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Virtual or In-Person: A Mixed Methods Survey to Determine Exercise Programming Preferences during COVID-19

Virtual or In-Person: A Mixed Methods Survey to Determine Exercise Programming Preferences during... Article Virtual or In-Person: A Mixed Methods Survey to Determine Exercise Programming Preferences during COVID-19 1 1 1 1 2,3,4 2,3 Kirsten Suderman , Tara Skene , Christopher Sellar , Naomi Dolgoy , Edith Pituskin , Anil A. Joy , 5,6 1,2,7, Susan Nicole Culos-Reed and Margaret L. McNeely * Department of Physical Therapy, University of Alberta, Edmonton, AB T6G 2G4, Canada Department of Oncology, Faculty of Medicine, University of Alberta, Edmonton, AB T6G 2R3, Canada Cross Cancer Institute, Alberta Health Services, Edmonton, AB T6G 1Z2, Canada Faculty of Nursing, University of Alberta, Edmonton, AB T6C 1C9, Canada Cumming School of Medicine, University of Calgary, Calgary, AB T2N 4N1, Canada Faculty of Kinesiology, University of Calgary, Calgary, AB T2N 1N4, Canada Cancer Care Alberta, Alberta Health Services, Edmonton, AB T5J 3E4, Canada * Correspondence: mmcneely@ualberta.ca; Tel.: +1-780-248-1531 Abstract: A survey was conducted to identify barriers and facilitators to engaging in virtual and in- person cancer-specific exercise during COVID-19. A theory-informed, multi-method, cross-sec- tional survey was electronically distributed to 192 individuals with cancer investigating preferences towards exercise programming during COVID-19. Respondents had previously participated in an exercise program and comprised two groups: those who had experience with virtual exercise pro- gramming (‘Virtual’) and those who had only taken part in in-person exercise (‘In-Person’). Quan- titative data were summarized descriptively. Qualitative data were thematically categorized using framework analysis and findings were mapped to an implementation model. The survey comple- tion response rate was 66% (N= 127). All respondents identified barriers to attending in-person ex- ercise programming during COVID-19 with concerns over the increased risk of viral exposure. Vir- Citation: Suderman, K.; Skene, T.; tual respondents (n = 39) reported: (1) feeling confident in engaging in virtual exercise; and (2) en- Sellar, C.; Dolgoy, N.; Pituskin, E.; hanced motivation, accessibility and effectiveness as facilitators to virtual exercise. In-Person re- Joy, A.A.; Culos-Reed, S.N.; spondents (n = 88) identified: (1) technology as a barrier to virtual exercise; and (2) low motivation, McNeely, M.L. Virtual or In-Person: accessibility and exercise effectiveness as barriers towards virtual exercise. Sixty-six percent (n = 58) A Mixed Methods Survey to of In-Person respondents reported that technology support would increase their willingness to ex- Determine Exercise Programming ercise virtually. With appropriately targeted support, perceived barriers to accessing virtual exer- Preferences during COVID-19. cise—including motivation, accessibility and effectiveness—may become facilitators. The availabil- Curr. Oncol. 2022, 29, 6735–6748. https://doi.org/10.3390/ ity of technology support may increase the engagement of individuals with cancer towards virtual curroncol29100529 exercise programming. Received: 26 July 2022 Keywords: cancer; exercise; eHealth; implementation Accepted: 9 September 2022 Published: 20 September 2022 Publisher’s Note: MDPI stays neu- tral with regard to jurisdictional 1. Introduction claims in published maps and institu- The novel Coronavirus Disease 19 (COVID-19) pandemic significantly increased bar- tional affiliations. riers and disrupted in-person access to healthcare services for immunocompromised pop- ulations. Barriers to healthcare delivery from COVID-19 have led to a fundamental shift of patient–clinician interactions from primarily ‘in-person’, to options that include virtual Copyright: © 2022 by the authors. care, telehealth, telemedicine, or ‘eHealth’ [1–3]. While eHealth platforms have the poten- Submitted for possible open access tial to provide multidisciplinary care to vulnerable chronic disease populations and over- publication under the terms and con- come remote/rural settings [4], research is still novel and emerging around successful tele- ditions of the Creative Commons At- health implementation [5]. tribution (CC BY) license (https://cre- The disruption to service access negatively impacted individuals with cancer, who ativecommons.org/licenses/by/4.0/). are at increased risk for severe complications from COVID-19 due to Curr. Oncol. 2022, 29, 6735–6748. https://doi.org/10.3390/curroncol29100529 www.mdpi.com/journal/curroncol Curr. Oncol. 2022, 29, 529 6736 immunocompromised side effects of cancer therapies, comorbidities and advanced age [6,7]. With the population of individuals diagnosed and living with cancer continuing to rapidly grow worldwide [8,9], there is a widening gap of supportive care services to ad- dress the many acute and chronic side effects from cancer and cancer-related treatments [10–12]. Supportive care refers to services designed to meet the physical, emotional, social and practical needs of individuals across the cancer spectrum [13]. An extensive body of evidence, including 16 published guidelines from major medical or health-oriented or- ganizations globally, recognize exercise as beneficial for individuals with cancer across the cancer spectrum [14]. Regular exercise results in numerous physiological and psycho- social benefits for cancer survivors, including improved survival outcomes for common cancers, overall quality of life, cancer-related fatigue, cardiorespiratory fitness and mus- cular strength [14–16]. Given the strength of evidence supporting the benefits of exercise for the cancer population, targeted efforts are needed to integrate cancer-specific exercise programming into standard patient care [17–20], now exacerbated due to increased barri- ers to exercise presented by COVID-19 [21,22]. With the rapid pivot to eHealth virtual platforms, COVID-19 has provided a unique environment to understand cancer survivors’ perspectives on the virtual delivery of exer- cise programming. Program accessibility is a known barrier identified by individuals with cancer towards engaging in exercise (i.e. transportation, parking, facility type and loca- tion, time of day) [23]. While home-based exercise improves accessibility, home programs lack support from exercise professionals and peers, which survivors have identified as significant facilitators towards exercise [24]. There is promise for the use of virtual plat- forms to deliver accessible cancer-specific exercise programming remotely while main- taining exercise professional and social supports [25,26]. Continuing research during the pandemic has led to initiatives around the large-scale implementation of eHealth plat- forms focusing on parameters of engagement, such as feasibility, acceptability and effi- cacy [27–29]. Virtual service delivery may provide a means to avoid the unnecessary risks of viral transmission associated with in-person settings [30]; however, the ability of eHealth to meet the exercise needs of people with and recovering from cancer is unclear. Moreover, with the rapid transition to eHealth platforms for cancer supportive care ser- vices, there is limited understanding of the best practices for implementing and delivering cancer-specific virtual exercise programming [31]. 1.1. Research Context of the Clinical Team 1.1.1. Alberta Cancer Exercise Hybrid Effectiveness–Implementation (ACE) Study The present study was part of the integrated knowledge translation (iKT) series [32] of sub-studies from the Alberta Cancer Exercise Hybrid Effectiveness–Implementation (ACE) study. ACE is an implementation study that proposes a clinic-to-community model of care to support the implementation of cancer-specific, community-based, exercise pro- gramming; the protocol and findings are described elsewhere [33–35]. The study involves a 12-week exercise program for individuals diagnosed with any cancer. The ACE study pivoted to providing virtual exercise programming during the lockdowns associated with COVID-19. 1.2. Objective This study aimed to understand the facilitators/preferences and barriers towards ex- ercise during COVID-19 to inform ongoing cancer-specific exercise programming. Spe- cific objectives included an understanding of the perspectives of individuals who had pre- viously participated in standardized exercise towards (1) in-person and virtual exercise, and (2) the use of technology to access virtual exercise programming. Findings were in- tended to inform ACE maintenance programming in Northern Alberta during the pan- demic and support future clinical implementation of virtual exercise programming in the cancer setting. Curr. Oncol. 2022, 29, 529 6737 2. Materials and Methods 2.1. Study Design A cross-sectional survey was administered to individuals with cancer who had pre- viously participated in ACE programming at Northern Alberta sites (Edmonton, Grande Prairie, Fort McMurray and Red Deer) either in-person prior to the pandemic, or virtually during the pandemic. A multi-method approach using both quantitative and qualitative data was utilized to provide a more inclusive understanding of the participants’ perspec- tives towards in-person and virtual exercise during COVID-19, as well as the use of tech- nology to access virtual exercise programming. Survey questions were theory informed and designed based on implementation theory from the Capability, Opportunity, Moti- vation—Behaviour (COM-B) model [36]. Survey questions were mapped from each of the three model domains/constructs: (1) capability—an individual’s psychological (knowledge) and physical capacity (skills) to perform behaviours or activities; (2) oppor- tunity—physical (environment) or social factors (interpersonal influences) external to an individual that influence the behaviour; and (3) motivation—brain processes that direct behaviour (optimism, habitual and emotional responses, and analytical decision making) [36]. Survey questions included both multiple choice and short answers to comprehen- sively capture each COM-B model construct. For question mapping and survey questions see Supplementary Material Table S1. Demographic and medical information were previ- ously collected through the ACE study [33]. Ethics approval for this sub-study was granted by the Health Research Board of Alberta: Cancer Committee (HREBA.16-0905) and the intervention component was prospectively registered (NTC02984163). 