Evidence map›Paper›PMID 32499213›Full record

ArticleJournal of medical Internet research2020

Evidence Regarding Automatic Processing Computerized Tasks Designed For Health Interventions in Real-World Settings Among Adults: Systematic Scoping Review.

Harshani Jayasinghe, Camille E Short, Annette Braunack-Mayer, Ashley Merkin, Clare Hume

Abstract readScoping Review
In one paragraph

Article in Journal of medical Internet research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–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

1 citing paper in PubMed.

  1. 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

5 authors.

Harshani JayasingheSchool of Public Health, The University of Adelaide, Adelaide, Australia.ORCID 0000-0001-6534-4005
Camille E ShortMelbourne Centre for Beahviour Change, Melbourne School of Psychological Science and Melbourne School of Health Science, University of Melbourne, Melbourne, Australia.ORCID 0000-0002-4177-4251
Annette Braunack-MayerSchool of Health and Society, University of Wollongong, Wollongong, Australia.ORCID 0000-0003-4427-0224
Ashley MerkinSchool of Medicine, The University of Adelaide, Adelaide, Australia.ORCID 0000-0001-8200-7852
Clare HumeSchool of Public Health, The University of Adelaide, Adelaide, Australia.ORCID 0000-0002-5719-3232

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDual process theories propose that the brain uses 2 types of thinking to influence behavior: automatic processing and reflective processing. Automatic processing is fast, immediate, nonconscious, and unintentional, whereas reflective processing focuses on logical reasoning, and it is slow, step by step, and intentional. Most digital psychological health interventions tend to solely target the reflective system, although the automatic processing pathway can have strong influences on behavior. Laboratory-based research has highlighted that automatic processing tasks can create behavior change; however, there are substantial gaps in the field on the design, implementation, and delivery of automatic processing tasks in real-world settings. It is important to identify and summarize the existing literature in this area to inform the translation of laboratory-based research to real-world settings.

objectiveThis scoping review aims to explore the effectiveness of automatic training tasks, types of training tasks commonly used, mode of delivery, and impacts of gamification on automatic processing tasks designed for digital psychological health interventions in real-world settings among adults.

methodsThe scoping review methodology proposed by Arskey and O'Malley and Colquhoun was applied. A scoping review was chosen because of the novelty of the digital automatic processing field and to encompass a broad review of the existing evidence base. Electronic databases and gray literature databases were searched with the search terms "automatic processing," "computerised technologies," "health intervention," "real-world," and "adults" and synonyms of these words. The search was up to date until September 2018. A manual search was also completed on the reference lists of the included studies.

resultsA total of 14 studies met all inclusion criteria. There was a wide variety of health conditions targeted, with the most prevalent being alcohol abuse followed by social anxiety. Attention bias modification tasks were the most prevalent type of automatic processing task, and the majority of tasks were most commonly delivered over the web via a personal computer. Of the 14 studies included in the review, 8 demonstrated significant changes to automatic processes and 4 demonstrated significant behavioral changes as a result of changed automatic processes.

conclusionsThis is the first review to synthesize the evidence on automatic processing tasks in real-world settings targeting adults. This review has highlighted promising, albeit limited, research demonstrating that automatic processing tasks may be used effectively in a real-world setting to influence behavior change.

Indexed as

AdultComputersElectronic Data ProcessingHumansInternet-Based InterventionYoung Adultadultautomatic processingbehavior change, mobile phonecomputerized taskshealth interventionsreal-world

Identifiers

PMID32499213
PMCPMC7424486

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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.