Effect of Fitbit and iPad Wearable Technology in Health-Related Quality of Life in Adolescent and Young Adult Cancer Patients

Abstract

Purpose:

Adolescent and young adult (AYA) patients with cancer face significant challenges with regard to fatigue, reduced physical activity, and social isolation, which may negatively impact quality of life. This study investigated whether the use of digital wearable technology (Fitbits, along with synced iPads) can affect health-related quality of life (HRQOL) in AYA aged patients with cancer.

Materials and Methods:

This was a prospective cohort study that offered Fitbits and iPads to all AYA patients aged 15 to 29 at an academic medical center at the time of cancer diagnosis. Patients completed the Short Form Health Survey developed by RAND (RAND-36) assessing eight dimensions of HRQOL on entering the study and at the time of their 6-month follow-up or the end of treatment, whichever occurred first. At the time of follow-up, patients also completed a questionnaire that assessed user experience, including frequency of wearable device use, enjoyment, challenges, and participation, in online communities.

Results:

Thirty-three patients participated in the study. Most patients reported enjoying the digital technology and using the devices to track multiple aspects of their health (85%). Most also reported a subjective increase in physical activity (79%). After the intervention, participants demonstrated significant improvements across all eight dimensions of HRQOL measured by the RAND-36 (p < 0.00 to 0.01).

Conclusion:

Distributing wearable technology at the time of diagnosis may provide an avenue for improving HRQOL in adolescents and young adults with cancer.

Introduction

Approximately 70,000 adolescent and young adult (AYA) aged patients (ages 15–39) are diagnosed with cancer in the United States annually.¹ These patients have distinct psychological, social, and medical needs. For instance, fatigue is a prevalent symptom in AYA patients and contributes to increased distress and reduced quality of life.² Compared with their counterparts without cancer, AYA cancer survivors report decreased physical activity.^3,4 They also report more cardiovascular disease, hypertension, diabetes, and higher rates of smoking.^5,6 In addition, identity development is a major developmental milestone for AYAs, and cancer treatment can interfere with healthy peer interactions resulting in social isolation.⁷

Related to these challenges is that AYA patients show reduced health-related quality of life (HRQOL), defined as the impact of health on a person's functional ability, physical, mental, and social well-being.⁸ In one study of 532 AYA patients with cancer, participants reported significantly worse HRQOL across a variety of physical and mental health domains compared with the general population.⁹ The authors also found several correlates of decreased HRQOL in this population, including younger age, less education, current symptoms, and current treatment.

There is growing evidence that physical activity may help patients face some of these challenges and specifically improve HRQOL. In adult patients with cancer, physical activity has been shown to reduce fatigue,^10,11 and in pediatric cancer patients, activity has been linked to improved HRQOL.¹² While the evidence on AYA patients is scarce, a limited body of research is beginning to suggest value. At the 2017 Texas AYA conference, Darby et al. showed the impact of a 6-week fitness program for AYA patients who had completed treatment.¹³ They found that patients had improvements in confidence, self-perceived fitness, and loneliness scores. At the same conference, Shields et al. reported that one-to-one exercise in AYA cancer patients improved cancer-related fatigue, quality of life, motivation, and confidence.¹⁴ In recognition of these benefits, the 2018 National Comprehensive Cancer Network (NCCN) practice guidelines for AYA patients now formally recommend exercise counseling to all AYA patients.¹⁵

Integrating technology into the cancer care experience may be a viable way to engage patients in physical activity and augment HRQOL. Mobile health applications may be paired with wearable devices such as Fitbits that track physical measurements such as step count, calories, and sleep. These applications can give feedback to users in real time as well as involve users in online communities that share physical activity progress and goals. With a majority of AYA cancer patients expressing interest in additional support services,¹⁶ and an increasing number of adolescent and young patients already using mobile technology,¹⁷ mobile health applications represent a potential avenue to help AYAs address unmet needs. However, despite this potential resource, there is yet limited empirical evidence linking wearable technology with improved outcomes in physical activity and quality of life.^18,19

With this study, we aimed to investigate whether wearable technology can affect HRQOL in AYA patients with cancer. We piloted a program that distributed free wearable technology with Fitbits, along with iPads that could be synced to the Fitbits for ease of use, to all AYA patients at an academic medical center at the time of cancer diagnosis, and we tracked HRQOL through pre- and postintervention surveys. Our goal was to determine whether wearable technology may offer benefits to AYA patients and to characterize what, specifically, those benefits may be. We also aimed to characterize user experience, including practical challenges and limitations to the technology. Ultimately, knowledge of how AYA patients use wearable technology may influence how cancer centers approach treating this population's unique challenges before, during, and after cancer treatment. These results may also help tailor interventions toward those patients who benefit most.

