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Special Communication

Measuring the Feasibility and Effectiveness of an Individualized Exercise Program Delivered Virtually to Cancer Survivors

Wonders, Karen Y. PhD, FACSM1,2; Gnau, Kara BS2; Schmitz, Kathryn H. PhD, MPH, FACSM3

Author Information
Current Sports Medicine Reports: May 2021 - Volume 20 - Issue 5 - p 271-276
doi: 10.1249/JSR.0000000000000846
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Abstract

Introduction

Decades of research have established that exercise is safe and effective in a cancer population (1–3). In the past, we have advocated for supervised, individualized exercise training taking place in-person (4). Research indicates that this form of training results in improved health outcomes, as evidenced by increases in aerobic fitness, muscular strength and body composition (5–7), reduced symptom severity (8), and decreased health care costs (9).

However, when faced with the COVID-19 global pandemic in the spring of 2020, social distancing guidelines made it impossible to carry out in-person exercise oncology sessions in this traditional format. Across the globe, practitioners were forced to make the decision to suspend their services altogether or adapt their exercise programming to a virtual model.

Our exercise oncology program made the decision to pivot to a virtual training model, in the hopes of keeping our patients engaged and active while still adhering to social distancing guidelines. It was expected that this quick change in the delivery of our exercise programs would be met with some barriers. That stated, we hypothesized that virtual exercise training would be feasible and safe, increase feelings of patient support, improve fitness parameters, and reduce symptom severity.

Methods

Subjects

This pre-post intervention trial evaluated the effects of individualized exercise therapy delivered in a virtual format to 491 patients undergoing antineoplastic treatment. Oncology patients who received treatment at Kettering Medical Center in Dayton, Ohio between March and June 2020 participated in a cancer exercise program through Maple Tree Cancer Alliance, a nonprofit organization that provides free exercise training to people living with and beyond cancer. Eligible patients received written information about the study and gave informed consent to participate. All study procedures were approved by the partner hospital's institutional review board prior to the onset of data collection.

Measures

One time each week, participants meet with their certified exercise oncology trainer in a virtual format, 1:1, via “Zoom”, “Skype”, or “FaceTime”. At the initial visit, demographic information, medical history, and relevant clinical data were ascertained from all consenting participants. Participants then completed a subjective symptom checklist, which was previously evaluated in a similar cancer population (10). This checklist was used to gauge the severity of treatment-related side effects and consisted of 35 items of severity graded from “no” to “very severe” [0–10]. The 35 items on the subjective symptom checklist are presented in Table 1. Finally, each participant completed the McGill Quality of Life questionnaire (11).

Table 1 - Subjective symptom checklist.
Pain
Fatigue
Nausea
Depression
Anxiety
Drowsiness
Appetite
Well-being
Shortness-of-breath
Difficulty concentrating
Lack of energy
Cough
Fear for the future
Feelings of control
Sense of purpose
Mouth sores
Change in the way food tastes
Weight loss
Hair loss
Constipation
Swelling of arms or legs
Changes in skin
Numbness/tingling in hands or feet
Difficulty sleeping
Feeling bloated
Problems with urination
Vomiting
Diarrhea
Sweats
Feeling sad
Problems with sexual interest or activity
Itching
Lack of appetite
Dizziness
Difficulty swallowing

Prior to the start of quarantine, patients who had already been enrolled at Maple Tree Cancer Alliance underwent a comprehensive fitness assessment (n = 423). Cardiovascular fitness was measured via the Rocky Mountain Cancer Rehabilitation Institute Multistage Treadmill Protocol for Cancer Survivors (12). The modified sit and reach test measured flexibility. Muscular endurance was assessed via partial curl up test. Body composition was measured via skinfold assessment. Muscular strength was determined via hand grip dynamometer. Height and weight measurements were used to calculate body mass index. Balance, circumference, and posture also were measured. These 423 patients participated in the supervised, in-person training for varying lengths of time before social distancing guidelines were enacted, ranging from 3 wk to less than 1 wk (average was 2.3 visits prior to quarantine beginning). All of these patients then took part in the virtual exercise training once quarantine began.

