Evidence map›Paper›PMID 28123997›Full record

ReviewFrontiers in public health2016

Behavior Change with Fitness Technology in Sedentary Adults: A Review of the Evidence for Increasing Physical Activity.

Alycia N Sullivan, Margie E Lachman

2 registry-linked trialsAbstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Frontiers in public health, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 188 papers, 14 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
188citing papers in PubMed, 14 pooled it
–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.

NCT03124537 nacompletednot on this mapstarted 2017, after this paper: background citation

Increasing Physical Activity Among Sedentary Older Adults:What, Where, When, and With Whom

TypeinterventionalSponsorBrandeis UniversityRan2017 to 2019Enrolled86ConditionsSedentary Lifestyle, Self Efficacy, Control Locus, AgingArmsApp Experimental condition, App Condition Control
NCT03529383 nacompletednot on this mapstarted 2018, after this paper: background citation

Randomized Controlled Trial Evaluating the Efficacy of an Adapted Physical Activity Program Using a Connected Device With Activity Trackers and a Therapeutic Education Program Among Women With Localized Breast Cancer

TypeinterventionalSponsorCentre Leon BerardRan2018 to 2022Enrolled436ConditionsBreast CancerArmsConnected device, Therapeutic education
3 · Its place in the literature

Who cites it

188 citing papers in PubMed, 14 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Associations Between the Use of Fitness and Diet Tracking Technology and Disordered Eating Behaviour: A Systematic Review.European eating disorders review : the journal of the Eating Disorders Association · 2025
    Pooled it
  6. Pooled it
  7. Effects of habit formation interventions on physical activity habit strength: meta-analysis and meta-regression.The international journal of behavioral nutrition and physical activity · 2023
    Pooled it
  8. Pooled it
  9. Pooled it
  10. Pooled it
  11. Guideline
  12. Pooled it
  13. Pooled it
  14. Pooled it
  15. Trial
  16. Trial
  17. Trial
  18. Using photovoice to explore young women's experiences of behaviour change techniques in physical activity mobile apps.The international journal of behavioral nutrition and physical activity · 2023
    Trial
  19. Trial
  20. Trial

128 more citing papers are in PubMed but not listed here.

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

2 authors.

Alycia N SullivanPsychology Department, Brandeis University , Waltham, MA , USA.
Margie E LachmanPsychology Department, Brandeis University , Waltham, MA , USA.

Funding

Core B - Pilot StudiesP30AG048785 · NIA · BRANDEIS UNIVERSITY · PI LACHMAN, MARGIE E · 2014 to 2023
$4.5M
NIA NIH HHS P30 AG048785
6 · The paper itself

Abstract

Physical activity is closely linked with health and well-being; however, many Americans do not engage in regular exercise. Older adults and those with low socioeconomic status are especially at risk for poor health, largely due to their sedentary lifestyles. Fitness technology, including trackers and smartphone applications (apps), has become increasingly popular for measuring and encouraging physical activity in recent years. However, many questions remain regarding the effectiveness of this technology for promoting behavior change. Behavior change techniques such as goal setting, feedback, rewards, and social factors are often included in fitness technology. However, it is not clear which components are most effective and which are actually being used by consumers. We discuss additional strategies not typically included in fitness technology devices or apps that are promising for engaging inactive, vulnerable populations. These include action planning, restructuring negative attitudes, enhancing environmental conditions, and identifying other barriers to regular physical activity. We consider which strategies are most conducive to motivating behavior change among sedentary adults. Overall, fitness technology has the potential to significantly impact public health, research, and policies. We suggest ways in which app developers and behavior change experts can collaborate to develop successful apps. Advances are still needed to help inactive individuals determine how, when, where, and with whom they can increase their physical activity.

Indexed as

behavior changeexercisefitness trackersolder adultsphysical activitytechnology

Identifiers

PMID28123997
PMCPMC5225122

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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.