Improving the efficacy of cognitive training for digital mental health interventions through avatar customization: crowdsourced quasi-experimental study

Max Valentin Birk (Corresponding author), Regan Lee Mandryk

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Abstract

Background: The success of internet-based mental health interventions in practice—that is, in the wild—depends on the uptake and retention of the application and the user’s focused attention in the moment of use. Incorporating game-based motivational design into digital interventions delivered in the wild has been shown to increase uptake and retention in internet-based training; however, there are outstanding questions about the potential of game-based motivational strategies to increase engagement with a task in the moment of use and the effect on intervention efficacy. Objective: Designers of internet-based interventions need to know whether game-based motivational design strategies can increase in-the-moment engagement and thus improve digital interventions. The aim of this study was to investigate the effects of 1 motivational design strategy (avatar customization) in an example mental health intervention (computerized cognitive training for attention bias modification). Methods: We assigned 317 participants to either a customized avatar or an assigned avatar condition. After measuring state anxiety (State-Trait Anxiety Inventory), we randomly assigned half of the participants in each condition to either an attentional retraining condition (Attention Bias Modification Training) or a control condition. After training, participants were exposed to a negative mood induction using images with strong negative valance (International Affective Picture System), after which we measured state anxiety again. Results: Avatar customization decreased posttraining state anxiety when controlling for baseline state anxiety for those in the attentional retraining condition; however, those who did not train experienced decreased resilience to the negative mood induction (F 1,252=6.86, P=.009, η p 2=.027). This interaction effect suggests that customization increased task engagement with the intervention in the moment of use. Avatar customization also increased avatar identification (F 5,252=12.46, P<.001, R 2=.23), regardless of condition (F 1,252=.79, P=.38). Avatar identification reduced anxiety after the negative mood induction for participants who underwent training but increased poststimulus anxiety for participants who did not undergo training, further suggesting that customization increases engagement in the task (F 1,252=6.19, P=.01). The beneficial effect of avatar customization on training was driven by participants who were low in their basic satisfaction of relatedness (F 10,248=18.5, P<.001, R 2=.43), which is important because these are the participants who are most likely in need of digital interventions for mental health. Conclusions: Our results suggest that applying motivational design—specifically avatar customization—is a viable strategy to increase engagement and subsequently training efficacy in a computerized cognitive task.

Original languageEnglish
Article numbere10133
Number of pages18
JournalJournal of Medical Internet Research
Volume21
Issue number1
DOIs
Publication statusPublished - Jan 2019

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Mental Health
Anxiety
Internet
Non-Randomized Controlled Trials
Equipment and Supplies

Keywords

  • Attentional bias
  • Cognitive bias
  • Cognitive therapy
  • Computer-assisted therapy
  • Motivation
  • Video games
  • computer-assisted therapy
  • cognitive bias
  • motivation
  • attentional bias
  • cognitive therapy
  • video games