2.2. Data Collection Participants were eligible to participate in the survey if: (1) they had enrolled in either fall 2019 or winter 2020 (both in-person), or spring 2020 (virtual) of the ACE 12-week can- cer-specific exercise program through sites in Edmonton, Fort McMurray, Red Deer or Grande Prairie; (2) had consented to future contact from the ACE research team; (3) had an active email address; and (4) had completed 12-week and, if applicable, 24-week post program ACE questionnaires. ‘In-Person’ are respondents who participated in ACE community-based classes prior to COVID-19 (fall 2019, winter 2020). ‘Virtual’ are those who participated virtually (live supervised online classes) during COVID-19 (either ACE spring 2020, or independently). Inclusion criteria for the ACE study required participants to: (1) have a diagnosis of cancer of any type; (2) be over the age of 18 years; (3) be able to participate in mild levels of activity at minimum; (4) be pretreatment or receiving active cancer treatment (e.g., sur- gery, systemic therapy and/or radiation therapy), or have received cancer treatment within the past 3 years or have existing long-term, or have late presenting effects of their cancer treatment (e.g., radiation fibrosis syndrome, lymphoedema, communication defi- cits related to cancer treatment or incontinence); and (5) be able to provide informed writ- ten consent in English. ACE classes involved a combination of aerobic, resistance, balance and flexibility exercises delivered in a standardized circuit-type class setting twice weekly for a minimum of 60 min per session for a 12-week period (approximately 3–4 metabolic equivalent units per session). For intervention description refer to Table 1. The ACE study protocol has been previously reported in detail elsewhere [33]. Curr. Oncol. 2022, 29, 529 6738 Table 1. Intervention description using the template for description and replication checklist (TI- DieR). Intervention Alberta Cancer Exercise (ACE) Hybrid Effectiveness Implementation Study [33] Why Exercise improves aerobic fitness, muscular strength and cancer-related symptoms Exercise studio for circuit classes: bands, free weights, mats, bender balls, bosu; Community fitness What: Materials centre or cancer-specific clinic for group personal training: treadmill, stationary bike, exercise machines (chest press, bicep curl, leg curl/extension, seated row, pullies) free weights and mats What: Procedures Providers Oversight: exercise physiologist or physical therapist. Instructor: qualified exercise professional How Supervised sessions of either standardized circuit-type class setting or group personal training Where Community-based exercise facilities and cancer-specific exercise clinics Type Aerobic, resistance, balance and flexibility exercises Intensity 3-4 metabolic equivalent (MET) units per session (360–480 MET-minutes/ week) Progression of inten- sity to 4–5 METs over the 12-week duration (480–600 MET-minutes/week 2-4 (light to somewhat heavy) on the 11-point Borg Rating of Perceived Exertion Scale Frequency Twice weekly Session time 60 minutes per session Overall duration 12-weeks Tailoring Adaptations to address cancer-related symptoms, muscular stiffness and dizziness, and prevent ad- verse events Trial fidelity Staff with training and experience in exercise oncology Exercise supervision Attendance tracked for number of completed sessions Monitoring of symptoms (e.g. fatigue, muscle soreness) Recording of minor and serious adverse events The ACE study pivoted to providing virtual exercise programming during COVID- 19. Virtual exercise programming classes were live, supervised and conducted over zoom within the context of the following parameters: (1) participants were provided with tech- nology support in setting up and using their device in preparation for virtual program- ming that involved orientation to the virtual platform, evaluating connectivity and trou- bleshooting any issues related to the virtual environment (i.e., location of device and alignment with the computer camera for facilitating monitoring of exercise performance); (2) all exercise sessions were conducted live over a consistent virtual platform (Zoom); (3) three intensity levels of each exercise (light, moderate, vigorous) were continuously demonstrated for participants by designated exercise professionals; (4) participants were directed to follow appropriate intensity levels and pin the instructor demonstrating the preferred level; (5) exercises were chosen that could be completed in home environments, focused on body weight exercises with consideration of limited space and equipment; (6) each virtual session was monitored by a qualified exercise professional who was respon- sible for monitoring performance, correcting exercise form and helping troubleshoot any technology issues etc.; (7) exercise resistance bands were provided for participants. Curr. Oncol. 2022, 29, 529 6739 The survey was active from August 2020–September 2020 to coincide with and in- form Northern Alberta fall 2020 and winter 2021 ACE exercise programming. The survey was administered electronically through Research Electronic Data Capture (REDCap), a secure, web-based application designed for research study data collection, provided by Women and Children’s Health Research Institute [37], hosted on a secure server in the University of Alberta’s Faculty of Medicine and Dentistry’s data centre. Eligible partici- pants were emailed a secure survey link through REDCap. 2.3. Data Analysis Data from the survey included both continuous and categorical variables. Basic de- scriptive statistics were generated by REDCap including frequencies, percentages and counts of responses to quantitative questions. Qualitative data from short answer and open-ended questions were analyzed using framework analysis, a form of content analy- sis to identify patterns in qualitative data, with a defining feature involving matrix out- puts of rows and columns of summarized data [38]. Framework analysis provides a prac- tical lens to answer specific questions with actionable outcomes, lending itself well to in- forming clinical and implementation practices [39]. Three researchers independently coded written responses (KS, MM, ND) into framework tables. After initial coding, re- searchers collaborated to amend and refine codes, and develop framework tables in rela- tion to patterns of barriers, facilitators and/or preferences towards exercise and technol- ogy. Themes were then mapped to respective domains of the COM-B Model to inform implementation strategies for local fall 2020 ACE exercise programming and future clini- cal practice [40]. 3. Results 3.1. Demographics A total of 127 cancer survivors responded (66% response rate), with 69% (n = 63) aged 55 and older, and 25% (n = 32) 40–55 years of age. The average age of respondents was 59 years (SD = 11.4). The most common cancer diagnosis was breast (44%, n = 56), followed by digestive cancer (17%, n = 22), and head and neck cancer (11%, n = 14). The majority of respondents were female (71%, n = 90), and 46% (n = 58) of all respondents were actively receiving treatment for cancer. Respondents mainly resided in an urban centre (n = 93, 73%) or within 15–30 kms of an urban centre (n = 28, 22%). The average commute to In- Person exercise programming was 14.3 km. Respondent demographics can be viewed in Table 2. As all survey recipients had previously participated in exercise programming through ACE, we were able to explore the characteristics of non-respondents compared to respondents. Non-respondents were slightly younger with an average age of 57 years of age (SD 11.1) compared to respondents (59 years, SD 11.4). A larger proportion of non- respondents were males (n = 29, 45%) compared to respondents (n = 37, 29%). Further details on non-respondent demographics can be viewed in Table 2. Curr. Oncol. 2022, 29, 529 6740 Table 2. Baseline Demographic and Medical Data. Respondent In-Person Exercise Virtual Exercise Total Non- Characteristics (Spring 2019–Winter 2020) (Spring 2020) Respondents Respondents n = 88, No. (%) n = 39, No. (%) n = 127, No. (%) n = 65, No. (%) Sex Male 29 (33.0) 8 (20.5) 37 (29.1) 29 (44.6) Female 59 (67.0) 31 (79.5) 90 (70.9) 36 (55.4) Age 26–39 7 (7.8) 1 (2.6) 8 (6.3) 5 (7.7) 40–54 18 (20.5) 14 (35.9) 32 (25.2) 22 (33.8) 55–69 47 (53.4) 16 (41.0) 63 (49.6) 30 (46.2) >70 16 (18.2) 8 (20.5) 24 (18.9) 8 (12.3) Average Age 58.7 (11.5) 59.0 (11.3) 59.0 (11.4) 56.7 (11.1) (Years, Standard deviation) Tumor Type Blood 12 (11.1) 1 (5.3) 13 (10.2) 3 (4.6) Breast 35 (39.8) 21 (53.8) 56 (44.1) 17 (26.2) Gastrointestinal 16 (18.2) 6 (15.4) 22 (17.3) 7 (10.8) Genitourinary 3 (3.4) 2 (5.1) 5 (3.9) 1 (1.5) Gynecological 2 (2.3) 2 (5.1) 4 (3.1) 5 (7.7) Head and neck 11 (12.5) 3 (7.7) 14 (11.0) 7 (10.8) Lung 1 (1.1) 1 (2.6) 2 (1.6) 2 (3.1) Neurological 6 (6.8) 1 (2.6) 7 (5.5) 6 (9.2) Skin 1 (0.9) 0 (0.0) 1 (0.8) 3 (4.6) Other 1 (0.9) 2 (10.5) 3 (2.4) 2 (3.1) Currently receiving treatment (while in exercise program) Yes 39 (44.3) 19 (48.7) 58 (45.7) 31 (47.7) No 49 (55.7) 20 (51.3) 69 (54.3) 34 (52.3) Cancer Treatment (received while in exercise program) Chemotherapy 17 (19.3) 7 (17.9) 24 (18.9) 10 (15.4) Radiation 7 (6.5) 0 (0.0) 7 (5.5) 4 (6.2) Hormone Therapy 10 (11.3) 11 (28.2) 21 (16.5) 10 (15.4) Biological Therapy 0 (0.0) 1 (2.6) 1 (0.8) 4 (6.2) Other 12 (13.6) 2 (5.1) 14 (11.0) 6 (9.2) Cancer Treatment (completed) Chemotherapy 57 (64.8) 18 (46.1) 75 (59.1) 40 (61.5) Radiation 47 (53.4) 25 (64.1) 72 (56.7) 34 (52.3) Hormone Therapy 6 (6.8) 2 (5.1) 8 (6.3) 3 (4.6) Biological Therapy 0 (0.0) 0 (0.0) 0 (0.0) 2 (3.1) Surgery 58 (65.9) 30 (76.9) 88 (69.3) 47 (72.3) Other 12 (13.6) 2 (5.1) 14 (11.0) 6 (9.2) Location of Residence Edmonton (urban) 62 (70.5) 31 (79.5) 93 (73.2) 53 (81.5) Catchment area 15–30 kms 24 (27.3) 4 (10.3) 28 (22.0) 6 (9.2) Catchment area 30–100 kms 2 (2.3) 3 (7.7) 5 (3.9) 5 (7.7) Rural > 100 kms 0 (0.0) 1 (2.6) 1 (0.8) 1 (1.5) Average km Commute 14.3 km N/A N/A 19.0 km Curr. Oncol. 