Background

More than 12 million Americans are cancer survivors living with one or more comorbid chronic conditions (e.g., type 2 diabetes, cardiovascular diseases) [1]. Compared with cancer survivors without chronic conditions, cancer survivors with Multiple Chronic Conditions (MCC) have a significantly higher prevalence and severity of symptoms [2-6]. Resilience, an ability to resist, recover, or rebound from stressors, [7] influences the perception of symptoms including fatigue and depression [813]. People with high resilience report lower depression, fatigue, and better physical functioning than those with low resilience [7,14-16]. MCC-related symptoms affect individuals’ functional capacity, quality of life, and a higher risk of premature death than those without symptoms [17,18]. Active participation by persons is paramount in the effective management of MCC-related symptoms, which are long-term, variable, and often degenerative. Low-income persons are more likely to not adhere to the disease and symptoms management recommendations due to financial limitations and lack of accessibility to the facility [19]. As such, self-management intervention programs that provide persons and their families with information and skills that enhance their ability to participate in their health care (e.g., symptom management, treatment adherence) and that consider individual context and goals are increasingly recognized not only as an essential component of chronic illness management but also as part of secondary prevention and a way of reducing the burden of chronic illness on individuals and the community.

 Increasing Physical Activity (PA) is one of the most effective interventions for managing chronic conditions and symptoms, and for improving one’s health [20]. Studies have shown that a continuous aerobic moderate-intensity exercise program not only reduces fatigue, pain, [21,22] and improves AWB, [23,24], but also delays the onset and progression of other chronic conditions. In spite of the benefits of PA, evidence shows that less than 10-20% of patients with chronic conditions are active [25-28]. To overcome the barriers to exercise, home-based exercise programs have been developed and report promising effectiveness on pain, fatigue, and AWB of cancer survivors with several chronic conditions [2931]. However, these studies have examined the effectiveness of the programs on an individual chronic condition and reported that most home-based exercise programs are challenged by a lack of motivation and low engagement rates with the exercise regimen [32-34].

Recent evidence shows that the use of technology to provide immediate feedback on physical performance and reminder messaging can increase motivation and adherence to PA [34-36]. The scientific premise of this messaging is based on the selfefficacy theory. The performance accomplishments and feedback can impact the self-efficacy that leads to the motivation to maintain healthy behaviors [35]. A recent review paper reported that selfmonitoring and performance feedback are key components of successful mobile health interventions to promote physical activity in older cancer survivors [37]. To address the limitations of engagement in exercise interventions, a home-based exercise (iHBE) program that integrated a smartphone application and physical activity tracking technology with a goal-setting and problem-solving intervention to tailor PA to individual daily life and physical fitness goals and preferences seems to provide promising results [38-40].

In the past decade, there has been a significant increase in digitally delivered exercise programs targeting individuals with various chronic conditions (e.g., cardiovascular diseases, osteoarthritis, cancer, and chronic kidney disease). However, the majority are focused on individuals with a single chronic condition and target achieving recommended daily physical activity goals and often do not include individuals’ incomes as one of the factors. Exercise programs for low-income cancer survivors with MCC may require unique consideration of an individual’s financial burdens and challenges (e.g., multiple caregiving demands, and less access to safe and clean spaces to exercise due to unsafe living conditions, etc.) [41,42]. While integrating mobile and physical activity tracking technologies seems to have a positive impact on individuals’ physical activity levels, evidence on the feasibility and challenges of these devices and physical activity among lowincome individuals was limited. Our pilot study aims to develop a tailored program that could meet the complex needs of cancer survivors with at least one or more comorbidities who have annual incomes of less than 50,000 US dollars (less than 200% above the US 2019 national poverty line), using the goal setting process and tailored the exercise recommendation weekly to meet individual’s physical function and challenges.

The aim of this paper is to assess the feasibility of the homebased exercise program using mobile technologies (physical activity tracker and phone application) and tailored exercise for low-income cancer survivors with MCC.

