Background: Physical activity (PA) interventions can increase PA and improve well-being among adults affected by cancer; however, most adults do not meet cancer-specific PA recommendations. Lack of time, facility access, and travel distances are barriers to participation in PA interventions. eHealth technologies may address some of these barriers, serving as a viable way to promote PA behavior change in this population. However, no review from July 2018 has synthesized available evidence across eHealth and cancer types or examined the use of behavioral theory and behavior change techniques (BCTs), leaving important gaps in knowledge. Objective: This review aims to provide a comprehensive, updated overview of evidence on eHealth PA interventions for adults with cancer by describing the current state of the literature, exploring associations between intervention characteristics and effectiveness, and identifying future research needs. Methods: MEDLINE, Embase, CINAHL, SportDiscus, Scopus, and CENTRAL were searched for eHealth PA interventions for adults affected by cancer. Study selection and data extraction were performed in duplicate, with consultation from the senior author (NCR). BCT coding, risk of bias, and completeness of reporting were performed using standardized tools. Results were summarized via narrative synthesis and harvest plots. Weight analyses were conducted to explore the associations between intervention characteristics and effectiveness. Results: A total of 71 articles (67 studies) involving 6655 participants (mean age 56.7 years, SD 8.2) were included. Nearly 50% (32/67) of the articles were published after July 2018. Significant postintervention PA increases were noted in 52% (35/67) of the studies, and PA maintenance was noted in 41% (5/12) of the studies that included a follow-up. Study duration, primary objectives, and eHealth modality (eg, websites, activity trackers, and SMS text messaging) varied widely. Social cognitive theory (23/67, 34%) was the most used theory. The mean number of BCTs used across the studies was 13.5 (SD 5.5), with self-monitoring, credible sources, and goal setting being used in >90% of studies. Weight analyses showed the greatest associations between increased PA levels and PA as a primary outcome (0.621), interventions using websites (0.656) or mobile apps (0.563), interventions integrating multiple behavioral theories (0.750), and interventions using BCTs of problem solving (0.657) and action planning (0.645). All studies had concerns with high risk of bias, mostly because of the risk of confounding, measurement bias, and incomplete reporting. Conclusions: A range of eHealth PA interventions may increase PA levels among adults affected by cancer, and specific components (eg, websites, use of theory, and action planning) may be linked to greater effectiveness. However, more work is needed to ascertain and optimize effectiveness, measure long-term effects, and address concerns with bias and incomplete reporting. This evidence is required to support arguments for integrating eHealth within PA promotion in oncology.

Barriers to exercise-oncology programs remain for those living with and beyond cancer in rural and remote communities, including geographic isolation and access to programs. The EXercise for Cancer to Enhance Living Well (EXCEL) study was designed to support exercise-oncology implementation in rural and remote communities across Canada. The purpose of this analysis was to evaluate the first-year reach, adoption, and implementation of the EXCEL study. Reach outcomes included participant characteristics, study enrolment, and referral type (self vs. healthcare-provider [HCP] referral). Adoption outcomes included the number of clinical contacts, trained qualified exercise professionals (QEPs), and QEPs delivering EXCEL exercise classes. Implementation outcomes included retention, adherence, assessment completion rates, and adverse-event reporting. A total of 290 individuals living with cancer enrolled in EXCEL in year one, with an 81.4% retention to the study intervention. Most participants self-referred to EXCEL (75.8%). EXCEL’s HCP network consisted of 163 clinical contacts, and the QEP network included 45 trained QEPs, 22 of whom delivered EXCEL classes. Adherence to the exercise intervention was 78.2%, and only one adverse event (mild) was reported. Fitness assessment and patient-reported outcome completion rates were above 85% pre- and post-intervention. EXCEL has developed HCP and QEP networks supporting exercise referral and online delivery, and the intervention is meeting feasibility markers. These implementation findings will inform the continued gathering of feedback across stakeholders to ensure that best evidence informs best practices.