An additional 68 patients started their exercise program at Maple Tree in a virtual format once quarantine began in March of 2020. For these patients, we created a virtual fitness assessment to determine strengths and weaknesses, and to assist in program development. This virtual assessment included the Timed Get up and Go test, which was used as an alternative to the treadmill test for patients. This assessment is already used in practice at Maple Tree Cancer Alliance for patients who are at an elevated level of falling. The test is conducted using a chair (preferably without arms and without wheels), a stopwatch, and two objects spaced 3 m apart. From a sitting position, patients will stand without using their arms for support and walk forward 10 ft (3 m), turn around and return to the chair where they will take a seat without using their arms for support. Patients who cannot complete the test in under 10 s or demonstrate unsteadiness would be at an increased risk of falls. In addition, the partial curl-up test was used to measure muscular endurance (using anatomical references for assist in the curl-up), modified sit and reach measured flexibility, and self-reported height and weight measures were used to determine body mass index. Balance and posture were assessed by the exercise trainer, virtually. Finally, when possible, circumference measurements were made by the patient under the direct supervision and instruction of the exercise trainer.

After the assessment, an audit was performed with each participant to determine the availability of fitness equipment in their home. Results from this audit and the fitness assessment were used to create an individualized exercise program that focused on each patient's specific goals, as well as their strengths and weaknesses.

Exercise Training Protocol

Each patient completed 12 wk of prescribed, individualized exercise that included cardiovascular, resistance, and flexibility training. They met with their trainer virtually once each week. The intensity level for the cardiovascular exercise ranged from 30% to 45% of the individual's predicted V̇O2max,. The Karvonnen Formula [(Max HR − Resting HR) * % + Resting HR] was used to determine exercise intensity, using estimated maximum heart rate based on the participant's age. The goal was for participants to do approximately 30 min/session of cardiovascular training, with the goal of achieving 150 min total for the week. The strength training involved a full body workout, with emphasis on all major muscle groups. Free weights, tubing, and body weight exercises were all used, depending on equipment availability in their home. Patients completed three sets of 10 repetitions for each resistance exercise. Flexibility training involved static stretching of all major muscle groups for 15 s to 20 s at the completion of each workout. Patients also were given instructions on how to remain active the rest of the week on their own. Exercise trainers remained in contact with their patients throughout the week to monitor activity levels and encourage the patient to move. The activity level of the patient was noted in each patient's chart and used to guide the virtual exercise programming.

Strict stay-at-home measures were in place in Dayton, Ohio for exactly 12 wk, beginning March 16, 2020, and ending on June 5, 2020. On June 8, we were able to resume in-person exercise training (with social distancing measures in place and physician approval) for patients who felt comfortable with it. Of the 491 patients in this virtual study, 223 opted to return to in-person training. The remaining 268 patients chose to stay with virtual exercise training.

The 223 patients who resumed in-person training underwent a follow-up reassessment and completed the subjective symptom checklist. Participants who opted to remain virtual completed these assessments once they had completed 12 wk of training. Finally, all participants were given the option to participate in a phone interview conducted by an independent investigator to determine the effectiveness of their virtual exercise experience.

To account for the varying lengths of time patients spent in in-person and virtual training, we analyzed all study measures two ways — pre-post intervention and also as four separate groups of patients in this study: in-person to virtual to in-person, in-person to virtual to virtual, virtual to in-person, and virtual to virtual. These, along with each individual group numbers, are detailed in Table 2.

Table 2 - Groups defined.
Group Pathway n
Group 1 In-person > > virtual > > in-person 208
Group 2 In-person > > virtual > > virtual 215
Group 3 Virtual > > in-person 15
Group 4 Virtual > > virtual 53

Statistical Methods

A post hoc power analysis was calculated for this sample of convenience (http://clincalc.com/stats/Power.aspx) for this within group comparison. With an alpha = 0.05 and power = 0.80, the effect size was considered to be extremely large using Cohen's (1988) criteria. Thus, our sample size of N = 491 was more than adequate for the main objective of this study. Exercise adherence was measured by calculating the percentage of sessions attended/scheduled. Assessment scores, subjective symptom data, and quality of life parameters were analyzed using Statistical Package for Social Sciences version 20.0 for PC Windows 2000. Mean scores were calculated for the complete sample and evaluated via analysis of variance. Within and between groups differences were determined using multivariate analysis of variance. A significance level of P ≤ 0.05 was used for all statistical analyses.

Results

Participants in the virtual exercise program included a total of 491 individuals. Participants' ages ranged from 14 to 83 years, with a mean age of 60 years (Table 3). Participants completed 4949 of the 5892 prescribed supervised exercise sessions, which yielded an adherence rate of 84%. This was slightly lower than our in-person adherence rates, which is typically around 89% to 90%. A total of 18 (3.5%) participants withdrew from the intervention before completion. Reasons behind the withdrawal were related to unexpected health and family problems or, in one case, because of Internet connection issues which could not be solved. There were no adverse events related to virtual training reported by any of the participants.

