Evidence mapPaperPMID 36040779Full record

SynthesisJournal of medical Internet research2022

Association Between Patient Factors and the Effectiveness of Wearable Trackers at Increasing the Number of Steps per Day Among Adults With Cardiometabolic Conditions: Meta-analysis of Individual Patient Data From Randomized Controlled Trials.

Alexander Hodkinson, Evangelos Kontopantelis, Salwa S Zghebi, Christos Grigoroglou, Brian McMillan, Harm van Marwijk, Peter Bower, Dialechti Tsimpida, Charles F Emery, Mark R Burge and 14 more

Open access · goldAbstract readMeta-AnalysisReview
In one paragraph

Synthesis in Journal of medical Internet research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 3 pooled it
2.8field-weighted citation impact, top 9% of its field
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

8 citing papers in PubMed, 3 syntheses or guidelines pooled it, 10 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Article
  5. Review
  6. Review
  7. Article
  8. Review
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

24 authors at 13 institutions in 4 countries.

Alexander Hodkinson *Division of Population Health, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom.ORCID 0000-0003-2063-0977
Evangelos KontopantelisDivision of Population Health, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom.ORCID 0000-0001-6450-5815
Salwa S ZghebiDivision of Population Health, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom.ORCID 0000-0002-7978-1094
Christos GrigoroglouDivision of Population Health, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom.ORCID 0000-0003-1621-8648
Brian McMillanDivision of Population Health, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom.ORCID 0000-0002-0683-3877
Harm van MarwijkDepartment of Primary Care and Public Health, Brighton and Sussex Medical School, University of Brighton, Brighton, United Kingdom.ORCID 0000-0001-6206-485X
Peter BowerDivision of Population Health, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom.ORCID 0000-0001-9558-3349
Dialechti TsimpidaDivision of Population Health, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom.ORCID 0000-0002-3709-5651
Charles F EmeryDepartment of Psychology, The Ohio State University College of Arts and Sciences, Columbus, OH, United States.ORCID 0000-0001-9397-7424
Mark R BurgeDepartment of Medicine, Endocrinology and Metabolism, University of New Mexico Health Sciences Center, Albuquerque, NM, United States.ORCID 0000-0002-3015-3660
Hunter EsmiolDepartment of Medicine, Endocrinology and Metabolism, University of New Mexico Health Sciences Center, Albuquerque, NM, United States.ORCID 0000-0003-1250-7004
Margaret E CupplesDepartment of General Practice and Primary Care, Centre for Public Heath, Queen's University Belfast, Belfast, United Kingdom.ORCID 0000-0002-4248-9700
Mark A TullySchool of Medicine, Ulster University, Londonderry, United Kingdom.ORCID 0000-0001-9710-4014
Kaberi DasguptaDepartment of Medicine, McGill University, Montreal, QC, Canada.ORCID 0000-0002-2447-3553
Stella S DaskalopoulouDepartment of Medicine, McGill University, Montreal, QC, Canada.ORCID 0000-0003-4774-2549
Alexandra B CookeDepartment of Medicine, McGill University, Montreal, QC, Canada.ORCID 0000-0002-1081-8397
Ayorinde F FayehunDepartment of Family Medicine, University College Hospital, Ibadan, Nigeria.ORCID 0000-0003-2302-8156
Julie HouleDepartment of Nursing, Université du Québec à Trois-Rivières, Trois-Rivières, QC, Canada.ORCID 0000-0002-2009-883X
Paul PoirierInstitut Universitaire de Cardiologie et de Pneumologie de Québec, Université Laval, Laval, QC, Canada.ORCID 0000-0002-2563-1242
Thomas YatesDiabetes Research Centre, University of Leicester, Leicester, United Kingdom.ORCID 0000-0002-5724-5178
Joseph HensonDiabetes Research Centre, University of Leicester, Leicester, United Kingdom.ORCID 0000-0002-3898-7053
Derek R AndersonDepartment of Psychology, The Ohio State University College of Arts and Sciences, Columbus, OH, United States.ORCID 0000-0003-2308-0325
Elisabeth B GreyCentre for Motivation and Health Behaviour Change, Department for Health, University of Bath, Bath, United Kingdom.ORCID 0000-0001-9719-9690
Maria PanagiotiDivision of Population Health, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom.ORCID 0000-0002-7153-5745
Manchester Academic Health Science Centre · GBFlorida State University · USMcGill University Health Centre · CAUniversity of Leicester · GBUniversity of New Mexico · USBrighton and Sussex Medical School · GBInstitut universitaire de cardiologie et de pneumologie de Québec · CAMcGill University · CAQueen's University Belfast · GBUniversité du Québec à Trois-Rivières · CAUniversity College Hospital, Ibadan · NGUniversity of Bath · GBUniversity of Ulster · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCurrent evidence supports the use of wearable trackers by people with cardiometabolic conditions. However, as the health benefits are small and confounded by heterogeneity, there remains uncertainty as to which patient groups are most helped by wearable trackers.

objectiveThis study examined the effects of wearable trackers in patients with cardiometabolic conditions to identify subgroups of patients who most benefited and to understand interventional differences.

methodsWe obtained individual participant data from randomized controlled trials of wearable trackers that were conducted before December 2020 and measured steps per day as the primary outcome in participants with cardiometabolic conditions including diabetes, overweight or obesity, and cardiovascular disease. We used statistical models to account for clustering of participants within trials and heterogeneity across trials to estimate mean differences with the 95% CI.

resultsIndividual participant data were obtained from 9 of 25 eligible randomized controlled trials, which included 1481 of 3178 (47%) total participants. The wearable trackers revealed that over the median duration of 12 weeks, steps per day increased by 1656 (95% CI 918-2395), a significant change. Greater increases in steps per day from interventions using wearable trackers were observed in men (interaction coefficient -668, 95% CI -1157 to -180), patients in age categories over 50 years (50-59 years: interaction coefficient 1175, 95% CI 377-1973; 60-69 years: interaction coefficient 981, 95% CI 222-1740; 70-90 years: interaction coefficient 1060, 95% CI 200-1920), White patients (interaction coefficient 995, 95% CI 360-1631), and patients with fewer comorbidities (interaction coefficient -517, 95% CI -1188 to -11) compared to women, those aged below 50, non-White patients, and patients with multimorbidity. In terms of interventional differences, only face-to-face delivery of the tracker impacted the effectiveness of the interventions by increasing steps per day.

conclusionsIn patients with cardiometabolic conditions, interventions using wearable trackers to improve steps per day mostly benefited older White men without multimorbidity.

trial registrationPROSPERO CRD42019143012; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=143012.

Indexed as

Cardiovascular DiseasesWearable Electronic DevicesAdultAgedComorbidityExerciseFemaleFitness TrackersHumansMaleMiddle AgedRandomized Controlled Trials as Topiccardiometabolic conditionscardiovascular diseasediabetesindividual patient datameta-analysisobesitysteps/daysystematic reviewwearable tracker

Identifiers

PMID36040779
PMCPMC9472038
OpenAlexW4293698136

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

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 Socratic graph.