will compare self-reported daily mood ratings; self-reported depression, using the 8-item Patient Health Questionnaire; and self-reported anxiety, using the 7-item Generalized Anxiety Disorder scale at baseline and at intervention completion.

RESULTS

The Committee for the Protection of Human Subjects at the University of California Berkeley approved this study in April 2020 (No. 2020-04-13162). Data collection began in April 2020 and will run to April 2021. As of August 24, 2020, we have enrolled 229 participants. We plan to submit manuscripts describing the main results of the trial and results from the microrandomized trial for publication in peer-reviewed journals and for presentations at national and international scientific meetings.

CONCLUSIONS

Results will contribute to our knowledge of effective psychological tools to alleviate the negative effects of social distancing and the benefit of using machine learning to personalize digital mental health interventions.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04473599; https://clinicaltrials.gov/ct2/show/NCT04473599.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/23592.

Facilitators and barriers of using digital technology for the management of diabetic foot ulcers: A qualitative systematic review

The use of digital technology has been shown to be effective in managing chronic conditions. Telemedicine and mobile application are two common applications of digital technology in managing diabetic foot ulcers (DFU). The facilitators and barriers of using it for DFU management are yet to be explored. This is a qualitative systematic review. Five bibliography databases and grey literature sources were searched (2000‐2019). Two reviewers independently screened the citations, extracted the data, assessed the quality of the included studies, and performed thematic synthesis. Three studies on patients and five studies on healthcare practitioners (HCPs) were included. Two studies focused on the use of mobile applications and six on telemedicine. In studies on patients, four analytical themes were generated: the relationships with HCPs; the attitude towards the usage of digital technology; the role of wound image taking; and impact of digital technology on DFU care, encompassing 15 facilitators (eg, enabling community support, improving wound care knowledge) and 12 barriers (eg, lack of technological savviness, difficulty reading on smartphones). Three analytical themes were generated from studies on HCPs: the impact of digital technology on HCPs; the role of digital technology in DFU care; and organisation of DFU care delivery, encompassing 17 facilitators (eg, adequate wound care training, digital technology enables holistic care) and 16 barriers (eg, lack of multidisciplinary approach in caring for DFU, lack of direct contact in care provision). Patients and HCPs reported various barriers and facilitators relating to different aspects of using digital technology in DFU management. Our findings can help inform future research as well as the adoption of digital technology in DFU management.

Consumer preference to utilise a mobile health app: A stated preference experiment

BACKGROUND

One prominent barrier faced by healthcare consumers when accessing health services is a common requirement to complete repetitive, inefficient paper-based documentation at multiple registration sites. Digital innovation has a potential role to reduce the burden in this area, through the collection and sharing of data between healthcare providers. While there is growing evidence for digital innovations to potentially improve the effectiveness and efficiency of health systems, there is less information on the willingness of healthcare consumers to embrace and utilise technology to provide data.

AIM

The study aims to improve understanding of consumers' preference for utilising a digital health administration mobile app.

METHODS

The online study used a stated preference experiment design to explore aspects of consumers' preference for a mobile health administration app and its impact on the likelihood of using the app. The survey was answered by a representative sample (by age and gender) of Australian adults, and sociodemographic factors were also recorded for analysis. Each participant answered eight choice sets in which a hypothetical app (defined by a set of dimensions and levels) was presented and the respondent was asked if they would be willing to provide data using that app. Analysis was conducted using bivariate logistic regression.

RESULTS

For the average respondent, the two most important dimensions were the time it took to register on the app and the electronic governance arrangements around their personal information. Willingness to use any app was found to differ based on respondent characteristics: people with higher education, and women, were relatively more willing to utilise the mobile health app.

CONCLUSION

This study investigated consumers' willingness to utilise a digital health administration mobile app. The identification of key characteristics of more acceptable apps provide valuable insight and recommendations for developers of similar digital health administration technologies. This would increase the likelihood of achieving successful acceptance and utilisation by consumers. The results from this study provide evidence-based recommendations for future research and policy development, planning and implementation of digital health administration mobile applications in Australia.

