The purpose of the study is to evaluate whether EnergyPoints, a mobile phone health app that guides the participant to do self-acupressure, can decrease fatigue and improve sleep. Acupressure consists of applying physical pressure with fingers or a device to small locations on the body called acupoints.

• The investigators will conduct this clinical trial remotely, allowing participants to use the app wherever they are. Participation will involve using the app daily while wearing a fitness tracker (a Fitbit) on the wrist, answering questions on the app and online, as well as completing a questionnaire and participating in an online interview at the end of the study. Participants will be assigned by chance to one of two groups. In both groups, participants will have a 1 week baseline week (Week 0) to get used to the Fitbit. Participants in the Immediate Group will start the 6 week trial of EnergyPoints immediately (Week 1). Participants in the Wait-List Group will be on a wait-list for 6 weeks during which time they will wear the Fitbit and answer online questions daily and weekly. At the end of the waiting period (week 7), these participants will begin the 6 week trial of EnergyPoints.
• The risks to participating are minimal. There is a small risk of bruising or getting sore at a point where participants apply pressure. As with any mobile app, there is the possibility that electronic information could be viewed by third parties not involved in the study. The investigators cannot promise any benefits from participating in the study. However, it is possible that using acupressure might improve fatigue or sleep. Participants may use any other approaches to improve fatigue and sleep while in the study.

A pilot study will be conducted first with 8 participants and 1 week periods (1 week baseline, 1 week waitlist, and 1 week intervention followed by an End of Study Questionnaire and Exit Interview

This study from 5 Point App, Inc. aims to further test EnergyPoints-an app to help cancer survivors (people living with cancer both on and off treatment) administer acupressure to self-manage cancer-related fatigue (CRF) and sleep deficiency. The study aims to validate the effectiveness of the app on clinical outcomes in a decentralized clinical trial (DCT). The expert interdisciplinary team consists of scientists and clinical experts in acupressure, symptom management, and informatics; qualitative and quantitative analysts; software engineers and marketing experts.

Up to 90% of patients receiving cancer treatment experience CRF; 30% may experience long-lasting fatigue. Sleep deficiency affects up to 75% of survivors, contributes to poor health and may exacerbate fatigue. These symptoms impact the physical, emotional, and social health of millions of cancer survivors. Exercise is most recommended for CRF, yet exercise may be difficult for some. Evidence supports benefits of other non-pharmacologic therapies (e.g., cognitive behavioral therapy-insomnia and mindfulness) for CRF and sleep disturbances, but these therapies may be unavailable, costly, or not widely adopted. Evidence supports the efficacy of acupressure to reduce fatigue (Effect size = 0.87) and improve sleep [Mean Difference (MD)= 3.72]14-19, but it is currently unfamiliar to many cancer survivors. Acupressure requires instruction by a skilled practitioner and is not covered by insurance; EnergyPoints addresses these critical barriers to adoption.

EnergyPoints app, on iOS and Android, educates and guides use of acupressure rituals to self-manage fatigue and sleep disturbances1. A follow-along format guides correct point stimulation for two acupressure rituals (stimulating and relaxing). The app synchronizes symptom self-reports with fitness tracker (e.g., an Apple Watch or Fitbit) sleep and activity data, allowing evaluation of response to acupressure. Regardless of location or access to a qualified instructor, users can self-treat and monitor symptoms and share a pdf of progress with their health care providers. The long-term goal is to improve clinical outcomes for cancer survivors by mainstreaming acupressure as a safe, affordable, self-care technique for managing symptoms. Once widely adopted, real-world-data from the app will advance science, allowing assessment of varying doses, types, and durations on effectiveness of acupressure.

During systematic user testing of EnergyPoints, cancer survivors performed acupressure as directed. Participants correctly located points and found the app easy to use; we established feasibility of connecting fitness tracker data. We added features identified by participants, such as music during the acupressure session. Participants completed at least one ritual (3 minutes per point) 87% of the time and both rituals 68% of the time. Some participants asked for "an express version." As there is no established standard for type of ritual or minimal dose of acupressure, the investigators developed a more scalable approach, allowing users to personalize their acupressure rituals to improve the experience and outcome. Users can choose rituals and timing for ½, 1, or 2 minutes per point.

