Evidence map›Paper›PMID 37083710›Full record

ArticleJMIR formative research2023

Motivational Message Framing Effects on Physical Activity Dynamics in a Digital Messaging Intervention: Secondary Analysis.

Alexandra M Lee, Sahar Hojjatinia, Jimikaye B Courtney, Deborah Brunke-Reese, Sarah Hojjatinia, Constantino M Lagoa, David E Conroy

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 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
1.4field-weighted citation impact, top 18% 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

5 citing papers in PubMed, 1 synthesis or guideline pooled it, 7 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Optimizing generative artificial intelligence prompts to engage urges for physical activity in middle-aged and older adults.Annals of behavioral medicine : a publication of the Society of Behavioral Medicine · 2026
    Article
  4. Article
  5. 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

7 authors at 1 institution in 1 country.

Alexandra M LeeThe Pennsylvania State University, University Park, PA, United States.ORCID https://orcid.org/0000-0001-8146-1674
Sahar HojjatiniaThe Pennsylvania State University, University Park, PA, United States.ORCID https://orcid.org/0000-0002-9748-1239
Jimikaye B CourtneyThe Pennsylvania State University, University Park, PA, United States.ORCID https://orcid.org/0000-0002-4609-4984
Deborah Brunke-ReeseThe Pennsylvania State University, University Park, PA, United States.ORCID https://orcid.org/0000-0002-8973-8671
Sarah HojjatiniaThe Pennsylvania State University, University Park, PA, United States.ORCID https://orcid.org/0000-0002-9307-2462
Constantino M LagoaThe Pennsylvania State University, University Park, PA, United States.ORCID https://orcid.org/0000-0001-6871-3240
David E ConroyThe Pennsylvania State University, University Park, PA, United States.ORCID https://orcid.org/0000-0003-0204-4093
Pennsylvania State University · US

Funding

Phase 1 clinical trial to develop a personalized adaptive text message intervention using control systems engineering tools to increase physical activity in early adulthoodR01HL142732 · NHLBI · PENNSYLVANIA STATE UNIVERSITY, THE · PI CONROY, DAVID E., LAGOA, CONSTANTINO MANUEL · 2018 to 2021
$2.4M
NHLBI NIH HHS R01 HL142732
6 · The paper itself

Abstract

backgroundDigital smartphone messaging can be used to promote physical activity to large populations with limited cost. It is not clear which psychological constructs should be targeted by digital messages to promote physical activity. This gap presents a challenge for developing optimal content for digital messaging interventions.

objectiveThe aim of this study is to compare affectively framed and social cognitively framed messages on subsequent changes in physical activity using dynamical modeling techniques.

methodsWe conducted a secondary analysis of data collected from a digital messaging intervention in insufficiently active young adults (18-29 years) recruited between April 2019 and July 2020 who wore a Fitbit smartwatch for 6 months. Participants received 0 to 6 messages at random per day across the intervention period. Messages were drawn from 3 content libraries: affectively framed, social cognitively framed, or inspirational quotes. Person-specific dynamical models were identified, and model features of impulse response and cumulative step response were extracted for comparison. Two-way repeated-measures ANOVAs evaluated the main effects and interaction of message type and day type on model features. This early-phase work with novel dynamic features may have been underpowered to detect differences between message types so results were interpreted descriptively.

resultsMessages (n=20,689) were paired with valid physical activity monitoring data from 45 participants for analysis. Received messages were distributed as 40% affective (8299/20,689 messages), 39% social-cognitive (8187/20,689 messages), and 20% inspirational quotes (4219/20,689 messages). There were no statistically significant main effects for message type when evaluating the steady state of step responses. Participants demonstrated heterogeneity in intervention response: some had their strongest responses to affectively framed messages, some had their strongest responses to social cognitively framed messages, and some had their strongest responses to the inspirational quote messages.

conclusionsNo single type of digital message content universally promotes physical activity. Future work should evaluate the effects of multiple message types so that content can be continuously tuned based on person-specific responses to each message type.

Indexed as

behavior changedynamical modelexerciseFitbitfitnessfitness trackermessagingmotivationpatient specificpatient-specific modelingphysical activitypsychological theorytracking

Identifiers

PMID37083710
PMCPMC10163402
OpenAlexW4366602439

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.