Methods

Aims

The purposes of this study were as follows: (1) to develop and test the feasibility of a home exercise program tailored to participants’ goals and preferences among low-income cancer survivors with MCC, and (2) to pilot test 

the effect of the program on symptoms (pain and fatigue), resilience and well-being.

Study Design

This study was an open-label pre-post test pilot study to examine the feasibility of an exercise intervention, mobile technology, and data collection process of the iHBE program in cancer survivors with MCC and pain problems.

Sample and Setting

Inclusion criteria included the following: adults aged 55 and older, diagnosed with cancer and at least one more chronic condition (e.g., diabetes, hypertension, etc.) for at least a year, self-reported annual income below 50,000 US dollars (below 200% of the federal poverty level) [25], and experiencing at least mild pain and fatigue (self-reported of at least 3 on the scale 0 (no symptom) to 10 (worst possible symptom). Exclusion criteria included: undergoing cancer treatment, having an active infection (e.g., fever, localized redness, swelling, sinus congestion), or being diagnosed with a psychological disorder (e.g., suicidal ideation, extreme anxiety, or depression).

Recruitment and Data Collection

Upon receiving approval from the Johns Hopkins University Institutional Review Board, participants were recruited from home healthcare agencies in Baltimore, Maryland using flyers, inperson contact, and referrals from home health providers. After participants were screened for eligibility criteria and signed the informed consent, a research team member visited the home for the initial assessment and to provide instruction on the physical activity tracking device (Fitbit, San Francisco, CA), to download and set up the two smartphone applications; one for sending and receiving a daily symptoms survey and another for activity tracking device assess the participants’ baseline physical capacity, and determine their physical activity goals and preferences. Participants were asked to wear the physical activity tracker on the non-dominant arm 24 hours/day and respond to a short symptoms survey on the smartphone application daily for 4 weeks. For participants who did not have a smartphone, a research phone was lent. Participants received a hard copy of the questionnaires and were asked to complete the questionnaires for outcomes at baseline (T1) and completion (T2). At the end of the program, participants were asked to complete open-ended questions to evaluate the program. The completed questionnaires were collected during the home visits. At the end of the program, each participant received 40 US dollars cash for participating in the study.

Intervention

The initial 4-week tailored technology-enhanced homebased exercise (iHBE) program was developed by the following research team: a symptom management expert (NL), an American College of Sports Medicine certified physiologist (DM), and an oncologist (JYS). The program was developed based on existing evidence to address the challenges in most exercise programs (Figure 1). The combination of the tailored home exercise intervention based on the goals, preferences, and baseline physical function, and mobile technologies (e.g., physical activity tracker and smartphone application) to monitor physical activity and symptoms, and adherence to a home exercise program. Prior to the data collection, the research staff was trained on 1) setting up the physical activity tracking device and smartphone application and how to extract and interpret the daily symptoms and step data; 2) troubleshooting some technical issues for the physical activity tracking device and the smartphone application; 3) communication with the participants on goals setting and adjusting weekly exercise goals and 4) exercise safety.

We conducted a baseline home visit (week 0) to set up and train participants on how to use the physical activity tracking device and smartphone applications. Participants were asked to wear the physical activity tracker and respond to the daily symptoms survey for one week for baseline physical activity (step count and active minutes) and asked to select one of the following exercise modalities: National Institute on Aging Go4Life exercise, walking, modified Otago exercise, or yoga. The physical activity goals were set up with the participants based on their selected exercise options and baseline physical activity levels. On weeks 1 to 3, a research staff member conducted weekly home visits to review each participant’s weekly performance (activity and sleep) from the physical activity tracker and daily symptoms from daily symptoms survey through the smartphone application, discuss the achievement of goals and challenges of exercising at home, and to adjust the physical activity goals.

Participants were trained for 15-20 minutes for exercise based on their selected modalities. The activity engagement was measured by self-report of achievement of a weekly goal. At the end of each week, participants were asked to rate their perceived physical activity goals on an achievement scale from 0 (not met at all) to 5 (completed all physical activity goals). At the end of the fourth week (week 4), a research staff member visited each participant at home, reviewed the overall performance compared to the baseline, and discussed the long-term goals for each participant to maintain the activity (Figure 1).