2022, 29, 529 6741 3.2. Cancer Survivor Exercise Behaviours and Preferences during COVID-19 In response to the question ‘Would you have concerns about taking part in an exer- cise class delivered in-person this Fall?’ 56% (n = 71 of 127) of all respondents indicated ‘yes’ (Figure 1a). The majority of respondents who identified concern over in-person ex- ercise rated their level of concern for joining in-person exercise programming (fall 2020) from ‘Quite a bit’ to ‘Very Much’ (61%, n =43 of 71) (Figure 1b). All respondents identified barriers to attending in-person exercise programming related to personal safety and con- cerns over increased risk of COVID-19 exposure and transmission with an in-person ex- ercise setting. The identified risks included: environmental exposure; space and cleaning procedures (e.g., cleaning of equipment, physical distancing, ventilation, sharing of equip- ment, type of exercise); the burden of masking while exercising; and health-specific risks due to an immunocompromised status from cancer treatments and preexisting comorbid- ities. Figure 1. (a) Virtual and In-Person exercise preferences and reported exercise counsel by a healthcare professional. (b) Virtual and In-Person level of concern regarding in-person exercise in COVID-19. (c) Priority of exercise during COVID-19 and confidence ratings accessing virtual exer- cise and using electronic devices. In response to the question, ‘How much of a priority is exercise currently for you given COVID-19?’, responses were mixed with 45% (n = 57) reporting ‘Not at all’ or ‘Some- what’, and 55% (n = 70) reporting ‘Quite a bit’ or ‘Very Much’ (Figure 1c). The reported exercise frequency was: 1–2 times per week for 32% of respondents (n = 41); 3–4 times per week also for 32% (n = 41); greater than 5 times a week for 24% (n = 30) and ‘Not at all’ for 12% (n = 15). Current exercise environments were identified as: ‘self-exercise alone’ at 71% (n = 90); followed by ‘self-directed exercise with others’ (socially distanced walking, run- ning, biking) at 29% (n = 37). The three main types of exercise engaged in were reported as: (1) aerobic exercise at 78% (n = 99); (2) resistance exercise at 43% (n = 54); (3) and flexi- bility and stretching at 26% (n = 33). Thirteen percent (n = 17) of respondents were partak- ing in virtual exercise classes (live or prerecorded). Only 17% (n = 21) of respondents re- ported healthcare provider (HCP)-initiated counseling regarding exercise during COVID- 19 (Figure 1a). We explored the differences in rating barriers and facilitators between those who pri- oritized exercise (n = 70) compared to those who did not prioritize exercise (n = 57) during Curr. Oncol. 2022, 29, 529 6742 COVID-19. The only notable difference was those who did not prioritize exercise were more confident (self-identified as fairly to completely confident) using their electronic de- vice (n = 40 of 57, 71%) compared to those who prioritized exercise (n = 36 of 70, 51%). 3.3. ACE In-Person Participants and Virtual Exercise Programming For In-Person participants (n = 88), 73% (n = 64) indicated that they were ‘Not at all’ to at most ‘Somewhat’ confident participating in a virtual exercise program (Figure 1c). Communication applications such as Facetime, Skype and Zoom were identified by 20% (n = 18) of In-Person respondents to be used at least once a day. The majority, 61% (n = 54), ‘Agreed’ or ‘Strongly Agreed’ that the provision of technological support would increase their comfort in taking part in a virtual exercise program (Figure 2a). Responses to the statement, ‘Would knowing you have access to [technology] support change your will- ingness to take part in a virtual exercise program?’ can be divided into four categories (Figure 2b): (1) 42% (n = 37) responded ‘Yes, I WAS willing to take part in virtual program- ming before, and now I am even MORE willing to take part’; (2) 24% (n = 21) indicated ‘Yes, I was NOT willing to take part in virtual programming before, but now I am MORE willing to take part’; (3) 13% (n = 11) indicated, ‘No, a technical support staff has no effect on my choice to take part’; (4) 22% (n = 19) responded ‘NO—I was NOT willing to take part in virtual programming before, and I am still NOT willing to take part.’ Of the re- spondents who indicated technical support staff had no impact on their participation, 68% (n = 13 of 19) stated they were already comfortable with technology and did not need assistance (Figure 2c). Of all In-Person respondents, only 6% (n = 5) indicated they would not participate virtually regardless of technology support. Only one respondent indicated they did not have access to the technology needed to participate in exercise virtually. Pref- erences for virtual exercise program features were identified by In-Person respondents, in order of highest to least priority: (1) access to recordings of classes; (2) exercise descrip- tions provided prior to the class; (3) convenient class timing; (4) having an engaging in- structor; and (5) support for set up (including online platform, computer and set up of exercise space at home) (Figure 2d). Figure 2. In-Person virtual exercise and technology responses. (a) Willingness to take part in an exercise program with technology support available. (b) Technology support staff specified re- sponses for unchanged willingness. (c) Programming facilitators for virtual exercise engagement. (d) Comfort ratings with available technology support staff towards virtual exercise programming. Curr. Oncol. 2022, 29, 529 6743 3.4. ACE Virtual Participants and Virtual Exercise Programming Experience ACE spring 2020 online participants who took part in the survey (n = 19) responded to the statement ‘I experienced unique benefits taking part in the ACE virtual exercise program during the pandemic’, with 89% (n = 17) ‘Agreeing’ or ‘Strongly Agreeing’. These participants were provided with technology support in setting up and using their device to virtually participate in exercise programming, of which 63% (n = 12) ‘agreed’ or ‘strongly agreed’ technology support was beneficial. ACE online respondents did not identify any concerns regarding the virtual exercise program itself. Seventy-nine percent (n = 15 of 19) of respondents reported they had no difficulties accessing the virtual exercise program. Identified barriers to the virtual exercise programming were reported as a poor internet connection (16%, n = 3) and a lack of home exercise equipment (11%, n = 2). One respondent reported a lack of comfort using technology and a separate respondent re- ported their screen was too small to properly follow the virtual program. 3.5. Thematic Findings and Implementation Mapping to COM-B Model For the purposes of exploratory and qualitative analyses, participants were divided into two main groups: (1) respondents with in-person exercise experience alone (‘In-per- son’, n = 88); and (2) respondents with experience exercising in a virtual environment (‘Virtual’, n = 39), which included 19 respondents from the spring 2020 session as well as 20 respondents who had participated in-person in the fall 2019 and winter 2020 ACE study sessions as well. 3.5.1. In-Person Individuals with experience with in-person exercise alone identified three main per- ceived thematic barriers to attending virtual exercise classes: (1) accessibility: lack of tech- nology competency and limited space and exercise equipment at home; (2) effectiveness: virtual exercise programming viewed as less effective than in-person without personal- ized hands-on cuing, monitoring and corrections from the exercise instructor(s); less ef- fective in managing safety and treatment side effects; and (3) motivation: a perceived lack of accountability with no face-to-face interactions; a lack of social support/community; perceived invasion of privacy (home setting being seen on screen); and a loss of routine. For thematic findings refer to Figure 3A. Figure 3. Perceived Barriers and Identified Facilitators towards Virtual Exercise Programming. (A): Perceived Barriers to Virtual Exercise; (B): Identified Facilitators to Virtual Exercise Mapping of themes to the COM-B model corresponded with the following model components: (1) accessibility mapped to Capability: participant identified lack of Curr. Oncol. 