Evidence map›Paper›PMID 33871865›Full record

ReviewMethods in molecular biology (Clifton, N.J.)2021

Changing Health-Related Behaviors 3: Lessons from Implementation Science.

Amanda Hall, Helen Richmond, Krista Mahoney, James Matthews

Abstract readReview
PubMed Publisher
In one paragraph

Review in Methods in molecular biology (Clifton, N.J.), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

4 authors.

Amanda HallPrimary Healthcare Research Unit, Faculty of Medicine, Memorial University of Newfoundland, St. John's, NL, Canada. Amanda.hall@med.mun.ca.
Helen RichmondPrimary Healthcare Research Unit, Faculty of Medicine, Memorial University of Newfoundland, St. John's, NL, Canada.
Krista MahoneyDiscipline of Medicine, Memorial University of Newfoundland, St. John's, NL, Canada.
James MatthewsSchool of Public Health, Physiotherapy and Sports Science, University College Dublin, Dublin, Ireland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Health-related behavior change refers to a body of behavior change strategies that aim to align people's behavior with advances in evidence-based knowledge and decision-making. However, human behavior is complex, and changing it often requires a combination of strategies to be effective. The challenge is in choosing the combination of strategies that will work best. Implementation science, the study of behavior change, has rapidly expanded in recent years and has pioneered work in providing more transparent and theory-based methods for choosing and evaluating behavior change strategies. There are several models and frameworks that underlie the science of implementation, the most recent and comprehensive of which include the Implementation of Change Model, the COM-B (capability, motivation, and behavior) Model, and the Theoretical Domains Framework, as well as the behavior change techniques (BCTs) taxonomy. These models and frameworks can be applied to help support the development and evaluation of behavior change interventions. In this chapter, we will review the latest advances and lessons learned from implementation science as it applies to health-related behavior change.

Indexed as

Health BehaviorImplementation ScienceCanadaEvidence-Based MedicineHealth Knowledge, Attitudes, PracticeHumansBehavioral theoryBehavior changeBehavior change interventionsCluster randomized trialsCognitive behavioral approachImplementation scienceOutcome evaluationTheoretical Domains FrameworkWheel

Identifiers

What OpenQuestion holds

Textmetadata
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.