The investigators will conduct a DCT in which 180 adult cancer survivors with CRF will test the EnergyPoints app at home for 6 weeks. Blocking on treatment status (on and off cancer treatment), the investigators will randomize a national, geographically, racially, and ethnically diverse sample of 180 adult cancer survivors with CRF to the EnergyPoints App-Immediate Group or a Wait-List Control Group. Data includes weekly self-report and daily app and fitness tracker measures of fatigue, sleep, and quality of life (physical and mental health). An exit interview and questionnaire will assess usability, acceptance, and desirability.

Specific Aim 1: Determine the effectiveness of EnergyPoints on clinical outcomes. The investigators will first identify key time points [baseline, start of benefit, peak of benefit] in trajectories of six weekly outcomes: fatigue, sleep, physical and mental health, total steps, and sleep efficiency. The primary analysis will then test effectiveness (Baseline to Start and Baseline to Peak, controlling for age, gender, and treatment status) by examining between- and within-subjects effects with linear mixed models in an intent-to-treat approach. The investigators will also explore the moderating effect of other personal factors and co-occurring symptoms. Milestone: Use of the app (vs. control) will clinically (MD=0.5 SD) and statistically (Group by Time interaction, p<.001) improve outcomes.

Specific Aim 2: Identify important intervention dose and enhancement effects to guide ongoing app modifications. Combining intervention data from both groups, the investigators will estimate dose and enhancement effects by analyzing interaction of time (Baseline to Peak) with intervention dose and enhancement features (e.g., dose of each ritual, time of pressing points, ritual adherence, and use of music). Milestone Significant (p<.001) interaction effects will elucidate important intervention features; effect sizes will estimate the impact.

Inclusion Criteria:

• Have cancer or have been treated for cancer;
• at least a moderate level of fatigue (greater than 4 on a 0 to 10 Likert-type scale);
• able to read and speak in English;
• age 18 years or older; Android 11 or later),
• adequate hearing, vision, and functional ability to see, hear and use the app and participate in interviews,
• willing to wear a provided Fitbit 24/7 (except when charging) throughout the study.

Exclusion Criteria:

• recent history of easy bruising or bleeding
• previous use of the EnergyPoints app.

Note: The functional ability questions will exclude anyone who is too sick to participate due to life-limiting disease.

A. Types and amount of scientific data expected to be generated in the project:

The decentralized clinical trial (DCT) will produce data from 180 cancer survivors with fatigue. There will both be quantitative and qualitative data including surveys, data synchronized from the Fitbit, and exit interview transcripts. All data will be deidentified. We will not share the software for the EnergyPoints app as it is proprietary and patented (application filed December 2023, patent pending).

The MPIs agree to make data available within one year of the completion of the funded project period and completed publication of manuscripts pertaining to the specific aims. The duration of preservation and sharing of the data will be a minimum of 10 years after the end of the funding period. The MPIs agree to share data in a manner that is fully consistent with NIH data sharing policies and applicable laws and regulations effective at the time of grant submission.

All dataset(s) that can be shared will be available in Mendeley Data (a no cost repository).Mendeley Data provides searchable study-level metadata for dataset discovery. Data will be discoverable online through standard web search of the study-level metadata as well as the persistent pointer from the DOI to the dataset. Once deposited in Mendeley Data, all data will be shared in a controlled fashion to assure compliance with the approved protocol and informed consent and privacy regulations. Institutions, groups, or researchers who propose to use the DCT data are required to submit a brief proposal/data request form describing the goals and methods of the proposed analyses. Based on this document and additional discussions with the party(ies) proposing the collaboration, the decision as to whether and/or how to proceed is made by consensus between the MPIs and the 5 Point App's CEO.

Study Participants (SPs) will know whether they are using the app or not and study staff must guide them in the onboarding process. The data collection process is independent of any research staff and occurs virtually using online surveys and trackers. The one exception is the exit interviews via Zoom. The Research Coordinator will be trained in proper interviewing techniques and the interview guide is designed to avoid leading questions. All SPs will receive the intervention and participate in an interview. The investigators will need to be aware of whether SPs are currently using the app to evaluate and report any adverse events. The statistical team will have no contact with SPs; group assignment will be revealed as part of analysis. Care providers may make referrals but will not be told of study assignment.