Figure 1: Study visits and mobile technology in the tailored Home-based Exercise Program

In the iHBE program, the physical activity tracking device was used to monitor the physical activity (step counts, active minutes) and sleep hours. The smartphone application was used to send a notification once a day (9:00 am) to remind the participant to complete the brief survey for daily symptoms and complete the weekly goals. The data from both physical activity tracking devices and applications were extracted from the research computer to generate the weekly performance report for each participant. The report was used by the research staff to adjust the weekly goals during the study visit.

Primary Outcome Measures

Recruitment and Retention were assessed from the research coordinator’s records. Information on reasons why participants were ineligible or refused to participate was recorded.

Program Implementation was measured by the actual values on total contact time/each visit, the research team member’s notes regarding the challenges of the intervention, and participants’ perceptions of the intervention’s content.

Adherence to the exercise goals was measured by participants’ self-report. Participants were asked to complete a goal achievement survey (how much did you meet your physical activity goal(s) this week?) on a scale of 0 (not meet at all) to 5 (meet all physical activity goal(s)). Adherence to daily survey and step count monitor (wearing 24 hours/7 days for 4 weeks) were measured by the number of days with the missing data. 

Adverse events were recorded. During the program, participants were asked to take note of any symptoms or discomfort during and after exercise. They were told to stop the exercise if experiencing unusual symptoms such as falling, lightheaded or fainting, shortness of breath, chest pain, severe and sharp pain, seek medical attention, and report to the research staff. For each home visit, a registered nurse (NL) or trained research staff discussed the participants’ experience during the exercise at home.

Participants’ Opinions and Acceptability of the intervention and the technology used in the program were measured using open-ended questions.

Secondary Outcome Measures

Pain was measured by the Patient-Reported Outcomes Measurement Information System (PROMIS) Short Form.

Participants were asked to rate their worst, average, and current pain on a scale of 1 (no pain) to 5 (very severe). The sum of raw scores was translated into the T-score. A high score indicated high pain intensity. This measure had high internal consistency (Cronbach’s α = .91) [43].

Fatigue was measured by the Patient-Reported Outcome Measurement Information System (PROMIS) Short Form (V1.0Fatigue 6a), a 6-item self-reported fatigue scale. Questions were asked regarding the characteristics of fatigue (frequency, duration, intensity) and its impact on physical, mental, and social activities. Participants were asked to rate their answers on five response options (1 or never to 5 or always). The reliability of the instrument (Cronbach’s α) was 0.99 [43].

Resilience was measured by the Connor-Davidson Resilience Scale (CD-RISC). This 25-item self-report scale was rated on a 5-point Likert scale ranging from not true at all (0) to true nearly all the time (4). The total score ranged from 0 to 100; a higher score indicated greater resilience [44]. The reliability estimate for this measure was α > .90 [45].

Well-being was measured by the self-reported ShortForm Health Survey (SF-36), a questionnaire that included eight subscales that evaluated physical function, social functioning, role limitations due to physical problems, role limitations due to emotional problems, and mental health, vitality, pain, and general health perceptions [46]. The total score on each subscale ranged from 0 to 100. The scores were divided into two summary scores: physical component summary (PCS: sum score of the physical function, role limitations due to physical problems, pain, and general health perceptions) and mental component summary (MCS: sum score of the social functioning, role limitations due to emotional problems, mental health, and vitality). A higher score indicated better well-being. The internal consistency of this subscale ranged from 0.693 to 0.924 [47].

Participants’ Opinions and Acceptability. After completing the 4 weeks intervention, participants were asked to answer open-ended questions regarding their opinions and suggestions for the program. Qualitative data relating to the intervention were categorized into two main themes: exercise program, and technology and technical issues. Exercise program. Participants found the exercise intervention feasible to follow and maintain. Participants highlighted three specific key elements they preferred in the program as follows.

Element 1: The ability to exercise at home and connect with providers.