2022, 29, 529 6744 knowledge and skills towards engaging with technology; (2) effectiveness mapped to Op- portunity: a lack of physically present social influences (instructors and other participants) and barriers of the local environmental context and resources; and (3) motivation mapped to Motivation: lack of optimism towards virtual exercise encounters. For thematic map- ping to COM-B, refer to Figure 4. Figure 4. Thematic Findings Mapped to COM-B Model with Clinically Actionable Items to Support Virtual Exercise Implementation. [36] 3.5.2. Virtual Individuals with experience exercising in the virtual environment identified three main thematic benefits to virtual exercise: (1) accessibility: pandemic-related safety; exer- cise comfort as no masking needed; (2) effectiveness: self-reported physical and mental health benefits including better coping with stress and cancer-related symptom burden reduction; an individualized approach maintained with exercise options in the group class; support for setting up home exercise space and home equipment (resistance bands provided); and (3) motivation: virtual exercise provided sense of community, support and encouragement. For thematic findings refer to Figure 3B. Mapping of themes to the COM-B corresponded with the following model domains: (1) accessibility mapped to Capability: virtual platform alleviated pandemic-related safety and masking concerns for participants to engage in exercise (2) effectiveness mapped to Opportunity: the virtual class structure facilitated a conducive environment with appro- priate resources and social support for participants to engage and exercise safely; and (3) motivation mapped to Motivation: virtual community environment facilitated optimism, and intrinsic goal setting and intentions towards virtual exercise encounters. For thematic mapping to COM-B, refer to Figure 4. 4. Discussion Survey findings showed that a majority of individuals with cancer who had taken part in the ACE program had limited experience engaging with virtual exercise—at a time when they were also uncomfortable attending in-person exercise due to COVID-19. This finding highlights the need for the consideration of alternative modes of exercise pro- gramming delivery. Home-based exercise programs have been previously reported to lack community and peer support, leading to reduced adherence and effectiveness in in- dividuals with cancer [41]. Virtual group exercise offers the promise of group support while maintaining social distancing, allowing the convenience of home (no travel time or costs) and increasing accessibility to individuals residing outside of urban centers [29,31]. A study examining the effectiveness of a virtual exercise oncology program, involving 491 Curr. Oncol. 2022, 29, 529 6745 cancer participants undergoing antineoplastic therapy between March and June 2020, re- ported significant benefits for psychological outcomes of improved feelings of support (58.7% increase, p < 0.05) and a significant decrease in loneliness (54% decrease, p < 0.05) [26]. A primary finding of this survey was that perceived barriers to virtual exercise pro- gramming by individuals without virtual exercise experience were identified as facilita- tors by those who had virtual experience. Virtual programming may be enhanced by con- sidering accessibility and capability options and underlying motivation to facilitate greater engagement. Our survey findings highlight that successful transition from in-per- son to virtual programming involves more than just offering virtual classes. A recent sur- vey of 593 cancer respondents found strong predictors of cancer survivors’ virtual engage- ment with HCPs to be access to, and past experiences with, interactive technologies for health-related purposes [42]. Successful transitioning to telehealth for exercise program- ming was found to be largely influenced by patients’ willingness (motivation) and capa- bility to use technology. The success of in-person programming for individuals with cancer may not neces- sarily correlate to successful virtual programs. Implementation efforts may need to spe- cifically address the nuance of virtual versus in-person exercise programming. Specifi- cally, time and resources may need to be allocated for the upskilling of technological com- petency and confidence, as well as program support (i.e., dedicated staff monitoring vir- tual exercise participant performance) to preserve service quality in a virtual setting. Ex- ercise professionals may need to adjust their approaches to match the limitations of virtual engagement and allot time to support the setup of an appropriate home virtual exercise environment. The availability of technology training support for participants could help increase willingness and comfort, and thus optimize motivation. A survey of 377 cancer partici- pants from the Macmillan Move More Northern Ireland (MMNI) exercise program inves- tigated the impact of COVID-19 on the physical activity patterns and attitudes towards digitally supported exercise in individuals with cancer [43]. MMNI pandemic program- ming offered ‘live’ virtual exercise sessions and a recorded exercise library available on YouTube. Sixty-two percent of respondents (n = 233 of 377) reported participating in ex- ercise virtually. Of the 38% of MMNI respondents (n = 144) who did not engage with vir- tual technology, 43% (n = 62 of 144) responded they were interested, with participants identifying a lack of technological proficiency/support as a barrier to participation. Given the older age of individuals with cancer at diagnosis [8], it is likely that many individuals have less experience and comfort with virtual environments. Lower computer literacy in combination with age has been reported as a barrier to virtual exercise engagement for individuals with cancer [44]. Thus, an aging cancer population with limited exposure to virtual platforms may warrant additional technology support for effective transition to virtual exercise programming. A growing body of evidence supports that successful telehealth implementation in- volves identifying user technology competencies to facilitate participation [45,46]. Provid- ing a standardized technological proficiency assessment tool for initial screening could preemptively identify participants who require further technology support [4]. A recent scoping review examining best practices in the implementation of telehealth-based cancer supportive care included 19 review papers and 23 telehealth guidance documents [28]. Findings concluded that factors related to both the user (cancer population) and the pro- vider (healthcare/supportive care providers) influence the acceptability and effectiveness of telehealth services. The findings suggest that for successful telehealth, providers need to focus on technology competency, device adequacy, participant confidence in utilizing or providing services, and mitigation of the impact on service quality. For clinically ac- tionable items to support virtual exercise implementation see Figure 4. Strengths of this study included a novel comparison of the perspectives of individu- als with cancer towards engaging in in-person and virtual exercise during a pandemic, Curr. Oncol. 2022, 29, 529 6746 after previous exercise participation. The online survey format allowed for a greater reach of participants (n = 127) and aligned with current COVID-19-related policies for avoiding in-person contact. Consistent with percentages from the overall ACE population, the ma- jority of respondents were female (71%, n = 90) and diagnosed with breast cancer (44%, n = 56), limiting generalizability to males and other tumor groups. The average age of re- spondents was 59 years, limiting generalizability to older cancer survivors; however, the average age is similar to the average age of participants (~58 years) in the overall ACE program (n = 2270). Non-respondents were slightly younger with a higher proportion of males, with a potential bias in those motivated to respond. All respondents had used an electronic format for patient-reported outcomes during their respective ACE program- ming (both in person and virtual), so there may be bias in terms of familiarity with the online response format. Additionally, fewer individuals had experience exercising virtu- ally compared to in-person, which offers the potential of skewed responses. The findings of this survey provide a perspective in understanding how cancer-spe- cific exercise programming delivery can be facilitated to meet the needs of individuals with cancer during a pandemic. The identified differences between In-Person versus Vir- tual programming highlight the need to create and deliver content matched to both the virtual platforms and to the participants’ levels of capability and confidence in technol- ogy. These survey findings indicate the potential benefit of providing dedicated technol- ogy support to increase the willingness to participate and engage with novel virtual exer- cise services. Supplementary Materials: The following supporting information can be downloaded at: www.mdpi.com/xxx/s1, Table: S1. Capability, Opportunity, Motivation-Behaviour (COM-B) Model1 Survey Question Mapping. Author Contributions: Conceptualization, K.S., M.L.M., C.S. T.S., E.P., S.N.C.-R. and A.A.J.; meth- odology, K.S and M.L.M.; software, K.S., T.S., C.S. and M.L.M.; validation, K.S., T.S., N.D. and M.L.M.; formal analysis, K.S. N.D. and M.L.M.; investigation, K.S., C.S. and M.L.M.; resources, M.L.M.; data curation, K.S., T.S. and M.L.M.; writing—original draft preparation, K.S. and M.L.M.; writing—review and editing, K.S., M.L.M., N.D., T.S., C.S., A.A.J., E.P. and S.N.C.-R.; visualization, K.S., N.D. and M.L.M.; supervision, M.L.M., E.P. and S.N.C.-R.; project administration, K.S. and M.L.M.; funding acquisition, M.L.M. All authors have read and agreed to the published version of the manuscript. Funding: We acknowledge the support and funding received from the Alberta Innovates Cancer Prevention Research Opportunity (Reference: 201500855) and the Alberta Cancer Foundation (Ref- erence: 27236) Institutional Review Board Statement: Institutional approval was received from the Health Re- search Ethics Board of Alberta: Cancer Committee (HREBA-CC: 16-0905: 05-May-2020) Informed Consent Statement: Informed consent was obtained from all subjects involved in the study. Data Availability Statement: The data on repository will be available on request to the correspond- ing author. Conflicts of Interest: The authors declare no conflict of interest. References 1. Bitar, H.; Alismail, S. The role of eHealth, telehealth, and telemedicine for chronic disease patients during COVID-19 pandemic: A rapid systematic review. Digit. Health 2021, 7, 20552076211009396. 2. Monaghesh, E.; Hajizadeh, A. The role of telehealth during COVID-19 outbreak: A systematic review based on current evidence. 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Virtual or In-Person: A Mixed Methods Survey to Determine Exercise Programming Preferences during COVID-19

