Evidence map›Paper›PMID 26466601›Full record

ArticleHealth (London, England : 1997)2016

In the loop: Practices of self-monitoring from accounts by trial participants.

Rebecca Lynch, Simon Cohn

Abstract read
In one paragraph

Article in Health (London, England : 1997), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

2 authors.

Rebecca LynchUniversity of Cambridge, UK.
Simon CohnLondon School of Hygiene & Tropical Medicine, UK simon.cohn@lshtm.ac.uk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Self-monitoring, by which individuals record and appraise ongoing information about the status of their body in order to improve their health, has been a key element in the personal management of conditions such as diabetes, but it is now also increasingly used in relation to health-associated behaviours. The introduction of self-monitoring as an intervention to change behaviour is intended to provide feedback that can be used by individuals to both assess their status and provide ongoing support towards a goal that may be formally set or remains implicit. However, little attention has been paid to how individuals actually engage in the process or act upon the information they receive. This article addresses this by exploring how participants in a particular trial ('Get Moving') experienced the process and nature of feedback. Although the trial aimed to compare the potential efficacy of three different monitoring activities designed to encourage greater physical activity, participants did not present distinctly different accounts of each intervention and the specifics of the feedback provided. Instead, their accounts took the form of much more extended and personal narratives that included other people and features of the environment. We draw on these broader descriptions to problematise the notion of self-monitoring and conclude that self-monitoring is neither solely about 'self' nor is it exclusively about 'monitoring'. We suggest that a more expansive social and material understanding of feedback can give insight into the ways information is made active and meaningful for individuals in their everyday contexts.

Indexed as

Attitude to HealthExerciseHealth BehaviorMonitoring, AmbulatorySelf CareAdultFeedbackFemaleHealth PromotionHumansInterviews as TopicMaleMiddle Agedfeedbackmonitoringphysical activitypublic health interventionself-monitoring

Identifiers

PMID26466601
PMCPMC5007662

What OpenQuestion 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 OpenQuestion graph.