 “She [the research staff member] came to my house (yay, no more driving all over) to teach me some basic yoga and stretching.” (iHBE001)

“I like that I didn’t have to go to any other site.” (iHBE002)

“Being able to work out in my home with my wonderful team (researchers). I wish the program duration

were longer.” (iHBE005).

Element 2: Simple and achievable goals

“A simple program, with simple goals-but what a powerful change in both my physical and mental wellbeing.” (iHBE001)

“It serves as a regimental spark to do the exercises; has become nearly a routine part of our week and has produced a gratifying sense of accomplishment. Also, its request to adhere to a regular schedule and commitment.” (iHBE004)

“It concentrates on areas I can improve.” (iHBE006)

“Exercise program fits nicely with my usual exercise routine.” (iHBE009).

Element 3: Ability to monitor activity and sleep.

“I like the ability to track sleep, pulse, active minutes and calories.” (iHBE009).

Technology and Technical Issues. The technologies used in the intervention included the physical activity tracker (Fitbit) and the smartphone application. While the physical activity tracker was generally well-liked and well-accepted among participants, technology glitches were reported for the smartphone application. The simplicity, ability to monitor health information, and long battery life were the most helpful features of the physical activity tracker.

“I found it (Fitbit) fairly simple to use and comfortable to wear. I liked that it held a long charge. I liked that it kept track of my steps and activity levels with accuracy. I liked the BPM measurement as well.” (iHBE001).

“Very helpful to track my activities and progress.” (iHBE005)

“I thoroughly enjoyed the access to data on a minute-tominute, daily, weekly and monthly basis. Gained better understanding of sleep patterns and calorie burn.” (iHBE009)

However, many participants reported the physical activity tracker data (steps, sleeps hours) were inaccurate.

“It needs to be more accurate, especially with stairs. I do not think it helped me by being more aware of moving.” (iHBE002)

“Poor! Very inaccurate! It reports an inflated, erroneous score for number of steps and number of stairs!” (iHBE004)

Participants’ opinions for the smartphone application were mixed. Some participants found the daily notification increased awareness of exercise and individual feelings.

“I think that this [the smartphone application] has made me more aware of the need to exercise and to plan the time to exercise which previously was ignored.” (iHBE002)

“[the smartphone application is] helpful in assessing my feeling of the day.” (iHBE005)

However, some participants perceived that the daily notification and technical glitches were burdensome.

“I did not like the daily reminder feature for many reasons. First, the notification sound was barely audible, even when there was no other noise in the room. Further, the notification sound could NOT be detected unless you had the phone right next to you AND there was no other sound going on AND you were not distracted by something else at the exact moment.” (iHBE001)

“Technical glitches in the operation of applications is a nuisance. Sometimes having to answer questions severally and delayed downloading.” (iHBE009)

Secondary Outcomes

At the completion of the 4-week program, participants experienced a reduction in self reported pain intensity (6%) and fatigue (7%), and an improvement in resilience (11%) and wellbeing in both the physical (8%) and mental components (2%) (Table 3).

Table 3: Mean self-reported pain, fatigue, resilience, and well-being scores and percent change of the score at the completion visit compared to the baseline.

Discussion

Our study results support the safety and feasibility of the tailored home-based exercise program (iHBE) using mobile technology and a physical activity tracking device for cancer survivors with MCC and related pain problems. Similar to other home-based exercise studies that focused on a single chronic condition [16-18], no serious adverse events were reported among participants with MCC and pain. The four-week program reduced pain, and fatigue, and improved resilience and well-being. Of the seven participants who completed the program, 43% were able to fully adhere to the weekly exercise goals with 71% adhering to at least 75% of their weekly goals; the step count increases ranged from -1 to 40% from baseline. Adherence to at least 80% of wearing a physical activity tracking device daily (100%, n=7) and at least 75% reporting symptoms through smartphone application daily (71%, n=5) were acceptable.

The ability to safely exercise at home and co-create the personalized weekly physical activity goals with the research staff members enhanced the participants’ self-efficacy and motivation to continue to exercise. The mobile technologies used in this study served as a tool to remind participants to exercise, provided immediate feedback, and communicated between the research team and participants. The study results provide preliminary evidence for the use of the tailored home exercise program as a supportive intervention to improve symptoms and overall wellbeing among cancer survivors with MCC.