Materials and Methods

Study design and participants

This was a prospective cohort study in which AYA patients with a new cancer diagnosis were invited to participate. Participants were recruited from Stanford Hospital and Clinics (SHC) and Lucile Packard Children's Hospital (LPCH) and were evaluated for participation by SAYAC (Stanford Adolescent and Young Adult Cancer) personnel. Inclusion criteria included age 15 to 29 years, a new cancer diagnosis, and ability to provide written consent in English. For participants younger than 18 years, consent was obtained by a participant's parent or legal guardian. All genders and ethnic backgrounds were invited to participate.

Eligible subjects interested in participation were asked to complete baseline surveys of quality of life. Participants then received the intervention, which consisted of a Fitbit, an iPad Air tablet computer, and one charger for each device. All iPads were equipped with several preloaded applications intended to offer potential benefits for social, emotional, or physical well-being; these applications included Headspace (a meditation app), Remission 2 (an interactive game that allows users to fight cancer on a microscopic level), and NCCN AYA guidelines (an information sheet with recommendations and treatment plans). Fitbits had the capacity to record steps and sleep and were equipped with the additional option of tracking calories. Participants were counseled on how to use the wearable technology and how to sync the Fitbit with their iPad or personal phone by trained SAYAC staff. Participants were encouraged to create an anonymous profile through which they could participate in an online community and were also encouraged to use the technology regardless of location (e.g., in the hospital or at home). All participants were permitted to download additional applications of their choosing, and all were informed that they could withdraw from the study at any time.

Study participants repeated the HRQOL survey at the end of 6 months or at the end of their treatment, whichever occurred first. At the time of the second survey, they also filled out an original survey created by the authors about their use of the wearable technology. This study was conducted over the course of 1 year, with invitations to participate occurring from April 2016 to December 2016. Follow-up survey data were obtained from April 2017 through August 2017. The study was approved by the IRB at Stanford University.

Survey instruments

HRQOL was assessed pre- and postintervention with the Short Form Health Survey developed by RAND (RAND-36), one of the most widely used tools to assess HRQOL.^20,21 The RAND-36 contains 36 multiple choice questions, each asking participants to rate their subjective interpretation of various aspects of health and well-being on a scale. The 36 questions may be grouped into eight different dimensions of HRQOL, each containing 2 to 10 questions, which include the following: physical functioning, role functioning (physical), role functioning (emotional), energy/fatigue, emotional well-being, social functioning, pain, and general health.

The second survey was a shorter, original survey created by SAYAC staff. This survey consisted of 14 questions, some multiple choice and others free response. Surveys were designed to ascertain participants' experiences of using the Fitbit and iPad, including whether they enjoyed the intervention, how often they used it, technical challenges and limitations, participation in social communities, and most commonly used activities.

Data analysis

All items on the RAND-36 questionnaires were converted to a scoring system of 0 to 100 based on standard protocol, with high scores indicating high quality of life and level of functioning.²² Items were grouped into the eight scales, and scores for each health dimension were obtained via averages of all questions classified as belonging to that scale.

Intergroup comparisons between pre- and postintervention dimension scores were performed using paired T-tests with unequal variances. Two-tailed tests were used throughout and a p value <0.05 was considered significant. Internal reliability of the RAND-36 was measured by calculating Cronbach's α coefficient for the eight domains before and after the intervention. Analyses were performed using Stat Tools v7.5, advanced statistical analysis for Microsoft Excel (Palisade Corporation, Ithaca, New York).

Results

Forty-four surveys were distributed to AYA patients at SHC and LPCH, among which 33 pre- and postsurveys were returned (response rate: 75%). Three patients passed away during the investigation. One transferred care to another institution. Among the other seven for whom repeat surveys were not obtained, two did not have follow-up office visits, two followed up with a local provider instead of at Stanford, and three did follow up at Stanford but did not complete surveys. There was a roughly equal distribution of genders (58% female) and ages (range: 15–28, with average age of 22 years) (Table 1). The majority of participants were diagnosed with leukemia (48%), followed by sarcoma (21%) and lymphoma (15%). The median number of days from cancer diagnosis to study consent was 30 days (range: 3–1499 days). The average duration until follow-up was 298 days, with a range of 141 to 433 days. Of note, this was longer, on average, than the intended follow-up of 6 months or the end of therapy due to many participants taking additional time to bring back their follow-up surveys.

Table 1.