Satisfaction with a digitally-enabled telephone health coaching intervention for people with non-diabetic hyperglycaemia

International evidence shows that lifestyle interventions can effectively reduce the risk of developing diabetes in people with non-diabetic hyperglycaemia (NDH). A candidate intervention that has potential to be rolled out at population level is health coaching. Digital interventions offer the means to potentially enhance user satisfaction with health coaching and improve efficiencies. We used a randomised controlled trial to test whether a digitally-enabled health coaching intervention that included an online dashboard and telephone health coaching improved user satisfaction and cost-efficiencies compared with a telephone only health coaching intervention. The primary outcome was satisfaction measured by Client Satisfaction Questionnaire (CSQ-8). 103 participants with NDH were allocated to the telephone coaching only intervention and 106 participants with NDH were allocated to the digital and telephone coaching intervention. In an intention-to-treat analysis satisfaction was higher in participants allocated to the digital and telephone coaching intervention than those allocated to the telephone only intervention, but the difference was not significant. There were no significant differences between the groups on secondary outcomes (HbA1c, BMI, activation, depression, self-management, health status). From a service commissioning perspective the mean incremental cost of the digitally-enabled intervention was £236 ($332; €270). Call times, including administration, were longer for participants allocated to the digitally-enabled intervention. The results show that user satisfaction with digitally-enabled intervention is broadly equivalent with that of telephone delivered interventions in the context of routinely delivered diabetes prevention programmes. There is scope for future work that assesses how economies of scale can be achieved at larger user bases.

Development of a techno-humanist model for e-health adoption of innovative technology

BACKGROUND AND PURPOSE

After investing billions of dollars in an integrated Electronic Medical Records (physicians) and Personal Health Records (patients) system to allow both parties to manage and communicate through e-health innovative technologies, Canada is still making slow adoption progress. In an attempt to bridge the human and technological perspectives by developing and testing a holistic model, this study purports to predict patients' behavioral intentions to use e-health applications.

METHODS

An interdisciplinary approach labelled as a techno-humanism model (THM) is testing twelve constructs identified from the technological, sociological, psychological, and organizational research literature and deemed to have a significant effect upon and positive relationship with patients' e-health applications adoption. Subjects were Canadians recruited in a mall-intercept mode from a region representing a demographically diverse population, including rural and urban residents. The SmartPLS measurement tool was used to evaluate the reliability and validity of study constructs. The twelve constructs were separately tested with quantitative data such as factor analysis, single, multiple, and hierarchical multiple regression.

RESULTS

The hierarchical multiple regression analysis process led us to formulate four models, each hinged on a combination of interdisciplinary variables. Model 1 consisted of the technological predictors and explained 62.3% (p < .001) of variance in the behavioral intention to use e-health. Model 2 added the sociological predictors to the equation and explained 72.3% (p < .001) of variance. Model 3 added the psychological predictors to Model 2 and explained 72.8% (p < .001). Finally, Model 4 included all twelve predictors and explained 73% (p < .001) of variance in the behavioral intention to use e-health applications.

CONCLUSIONS

One of the greatest barriers to applying e-health records in Canada resides in the lack of coordination among stakeholders. The present study implies that healthcare policy makers must consider the twelve variables with their findings and implications as a whole. The techno-humanist model (THM) we are proposing is a more holistic and continuous approach. It pushes back to a breakdown of the various technological, sociological, psychological, and managerial factors and stakeholders that are at the root cause of behavioral intentions to use e-health, as opposed to merely observing behavioral outcomes at the end of the "assembly line". Active participation and coordination of all stakeholders is a key feature.

Methods to Evaluate the Effects of Internet-Based Digital Health Interventions for Citizens: Systematic Review of Reviews

Background

Digital health can empower citizens to manage their health and address health care system problems including poor access, uncoordinated care and increasing costs. Digital health interventions are typically complex interventions. Therefore, evaluations present methodological challenges.

Objective

The objective of this study was to provide a systematic overview of the methods used to evaluate the effects of internet-based digital health interventions for citizens. Three research questions were addressed to explore methods regarding approaches (study design), effects and indicators.

Methods

We conducted a systematic review of reviews of the methods used to measure the effects of internet-based digital health interventions for citizens. The protocol was developed a priori according to Preferred Reporting Items for Systematic review and Meta-Analysis Protocols and the Cochrane Collaboration methodology for overviews of reviews. Qualitative, mixed-method, and quantitative reviews published in English or French from January 2010 to October 2016 were included. We searched for published reviews in PubMed, EMBASE, The Cochrane Database of Systematic Reviews, CINHAL and Epistemonikos. We categorized the findings based on a thematic analysis of the reviews structured around study designs, indicators, types of interventions, effects and perspectives.

