Evidence map›Paper›PMID 35108213›Full record

ArticleJMIR formative research2022

Adapting an Evidence-Based e-Learning Cognitive Behavioral Therapy Program Into a Mobile App for People Experiencing Gambling-Related Problems: Formative Study.

Gayl Humphrey, Joanna Ting Chu, Rebecca Ruwhiu-Collins, Stephanie Erick-Peleti, Nicki Dowling, Stephanie Merkouris, David Newcombe, Simone Rodda, Elsie Ho, Vili Nosa and 2 more

Open access · goldAbstract read
In one paragraph

Article in JMIR formative research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
2.3field-weighted citation impact, top 13% 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

6 citing papers in PubMed, 12 citations in OpenAlex.

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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

12 authors at 2 institutions in 2 countries.

Gayl HumphreyNational Institute for Health Innovation, University of Auckland, Auckland, New Zealand.ORCID https://orcid.org/0000-0002-2837-5707
Joanna Ting ChuNational Institute for Health Innovation, University of Auckland, Auckland, New Zealand.ORCID https://orcid.org/0000-0002-5900-8141
Rebecca Ruwhiu-CollinsHapai Te Hauora, Auckland, New Zealand.ORCID https://orcid.org/0000-0003-0353-3569
Stephanie Erick-PeletiHapai Te Hauora, Auckland, New Zealand.ORCID https://orcid.org/0000-0003-2893-3606
Nicki DowlingDeakin University, Melbourne, Australia.ORCID https://orcid.org/0000-0001-8592-2407
Stephanie MerkourisSchool of Psychology, Deakin University, Melbourne, Australia.ORCID https://orcid.org/0000-0001-9037-6121
David NewcombeSocial and Community Health, University of Auckland, Auckland, New Zealand.ORCID https://orcid.org/0000-0002-6268-786X
Simone RoddaSocial and Community Health, University of Auckland, Auckland, New Zealand.ORCID https://orcid.org/0000-0002-7973-1003
Elsie HoSocial and Community Health, University of Auckland, Auckland, New Zealand.ORCID https://orcid.org/0000-0002-7866-032X
Vili NosaPacific Health, University of Auckland, Auckland, New Zealand.ORCID https://orcid.org/0000-0002-7144-2805
Varsha ParagNational Institute for Health Innovation, University of Auckland, Auckland, New Zealand.ORCID https://orcid.org/0000-0001-6971-5782
Christopher BullenNational Institute for Health Innovation, University of Auckland, Auckland, New Zealand.ORCID https://orcid.org/0000-0001-6807-2930
University of Auckland · NZDeakin University · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMany people who experience harm and problems from gambling do not seek treatment from gambling treatment services because of personal and resource barriers. Mobile health (mHealth) interventions are widely used across diverse health care areas and populations. However, there are few in the gambling harm field, despite their potential as an additional modality for delivering treatment and support.

objectiveThis study aims to understand the needs, preferences, and priorities of people experiencing gambling harms and who are potential end users of a cognitive behavioral therapy mHealth intervention to inform design, features, and functions.

methodsDrawing on a mixed methods approach, we used creators and domain experts to review the GAMBLINGLESS web-based program and convert it into an mHealth prototype. Each module was reviewed against the original evidence base to maintain its intended fidelity and conceptual integrity. Early wireframes, design ideas (look, feel, and function), and content examples were developed to initiate discussions with end users. Using a cocreation process with a young adult, a Māori, and a Pasifika peoples group, all with experiences of problem or harmful gambling, we undertook 6 focus groups: 2 cycles per group. In each focus group, participants identified preferences, features, and functions for inclusion in the final design and content of the mHealth intervention.

resultsOver 3 months, the GAMBLINGLESS web-based intervention was reviewed and remapped from 4 modules to 6. This revised program is based on the principles underpinning the transtheoretical model, in which it is recognized that some end users will be more ready to change than others. Change is a process that unfolds over time, and a nonlinear progression is common. Different intervention pathways were identified to reflect the end users' stage of change. In all, 2 cycles of focus groups were then conducted, with 30 unique participants (13 Māori, 9 Pasifika, and 8 young adults) in the first session and 18 participants (7 Māori, 6 Pasifika, and 5 young adults) in the second session. Prototype examples demonstrably reflected the focus group discussions and ideas, and the features, functions, and designs of the Manaaki app were finalized. Attributes such as personalization, cultural relevance, and positive framing were identified as the key. Congruence of the final app attributes with the conceptual frameworks of the original program was also confirmed.

conclusionsThose who experience gambling harms may not seek help. Developing and demonstrating the effectiveness of new modalities to provide treatment and support are required. mHealth has the potential to deliver interventions directly to the end user. Weaving the underpinning theory and existing evidence of effective treatment with end-user input into the design and development of mHealth interventions does not guarantee success. However, it provides a foundation for framing the intervention's mechanism, context, and content, and arguably provides a greater chance of demonstrating effectiveness.

Indexed as

behavior changeCBTco-designengagementgamblingmHealthmobile phoneself-directedsmartphone

Identifiers

PMID35108213
PMCPMC8994147
OpenAlexW4205120755

What Socratic 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 Socratic graph.