Demographic Characteristics of Survey Participants, N = 33

Characteristics
Age in years, mean (range)	22.0 (15–28)
Age group, n (%)
15–19	11 (33)
20–24	12 (36)
25–29	10 (30)
Gender, n (%)
Female	19 (58)
Male	14 (42)
Diagnosis, n (%)
Leukemia (ALL, AML)	16 (48)
Sarcoma	7 (21)
Lymphoma	5 (15)
Other	5 (15)
Duration to follow-up in days, mean (range)	298 (141–433)
Time from diagnosis to study consent in days, median (range)	30 (3–1499)

ALL, acute lymphoblastic leukemia; AML, acute myeloid leukemia.

Based on the pre- and post-RAND-36 surveys, the postintervention mean scores of all participants demonstrated significant improvements across all eight dimensions of HRQOL (Table 2). Power analysis revealed a mean power of 0.83 across the eight domains, suggesting sufficient power to detect differences pre- and postintervention using a standard power cutoff of greater than 0.80. Based on the original follow-up survey created by SAYAC staff (Table 3), the majority of patients (85%) reported that they enjoyed wearing the Fitbit. Most felt that the Fitbit helped them to be more active (79%), while a minority (18%) felt their activity level was the same, and none reported becoming less active. Many used the Fitbit to track multiple aspects of their health and physical activity, with the most popular being steps (97%), followed by sleep (39%) and calories (24%). On the iPad, the most commonly utilized pre-equipped application was Headspace (58%) followed by Remission 2 (27%). Some patients used the iPad for other activities, including reading and doing homework (15%), watching Netflix (15%), and playing games (12%). Nine patients (27%) participated in an online community. Several patients reported technical and practical challenges to using the technology, with the most common complaint of low battery life/forgetting to charge the Fitbit (21%). There was a wide range of how often patients wore their Fitbit from to 1 to 2 times a week to all the time. A little under half (45%) of the participants used their Fitbit in the hospital.

Table 2.

Mean Scores for RAND-36 Dimensions of Health-Related Quality of Life, Pre- and Postintervention for All Participants, N = 33

Health-related quality of life domain	Before intervention (reliability coefficient)	After intervention (reliability coefficient)	p
Physical functioning	49.80 (0.80)	75.00 (0.91)	<0.00
Role functioning/physical	21.30 (0.78)	54.03 (0.90)	<0.00
Role functioning/emotional	60.67 (0.84)	80.65 (0.66)	<0.00
Energy/fatigue	37.74 (0.72)	54.75 (0.85)	<0.00
Emotional well-being	66.17 (0.69)	73.60 (0.87)	0.01
Social functioning	50.00 (0.76)	69.35 (0.82)	<0.00
Pain	59.82 (0.94)	79.18 (0.89)	<0.00
General health	48.29 (0.81)	56.77 (0.77)	0.01

Based on the RAND-36 scoring system, a high score defines a more favorable health state. Reliability coefficients, as calculated by Cronbach's α coefficient, indicate internal consistency of the survey data, with scores closer to 1 representing higher internal consistency.

RAND-36, Short Form Health Survey developed by RAND.

Table 3.

Participants' Experiences with Fitbit and iPad, Assessed by a Survey Containing Both Multiple-Choice and Free-Response Questions

Did you enjoy wearing your Fitbit? (MC)	Percent (N = 33)
Yes	85%
How often did you wear the Fitbit? (MC)
All the time	30%
5–6 times/week	18%
3–4 times/week	21%
1–2 times/week	24%
What did you find most challenging about wearing the Fitbit? (FR)
Low battery life/remembering to charge	21%
Fitbit not waterproof	15%
Fitbit not comfortable	12%
Syncing Fitbit to iPad	9%
Did you use the Fitbit in the hospital? (MC)
Yes	45%
No	48%
Do you feel you were more active, less active, or the same as a result of wearing your Fitbit? (MC)
More active	79%
Same activity	18%
Less active	0%
Did you participate in an online community for Fitbit? (MC)
Yes	27%
No	67%
Did you have an iPad before this study? (MC)
Yes	70%
No	24%
Did you use any of the recommended iPad apps? (MC)
Headspace	58%
Remission 2	27%
NCCN AYA guidelines	12%
What did you do most on your iPad (outside of recommended apps)? (FR)
Reading/homework	15%
Netflix	15%
Games	12%

Type of answer choice indicated.

AYA, adolescent and young adult; FR, free response; MC, multiple choice; NCCN, National Comprehensive Cancer Network.

Discussion

Prior research has linked increased physical activity with improved quality of life for cancer patients. This study investigated whether wearable technology may be a useful tool for helping AYA patients with cancer meet activity goals and augment HRQOL from the time of diagnosis forward. Patient feedback was generally positive toward the pilot program. Moreover, results showed statistical and clinical significance in improving all eight dimensions of HRQOL as measured by the RAND-36. Overall, our results suggest that distributing wearable technology to patients newly diagnosed with cancer can be one way to increase physical activity and quality of life.

