Evidence map›Paper›PMID 37067890›Full record

ArticleJMIR formative research2023

SNapp, a Tailored Smartphone App Intervention to Promote Walking in Adults of Low Socioeconomic Position: Development and Qualitative Pilot Study.

Anne L Vos, Gert-Jan de Bruijn, Michel C A Klein, Jeroen Lakerveld, Sophie C Boerman, Edith G Smit

Abstract read
In one paragraph

Article in JMIR formative research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Trial
  2. Trial
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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

6 authors.

Anne L VosAmsterdam School of Communication Research, University of Amsterdam, Amsterdam, Netherlands.ORCID https://orcid.org/0000-0002-2218-1119
Gert-Jan de BruijnDepartment of Communication Studies, University of Antwerp, Antwerp, Belgium.ORCID https://orcid.org/0000-0001-9759-3938
Michel C A KleinSocial Artificial Intelligence Group, Department of Computer Science, Vrije Universiteit Amsterdam, Amsterdam, Netherlands.ORCID https://orcid.org/0000-0003-4119-1846
Jeroen LakerveldEpidemiology and Data Science, Amsterdam University Medical Centers, Location Vrije Universiteit Amsterdam, Amsterdam, Netherlands.ORCID https://orcid.org/0000-0002-8551-6748
Sophie C BoermanStrategic Communication Group, Wageningen University & Research, Wageningen, Netherlands.ORCID https://orcid.org/0000-0002-2453-1493
Edith G SmitAmsterdam School of Communication Research, University of Amsterdam, Amsterdam, Netherlands.ORCID https://orcid.org/0000-0002-6913-4897

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAdults of low socioeconomic position (SEP) are generally less physically active than those who are more socioeconomically advantaged, which increases their cardiovascular disease incidence risk. Moreover, individuals of low SEP are often less easily reached with physical activity (PA) interventions than individuals of higher SEP. Smartphone apps have been presented as a promising platform for delivering PA interventions to difficult-to-reach individuals of low SEP. Although PA apps are widely available, they are rarely based on health behavior theories and most predominantly offer generic PA advice. Consequently, it is unlikely that available apps are the most effective PA intervention tools.

objectiveTo respond to these areas for improvement, we developed SNapp, an app-based intervention encouraging adults of low SEP to increase PA by providing tailored coaching messages targeting walking behavior. This study aimed to describe SNapp's stepwise development and pilot evaluation process.

methodsWe applied a stepwise approach: analyzing the health problem, developing a program framework, developing tailoring assessments, writing tailored messages, automating the tailoring process, and implementing and evaluating the program in a qualitative pilot study (11 participants).

resultsSNapp consisted of several elements. First, an app was developed to collect step count and geolocation data using smartphone sensor functionalities. In addition, a survey measure was created to assess users' behavior change technique (BCT) preferences. These 3 data types were used to tailor SNapp's coaching messages to stimulate walking. This allows SNapp to offer feedback on performance levels, contextually tailored prompts when users are near green spaces, and coaching content that aligns with individual BCT preferences. Finally, a server-based Python program that interacts with databases containing user data and tailored messages was built using Microsoft Azure to select and automatically send messages to users through Telegram messenger. Pilot study findings indicated that SNapp was rated positively, with participants reporting that its design, technical functioning, and message content were acceptable. Participants suggested additional functionalities that are worth considering for future updates.

conclusionsSNapp is an app-based intervention that aims to promote walking in adults of low SEP by offering tailored coaching messages. Its development is theory based, and it is among the first to incorporate contextualized feedback and content tailored to individual BCT preferences. The effectiveness of SNapp will be evaluated in a 12-month real-life parallel cluster-randomized controlled trial.

Indexed as

behavior change techniquescardiovascular diseaseintervention developmentmHealthmobile appmobile healthmobile phonephysical activitysmartphonesocioeconomic positiontailoringwalking

Identifiers

PMID37067890
PMCPMC10152336

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Registered trials

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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.