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Article Virtual or In-Person: A Mixed Methods Survey to Determine Exercise Programming Preferences during COVID-19 1 1 1 1 2,3,4 2,3 Kirsten Suderman , Tara Skene , Christopher Sellar , Naomi Dolgoy , Edith Pituskin , Anil A. Joy , 5,6 1,2,7, Susan Nicole Culos-Reed and Margaret L. McNeely * Department of Physical Therapy, University of Alberta, Edmonton, AB T6G 2G4, Canada Department of Oncology, Faculty of Medicine, University of Alberta, Edmonton, AB T6G 2R3, Canada Cross Cancer Institute, Alberta Health Services, Edmonton, AB T6G 1Z2, Canada Faculty of Nursing, University of Alberta, Edmonton, AB T6C 1C9, Canada Cumming School of Medicine, University of Calgary, Calgary, AB T2N 4N1, Canada Faculty of Kinesiology, University of Calgary, Calgary, AB T2N 1N4, Canada Cancer Care Alberta, Alberta Health Services, Edmonton, AB T5J 3E4, Canada * Correspondence: mmcneely@ualberta.ca; Tel.: +1-780-248-1531 Abstract: A survey was conducted to identify barriers and facilitators to engaging in virtual and in- person cancer-specific exercise during COVID-19. A theory-informed, multi-method, cross-sec- tional survey was electronically distributed to 192 individuals with cancer investigating preferences towards exercise programming during COVID-19. Respondents had previously participated in an exercise program and comprised two groups: those who had experience with virtual exercise pro- gramming (‘Virtual’) and those who had only taken part in in-person exercise (‘In-Person’). Quan- titative data were summarized descriptively. Qualitative data were thematically categorized using framework analysis and findings were mapped to an implementation model. The survey comple- tion response rate was 66% (N= 127). All respondents identified barriers to attending in-person ex- ercise programming during COVID-19 with concerns over the increased risk of viral exposure. Vir- Citation: Suderman, K.; Skene, T.; tual respondents (n = 39) reported: (1) feeling confident in engaging in virtual exercise; and (2) en- Sellar, C.; Dolgoy, N.; Pituskin, E.; hanced motivation, accessibility and effectiveness as facilitators to virtual exercise. In-Person re- Joy, A.A.; Culos-Reed, S.N.; spondents (n = 88) identified: (1) technology as a barrier to virtual exercise; and (2) low motivation, McNeely, M.L. Virtual or In-Person: accessibility and exercise effectiveness as barriers towards virtual exercise. Sixty-six percent (n = 58) A Mixed Methods Survey to of In-Person respondents reported that technology support would increase their willingness to ex- Determine Exercise Programming ercise virtually. With appropriately targeted support, perceived barriers to accessing virtual exer- Preferences during COVID-19. cise—including motivation, accessibility and effectiveness—may become facilitators. The availabil- Curr. Oncol. 2022, 29, 6735–6748. https://doi.org/10.3390/ ity of technology support may increase the engagement of individuals with cancer towards virtual curroncol29100529 exercise programming. Received: 26 July 2022 Keywords: cancer; exercise; eHealth; implementation Accepted: 9 September 2022 Published: 20 September 2022 Publisher’s Note: MDPI stays neu- tral with regard to jurisdictional 1. Introduction claims in published maps and institu- The novel Coronavirus Disease 19 (COVID-19) pandemic significantly increased bar- tional affiliations. riers and disrupted in-person access to healthcare services for immunocompromised pop- ulations. Barriers to healthcare delivery from COVID-19 have led to a fundamental shift of patient–clinician interactions from primarily ‘in-person’, to options that include virtual Copyright: © 2022 by the authors. care, telehealth, telemedicine, or ‘eHealth’ [1–3]. While eHealth platforms have the poten- Submitted for possible open access tial to provide multidisciplinary care to vulnerable chronic disease populations and over- publication under the terms and con- come remote/rural settings [4], research is still novel and emerging around successful tele- ditions of the Creative Commons At- health implementation [5]. tribution (CC BY) license (https://cre- The disruption to service access negatively impacted individuals with cancer, who ativecommons.org/licenses/by/4.0/). are at increased risk for severe complications from COVID-19 due to Curr. Oncol. 2022, 29, 6735–6748. https://doi.org/10.3390/curroncol29100529 www.mdpi.com/journal/curroncol Curr. Oncol. 2022, 29, 529 6736 immunocompromised side effects of cancer therapies, comorbidities and advanced age [6,7]. With the population of individuals diagnosed and living with cancer continuing to rapidly grow worldwide [8,9], there is a widening gap of supportive care services to ad- dress the many acute and chronic side effects from cancer and cancer-related treatments [10–12]. Supportive care refers to services designed to meet the physical, emotional, social and practical needs of individuals across the cancer spectrum [13]. An extensive body of evidence, including 16 published guidelines from major medical or health-oriented or- ganizations globally, recognize exercise as beneficial for individuals with cancer across the cancer spectrum [14]. Regular exercise results in numerous physiological and psycho- social benefits for cancer survivors, including improved survival outcomes for common cancers, overall quality of life, cancer-related fatigue, cardiorespiratory fitness and mus- cular strength [14–16]. Given the strength of evidence supporting the benefits of exercise for the cancer population, targeted efforts are needed to integrate cancer-specific exercise programming into standard patient care [17–20], now exacerbated due to increased barri- ers to exercise presented by COVID-19 [21,22]. With the rapid pivot to eHealth virtual platforms, COVID-19 has provided a unique environment to understand cancer survivors’ perspectives on the virtual delivery of exer- cise programming. Program accessibility is a known barrier identified by individuals with cancer towards engaging in exercise (i.e. transportation, parking, facility type and loca- tion, time of day) [23]. While home-based exercise improves accessibility, home programs lack support from exercise professionals and peers, which survivors have identified as significant facilitators towards exercise [24]. There is promise for the use of virtual plat- forms to deliver accessible cancer-specific exercise programming remotely while main- taining exercise professional and social supports [25,26]. Continuing research during the pandemic has led to initiatives around the large-scale implementation of eHealth plat- forms focusing on parameters of engagement, such as feasibility, acceptability and effi- cacy [27–29]. Virtual service delivery may provide a means to avoid the unnecessary risks of viral transmission associated with in-person settings [30]; however, the ability of eHealth to meet the exercise needs of people with and recovering from cancer is unclear. Moreover, with the rapid transition to eHealth platforms for cancer supportive care ser- vices, there is limited understanding of the best practices for implementing and delivering cancer-specific virtual exercise programming [31]. 1.1. Research Context of the Clinical Team 1.1.1. Alberta Cancer Exercise Hybrid Effectiveness–Implementation (ACE) Study The present study was part of the integrated knowledge translation (iKT) series [32] of sub-studies from the Alberta Cancer Exercise Hybrid Effectiveness–Implementation (ACE) study. ACE is an implementation study that proposes a clinic-to-community model of care to support the implementation of cancer-specific, community-based, exercise pro- gramming; the protocol and findings are described elsewhere [33–35]. The study involves a 12-week exercise program for individuals diagnosed with any cancer. The ACE study pivoted to providing virtual exercise programming during the lockdowns associated with COVID-19. 1.2. Objective This study aimed to understand the facilitators/preferences and barriers towards ex- ercise during COVID-19 to inform ongoing cancer-specific exercise programming. Spe- cific objectives included an understanding of the perspectives of individuals who had pre- viously participated in standardized exercise towards (1) in-person and virtual exercise, and (2) the use of technology to access virtual exercise programming. Findings were in- tended to inform ACE maintenance programming in Northern Alberta during the pan- demic and support future clinical implementation of virtual exercise programming in the cancer setting. Curr. Oncol. 