A strength of this study was the inclusion of cancer survivors diagnosed with at least two chronic conditions, which had been underrepresented in previous studies. The use of a commercially available activity tracking device (Fitbit) and smartphone app helped us understand the physical activity pattern in participants’ natural environment. The data obtained from the mobile technology provided additional objective information in guiding the tailoring of weekly exercise recommendations and setting up realistic physical activity goals. Tailoring the exercise recommendations, setting up weekly achievable goals, and allowing participants to cocreate their exercise program based on their goals and preferences increased the participants’ willingness to exercise and sustain an active lifestyle after the program.

Limitations of this exploratory study included the small sample size of participants and no control groups for comparison. While the study showed favorable results, the intervention effectiveness may have occurred by chance due to the low statistical power and uncontrolled observations. Larger clinical control trials are needed to confirm the findings. An additional limitation is the lack of assessment of cognitive and physical functions. Although we measured baseline physical activity (step counts and active min), set achievable physical activity goals with participants, and conducted multiple home visits, the lack of systematic assessment of participant’s cognitive and physical function, and acuity could limit the effect of exercise on the outcomes. Finally, all participants of this pilot study were recruited from one geographic area (Maryland, USA), which could limit the generalizability of the findings to other populations.

Multiple challenges were noted by both participants and research staff members during the program. The first challenge was the low eligibility (40%) and enrollment (10%) rates in the recruitment process. We found that the change of contact address and phone numbers was a specific challenge among people who were referred from other research studies. Therefore, we changed the recruitment strategy from seeking referrals from other research studies to searching and identifying electronic medical records. The second challenge was the technical glitches for both physical activity tracking devices and the smartphone application. This challenge led us to create the technology training to increase mobile health literacy among research staff members to increase their confidence and competency in providing support to our participants.

Another challenge was the unavailability of the technology and internet connection at the participant’s home. Due to the low-income inclusion criteria and participants’ age range, some participants did not have internet service or had a smartphone with limited capacity. Although we were able to rent a smartphone for the participant with the data plan, a more effective and sustainable solution is needed for future study. Lastly, a total of 5 weekly home visits was overwhelming for some participants because of their busy schedules. We found that most participants were able to safely exercise at home.

This pilot study was the first phase of our intervention trial. We used the listed limitations, challenges, and suggestions from participants and research staff to adjust recruitment and eligibility screening strategies and to adjust the intervention program for the phase 2 study and created a training plan and manual for research staff. The intervention adjustments included the following: (1) adding cognitive and physical function assessment, (2) readjusting the daily reminders and brief symptoms survey and creating a manual on how to use the physical activity tracker and the smartphone application for participants, and (3) expanding the duration and changing the intervention delivering method from 4 weekly home visits to 3 home visits (first two weeks and last week), and nine weekly phone visits. The phase 2 study will examine the effectiveness of the adjusted tailored intervention on symptoms and health outcomes.

Conclusion

In conclusion, the study results suggest that tailored home exercise is safe and feasible for cancer survivors with Multiple Chronic Conditions (MCC) and pain, who had previously been underrepresented in research. However, due to multiple challenges and limitations, adjustment of this exercise program is needed. With adjustment to the use of mobile technology and refinements in the process of tailoring interventions, this program can be an effective supportive intervention to help reduce cancer survivors’ pain and fatigue and improve their well-being. Future randomized clinical control trials with a larger sample size are warranted to confirm these preliminary findings.

Funding

This study was supported by the Johns Hopkins School of Nursing PROMOTE Center (P30 Center, National Institute of Nursing Research: grant number 1P30NR018093-01).

Acknowledgments

The authors acknowledge Dr. Sarah Szanton, Dr. Nancy Reynold, and Dr. Patricia Davidson for insightful discussion and guidance on the intervention development idea. We thank Mr. Martin Blair for reviewing and editing this manuscript. Most importantly, we are grateful to all of our research participants and research team for providing valuable time and suggestions for program improvement.

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