Cite this

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title = "Improving the efficacy of cognitive training for digital mental health interventions through avatar customization: crowdsourced quasi-experimental study",
abstract = "Background: The success of internet-based mental health interventions in practice—that is, in the wild—depends on the uptake and retention of the application and the user’s focused attention in the moment of use. Incorporating game-based motivational design into digital interventions delivered in the wild has been shown to increase uptake and retention in internet-based training; however, there are outstanding questions about the potential of game-based motivational strategies to increase engagement with a task in the moment of use and the effect on intervention efficacy. Objective: Designers of internet-based interventions need to know whether game-based motivational design strategies can increase in-the-moment engagement and thus improve digital interventions. The aim of this study was to investigate the effects of 1 motivational design strategy (avatar customization) in an example mental health intervention (computerized cognitive training for attention bias modification). Methods: We assigned 317 participants to either a customized avatar or an assigned avatar condition. After measuring state anxiety (State-Trait Anxiety Inventory), we randomly assigned half of the participants in each condition to either an attentional retraining condition (Attention Bias Modification Training) or a control condition. After training, participants were exposed to a negative mood induction using images with strong negative valance (International Affective Picture System), after which we measured state anxiety again. Results: Avatar customization decreased posttraining state anxiety when controlling for baseline state anxiety for those in the attentional retraining condition; however, those who did not train experienced decreased resilience to the negative mood induction (F 1,252=6.86, P=.009, η p 2=.027). This interaction effect suggests that customization increased task engagement with the intervention in the moment of use. Avatar customization also increased avatar identification (F 5,252=12.46, P<.001, R 2=.23), regardless of condition (F 1,252=.79, P=.38). Avatar identification reduced anxiety after the negative mood induction for participants who underwent training but increased poststimulus anxiety for participants who did not undergo training, further suggesting that customization increases engagement in the task (F 1,252=6.19, P=.01). The beneficial effect of avatar customization on training was driven by participants who were low in their basic satisfaction of relatedness (F 10,248=18.5, P<.001, R 2=.43), which is important because these are the participants who are most likely in need of digital interventions for mental health. Conclusions: Our results suggest that applying motivational design—specifically avatar customization—is a viable strategy to increase engagement and subsequently training efficacy in a computerized cognitive task.",
keywords = "Attentional bias, Cognitive bias, Cognitive therapy, Computer-assisted therapy, Motivation, Video games, computer-assisted therapy, cognitive bias, motivation, attentional bias, cognitive therapy, video games",
author = "Birk, {Max Valentin} and Mandryk, {Regan Lee}",
year = "2019",
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T1 - Improving the efficacy of cognitive training for digital mental health interventions through avatar customization

T2 - crowdsourced quasi-experimental study

AU - Birk, Max Valentin

AU - Mandryk, Regan Lee

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N2 - Background: The success of internet-based mental health interventions in practice—that is, in the wild—depends on the uptake and retention of the application and the user’s focused attention in the moment of use. Incorporating game-based motivational design into digital interventions delivered in the wild has been shown to increase uptake and retention in internet-based training; however, there are outstanding questions about the potential of game-based motivational strategies to increase engagement with a task in the moment of use and the effect on intervention efficacy. Objective: Designers of internet-based interventions need to know whether game-based motivational design strategies can increase in-the-moment engagement and thus improve digital interventions. The aim of this study was to investigate the effects of 1 motivational design strategy (avatar customization) in an example mental health intervention (computerized cognitive training for attention bias modification). Methods: We assigned 317 participants to either a customized avatar or an assigned avatar condition. After measuring state anxiety (State-Trait Anxiety Inventory), we randomly assigned half of the participants in each condition to either an attentional retraining condition (Attention Bias Modification Training) or a control condition. After training, participants were exposed to a negative mood induction using images with strong negative valance (International Affective Picture System), after which we measured state anxiety again. Results: Avatar customization decreased posttraining state anxiety when controlling for baseline state anxiety for those in the attentional retraining condition; however, those who did not train experienced decreased resilience to the negative mood induction (F 1,252=6.86, P=.009, η p 2=.027). This interaction effect suggests that customization increased task engagement with the intervention in the moment of use. Avatar customization also increased avatar identification (F 5,252=12.46, P<.001, R 2=.23), regardless of condition (F 1,252=.79, P=.38). Avatar identification reduced anxiety after the negative mood induction for participants who underwent training but increased poststimulus anxiety for participants who did not undergo training, further suggesting that customization increases engagement in the task (F 1,252=6.19, P=.01). The beneficial effect of avatar customization on training was driven by participants who were low in their basic satisfaction of relatedness (F 10,248=18.5, P<.001, R 2=.43), which is important because these are the participants who are most likely in need of digital interventions for mental health. Conclusions: Our results suggest that applying motivational design—specifically avatar customization—is a viable strategy to increase engagement and subsequently training efficacy in a computerized cognitive task.

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KW - Cognitive therapy

KW - Computer-assisted therapy

KW - Motivation

KW - Video games

KW - computer-assisted therapy

KW - cognitive bias

KW - motivation

KW - attentional bias

KW - cognitive therapy

KW - video games

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