Table 3 - Patient characteristics.
Average Age, yr 60 ± 0.05
Sex
Male 16%
Female 84%
Ethnicity
White 74.69%
African American 10.23%
Hispanic 3.91%
Asian 5.67%
Unknown 4.39%
Type of cancer
Breast 58.15%
Colon 4.49%
Prostate 1.97%
Lung 3.93%
Leukemia 0.28%
Brain 0.84%
Multiple myeloma 2.25%
Other 29.08%

Fitness Parameters

Twelve weeks of supervised, individualized exercise delivered in a virtual format had a positive impact on fitness parameters. Specifically, patients experienced significant improvements in cardiovascular endurance (15.2% increase, P < 0.05), muscular endurance (18.2% increase, P < 0.05), and flexibility (31.9% increase, P < 0.05, Fig. 1). Patients who completed the Timed Get up and Go Assessment saw a 27.5% decrease in their time (pretest score was 13.1 s, posttest score was 9.5 s, P < 0.05). Significant differences were not measured within the separate groups accounting for the differing start times (Table 4).

Figure 1
Figure 1:
Changes in fitness parameters from pre-post exercise programming. Values are mean scores + SE, V̇O2 in mL·kg−1·min−1, muscular endurance in repetitions, muscular strength in psi, flexibility in inches (n = 491). *P < 0.05.
Table 4 - Group comparison of study variables.
Parameter Overall, % Group 1, % Group 2, % Group 3, % Group 4, %
Timed get up and go 27.50 25.89 28.30 26.38 29.30
Cardiovascular endurance 15.20 15.20 n/a n/a n/a
Muscular endurance 18.20 17.90 19.20 18.69 16.87%
Flexibility 31.90 32.87 30.45 31.20 32.96
Feelings of support 58.70 60.76 59.30 56.77 57.89
Quality of life 32.20 29.88 30.70 34.79 33.42
Feelings of loneliness −54 −52.40 −54.68 −53.41 −55.31
Fatigue −48.70 −49.92 −48.77 −46.79 −49.40
n/a, not applicable.

Psychological Parameters

Psychological measures indicated that the virtual exercise training was a positive experience for our patients. This translated into significant improvements in fatigue levels (48.7% decrease, P < 0.05), feelings of support (58.7% increase, P < 0.05), quality of life (32.2% increase, P < 0.05), and a significant decrease in loneliness (54% decrease, P < 0.05). These values are presented in Table 5.

Table 5 - Psychological parameters.
Parameter Overall, % Group 1, % Group 2, % Group 3, % Group 4, %
Fatigue −48.70* −49.92 −48.77 −46.79 −49.40
Feelings of support 58.7* 60.76 59.30 56.77 57.89
Quality of life 32.22* 29.88 30.70 34.79 33.42
Loneliness −54* −52.40 −54.68 −53.41 −55.31
Values are mean scores ± SE. *P < 0.05.

Feasibility of Virtual Training

Consenting participants were contacted by an independent third-party to gain perspective on their experiences in virtual training through a phone interview. Of the 491 patients who participated in our virtual training, 304 chose to participate in the interview (62% response rate).

The majority of patients surveyed used their cell phone to attend their virtual sessions (46%), while the remainder used a laptop (28%), tablet (22%), or desktop (4%). While patients were given the option of selecting the delivery of the virtual program, based on their level of comfort, 67% selected “Zoom” or “Skype.” The remainder utilized “FaceTime” (21%), and a small minority (12%) opted for a phone call.

In terms of exercise intensity, 67.3% of patients reported that they felt the intensity of their virtual training was the same as it was in person, while 12.3% of patients thought it was a harder intensity and 21.4% of patients thought it was an easier intensity (Fig. 2).

Figure 2
Figure 2:
Intensity level comparison. Comparing intensity level of visual exercise sessions to in-person exercise training.

Of note, 30% of patients surveyed reported no real challenges during virtual training. For the remainder, 20.4% reported minor technical issues. Another 18.3% of respondents cited the challenge of simply “getting used to” virtual instruction. Encouragingly, 98% of those who completed the interview shared that they enjoyed virtual training. Of these, 92.8% stated that they would continue to virtual training, should the pandemic continue indefinitely.

Discussion

The purpose of this investigation was to determine the feasibility, acceptability, and effectiveness of an exercise oncology program, delivered virtually. For this study, all patients previously involved with the Maple Tree Cancer Alliance were invited to participate in this home-based, virtual exercise program for 12 wk. After the 12-wk program, the overall patient adherence to virtual training was calculated at 84%. In addition, significant improvements in fitness parameters and psychological health were measured.