Despite most patients indicating positive feedback toward the devices, less than half wore them in the hospital. As this is a setting in which inactivity and fatigue are common, we were surprised that a relatively low number of participants wore the devices in this location. However, many of those who did specifically free-texted comments showing recognition of inactivity risk linked to hospital stays and expressed appreciation at having the devices to motivate them. Having to take the Fitbits off and on for scans such as MRIs represented a practical barrier for some patients, as did having to keep the devices dry and remembering to charge, although these challenges were not restricted to the hospital setting.

It is worth noting that distributing iPads to adolescents and young adults may have unintended consequences. In particular, many reported that they used the iPads primarily for Netflix and playing games, counterproductive to the goal of increasing physical activity. Even before the study, there has been no standard protocol for encouraging patients with cancer admitted to the hospital to remain active, despite widespread recognition of its importance. However, even despite many patients enjoying their iPads for television and games, no patients reported that they felt more sedentary with the intervention (in fact, most reported the opposite). The fact that 70% of patients had iPads before this study may account, in part, for these findings, suggesting that patients may have been already engaging in these activities before the intervention. It is possible that the 70% figure underestimates prior use, as the question addressed iPads specifically and not other tablets. It is also conceivable that engaging in these enjoyable activities increased other aspects of HRQOL, such as emotional well-being.

Only about a quarter of patients participated in online communities, suggesting that increasing peer communities in AYA patients remains an ongoing challenge. These results are consistent with those from an article by Mendoza et al., which found that 14- to 18-year olds with cancer had lower than expected engagement with a Facebook app and that most demonstrated passive rather than active engagement (e.g., viewing posts rather than initiating or responding to them).¹⁹

Our results were not consistent, however, with other findings from the Mendoza et al. article, a randomized controlled study that looked at physical activity 1 year after cancer treatment in AYA patients. In particular, participants in the experimental arm of that study, who spent 10 weeks with a Fitbit Flex and had access to a virtual support group, showed no significant differences in physical activity compared with the control group that did not receive access to the technology. Notable differences between the prior study and ours include design (randomized controlled trial vs. prospective cohort), measurement of outcomes (objective step tracking vs. surveys), and duration of intervention (10 weeks vs. an average of 43 weeks). It is possible that the participants in our study overestimated their activity levels from the Fitbit, reported through subjective data rather than objective tracking. It is also possible that the longer duration in our study may have led to differing results. If additional studies do show continued benefit, an important study question would be optimal time and duration of Fitbit use to achieve such benefit.

There were several limitations to this investigation. In this pilot study, we chose not to randomize participants but rather offered the technology to all eligible patients. As such, it is possible that those who chose to participate were already more interested in increasing their physical activity, potentially skewing our results in the positive direction. Another limitation of this study was subjectivity. As above, our outcomes were based on subjective assessments of physical activity, as we did not set out the study design asking for participants' actual step counts. It is possible that subjective reports of physical activity do not correlate exactly with objective activity data, and we believe it may be beneficial for future researchers to track objective data from the start to determine if subjective and objective measures correlate. However, even without objective data in our study design, we would posit that subjective measurements of HRQOL are an important variable to understand. A third limitation was our limited sample size (N = 33). The positive results from our limited sample size suggest larger studies are warranted to determine if our results may generalize on a broader scale. However, we hope that our high yield (only three patients followed up at Stanford but not did complete the study) suggests a broad general interest in the topic.

Finally, a fourth and important limitation is that as this was as prospective cohort study of participants before and after an intervention, it remains unclear whether it was truly the intervention that caused the effect. For instance, the simple passage of time also occurred, and it is plausible that the improvement in HRQOL may be partially attributed to this, as participants may have become more emotionally or socially adjusted to the reality of their illnesses. Moreover, given the distribution of several related interventions (Fitbits, iPads, preloaded apps), the contribution of each toward the outcomes seen in HRQOL is not exactly clear. Based on our results, a next step would be a randomized controlled trial to try to tease out confounders and determine if wearable technology alone may improve HRQOL.

As more AYAs are surviving cancer, emphasis on quality of life during and after treatment will become increasingly salient. We are heartened by these pilot results that may offer one method for improving HRQOL in a vulnerable patient population very much in need of it.

Footnotes

Acknowledgments

The authors thank all participants for their eager involvement in this study and thoughtful responses to survey questions. They also thank the SAYAC team who scrupulously distributed the wearable technology and counseled participants on how to use it. They also thank the Stanford Cancer Center Clinical Innovation Fund for funding this work.

Author Disclosure Statement

No competing financial interests exist.

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