Evidence map›Paper›PMID 27909944›Full record

ArticleAnnals of behavioral medicine : a publication of the Society of Behavioral Medicine2017

Using an Analysis of Behavior Change to Inform Effective Digital Intervention Design: How Did the PRIMIT Website Change Hand Hygiene Behavior Across 8993 Users?

B Ainsworth, M Steele, B Stuart, J Joseph, S Miller, L Morrison, P Little, L Yardley

Open access · hybridAbstract read
In one paragraph

Article in Annals of behavioral medicine : a publication of the Society of Behavioral Medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed
2.3field-weighted citation impact, top 11% 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

29 citing papers in PubMed, 57 citations in OpenAlex.

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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

8 authors at 1 institution in 1 country.

B AinsworthCentre for Clinical and Community Applications of Health Psychology, Psychology, Faculty of Social and Human Sciences, University of Southampton, Southampton, SO17 1BJ, UK. ben.ainsworth@southampton.ac.uk.ORCID http://orcid.org/0000-0002-5098-1092
M SteeleCentre for Clinical and Community Applications of Health Psychology, Psychology, Faculty of Social and Human Sciences, University of Southampton, Southampton, SO17 1BJ, UK.
B StuartPrimary Care and Population Sciences, Faculty of Medicine, University of Southampton, Southampton, UK.
J JosephCentre for Clinical and Community Applications of Health Psychology, Psychology, Faculty of Social and Human Sciences, University of Southampton, Southampton, SO17 1BJ, UK.
S MillerCentre for Clinical and Community Applications of Health Psychology, Psychology, Faculty of Social and Human Sciences, University of Southampton, Southampton, SO17 1BJ, UK.
L MorrisonCentre for Clinical and Community Applications of Health Psychology, Psychology, Faculty of Social and Human Sciences, University of Southampton, Southampton, SO17 1BJ, UK.
P LittlePrimary Care and Population Sciences, Faculty of Medicine, University of Southampton, Southampton, UK.
L YardleyCentre for Clinical and Community Applications of Health Psychology, Psychology, Faculty of Social and Human Sciences, University of Southampton, Southampton, SO17 1BJ, UK.
University of Southampton · GB

Funding

Medical Research Council G0700459
6 · The paper itself

Abstract

backgroundIn designing digital interventions for healthcare, it is important to understand not just whether interventions work but also how and for whom-including whether individual intervention components have different effects, whether a certain usage threshold is required to change behavior in each intervention and whether usage differs across population subgroups. PURPOSE: We investigated these questions using data from a large trial of the digital PRimary care trial of a website based Infection control intervention to Modify Influenza-like illness and respiratory tract infection Transmission) (PRIMIT) intervention, which aimed to reduce respiratory tract infections (RTIs) by increasing hand hygiene behavior.

methodBaseline and follow-up questionnaires measured behaviors, intentions and attitudes in hand hygiene. In conjunction with objective measures of usage of the four PRIMIT sessions, we analysed these observational data to examine mechanisms of behavior change in 8993 intervention users.

resultsWe found that the PRIMIT intervention changed behavior, intentions and attitudes, and this change was associated with reduced RTIs. The largest hand hygiene change occurred after the first session, with incrementally smaller changes after each subsequent session, suggesting that engagement with the core behavior change techniques included in the first session was necessary and sufficient for behavior change. The intervention was equally effective for men and women, older and younger people and was particularly effective for those with lower levels of education.

conclusionsOur well-powered analysis has implications for intervention development. We were able to determine a 'minimum threshold' of intervention engagement that is required for hand hygiene change, and we discuss the potential implications this (and other analyses of this type) may have for further intervention development. We also discuss the application of similar analyses to other interventions.

Indexed as

Behavior TherapyHand HygieneIntentionAdultFemaleHumansInfluenza, HumanMaleMiddle AgedSurveys and QuestionnairesBehavior changeDigital interventionsEngagementHand hygieneUsage

Identifiers

PMID27909944
PMCPMC5440485
OpenAlexW2558876944

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.