2022, 29, 529 6737 2. Materials and Methods 2.1. Study Design A cross-sectional survey was administered to individuals with cancer who had pre- viously participated in ACE programming at Northern Alberta sites (Edmonton, Grande Prairie, Fort McMurray and Red Deer) either in-person prior to the pandemic, or virtually during the pandemic. A multi-method approach using both quantitative and qualitative data was utilized to provide a more inclusive understanding of the participants’ perspec- tives towards in-person and virtual exercise during COVID-19, as well as the use of tech- nology to access virtual exercise programming. Survey questions were theory informed and designed based on implementation theory from the Capability, Opportunity, Moti- vation—Behaviour (COM-B) model [36]. Survey questions were mapped from each of the three model domains/constructs: (1) capability—an individual’s psychological (knowledge) and physical capacity (skills) to perform behaviours or activities; (2) oppor- tunity—physical (environment) or social factors (interpersonal influences) external to an individual that influence the behaviour; and (3) motivation—brain processes that direct behaviour (optimism, habitual and emotional responses, and analytical decision making) [36]. Survey questions included both multiple choice and short answers to comprehen- sively capture each COM-B model construct. For question mapping and survey questions see Supplementary Material Table S1. Demographic and medical information were previ- ously collected through the ACE study [33]. Ethics approval for this sub-study was granted by the Health Research Board of Alberta: Cancer Committee (HREBA.16-0905) and the intervention component was prospectively registered (NTC02984163). 2.2. Data Collection Participants were eligible to participate in the survey if: (1) they had enrolled in either fall 2019 or winter 2020 (both in-person), or spring 2020 (virtual) of the ACE 12-week can- cer-specific exercise program through sites in Edmonton, Fort McMurray, Red Deer or Grande Prairie; (2) had consented to future contact from the ACE research team; (3) had an active email address; and (4) had completed 12-week and, if applicable, 24-week post program ACE questionnaires. ‘In-Person’ are respondents who participated in ACE community-based classes prior to COVID-19 (fall 2019, winter 2020). ‘Virtual’ are those who participated virtually (live supervised online classes) during COVID-19 (either ACE spring 2020, or independently). Inclusion criteria for the ACE study required participants to: (1) have a diagnosis of cancer of any type; (2) be over the age of 18 years; (3) be able to participate in mild levels of activity at minimum; (4) be pretreatment or receiving active cancer treatment (e.g., sur- gery, systemic therapy and/or radiation therapy), or have received cancer treatment within the past 3 years or have existing long-term, or have late presenting effects of their cancer treatment (e.g., radiation fibrosis syndrome, lymphoedema, communication defi- cits related to cancer treatment or incontinence); and (5) be able to provide informed writ- ten consent in English. ACE classes involved a combination of aerobic, resistance, balance and flexibility exercises delivered in a standardized circuit-type class setting twice weekly for a minimum of 60 min per session for a 12-week period (approximately 3–4 metabolic equivalent units per session). For intervention description refer to Table 1. The ACE study protocol has been previously reported in detail elsewhere [33]. Curr. Oncol. 2022, 29, 529 6738 Table 1. Intervention description using the template for description and replication checklist (TI- DieR). Intervention Alberta Cancer Exercise (ACE) Hybrid Effectiveness Implementation Study [33] Why Exercise improves aerobic fitness, muscular strength and cancer-related symptoms Exercise studio for circuit classes: bands, free weights, mats, bender balls, bosu; Community fitness What: Materials centre or cancer-specific clinic for group personal training: treadmill, stationary bike, exercise machines (chest press, bicep curl, leg curl/extension, seated row, pullies) free weights and mats What: Procedures Providers Oversight: exercise physiologist or physical therapist. Instructor: qualified exercise professional How Supervised sessions of either standardized circuit-type class setting or group personal training Where Community-based exercise facilities and cancer-specific exercise clinics Type Aerobic, resistance, balance and flexibility exercises Intensity 3-4 metabolic equivalent (MET) units per session (360–480 MET-minutes/ week) Progression of inten- sity to 4–5 METs over the 12-week duration (480–600 MET-minutes/week 2-4 (light to somewhat heavy) on the 11-point Borg Rating of Perceived Exertion Scale Frequency Twice weekly Session time 60 minutes per session Overall duration 12-weeks Tailoring Adaptations to address cancer-related symptoms, muscular stiffness and dizziness, and prevent ad- verse events Trial fidelity Staff with training and experience in exercise oncology Exercise supervision Attendance tracked for number of completed sessions Monitoring of symptoms (e.g. fatigue, muscle soreness) Recording of minor and serious adverse events The ACE study pivoted to providing virtual exercise programming during COVID- 19. Virtual exercise programming classes were live, supervised and conducted over zoom within the context of the following parameters: (1) participants were provided with tech- nology support in setting up and using their device in preparation for virtual program- ming that involved orientation to the virtual platform, evaluating connectivity and trou- bleshooting any issues related to the virtual environment (i.e., location of device and alignment with the computer camera for facilitating monitoring of exercise performance); (2) all exercise sessions were conducted live over a consistent virtual platform (Zoom); (3) three intensity levels of each exercise (light, moderate, vigorous) were continuously demonstrated for participants by designated exercise professionals; (4) participants were directed to follow appropriate intensity levels and pin the instructor demonstrating the preferred level; (5) exercises were chosen that could be completed in home environments, focused on body weight exercises with consideration of limited space and equipment; (6) each virtual session was monitored by a qualified exercise professional who was respon- sible for monitoring performance, correcting exercise form and helping troubleshoot any technology issues etc.; (7) exercise resistance bands were provided for participants. Curr. Oncol. 2022, 29, 529 6739 The survey was active from August 2020–September 2020 to coincide with and in- form Northern Alberta fall 2020 and winter 2021 ACE exercise programming. The survey was administered electronically through Research Electronic Data Capture (REDCap), a secure, web-based application designed for research study data collection, provided by Women and Children’s Health Research Institute [37], hosted on a secure server in the University of Alberta’s Faculty of Medicine and Dentistry’s data centre. Eligible partici- pants were emailed a secure survey link through REDCap. 2.3. Data Analysis Data from the survey included both continuous and categorical variables. Basic de- scriptive statistics were generated by REDCap including frequencies, percentages and counts of responses to quantitative questions. Qualitative data from short answer and open-ended questions were analyzed using framework analysis, a form of content analy- sis to identify patterns in qualitative data, with a defining feature involving matrix out- puts of rows and columns of summarized data [38]. Framework analysis provides a prac- tical lens to answer specific questions with actionable outcomes, lending itself well to in- forming clinical and implementation practices [39]. Three researchers independently coded written responses (KS, MM, ND) into framework tables. After initial coding, re- searchers collaborated to amend and refine codes, and develop framework tables in rela- tion to patterns of barriers, facilitators and/or preferences towards exercise and technol- ogy. Themes were then mapped to respective domains of the COM-B Model to inform implementation strategies for local fall 2020 ACE exercise programming and future clini- cal practice [40]. 3. Results 3.1. Demographics A total of 127 cancer survivors responded (66% response rate), with 69% (n = 63) aged 55 and older, and 25% (n = 32) 40–55 years of age. The average age of respondents was 59 years (SD = 11.4). The most common cancer diagnosis was breast (44%, n = 56), followed by digestive cancer (17%, n = 22), and head and neck cancer (11%, n = 14). The majority of respondents were female (71%, n = 90), and 46% (n = 58) of all respondents were actively receiving treatment for cancer. Respondents mainly resided in an urban centre (n = 93, 73%) or within 15–30 kms of an urban centre (n = 28, 22%). The average commute to In- Person exercise programming was 14.3 km. Respondent demographics can be viewed in Table 2. As all survey recipients had previously participated in exercise programming through ACE, we were able to explore the characteristics of non-respondents compared to respondents. Non-respondents were slightly younger with an average age of 57 years of age (SD 11.1) compared to respondents (59 years, SD 11.4). A larger proportion of non- respondents were males (n = 29, 45%) compared to respondents (n = 37, 29%). Further details on non-respondent demographics can be viewed in Table 2. Curr. Oncol. 