Evidence map›Paper›PMID 37995122›Full record

ArticleJMIR formative research2023

Biofeedback and Digitalized Motivational Interviewing to Increase Daily Physical Activity: Series of Factorial N-of-1 Randomized Controlled Trials Piloting the Precious App.

Johanna Nurmi, Keegan Knittle, Felix Naughton, Stephen Sutton, Todor Ginchev, Fida Khattak, Carmina Castellano-Tejedor, Pilar Lusilla-Palacios, Niklas Ravaja, Ari Haukkala

Open access · goldAbstract 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 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
0.9field-weighted citation impact, top 27% 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

2 citing papers in PubMed, 1 synthesis or guideline pooled it, 5 citations in OpenAlex.

  1. Pooled it
  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

10 authors at 6 institutions in 3 countries.

Johanna NurmiSocial Psychology, Faculty of Social Sciences, University of Helsinki, Helsinki, Finland.ORCID https://orcid.org/0000-0001-8414-3444
Keegan KnittleSocial Psychology, Faculty of Social Sciences, University of Helsinki, Helsinki, Finland.ORCID https://orcid.org/0000-0002-2108-7112
Felix NaughtonBehavioural and Implementation Science Group, School of Health Sciences, University of East Anglia, Norwich, United Kingdom.ORCID https://orcid.org/0000-0001-9790-2796
Stephen SuttonBehavioural Science Group, Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom.ORCID https://orcid.org/0000-0003-1610-0404
Todor GinchevDepartment of Communications and Networking, Aalto University, Espoo, Finland.ORCID https://orcid.org/0000-0002-7634-6097
Fida KhattakDepartment of Communications and Networking, Aalto University, Espoo, Finland.ORCID https://orcid.org/0000-0003-1405-7692
Carmina Castellano-TejedorGrupo de Investigación en Estrés y Salud, Basic Psychology Department, Autonomous University of Barcelona, Barcelona, Spain.ORCID https://orcid.org/0000-0003-2335-8550
Pilar Lusilla-PalaciosPsiquiatría, Salud Mental y Adicciones, Vall d'Hebron Institut de Recerca, Barcelona, Spain.ORCID https://orcid.org/0000-0002-4820-3937
Niklas RavajaDepartment of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Helsinki, Finland.ORCID https://orcid.org/0000-0003-1876-8731
Ari HaukkalaSocial Psychology, Faculty of Social Sciences, University of Helsinki, Helsinki, Finland.ORCID https://orcid.org/0000-0001-8567-1548
University of Helsinki · FIUniversitat Autònoma de Barcelona · ESAalto University · FIUniversity of Cambridge · GBUniversity of East Anglia · GBUniversity of Jyväskylä · FI

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundInsufficient physical activity is a public health concern. New technologies may improve physical activity levels and enable the identification of its predictors with high accuracy. The Precious smartphone app was developed to investigate the effect of specific modular intervention elements on physical activity and examine theory-based predictors within individuals.

objectiveThis study pilot-tested a fully automated factorial N-of-1 randomized controlled trial (RCT) with the Precious app and examined whether digitalized motivational interviewing (dMI) and heart rate variability-based biofeedback features increased objectively recorded steps. The secondary aim was to assess whether daily self-efficacy and motivation predicted within-person variability in daily steps.

methodsIn total, 15 adults recruited from newspaper advertisements participated in a 40-day factorial N-of-1 RCT. They installed 2 study apps on their phones: one to receive intervention elements and one to collect ecological momentary assessment (EMA) data on self-efficacy, motivation, perceived barriers, pain, and illness. Steps were tracked using Xiaomi Mi Band activity bracelets. The factorial design included seven 2-day biofeedback interventions with a Firstbeat Bodyguard 2 (Firstbeat Technologies Ltd) heart rate variability sensor, seven 2-day dMI interventions, a wash-out day after each intervention, and 11 control days. EMA questions were sent twice per day. The effects of self-efficacy, motivation, and the interventions on subsequent steps were analyzed using within-person dynamic regression models and aggregated data using longitudinal multilevel modeling (level 1: daily observations; level 2: participants). The analyses were adjusted for covariates (ie, within- and between-person perceived barriers, pain or illness, time trends, and recurring events).

resultsAll participants completed the study, and adherence to activity bracelets and EMA measurements was high. The implementation of the factorial design was successful, with the dMI features used, on average, 5.1 (SD 1.0) times of the 7 available interventions. Biofeedback interventions were used, on average, 5.7 (SD 1.4) times out of 7, although 3 participants used this feature a day later than suggested and 1 did not use it at all. Neither within- nor between-person analyses revealed significant intervention effects on step counts. Self-efficacy predicted steps in 27% (4/15) of the participants. Motivation predicted steps in 20% (3/15) of the participants. Aggregated data showed significant group-level effects of day-level self-efficacy (B=0.462; P<.001), motivation (B=0.390; P<.001), and pain or illness (B=-1524; P<.001) on daily steps.

conclusionsThe automated factorial N-of-1 trial with the Precious app was mostly feasible and acceptable, especially the automated delivery of the dMI components, whereas self-conducted biofeedback measurements were more difficult to time correctly. The findings suggest that changes in self-efficacy and motivation may have same-day effects on physical activity, but the effects vary across individuals. This study provides recommendations based on the lessons learned on the implementation of factorial N-of-1 RCTs.

Indexed as

activity braceletactivity trackerautomatedbehavior changebiofeedbackdaily stepsdigitalizedecological momentary assessmentintensive longitudinal multilevel modelinginterventionmobile phonemotivational interviewingN-of-1self-efficacyself-regulationsmartphonewithin-person design

Identifiers

PMID37995122
PMCPMC10704305
OpenAlexW4372047450

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.