Evidence map›Paper›PMID 39993013›Full record

ArticleJMIR cancer2025

Usability and Implementation Considerations of Fitbit and App Intervention for Diverse Cancer Survivors: Mixed Methods Study.

Zakery Dabbagh, Reem Najjar, Ariana Kamberi, Ben S Gerber, Aditi Singh, Apurv Soni, Sarah L Cutrona, David D McManus, Jamie M Faro

Abstract read
In one paragraph

Article in JMIR cancer, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Trial
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Zakery DabbaghDepartment of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, 55 N Lake Ave, Worcester, MA, 01655, United States, 1 (774) 455-3744.ORCID 0000-0003-4678-4579
Reem NajjarDepartment of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, 55 N Lake Ave, Worcester, MA, 01655, United States, 1 (774) 455-3744.ORCID 0009-0008-7248-635X
Ariana KamberiDepartment of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, 55 N Lake Ave, Worcester, MA, 01655, United States, 1 (774) 455-3744.ORCID 0000-0001-5363-825X
Ben S GerberDepartment of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, 55 N Lake Ave, Worcester, MA, 01655, United States, 1 (774) 455-3744.ORCID 0000-0003-4367-6396
Aditi SinghDepartment of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, United States.ORCID 0000-0001-9242-4406
Apurv SoniDepartment of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, United States.ORCID 0000-0001-5049-3657
Sarah L CutronaDepartment of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, 55 N Lake Ave, Worcester, MA, 01655, United States, 1 (774) 455-3744.ORCID 0000-0002-4795-8377
David D McManusDepartment of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, United States.ORCID 0000-0002-9343-6203
Jamie M FaroDepartment of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, 55 N Lake Ave, Worcester, MA, 01655, United States, 1 (774) 455-3744.ORCID 0000-0002-6592-463X

Funding

iDAPT: Implementation and Informatics - Developing Adaptable Processes and Technologies for Cancer Control P50CA244693 · NCI · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI DRESSLER, EMILY VAN METER · 2019 to 2023
$4.1M
ActivityChoice: A clinic-delivered implementation program to increase physical activity and decrease cardiovascular disease risk amongst cancer survivorsK01HL163254 · NHLBI · UNIV OF MASSACHUSETTS MED SCH WORCESTER · PI Jamie Faro · 2023 to 2026
$650k
NCI NIH HHS P50 CA244693NHLBI NIH HHS K01 HL163254
6 · The paper itself

Abstract

Background: Despite the known benefits of physical activity, cancer survivors remain insufficiently active. Prior trials have adopted digital health methods, although several have been pedometer-based and enrolled mainly female, non-Hispanic White, and more highly educated survivors of breast cancer. Objective: The objective of this study was to test a previously developed mobile health system consisting of a Fitbit activity tracker and the MyDataHelps smartphone app for feasibility in a diverse group of cancer survivors, with the goal of refining the program and setting the stage for a larger future trial. Methods: Participants were identified from one academic medical center's electronic health records, referred by a clinician, or self-referred to participate in the study. Participants were screened for eligibility, enrolled, provided a Fitbit activity tracker, and instructed to download the Fitbit: Health & Wellness and MyDataHelps apps. They completed usability surveys at 1 and 3 months. Interviews were conducted at the end of the 3-month intervention with participants and cancer care clinicians to assess the acceptability of the intervention and the implementation of the intervention into clinical practice, respectively. Descriptive statistics were calculated for demographics, usability surveys, and Fitbit adherence and step counts. Rapid qualitative analysis was used to identify key findings from interview transcriptions. Results: Of the 100 patients screened for eligibility, 31 were enrolled in the trial (mean age 64.8, SD 11.1 years; female patients=17/31, 55%; Hispanic or Latino=7/31, 23%; non-White=11/31, 35%; less than a bachelor's degree=14/31, 45%; and household income <US $75,000=11/31, 35%). The mean (SD) years since diagnosis was 7.1 (8.2), and the two most frequent cancer diagnoses were prostate (9/31, 29%) and breast (4/31, 13%) cancer. Participants provided positive feedback on the MyDataHelps app usability; the overall app quality received a mean score of 3.79 (SD 0.82) on a 5-point Likert scale (1=worst, 5=best). Interviews with 10 patients yielded four themes: (1) Fitbit and app setup was easy but the research team provided assistance, when needed, which was helpful, (2) motivational messages within the app were not memorable, (3) step counts and Fitbit notifications were motivating, and (4) medical professionals viewing their data were acceptable. Interviews with 5 cancer care clinicians yielded four themes: (1) some patients used wearables but rarely discussed data with clinicians; (2) activity trackers can be helpful to motivate patients and keep them accountable; (3) objective activity measures-similar to BMI, weight, and blood pressure- that they can track over time and refer to afterward were preferred; and (4) training and systematic processes to view these data as part of active workflow were desired. Conclusions: Implementing a remotely delivered, light-intensity physical activity program was feasible and acceptable in a sample of diverse cancer survivors. Future studies should consider registry-based methods and work with clinicians to engage hard-to-reach survivor populations who have low physical activity levels and disproportionately high adverse health outcomes.

Indexed as

Cancer SurvivorsExerciseFitness TrackersMobile ApplicationsNeoplasmsAdultAgedFemaleHumansMaleMiddle Agedactivity trackerbreast cancercancer survivordigital healthdigital health methoddiversefeasibilityFitbitHispanicmHealthmobile healthphysical activitysmartphone appusabilitywearablewearable devicewomen

Identifiers

PMID39993013
PMCPMC11875131

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.