Evidence map›Paper›PMID 32717836›Full record

ArticleInternational journal of environmental research and public health2020

The Northumberland Exercise Referral Scheme as a Universal Community Weight Management Programme: A Mixed Methods Exploration of Outcomes, Expectations and Experiences across a Social Gradient.

Caroline J Dodd-Reynolds, Dimitris Vallis, Adetayo Kasim, Nasima Akhter, Coral L Hanson

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in International journal of environmental research and public health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 3 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.

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

5 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. A systematic review and narrative synthesis of physical activity referral schemes' components.The international journal of behavioral nutrition and physical activity · 2023
    Pooled it
  3. Pooled it
  4. Inequalities and Inclusion in Exercise Referral Schemes: A Mixed-Method Multi-Scheme Analysis.International journal of environmental research and public health · 2021
    Article
  5. Article
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

5 authors.

Caroline J Dodd-ReynoldsDepartment of Sport and Exercise Sciences, Durham University, Durham DH1 3HN, UK.
Dimitris VallisDurham Research Methods Centre, Durham University, Durham DH1 3HN, UK.
Adetayo KasimWolfson Research Institute for Health and Wellbeing Physical Activity Special Interest Group, Durham University, Durham DH1 3HN, UK.ORCID 0000-0002-0411-3059
Nasima AkhterWolfson Research Institute for Health and Wellbeing Physical Activity Special Interest Group, Durham University, Durham DH1 3HN, UK.
Coral L HansonSchool of Health and Social Care, Edinburgh Napier University, Edinburgh EH11 4BN, UK.ORCID 0000-0003-1602-1968

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Exercise referral schemes (ERS) are internationally recognised, yet little attention has been paid to discrete referral groups or the influence of wider social determinants of health. The primary quantitative element of this mixed methods study used a mixed effects linear model to examine associations of sociodemographic predictors, obesity class and profession of referrer on weight and physical activity (PA) variables for weight-related referrals (

Indexed as

Weight Reduction ProgramsExerciseFemaleHumansMaleMotivationReferral and ConsultationWeight Lossexercise referralinequalitiesobesityphysical activitysociodemographic

Identifiers

PMID32717836
PMCPMC7432420

What OpenQuestion holds

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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.