Evidence map›Paper›PMID 35298199›Full record

ArticleThe American psychologist2022

Engagement in digital interventions.

Inbal Nahum-Shani, Steven D Shaw, Stephanie M Carpenter, Susan A Murphy, Carolyn Yoon

Abstract read
In one paragraph

Article in The American psychologist, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 113 papers, 7 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
113citing 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

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

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Pooled it
  6. Pooled it
  7. Pooled it
  8. Trial
  9. Trial
  10. Trial
  11. Trial
  12. Trial
  13. Trial
  14. Trial
  15. Trial
  16. Trial
  17. Trial
  18. Self-relevant appeals to engage in self-monitoring of alcohol use: A microrandomized trial.Psychology of addictive behaviors : journal of the Society of Psychologists in Addictive Behaviors · 2023
    Trial
  19. Trial
  20. Trial

53 more citing papers are in PubMed but not listed here.

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

5 authors.

Inbal Nahum-ShaniInstitute for Social Research.ORCID 0000-0001-6138-9089
Steven D ShawWharton School.ORCID 0000-0002-5556-5629
Stephanie M CarpenterInstitute for Social Research.ORCID 0000-0003-4523-7565
Susan A MurphyDepartment of Statistics & Computer Science.ORCID 0000-0002-2032-4286
Carolyn YoonStephen M. Ross School of Business.ORCID 0000-0002-5529-7708

Funding

Pilot and Mentoring CoreP50DA054039 · NIDA · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI LINDA M COLLINS, SUSAN A MURPHY · 2021 to 2026
$18.2M
Pilot, Mentoring, and Professional Development CoreP50DA039838 · NIDA · PENNSYLVANIA STATE UNIVERSITY, THE · PI COLLINS, LINDA M · 2015 to 2019
$13.9M
TR&D3 - Rapid Translation of AI-powered Temporally Precise mHealth Interventions via Efficient and Embeddable Trustworthy Biomarker ImplementationsP41EB028242 · NIBIB · UNIVERSITY OF MEMPHIS · PI Santosh Kumar · 2020 to 2026
$9.5M
Novel Methods for Intensive Longitudinal Data in SMART Studies of Drug Abuse and HIVR01DA039901 · NIDA · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI ALMIRALL, DANIEL, NAHUM-SHANI, INBAL BILLIE · 2015 to 2024
$5.4M
Personalized Digital Behavior Change Interventions to Promote Oral HealthUH3DE028723 · NIDCR · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI VIVEK SHETTY · 2022 to 2026
$3.8M
Novel use of mHealth data to identify states of vulnerability and receptivity to JITAIs SupplementU01CA229437 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI NAHUM-SHANI, INBAL BILLIE, WETTER, DAVID W · 2018 to 2022
$2.8M
Personalized Digital Behavior Change Interventions to Promote Oral HealthUG3DE028723 · NIDCR · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI SHETTY, VIVEK · 2019 to 2019
$460k
NCI NIH HHS U01 CA229437NIBIB NIH HHS P41 EB028242NIDA NIH HHS P50 DA039838NIDA NIH HHS P50 DA054039NIDA NIH HHS R01 DA039901NIDCR NIH HHS UG3 DE028723NIDCR NIH HHS UH3 DE028723NIH HHS
6 · The paper itself

Abstract

The notion of "engagement," which plays an important role in various domains of psychology, is gaining increased currency as a concept that is critical to the success of digital interventions. However, engagement remains an ill-defined construct, with different fields generating their own domain-specific definitions. Moreover, given that digital interactions in real-world settings are characterized by multiple demands and choice alternatives competing for an individual's effort and attention, they involve fast and often impulsive decision-making. Prior research seeking to uncover the mechanisms underlying engagement has nonetheless focused mainly on psychological factors and social influences and neglected to account for the role of neural mechanisms that shape individual choices. This article aims to integrate theories and empirical evidence across multiple domains to define engagement and discuss opportunities and challenges to promote effective engagement in digital interventions. We also propose the affect-integration-motivation and attention-context-translation (AIM-ACT) framework, which is based on a neurophysiological account of engagement, to shed new light on how in-the-moment engagement unfolds in response to a digital stimulus. Building on this framework, we provide recommendations for designing strategies to promote engagement in digital interventions and highlight directions for future research. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Indexed as

Motivation

Identifiers

PMID35298199
PMCPMC9481750

What OpenQuestion holds

Textmetadata
LicenceTDM
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.