Evidence map›Paper›PMID 31890619›Full record

ArticleInternet interventions2019

Predicting engagement with an online psychosocial intervention for psychosis: Exploring individual- and intervention-level predictors.

Chelsea Arnold, Kristi-Ann Villagonzalo, Denny Meyer, John Farhall, Fiona Foley, Michael Kyrios, Neil Thomas

Open access · goldAbstract read
In one paragraph

Article in Internet interventions, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed, 3 pooled it
5.8field-weighted citation impact, top 4% 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

34 citing papers in PubMed, 3 syntheses or guidelines pooled it, 68 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Predictors of initial engagement with an asynchronous cognitive behavioral stress management website among older women with nonmetastatic breast cancer.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2023
    Trial
  5. Trial
  6. Trial
  7. Trial
  8. Article
  9. Investigating the Role of Situational Disruptors in Engagement with Digital Mental Health Tools.CSCW : proceedings of the Conference on Computer-Supported Cooperative Work. Conference on Computer-Supported Cooperative Work · 2025
    Article
  10. Article
  11. Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Review
  20. 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 4 institutions in 1 country.

Chelsea ArnoldCentre for Mental Health, Swinburne University of Technology, Melbourne, Australia.
Kristi-Ann VillagonzaloCentre for Mental Health, Swinburne University of Technology, Melbourne, Australia.
Denny MeyerCentre for Mental Health, Swinburne University of Technology, Melbourne, Australia.
John FarhallDepartment of Psychology and Counselling, La Trobe University, Melbourne, Australia.
Fiona FoleyCentre for Mental Health, Swinburne University of Technology, Melbourne, Australia.
Michael KyriosCollege of Education, Psychology and Social Work, Flinders University, Adelaide, Australia.
Neil ThomasCentre for Mental Health, Swinburne University of Technology, Melbourne, Australia.
Swinburne University of Technology · AUFlinders University · AULa Trobe University · AUThe Alfred Hospital · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIndividuals with psychosis demonstrate positive attitudes towards utilising digital technology in mental health treatment. Although preliminary research suggests digital interventions are feasible and acceptable in this population, little is known about how to best promote engagement with these resources. Candidate predictors include therapist support, sources of motivation and recovery style. Understanding what factors predict engagement will aid more effective design and implementation of digital interventions to improve clinical benefits.

objectiveThis study aimed to investigate demographic, psychological, and treatment variables that predict overall and type of engagement with a psychosocial, online intervention for individuals with psychosis.

methodsNinety-eight participants with a history of psychosis were given access to a web program containing modules on self-management and recovery, which they were asked to use flexibly at their own pace. Activity was automatically logged by the system. Baseline measures of demographics, recovery style and motivation were administered, and participants were randomised to receive either website access alone, or website access plus weekly, asynchronous emails from an online coach over 12 weeks. Log and baseline assessment data were used in negative binomial regressions to examine predictors of depth and breadth of use over the intervention period. A logistic regression was used to examine the impact of predictor variables on usage profiles (active or passive).

resultsDepth and breadth of engagement were positively predicted by receiving email support, low levels of externally controlled motivations for website use, older age, and having a tertiary education. There was a significant interaction between level of controlled motivation and condition (+/-email) on breadth and depth of engagement: receiving asynchronous emails was associated with increased engagement for individuals with low, but not high, levels of externally controlled motivations. Receiving email support and more autonomous motivations for treatment predicted more active use of the website.

conclusionsAsynchronous email support can promote engagement with online interventions for individuals with psychosis, potentially enabling self-management of illness and improving clinical outcomes. However, those using online interventions due to external motivating factors, may have low levels of engagement with the intervention, irrespective of coaching provided. These findings may guide design and implementation of future online interventions in this population.

Indexed as

ACMTQ, Autonomous and Controlled Motivations for Treatment QuestionnaireDigital mental healthDigital technologyEngagementInterventionIRR, Incidence rate ratioPsychosisRSQ, Recovery Style QuestionnaireSCID, Structured Clinical Interview for DSM-IV-TR Axis I DisordersSMART, Self-Management and Recovery Technology

Identifiers

PMID31890619
PMCPMC6926321
OpenAlexW2968677664

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.