Previous studies have found home-based exercise programs to be effective and feasible in chronic disease populations, including cardiac (10–15), claudication (16,17), peripheral artery disease (17), and even thyroid (18), lung (19), pancreatic (20), and breast cancer (21). Many of these home-based exercise programs have yielded increases in physical activity participation and aerobic fitness, and decreased adverse effects of medication related to their chronic condition. Conversely, sedentary behavior is associated with mortality, risk of depression, and adverse effects on health and well-being in older adults (22,23).

Psychological Health

Previous literature has shown that intrinsically motivated people tend to engage in physical activity for personal improvement and enjoyment (24). Enjoyment of physical activity is believed to enhance motivation and foster long-term exercise adherence (25). We felt that this was important, given the average age of our population, and the fact that they had to adapt to virtual technology essentially overnight. Encouragingly, our 84% adherence rate represents a positive patient experience. Further, more than 80% of the patients who participated in the virtual exercise training adapted rather quickly. A minority of respondents (18.2%) reported needing some time to get used to the technology.

We observe that social features likely played a part in motivating patient participation to training sessions (26). Given the circumstances under which this study took place (during a global pandemic where patients were under quarantine), it is likely that the frequent contact with participants via technology helped to decrease loneliness and increase feelings of support. Together, this likely positively impacted quality of life. Frequent contact via telephone or other virtual means is common practice in clinical evaluation studies involving older adults, where social visits are often encouraged as a way to provide attention (27,28). It is possible that the effect of our virtual contact was strong enough to produce a significant decrease in participants' perception of loneliness during quarantine and improve feelings of support. Indeed, previous work with similar intervention periods (6–15 wk) has achieved significant reductions of loneliness, but also has included the physical presence of educators, trainers, and peers during the intervention (29).

Fitness Parameters

In our study, patients experienced significant improvements in fitness parameters. We attribute these improvements to our high adherence rates and intensity level of the virtual workout. Of those surveyed, 79.3% reported that intensity levels were the same or higher than their in-person training appointments. In previous studies, virtual programs aimed at promoting physical activity in older adults have demonstrated the potential to improve health and functional performance (30). This appears to be independent of the initial fitness level of the participant; however, those with a higher fitness level at the start of the intervention do tend to have a higher adherence to the training (31). These results suggest that the virtual exercise programming could potentially overcome a major issue reported in the literature in terms of the motivation level of participants. In addition, since our study included current patients in our program, it may have helped reduce the effect of the initial level of skill in the motivation of participants, with trainees complying to the overall norm of the organization.

Limitations

The complexity of the study setting resulted in limitations that are acknowledged in the following:

Different Entry Points to the Study

Given the circumstances in which this study took place and the sudden pivot from an in-person to a virtual model, study participants entered the virtual training at different times. Further, when in-person training was allowed again, study participants transitioned out of the virtual model at various time points. We tried to account for this by examining between and within group differences statistically, and by measuring their fitness and psychological parameters after each individual completed 12 wk of training, virtually.

Different Tools for Support

The virtual training sessions between the exercise oncology instructor and the participants were designed to give the same type of support, but did vary among the participant's comfort level with the technology. The majority of patients opted to complete their sessions via Zoom/Skype (67%) or through FaceTime (21%). However, a small percent of patients opted for a phone call (12%). This difference in the communication might have introduced a potential bias in the fitness and psychological outcomes of the study. Further, measuring objective fitness levels via Zoom was a limitation for this study. There are no existing studies that can validate that results of the assessment undertaken would be the same in-person and virtually. That said, any bias was likely similar for both measures and is unlikely to have impacted our findings. Future studies should include the use of wearable technology to quantify intensity levels.

Sex Imbalance

The sex imbalance, resulting in a skewed female-to-male ratio, also should be noted as a potential limitation. Previous studies, however, provide evidence in favor of the generalization of our results, noting that males and females respond similarly to exercise interventions, despite differences in initial motives for participation (27).

Conclusions

While there were some challenges reported when pivoting from an in-person training format to an entirely virtual format, our data support the conclusion that, overall, it was a positive experience for patients, based on qualitative feedback and the improvements in fitness and psychosocial outcomes. Our results indicate that exercise intensity levels are perceived to be similar to in-person training and result in improved fitness parameters. Further, the virtual training offered our patients a form of support they might not have otherwise had during a time of national quarantine. Given the current state of our public health crisis, we assert that virtual exercise training is a viable option in circumstances where in-person, individualized exercise training is not possible.

The authors declare no conflict of interest and do not have any financial disclosures.

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