2022, 29, 529 6740 Table 2. Baseline Demographic and Medical Data. Respondent In-Person Exercise Virtual Exercise Total Non- Characteristics (Spring 2019–Winter 2020) (Spring 2020) Respondents Respondents n = 88, No. (%) n = 39, No. (%) n = 127, No. (%) n = 65, No. (%) Sex Male 29 (33.0) 8 (20.5) 37 (29.1) 29 (44.6) Female 59 (67.0) 31 (79.5) 90 (70.9) 36 (55.4) Age 26–39 7 (7.8) 1 (2.6) 8 (6.3) 5 (7.7) 40–54 18 (20.5) 14 (35.9) 32 (25.2) 22 (33.8) 55–69 47 (53.4) 16 (41.0) 63 (49.6) 30 (46.2) >70 16 (18.2) 8 (20.5) 24 (18.9) 8 (12.3) Average Age 58.7 (11.5) 59.0 (11.3) 59.0 (11.4) 56.7 (11.1) (Years, Standard deviation) Tumor Type Blood 12 (11.1) 1 (5.3) 13 (10.2) 3 (4.6) Breast 35 (39.8) 21 (53.8) 56 (44.1) 17 (26.2) Gastrointestinal 16 (18.2) 6 (15.4) 22 (17.3) 7 (10.8) Genitourinary 3 (3.4) 2 (5.1) 5 (3.9) 1 (1.5) Gynecological 2 (2.3) 2 (5.1) 4 (3.1) 5 (7.7) Head and neck 11 (12.5) 3 (7.7) 14 (11.0) 7 (10.8) Lung 1 (1.1) 1 (2.6) 2 (1.6) 2 (3.1) Neurological 6 (6.8) 1 (2.6) 7 (5.5) 6 (9.2) Skin 1 (0.9) 0 (0.0) 1 (0.8) 3 (4.6) Other 1 (0.9) 2 (10.5) 3 (2.4) 2 (3.1) Currently receiving treatment (while in exercise program) Yes 39 (44.3) 19 (48.7) 58 (45.7) 31 (47.7) No 49 (55.7) 20 (51.3) 69 (54.3) 34 (52.3) Cancer Treatment (received while in exercise program) Chemotherapy 17 (19.3) 7 (17.9) 24 (18.9) 10 (15.4) Radiation 7 (6.5) 0 (0.0) 7 (5.5) 4 (6.2) Hormone Therapy 10 (11.3) 11 (28.2) 21 (16.5) 10 (15.4) Biological Therapy 0 (0.0) 1 (2.6) 1 (0.8) 4 (6.2) Other 12 (13.6) 2 (5.1) 14 (11.0) 6 (9.2) Cancer Treatment (completed) Chemotherapy 57 (64.8) 18 (46.1) 75 (59.1) 40 (61.5) Radiation 47 (53.4) 25 (64.1) 72 (56.7) 34 (52.3) Hormone Therapy 6 (6.8) 2 (5.1) 8 (6.3) 3 (4.6) Biological Therapy 0 (0.0) 0 (0.0) 0 (0.0) 2 (3.1) Surgery 58 (65.9) 30 (76.9) 88 (69.3) 47 (72.3) Other 12 (13.6) 2 (5.1) 14 (11.0) 6 (9.2) Location of Residence Edmonton (urban) 62 (70.5) 31 (79.5) 93 (73.2) 53 (81.5) Catchment area 15–30 kms 24 (27.3) 4 (10.3) 28 (22.0) 6 (9.2) Catchment area 30–100 kms 2 (2.3) 3 (7.7) 5 (3.9) 5 (7.7) Rural > 100 kms 0 (0.0) 1 (2.6) 1 (0.8) 1 (1.5) Average km Commute 14.3 km N/A N/A 19.0 km Curr. Oncol. 2022, 29, 529 6741 3.2. Cancer Survivor Exercise Behaviours and Preferences during COVID-19 In response to the question ‘Would you have concerns about taking part in an exer- cise class delivered in-person this Fall?’ 56% (n = 71 of 127) of all respondents indicated ‘yes’ (Figure 1a). The majority of respondents who identified concern over in-person ex- ercise rated their level of concern for joining in-person exercise programming (fall 2020) from ‘Quite a bit’ to ‘Very Much’ (61%, n =43 of 71) (Figure 1b). All respondents identified barriers to attending in-person exercise programming related to personal safety and con- cerns over increased risk of COVID-19 exposure and transmission with an in-person ex- ercise setting. The identified risks included: environmental exposure; space and cleaning procedures (e.g., cleaning of equipment, physical distancing, ventilation, sharing of equip- ment, type of exercise); the burden of masking while exercising; and health-specific risks due to an immunocompromised status from cancer treatments and preexisting comorbid- ities. Figure 1. (a) Virtual and In-Person exercise preferences and reported exercise counsel by a healthcare professional. (b) Virtual and In-Person level of concern regarding in-person exercise in COVID-19. (c) Priority of exercise during COVID-19 and confidence ratings accessing virtual exer- cise and using electronic devices. In response to the question, ‘How much of a priority is exercise currently for you given COVID-19?’, responses were mixed with 45% (n = 57) reporting ‘Not at all’ or ‘Some- what’, and 55% (n = 70) reporting ‘Quite a bit’ or ‘Very Much’ (Figure 1c). The reported exercise frequency was: 1–2 times per week for 32% of respondents (n = 41); 3–4 times per week also for 32% (n = 41); greater than 5 times a week for 24% (n = 30) and ‘Not at all’ for 12% (n = 15). Current exercise environments were identified as: ‘self-exercise alone’ at 71% (n = 90); followed by ‘self-directed exercise with others’ (socially distanced walking, run- ning, biking) at 29% (n = 37). The three main types of exercise engaged in were reported as: (1) aerobic exercise at 78% (n = 99); (2) resistance exercise at 43% (n = 54); (3) and flexi- bility and stretching at 26% (n = 33). Thirteen percent (n = 17) of respondents were partak- ing in virtual exercise classes (live or prerecorded). Only 17% (n = 21) of respondents re- ported healthcare provider (HCP)-initiated counseling regarding exercise during COVID- 19 (Figure 1a). We explored the differences in rating barriers and facilitators between those who pri- oritized exercise (n = 70) compared to those who did not prioritize exercise (n = 57) during Curr. Oncol. 2022, 29, 529 6742 COVID-19. The only notable difference was those who did not prioritize exercise were more confident (self-identified as fairly to completely confident) using their electronic de- vice (n = 40 of 57, 71%) compared to those who prioritized exercise (n = 36 of 70, 51%). 3.3. ACE In-Person Participants and Virtual Exercise Programming For In-Person participants (n = 88), 73% (n = 64) indicated that they were ‘Not at all’ to at most ‘Somewhat’ confident participating in a virtual exercise program (Figure 1c). Communication applications such as Facetime, Skype and Zoom were identified by 20% (n = 18) of In-Person respondents to be used at least once a day. The majority, 61% (n = 54), ‘Agreed’ or ‘Strongly Agreed’ that the provision of technological support would increase their comfort in taking part in a virtual exercise program (Figure 2a). Responses to the statement, ‘Would knowing you have access to [technology] support change your will- ingness to take part in a virtual exercise program?’ can be divided into four categories (Figure 2b): (1) 42% (n = 37) responded ‘Yes, I WAS willing to take part in virtual program- ming before, and now I am even MORE willing to take part’; (2) 24% (n = 21) indicated ‘Yes, I was NOT willing to take part in virtual programming before, but now I am MORE willing to take part’; (3) 13% (n = 11) indicated, ‘No, a technical support staff has no effect on my choice to take part’; (4) 22% (n = 19) responded ‘NO—I was NOT willing to take part in virtual programming before, and I am still NOT willing to take part.’ Of the re- spondents who indicated technical support staff had no impact on their participation, 68% (n = 13 of 19) stated they were already comfortable with technology and did not need assistance (Figure 2c). Of all In-Person respondents, only 6% (n = 5) indicated they would not participate virtually regardless of technology support. Only one respondent indicated they did not have access to the technology needed to participate in exercise virtually. Pref- erences for virtual exercise program features were identified by In-Person respondents, in order of highest to least priority: (1) access to recordings of classes; (2) exercise descrip- tions provided prior to the class; (3) convenient class timing; (4) having an engaging in- structor; and (5) support for set up (including online platform, computer and set up of exercise space at home) (Figure 2d). Figure 2. In-Person virtual exercise and technology responses. (a) Willingness to take part in an exercise program with technology support available. (b) Technology support staff specified re- sponses for unchanged willingness. (c) Programming facilitators for virtual exercise engagement. (d) Comfort ratings with available technology support staff towards virtual exercise programming. Curr. Oncol. 2022, 29, 529 6743 3.4. ACE Virtual Participants and Virtual Exercise Programming Experience ACE spring 2020 online participants who took part in the survey (n = 19) responded to the statement ‘I experienced unique benefits taking part in the ACE virtual exercise program during the pandemic’, with 89% (n = 17) ‘Agreeing’ or ‘Strongly Agreeing’. These participants were provided with technology support in setting up and using their device to virtually participate in exercise programming, of which 63% (n = 12) ‘agreed’ or ‘strongly agreed’ technology support was beneficial. ACE online respondents did not identify any concerns regarding the virtual exercise program itself. Seventy-nine percent (n = 15 of 19) of respondents reported they had no difficulties accessing the virtual exercise program. Identified barriers to the virtual exercise programming were reported as a poor internet connection (16%, n = 3) and a lack of home exercise equipment (11%, n = 2). One respondent reported a lack of comfort using technology and a separate respondent re- ported their screen was too small to properly follow the virtual program. 3.5. Thematic Findings and Implementation Mapping to COM-B Model For the purposes of exploratory and qualitative analyses, participants were divided into two main groups: (1) respondents with in-person exercise experience alone (‘In-per- son’, n = 88); and (2) respondents with experience exercising in a virtual environment (‘Virtual’, n = 39), which included 19 respondents from the spring 2020 session as well as 20 respondents who had participated in-person in the fall 2019 and winter 2020 ACE study sessions as well. 3.5.1. In-Person Individuals with experience with in-person exercise alone identified three main per- ceived thematic barriers to attending virtual exercise classes: (1) accessibility: lack of tech- nology competency and limited space and exercise equipment at home; (2) effectiveness: virtual exercise programming viewed as less effective than in-person without personal- ized hands-on cuing, monitoring and corrections from the exercise instructor(s); less ef- fective in managing safety and treatment side effects; and (3) motivation: a perceived lack of accountability with no face-to-face interactions; a lack of social support/community; perceived invasion of privacy (home setting being seen on screen); and a loss of routine. For thematic findings refer to Figure 3A. Figure 3. Perceived Barriers and Identified Facilitators towards Virtual Exercise Programming. (A): Perceived Barriers to Virtual Exercise; (B): Identified Facilitators to Virtual Exercise Mapping of themes to the COM-B model corresponded with the following model components: (1) accessibility mapped to Capability: participant identified lack of Curr. Oncol. 