Evidence map›Paper›PMID 32421196›Full record

ReviewTranslational behavioral medicine2021

Innovative methods for observing and changing complex health behaviors: four propositions.

Guillaume Chevance, Olga Perski, Eric B Hekler

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Translational behavioral medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers, 7 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
45citing papers in PubMed, 7 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

45 citing papers in PubMed, 7 syntheses or guidelines pooled it.

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  3. Effectiveness of face masks for reducing transmission of SARS-CoV-2: a rapid systematic review.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2023
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  12. Motivational profiles and change in physical activity during a weight loss intervention: a secondary data analysis.The international journal of behavioral nutrition and physical activity · 2021
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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

3 authors.

Guillaume ChevanceCenter for Wireless and Population Health Systems, University of California, San Diego, La Jolla, CA, USA.
Olga PerskiDepartment of Behavioural Science and Health, University College London, Torrington Place, London, UK.
Eric B HeklerCenter for Wireless and Population Health Systems, University of California, San Diego, La Jolla, CA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Precision health initiatives aim to progressively move from traditional, group-level approaches to health diagnostics and treatments toward ones that are individualized, contextualized, and timely. This article aims to provide an overview of key methods and approaches that can help facilitate this transition in the health behavior change domain. This article is a narrative review of the methods used to observe and change complex health behaviors. On the basis of the available literature, we argue that health behavior change researchers should progressively transition from (i) low- to high-resolution behavioral assessments, (ii) group-only to group- and individual-level statistical inference, (iii) narrative theoretical models to dynamic computational models, and (iv) static to adaptive and continuous tuning interventions. Rather than providing an exhaustive and technical presentation of each method and approach, this article articulates why and how researchers interested in health behavior change can apply these innovative methods. Practical examples contributing to these efforts are presented. If successfully adopted and implemented, the four propositions in this article have the potential to greatly improve our public health and behavior change practices in the near future.

Indexed as

Health BehaviorHumansAdaptive interventionsComputational modelsEcological momentary assessmentIdiographicPrecision health

Identifiers

PMID32421196
PMCPMC7963282

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.