Supervised physical activity interventions can improve cancer survivor quality of life. However, they are resource intensive and may not support physical activity maintenance. Therefore, most cancer survivors remain inactive. Electronic health is a promising tool to support physical activity maintenance, yet technology-based physical activity interventions in oncology have shown mixed effectiveness. We surveyed cancer participants in the Alberta Cancer Exercise program to better understand their experience with technology. Alberta Cancer Exercise participants were invited to complete a survey on technology literacy, usage, and perceived usefulness. Summary statistics were calculated for all variables. Multiple regression examined demographic prediction of technology usage and literacy. The response rate was 52.6% (n = 627/1191), with 93.3% survey completion (n = 585/627). Respondents were 60.6 ± 11.0 years old, 96.2% Caucasian, and of high socioeconomic status (83.3% with post-secondary education, 65.5% with income >$60,000). While electronic health literacy was low (mean 1.73 ± 0.73/4), computer (87.6%) and smartphone (87.5%) use was widespread, with 94.6% of smartphone users reporting daily use. One in two respondents used mobile applications or wearable trackers for physical activity, which were perceived as useful by >80% of users. Age and income were significant predictors of technology use and literacy. Technology is part of the lives of cancer survivors who engaged in a physical activity program, with mobile devices perceived as useful to support physical activity. However, the present findings highlight a need to increase electronic health literacy via education and tailoring of digital tools. These survey findings are being used to build our patient-centered, technology-supported physical activity interventions.

Background: Despite the benefits of physical activity (PA) for individuals with cancer, most remain insufficiently active. Exercise oncology interventions can improve PA levels. Individuals struggle to maintain PA levels after interventions because of persistent psychological and environmental PA barriers. Health technology (eHealth) may address some PA barriers and deliver effective, scalable PA interventions in oncology, yet its effectiveness for changing PA levels remains mixed. Using eHealth to support PA maintenance among rural populations with cancer, who may need greater PA support given lower PA levels and worse health outcomes, remains under-studied. Objective: This study examined the effectiveness of an app-based self-monitoring intervention in supporting PA maintenance among rural populations with cancer after a supervised web-based exercise oncology program. Methods: This 2-arm, cluster randomized controlled trial was embedded within the Exercise for Cancer to Enhance Living Well (EXCEL) effectiveness-implementation study. Upon consent, participants were randomized 1:1 by EXCEL class clusters to the intervention (24 weeks of app-based PA self-monitoring) or waitlist control (app access after 24 weeks). Both groups completed a 12-week supervised web-based exercise oncology program followed by a 12-week self-directed PA maintenance period. Baseline demographics, eHealth literacy, and patient-reported outcomes were compared using chi-square and 2-tailed t tests. App use was measured throughout the intervention. The primary outcome—self-reported moderate-to-vigorous PA (MVPA) minutes—and secondary outcomes—objective MVPA minutes and steps and app usability ratings—were collected at baseline, 12 weeks, and 24 weeks. Intervention effects on self-report MVPA maintenance were assessed via linear mixed modeling, with secondary outcomes explored descriptively. Results: Of the 359 eligible EXCEL participants, 205 (57.1%) consented, 199 (55.4%; intervention: 106/199, 53.3%; control: 93/199, 46.7%) started the study, and 183 (51%; intervention: 100/183, 54.6%; control: 83/183, 45.4%) and 141 (39.3%; intervention: 69/141, 48.9%; control: 72/141, 51.1%) completed 12- and 24-week measures, respectively. Mean age was 57.3 (SD 11.5) years. Most participants were female (174/199, 87.4%), White (163/199, 81.9%), and diagnosed with breast cancer (108/199, 54.3%). Median baseline self-report weekly MVPA minutes were 60.0 (IQR 0-180) and 40.0 (IQR 0-135) for the intervention and waitlist control groups, respectively (P=.74). Median app use duration was 10.3 (IQR 1.3-23.9) weeks, with 9.6 (IQR 4.4-17.8) self-monitoring entries/week. Both groups increased their weekly MVPA minutes significantly at 12 weeks (P<.001) and maintained the increases at 24 weeks (P<.001), relative to baseline, with no between-group differences (P=.87). The intervention group had significantly higher step counts for 7 of the 12 weeks during the PA maintenance period (P=.048 to <.001). Conclusions: The app-based self-monitoring intervention did not improve MVPA maintenance but may have contributed to increased step counts during the PA maintenance period. More work is needed to realize the full potential of eHealth in exercise oncology. Trial Registration: ClinicalTrials.gov NCT04790578; https://clinicaltrials.gov/study/NCT04790578 International Registered Report Identifier (IRRID): RR2-10.1016/j.cct.2021.106474

