Evidence map›Paper›PMID 31831080›Full record

ArticleTrials2019

Retraining automatic action tendencies for smoking using mobile phone-based approach-avoidance bias training: A study protocol for a randomized controlled study.

Alla Machulska, Kristian Kleinke, Tanja Joan Eiler, Armin Grünewald, Rainer Brück, Katharina Jahn, Björn Niehaves, Carl Friedrich Gethmann, Tim Klucken

Abstract readClinical Trial Protocol
In one paragraph

Article in Trials, 2019. 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
–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

6 citing papers in PubMed.

  1. Trial
  2. Trial
  3. Article
  4. Article
  5. Article
  6. Association between Smartphone Addiction and Suicide.International journal of environmental research and public health · 2022
    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

9 authors.

Alla MachulskaDepartment of Clinical Psychology, University of Siegen, Adolf-Reichwein-Str. 2a, 57068, Siegen, Germany. alla.machulsk@uni-siegen.de.ORCID http://orcid.org/0000-0001-5968-429X
Kristian KleinkeDepartment of Clinical Psychology, University of Siegen, Adolf-Reichwein-Str. 2a, 57068, Siegen, Germany.
Tanja Joan EilerDepartment of Medical Informatics und Microsystems Engineering, University of Siegen, Siegen, Germany.
Armin GrünewaldDepartment of Medical Informatics und Microsystems Engineering, University of Siegen, Siegen, Germany.
Rainer BrückDepartment of Medical Informatics und Microsystems Engineering, University of Siegen, Siegen, Germany.
Katharina JahnDepartment of Business Informatics, University of Siegen, Siegen, Germany.
Björn NiehavesDepartment of Business Informatics, University of Siegen, Siegen, Germany.
Carl Friedrich GethmannResearch College FoKoS, University of Siegen, Siegen, Germany.
Tim KluckenDepartment of Clinical Psychology, University of Siegen, Adolf-Reichwein-Str. 2a, 57068, Siegen, Germany.

Funding

Bundesministerium für Kultur und Wissenschaft des Landes NRW (DE) 005-1706-0006
6 · The paper itself

Abstract

backgroundAutomatic tendencies to approach drug-related cues have been linked to the development and maintainance of harmful drug-taking behavior. Recent studies have demonstrated that these automatic approach tendencies can be targeted directly by means of cognitive bias modification (CBM). Moreover, changing those approach tendencies may enhance treatment outcomes. However, training and therapy effects tend to be rather small and adherence to the training might be impaired by time-consuming multiple laboratory training sessions. Here, we present a protocol for a randomized controlled design to improve CBM training efficiency and facilitate access to the training by providing mobile-phone-based training sessions at home to current smokers motivated to quit smoking.

methodsParticipants (n = 100) are current smokers who smoke at least six cigarettes per day for at least 6 months and are willing to quit smoking. All participants attend a brief behavioral smoking cessation intervention (TAU) and are randomly assigned either to an experimental (TAU + training) or a control group. Participants in the experimental condition are given access to a training application (app) aimed at retraining automatic approach biases for smoking cues. Participants are instructed to perform the app training outside the laboratory context on a daily basis for 14 consecutive days. Participants in the control group do not receive the training. Primary outcome measures are changes in smoking-related approach biases and reductions in daily nicotine consumption as assessed at baseline, post-training and at 6-week follow up. Secondary outcome measures include approach biases for alternative stimuli or smoking stimuli to which participants were not exposed during training, attentional and association biases, biochemical outcomes, and self-reported smoking behavior, also measured at three different time points (baseline, post-training, and follow up). After completion of the study, smokers in the control condition will receive access to the training app. DISCUSSION: This randomized controlled trial is the first to test the effectiveness of an app-based CBM intervention as an adjunct to a brief smoking cessation intervention in smokers motivated to quit smoking. The results of this study can inform future research in the optimization and advancement of CBM treatment for addiction.

trial registrationCurrent Controlled Trials, ISRCTN15690771. Registered on 20 November 2018.

Indexed as

Cell PhoneAdultBiasCognitive Behavioral TherapyCuesHumansRandomized Controlled Trials as TopicSmokingSmoking CessationSmoking PreventionTobacco Use DisorderTreatment OutcomeApproach biasCigarette smokingCognitive bias modificationNicotine addictionRandomized controlled trialSmartphone apps

Identifiers

PMID31831080
PMCPMC6909563

What OpenQuestion holds

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Registered trials

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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.