Results

A total of 20 unique reviews were included. The most common digital health interventions for citizens were patient portals and patients' access to electronic health records, covered by 10/20 (50%) and 6/20 (30%) reviews, respectively. Quantitative approaches to study design included observational study (15/20 reviews, 75%), randomized controlled trial (13/20 reviews, 65%), quasi-experimental design (9/20 reviews, 45%), and pre-post studies (6/20 reviews, 30%). Qualitative studies or mixed methods were reported in 13/20 (65%) reviews. Five main categories of effects were identified: (1) health and clinical outcomes, (2) psychological and behavioral outcomes, (3) health care utilization, (4) system adoption and use, and (5) system attributes. Health and clinical outcomes were measured with both general indicators and disease-specific indicators and reported in 11/20 (55%) reviews. Patient-provider communication and patient satisfaction were the most investigated psychological and behavioral outcomes, reported in 13/20 (65%) and 12/20 (60%) reviews, respectively. Evaluation of health care utilization was included in 8/20 (40%) reviews, most of which focused on the economic effects on the health care system.

Conclusions

Although observational studies and surveys have provided evidence of benefits and satisfaction for patients, there is still little reliable evidence from randomized controlled trials of improved health outcomes. Future evaluations of digital health interventions for citizens should focus on specific populations or chronic conditions which are more likely to achieve clinically meaningful benefits and use high-quality approaches such as randomized controlled trials. Implementation research methods should also be considered. We identified a wide range of effects and indicators, most of which focused on patients as main end users. Implications for providers and the health system should also be included in evaluations or monitoring of digital health interventions.

A pragmatic examination of active and passive recruitment methods to improve the reach of community lifestyle programs: The Talking Health Trial

Background

A primary challenge for behavior change strategies is ensuring that interventions can be effective while also attracting a broad and representative sample of the target population. The purpose of this case-study was to report on (1) the reach of a randomized controlled trial targeting reduced sugary beverages, (2) potential participant characteristic differences based on active versus passive recruitment strategies, and (3) recruitment strategy cost.

Methods

Demographic and recruitment information was obtained for 8 counties and for individuals screened for participation. Personnel activities and time were tracked. Costs were calculated and compared by active versus passive recruitment.

Results

Six-hundred and twenty, of 1,056 screened, individuals were eligible and 301enrolled (77% women; 90% white; mean income $21,981 ± 16,443). Eighty-two and 44% of those responding to passive and active methods, respectively, enrolled in the trial. However, active recruitment strategies yielded considerably more enrolled (active = 199; passive = 102) individuals. Passive recruitment strategies yielded a less representative sample in terms of gender (more women), education (higher), and income (higher; p’s <0.05). The average cost of an actively recruited and enrolled participant was $278 compared to $117 for a passively recruited and enrolled participant.

Conclusions

Though passive recruitment is more cost efficient it may reduce the reach of sugary drink reduction strategies in lower educated and economic residents in rural communities.

Trial registration

Clinicaltrials.gov; ID: NCT02193009, July 2014, retrospectively registered.

Understanding factors affecting patient and public engagement and recruitment to digital health interventions: a systematic review of qualitative studies

BACKGROUND

Numerous types of digital health interventions (DHIs) are available to patients and the public but many factors affect their ability to engage and enrol in them. This systematic review aims to identify and synthesise the qualitative literature on barriers and facilitators to engagement and recruitment to DHIs to inform future implementation efforts.

METHODS

PubMed, MEDLINE, CINAHL, Embase, Scopus and the ACM Digital Library were searched for English language qualitative studies from 2000 - 2015 that discussed factors affecting engagement and enrolment in a range of DHIs (e.g. 'telemedicine', 'mobile applications', 'personal health record', 'social networking'). Text mining and additional search strategies were used to identify 1,448 records. Two reviewers independently carried out paper screening, quality assessment, data extraction and analysis. Data was analysed using framework synthesis, informed by Normalization Process Theory, and Burden of Treatment Theory helped conceptualise the interpretation of results.

RESULTS

Nineteen publications were included in the review. Four overarching themes that affect patient and public engagement and enrolment in DHIs emerged; 1) personal agency and motivation; 2) personal life and values; 3) the engagement and recruitment approach; and 4) the quality of the DHI. The review also summarises engagement and recruitment strategies used. A preliminary DIgital Health EnGagement MOdel (DIEGO) was developed to highlight the key processes involved. Existing knowledge gaps are identified and a number of recommendations made for future research. Study limitations include English language publications and exclusion of grey literature.

CONCLUSION

This review summarises and highlights the complexity of digital health engagement and recruitment processes and outlines issues that need to be addressed before patients and the public commit to digital health and it can be implemented effectively. More work is needed to create successful engagement strategies and better quality digital solutions that are personalised where possible and to gain clinical accreditation and endorsement when appropriate. More investment is also needed to improve computer literacy and ensure technologies are accessible and affordable for those who wish to sign up to them.

SYSTEMATIC REVIEW REGISTRATION

International Prospective Register of Systematic Reviews CRD42015029846.