Journal of Medical Internet Research - International Scientific Journal for Medical Research, Information and Communication on the Internet #Preprint #PeerReviewMe: Warning: This is a unreviewed preprint. Readers are warned that the document has not been peer-reviewed by expert/patient reviewers or an academic editor, may contain misleading claims, and is likely to undergo changes before final publication, if accepted, or may have been rejected/withdrawn. Readers with interest and expertise are encouraged to sign up as peer-reviewer, if the paper is within an open peer-review period. Please cite this preprint only for review purposes or for grant applications and CVs (if you are the author). Background: Targeting modifiable health behaviors can significantly reduce risk of disease, and result in saving up to 30% of health care costs. Recent interventions for affecting health behaviors are based on combining the social determinants of health (SDOH) and biosocial perspectives, shifting the focus from the individual to broader societal contexts under the SDOH approach. Tools for screening patients for individual and societal factors are being increasingly integrated into electronic health record (EHR) systems. Epic Systems © is one of the leading and most adopted EHR across the globe, with modules on SDOH and modifiable risk factors. There is a gap in literature on integration and use of screening tools for SDOH and modifiable risk factors. Objective: To synthesize evidence on the integration of screening tools for SDOH and modifiable risk factors in the Epic EHR, focusing on approaches, lessons, and impact. Methods: We followed established methods for conducting and reporting scoping reviews, including Joanna Briggs Institute’s (JBI) guidance, Arksey and O’Malley’s framework and the PRISMA-ScR checklist. We included 3 peer reviewed databases, 2 grey literature sources and citation chained from related reviews and articles. Results: All included studies (n=43) were from USA, spanning 24 states. Methods included 26 quantitative, 12 mixed methods, and 6 qualitative studies, across a variety of health settings. Most studies focused on adults, with data collected from patients on SDOH, and a smaller proportion for modifiable risk factors. Among the SDOH domains, housing, food and transportation were the top three, while physical activity, alcohol and tobacco were the most common risk factors targeted. There were a variety of screening tools used, with the PRAPARE tool being used the most across 6 studies. Most integrations used enhanced support or optimized workflows, with MyChart and Best Practice Advisories being the most used in-built Epic modules. MyChart was the most accepted module among patients. Screening and referral patient outcomes varied, with many studies presenting significant impact. Most important facilitators to integration included leadership support, dedicated clinical champions, and well-defined roles. Barriers to integration were clinician time, inefficient workflows, and availability of devices and staff to ensure use of integrated tools. Conclusions: Integration of SDOH and modifiable risk factors in the Epic EHR are being increasingly adopted to capture and target equitable health services. While Epic is one of the most globally adopted EHRs, studies are primarily from the USA. Epic’s SDOH wheel module is not sufficient for capturing context-based SDOH and behavioral domains. In addition, there is an increasing need for standardization of domains and tools. Future research is needed for enhanced learning on improvement and use of in-built tools, standardization, and processes for integrating interventions for targeting patient needs. Clinical Trial: Not applicable.

Objectives To review publicly available physical activity (PA) resources for individuals with rheumatoid arthritis (RA). Aims were to find online print and audiovisual resources, review their characteristics and critically examine their quality from medical, exercise and behavioural science perspectives. Design An environmental scan was completed using the Google search engine, following a pragmatic approach to reviewing patient-facing self-care resources. Data sources We used combinations of common search terms for RA and PA. The first five pages of results were reviewed for patient-facing resources. Eligibility criteria Resources were included if they were (1) included RA-specific content, (2) provided specific PA recommendations, (3) written in English and (4) freely available. Data extraction and synthesis Two independent experts completed a medical review of resources to ensure appropriateness for RA. Data were then extracted by two reviewers using a standardised template to record resource characteristics. Two research team members and two patient partners independently evaluated resources for readability, understandability and actionability. Finally, the quality of exercise recommendations and behaviour change technique use was evaluated by an expert reviewer. Results The search yielded 23 RA-specific PA resources, 17 of which passed the medical review. All 10 print resources and 7 audiovisual resources were created in English-speaking countries. The mean reading grade was 9.0±1.5. Print resources had mean understandability of 80.0±9.8% and actionability of 60.0±27.7%. Audiovisual materials had mean understandability of 86.0±9.2% and actionability of 86.9±22.9%. The quality of exercise recommendations was low. Only one resource provided comprehensive cardiovascular exercise advice, and two resources provided comprehensive strength exercise advice. 3–14 behaviour change technique groups were featured in each resource. The most common groups were ‘shaping knowledge’ and ‘natural consequences’. Conclusions The quality of RA-specific PA resources is variable. Some high-quality resources exist that provide actionable PA behaviour change advice. Healthcare teams may refer patients to these resources. However, more work is needed to improve the overall quality of resources. Codevelopment with patients, providers and exercise behaviour change experts is recommended, ensuring resources are actionable, contain clear exercise recommendations and promote behaviour change.