Cited by 89Cancer survivorship and careMobile Health and mHealth ApplicationsCancer Risks and Factors

Preventing weight gain in African American breast cancer survivors using smart scales and activity trackers: a randomized controlled pilot study

Open access
Valle, Carmina G., Deal, Allison M., Tate, Deborah F.·2017·Journal of Cancer Survivorship

Abstract

Purpose This study evaluated the feasibility and preliminary efficacy of two 6-month, self-regulation interventions that focused on daily self-weighing (DSW) and used objective monitoring and tailored feedback about weight (±activity), to prevent weight gain among African American breast cancer survivors.Methods Participants (n = 35) were randomized to an intervention + activity monitoring (INT+), intervention (INT), or control (CON) group. Interventions included a wireless scale (±activity tracker) that transmitted objective data to a mobile app/website, emailed lessons, and tailored feedback based on objective weight (±activity data). Participants completed in-person and online assessments at baseline, 3 months, and 6 months.Results Ninety-four percent of participants completed assessments at 3 months, and 97 % at 6 months. Median (IQR) weight change after 6 months was -0.9 % (-4.4-0.1) in the INT+ (p = 0.075; p = 0.067 vs. CON) and -0.2 % (-4.2-1.3) in the INT groups (p = 0.463; p = 0.357 vs. CON), versus a 0.2 % (-0.7-1.7) gain in the CON group. The proportion of INT+, INT, and CON participants that were at or below baseline weight was 72.7, 53.8, and 45.5 %, respectively (effect sizes d = 0.64, d = 0.18). Most INT+ participants weighed and wore trackers ≥5 days/week (INT+, 81.9 % vs. INT, 38.5 % vs. CON, 0 %; p < 0.0005; INT+, 72.7 %). Both intervention groups perceived DSW as positive, and 100 % would recommend the program to other breast cancer survivors.Conclusion An intervention focused on DSW as a self-monitoring strategy shows promise for preventing weight gain in breast cancer survivors.Implications for cancer survivors Daily self-monitoring of weight and activity may be a feasible and accessible approach to promote weight gain prevention in breast cancer survivors.Clinical trial registration ClinicalTrials.gov, NCT02030353.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1007/s11764-016-0571-2

Cites

58 of 58 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Blinding of outcome assessors (detection bias) was assessed as high risk for 7 studies [31,43,45-48,52] because of the use of subjective outcome measures.

    “Blinding of outcome assessors (detection bias) was assessed as high risk for 7 studies [31,43,45-48,52] because of the use of subjective outcome measures.”

    From Consumer-based wearable activity trackers increase physical activity participation: systematic review and meta-analysis (2019) · cites this paper as [52]

    The Discussion (page unavailable) identifies a lack of blinded outcome assessors as a limitation and says self-reported measures could bias some outcomes. The Methods > Measures section (page unavailable) also describes objectively measured outcomes, including weight. The paper therefore supports concerns about blinding and subjective measures in this trial, but it does not assess seven studies as high risk or say that its lack of blinding was high risk specifically because of subjective outcomes. (LLM, conf=0.86)

    Experimental — accuracy not yet measured
  • Two studies [48,52] presented data as median and IQRs, suggesting that the data were not normally distributed; authors provided mean and SD data, and the studies were included in the meta-analyses.

    “Two studies [48,52] presented data as median and IQRs, suggesting that the data were not normally distributed. Authors of both the studies were contacted, and they provided mean and SD data, and the studies were subsequently included in the meta-analyses [28].”

    From Consumer-based wearable activity trackers increase physical activity participation: systematic review and meta-analysis (2019) · cites this paper as [52]

    The Methods (Statistical analyses; page unavailable) say the data were considerably skewed and that study measures were reported as medians and interquartile ranges. Our copy does not establish that the authors were contacted, supplied means and SDs for the meta-analysis, or that this study was included in it. (LLM, conf=0.86)

    Experimental — accuracy not yet measured
  • 8 studies included more than 1 intervention group.

    “Overall, 8 studies included more than 1 intervention group [34,43,45-47,52-54].”
  • One study reported a reduction in daily steps, one reported a reduction in MVPA participation, and three reported a reduction in energy expenditure in at least one included intervention group.

    “One study reported a reduction in daily steps [42], 1 study reported a reduction in MVPA participation [37], and 3 studies reported a reduction in energy expenditure [46,47,52] in at least one of the included intervention groups.”

    From Consumer-based wearable activity trackers increase physical activity participation: systematic review and meta-analysis (2019) · cites this paper as [52]

    The Results > Effects passage reports a 432-kcal-per-week increase in energy expenditure in the INT+ group, but does not give the direction of change in the other intervention group. Searches for a decrease in energy expenditure and for reduced MVPA did not find a passage establishing the reduction attributed to this study; the reported increase does not rule out a decrease in another group. (LLM, conf=0.72)

    Experimental — accuracy not yet measured
  • Of the 10 survivorship studies, 4 found significant effects of the mHealth apps on weight loss.

    “Of the 10 studies, 4 found significant effects of the mHealth apps on weight loss [41-43,46].”

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Authors
Valle, C. G., Deal, A. M., & Tate, D. F.
Affiliations
University of North Carolina at Chapel Hill (US)
Corresponding author
Valle, Carmina G.
Venue
Journal of Cancer Survivorship
Published
2016-09-08
Volume
11
Issue
1
Pages
133-148
ISSN
  • 1932-2259 (ISSN-L)
  • 1932-2267
OpenAlex
W2512259942
Cited by
89
References
58
Citations by year
2026: 1 · 2025: 6 · 2024: 7 · 2023: 12 · 2022: 9 · 2021: 16 · 2020: 10 · 2019: 12 · 2018: 10 · 2017: 5 · 2016: 1
FWCI
5.03
Type
journal article
Language
en
Open access
Locations
  • Journal of Cancer Survivorship (publishedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
Funders
  • Lineberger Comprehensive Cancer Center, University of North Carolina (Lineberger Developmental Research Award)
  • National Cancer Institute (T32CA128582)
Topics
  • Health Sciences › Medicine › Oncology › Cancer survivorship and care
  • Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
  • Health Sciences › Medicine › Oncology › Cancer Risks and Factors
Keywords
breast cancer survivors, weight gain prevention, self-monitoring, smart scales, wearable activity trackers, personalized feedback, African American women, cancer survivorship, mobile health, feasibility
MeSH terms
Fitness Trackers, Black or African American, Body Weight, Breast Neoplasms, Female, Humans, Middle Aged, Pilot Projects, Weight Gain, Survivors

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review