2022, 29, 529 6744 knowledge and skills towards engaging with technology; (2) effectiveness mapped to Op- portunity: a lack of physically present social influences (instructors and other participants) and barriers of the local environmental context and resources; and (3) motivation mapped to Motivation: lack of optimism towards virtual exercise encounters. For thematic map- ping to COM-B, refer to Figure 4. Figure 4. Thematic Findings Mapped to COM-B Model with Clinically Actionable Items to Support Virtual Exercise Implementation. [36] 3.5.2. Virtual Individuals with experience exercising in the virtual environment identified three main thematic benefits to virtual exercise: (1) accessibility: pandemic-related safety; exer- cise comfort as no masking needed; (2) effectiveness: self-reported physical and mental health benefits including better coping with stress and cancer-related symptom burden reduction; an individualized approach maintained with exercise options in the group class; support for setting up home exercise space and home equipment (resistance bands provided); and (3) motivation: virtual exercise provided sense of community, support and encouragement. For thematic findings refer to Figure 3B. Mapping of themes to the COM-B corresponded with the following model domains: (1) accessibility mapped to Capability: virtual platform alleviated pandemic-related safety and masking concerns for participants to engage in exercise (2) effectiveness mapped to Opportunity: the virtual class structure facilitated a conducive environment with appro- priate resources and social support for participants to engage and exercise safely; and (3) motivation mapped to Motivation: virtual community environment facilitated optimism, and intrinsic goal setting and intentions towards virtual exercise encounters. For thematic mapping to COM-B, refer to Figure 4. 4. Discussion Survey findings showed that a majority of individuals with cancer who had taken part in the ACE program had limited experience engaging with virtual exercise—at a time when they were also uncomfortable attending in-person exercise due to COVID-19. This finding highlights the need for the consideration of alternative modes of exercise pro- gramming delivery. Home-based exercise programs have been previously reported to lack community and peer support, leading to reduced adherence and effectiveness in in- dividuals with cancer [41]. Virtual group exercise offers the promise of group support while maintaining social distancing, allowing the convenience of home (no travel time or costs) and increasing accessibility to individuals residing outside of urban centers [29,31]. A study examining the effectiveness of a virtual exercise oncology program, involving 491 Curr. Oncol. 2022, 29, 529 6745 cancer participants undergoing antineoplastic therapy between March and June 2020, re- ported significant benefits for psychological outcomes of improved feelings of support (58.7% increase, p < 0.05) and a significant decrease in loneliness (54% decrease, p < 0.05) [26]. A primary finding of this survey was that perceived barriers to virtual exercise pro- gramming by individuals without virtual exercise experience were identified as facilita- tors by those who had virtual experience. Virtual programming may be enhanced by con- sidering accessibility and capability options and underlying motivation to facilitate greater engagement. Our survey findings highlight that successful transition from in-per- son to virtual programming involves more than just offering virtual classes. A recent sur- vey of 593 cancer respondents found strong predictors of cancer survivors’ virtual engage- ment with HCPs to be access to, and past experiences with, interactive technologies for health-related purposes [42]. Successful transitioning to telehealth for exercise program- ming was found to be largely influenced by patients’ willingness (motivation) and capa- bility to use technology. The success of in-person programming for individuals with cancer may not neces- sarily correlate to successful virtual programs. Implementation efforts may need to spe- cifically address the nuance of virtual versus in-person exercise programming. Specifi- cally, time and resources may need to be allocated for the upskilling of technological com- petency and confidence, as well as program support (i.e., dedicated staff monitoring vir- tual exercise participant performance) to preserve service quality in a virtual setting. Ex- ercise professionals may need to adjust their approaches to match the limitations of virtual engagement and allot time to support the setup of an appropriate home virtual exercise environment. The availability of technology training support for participants could help increase willingness and comfort, and thus optimize motivation. A survey of 377 cancer partici- pants from the Macmillan Move More Northern Ireland (MMNI) exercise program inves- tigated the impact of COVID-19 on the physical activity patterns and attitudes towards digitally supported exercise in individuals with cancer [43]. MMNI pandemic program- ming offered ‘live’ virtual exercise sessions and a recorded exercise library available on YouTube. Sixty-two percent of respondents (n = 233 of 377) reported participating in ex- ercise virtually. Of the 38% of MMNI respondents (n = 144) who did not engage with vir- tual technology, 43% (n = 62 of 144) responded they were interested, with participants identifying a lack of technological proficiency/support as a barrier to participation. Given the older age of individuals with cancer at diagnosis [8], it is likely that many individuals have less experience and comfort with virtual environments. Lower computer literacy in combination with age has been reported as a barrier to virtual exercise engagement for individuals with cancer [44]. Thus, an aging cancer population with limited exposure to virtual platforms may warrant additional technology support for effective transition to virtual exercise programming. A growing body of evidence supports that successful telehealth implementation in- volves identifying user technology competencies to facilitate participation [45,46]. Provid- ing a standardized technological proficiency assessment tool for initial screening could preemptively identify participants who require further technology support [4]. A recent scoping review examining best practices in the implementation of telehealth-based cancer supportive care included 19 review papers and 23 telehealth guidance documents [28]. Findings concluded that factors related to both the user (cancer population) and the pro- vider (healthcare/supportive care providers) influence the acceptability and effectiveness of telehealth services. The findings suggest that for successful telehealth, providers need to focus on technology competency, device adequacy, participant confidence in utilizing or providing services, and mitigation of the impact on service quality. For clinically ac- tionable items to support virtual exercise implementation see Figure 4. Strengths of this study included a novel comparison of the perspectives of individu- als with cancer towards engaging in in-person and virtual exercise during a pandemic, Curr. Oncol. 2022, 29, 529 6746 after previous exercise participation. The online survey format allowed for a greater reach of participants (n = 127) and aligned with current COVID-19-related policies for avoiding in-person contact. Consistent with percentages from the overall ACE population, the ma- jority of respondents were female (71%, n = 90) and diagnosed with breast cancer (44%, n = 56), limiting generalizability to males and other tumor groups. The average age of re- spondents was 59 years, limiting generalizability to older cancer survivors; however, the average age is similar to the average age of participants (~58 years) in the overall ACE program (n = 2270). Non-respondents were slightly younger with a higher proportion of males, with a potential bias in those motivated to respond. All respondents had used an electronic format for patient-reported outcomes during their respective ACE program- ming (both in person and virtual), so there may be bias in terms of familiarity with the online response format. Additionally, fewer individuals had experience exercising virtu- ally compared to in-person, which offers the potential of skewed responses. The findings of this survey provide a perspective in understanding how cancer-spe- cific exercise programming delivery can be facilitated to meet the needs of individuals with cancer during a pandemic. The identified differences between In-Person versus Vir- tual programming highlight the need to create and deliver content matched to both the virtual platforms and to the participants’ levels of capability and confidence in technol- ogy. These survey findings indicate the potential benefit of providing dedicated technol- ogy support to increase the willingness to participate and engage with novel virtual exer- cise services. Supplementary Materials: The following supporting information can be downloaded at: www.mdpi.com/xxx/s1, Table: S1. Capability, Opportunity, Motivation-Behaviour (COM-B) Model1 Survey Question Mapping. Author Contributions: Conceptualization, K.S., M.L.M., C.S. T.S., E.P., S.N.C.-R. and A.A.J.; meth- odology, K.S and M.L.M.; software, K.S., T.S., C.S. and M.L.M.; validation, K.S., T.S., N.D. and M.L.M.; formal analysis, K.S. N.D. and M.L.M.; investigation, K.S., C.S. and M.L.M.; resources, M.L.M.; data curation, K.S., T.S. and M.L.M.; writing—original draft preparation, K.S. and M.L.M.; writing—review and editing, K.S., M.L.M., N.D., T.S., C.S., A.A.J., E.P. and S.N.C.-R.; visualization, K.S., N.D. and M.L.M.; supervision, M.L.M., E.P. and S.N.C.-R.; project administration, K.S. and M.L.M.; funding acquisition, M.L.M. All authors have read and agreed to the published version of the manuscript. 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Journal

Current Oncology – Multidisciplinary Digital Publishing Institute

Published: Sep 20, 2022

Keywords: cancer; exercise; eHealth; implementation

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