{"paper_id":"520128aa-0e4e-49c5-a6b7-9ccded376477","body_text":"Investigating the effects of a novel gamified cognitive training on adolescent mental health | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Investigating the effects of a novel gamified cognitive training on adolescent mental health Karina Grunewald, Savannah Minihan, Jack L. Andrews, Annabel Songco, and 9 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5900018/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 03 Jul, 2025 Read the published version in Child and Adolescent Psychiatry and Mental Health → Version 1 posted 9 You are reading this latest preprint version Abstract Background Adolescence is a time of increased emotional volatility, with emotion regulation still developing. Training the cognitive substrate of successful emotion regulation has been shown to benefit adolescents’ mental health. However, cognitive training interventions often have low adherence rates in this age group. The current study therefore trialled a novel gamified cognitive training program in adolescents. Methods A longitudinal study was conducted throughout 2023 where 144 culturally diverse adolescents (13–16 years, 48% female) completed 12 days of either a novel gamified affective control training program, the Social Brain Train (SBT), or a standard non-gamified affective control training program (AffeCT). Participants also completed mental health and mechanisms of change questionnaires at baseline, post-training, and 1-month follow-up, as well as behavioural affective control and interpretation bias measures at baseline and post-training. Results The total minutes spent training did not differ significantly across the two training groups. Participants assigned to SBT training, however, did engage in more training sessions than participants assigned to AffeCT training. Additionally, all participants showed improvements in affective control performance and a reduction in interpretation bias and rumination from baseline to post-training. The observed reduction in rumination persisted at 1-month follow-up. Conclusions As engagement is often the most difficult thing to achieve in cognitive training with adolescents, observing greater repeated engagement with the gamified cognitive training is promising, given training on these apps is entirely self-motivated. Observing benefits to affective and cognitive control performance and reduced interpretation bias and rumination tendencies after very limited training is also promising, as these factors have all been previously linked to improved mental health symptoms among adolescents. The present findings therefore suggest there may be merit in using gamification techniques to improve the design of future training programs, and employing these to improve affective, cognitive, and emotion regulation abilities in adolescents. Mental health Adolescent Depression Emotion Regulation Cognitive training Gamification Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Adolescence (10–24 years; ( 1 , 2 )), is a sensitive period for the development of mental health disorders. Indeed, most mental health disorders first onset by 24 years, and often persist across the lifespan ( 3 ). Of these, emotional disorders including depression and anxiety are the most common ( 4 ). Yet, despite these disorders being the leading burden of disease in adolescence ( 5 , 6 ), current psychological and pharmacological treatments often show limited efficacy. Meta-analytic evidence suggests that less than 40% of adolescents respond to psychological treatments for depression ( 9 ), and only 36% of adolescents receiving treatment for anxiety disorders were in remission post treatment ( 10 ). Adolescent responses to pharmacological treatments of depression have been similarly low ( 11 ). Identifying novel avenues for intervention and prevention of adolescent anxiety and depression that are deliverable at scale is therefore urgent. Researchers have proposed that current interventions may be unsuccessful in treating emotional disorders, as they fail to target key risk factors underlying vulnerability to these disorders ( 12 ). One such risk factor is emotion regulation ( 13 ), individuals’ ability to influence their emotions, where emotions refer to temporally limited, positively or negatively valenced and situationally-bound experiences ( 14 ). Difficulties in emotion regulation during adolescence have been robustly linked to the onset and maintenance of adolescent mental health problems ( 15 ), as well as treatment responsiveness ( 16 ). Developmental research shows that emotion regulation improves throughout adolescence ( 17 ), in tandem with its underlying cognitive ( 18 ) and neural ( 19 ) substrates. Successful emotion regulation has been proposed to rely on cognitive control ( 20 ), the ability to attend to and respond to goal-relevant stimuli while inhibiting attention and responses to goal-irrelevant stimuli ( 21 ). Especially, improvements in the application of cognitive control in affective contexts, affective control , may be central to the development of successful emotion regulation ( 22 ). Targeting these cognitive substrates has therefore been proposed as an effective means to intervene in the development and maintenance of emotional disorders ( 23 ). Encouragingly, researchers have found that affective control is amenable to cognitive training, and training effects have been associated with improvements in emotion regulation and a range of clinical outcomes including depression and anxiety in adolescence ( 23 ). However, studies have found that cognitive training interventions have low engagement and adherence rates among adolescents ( 24 – 26 ), as adolescents often report finding low motivation for exerting effort to complete cognitive tasks ( 27 ). As a result, while improving affective control through cognitive training constitutes a promising avenue for intervention, low engagement limits its viability as an intervention or as a target for prevention. One way to effectively augment adolescents’ participation in cognitive training is gamification. Gamification, the use of game-like features such as narrative storylines and points systems, has been reliably shown to improve both attentional engagement with training and motivation to increase training time ( 28 ). It may be especially useful for interventions aimed at adolescents, as 90% of Australian adolescents report playing digital games regularly, averaging approximately 98 minutes of gameplay each day ( 29 ). Gamification also allows the creation of ecologically-valid content that is reflective of users’ real-world environments and experiences. As motivation and attentional capture are crucial for cognitive training success ( 30 ), and ecological validity improves the transferability of training gains to real-world problems ( 31 ), gamification appears to offer an existing opportunity to boost the uptake of cognitive training in adolescents. The current study aimed to explore the effectiveness of a novel gamified app-based affective control training program, the Social Brain Train (SBT). The SBT comprised three components: a standard affective control training component (affective dual n -back task), a cognitive interpretation bias modification (CBM-I) component and a psychoeducation component. The affective dual n -back task required flexible engagement (remembering emotional words) and disengagement (inhibiting the processing of the task-irrelevant emotional expressions) with affective information. This specific task has previously been shown to lead to improvements in affective control, emotion regulation, and mental health in adolescents and young adults ( 26 , 32 , 33 ). In the SBT, the affective n -back task was gamified, with points awarded for performance. The CBM-I component required participants to solve ambiguous social “puzzles” in a positive way. CBM-I training has previously been shown to successfully reduce interpretation bias in adolescents ( 34 ), which is associated with adolescent depression and anxiety ( 4 , 35 ). The CBM-I also introduced a new “game” element to the training and allowed participants to directly train the application of affective control, as adolescents had to override any prepotent negative response tendencies and regulate any affective responses that the scenarios may elicit to resolve the puzzles positively. Lastly, the SBT further promoted gamification through the inclusion of badges and fun facts about mental health and the human brain (i.e., psychoeducation component) that could be unlocked throughout training completion. Psychoeducation in itself has small but positive effects on emotional disorders ( 36 , 37 ). Combining affective control training with CBM-I then increases opportunities to practice the application of affective control in real-world analogue scenarios. This intervention’s optimisation was further enhanced by psychoeducation contents that provide a rationale to motivate participation in the training. The SBT’s effectiveness was compared with a non-gamified affective control training (AffeCT). Participants were 13–16 years of age, as this age range precedes and includes the ages – 16–17 years ( 38 ) – at which a sudden rise in symptoms of emotional disorders is observed in epidemiological studies. The present study allowed us to investigate the following pre-registered hypotheses: The SBT group would spend more time training (in minutes) than the AffeCT group. Time spent training across groups would be associated with improved performance on a non-trained affective control task (H2a) and social interpretation bias (H2b); and the effect of training time on interpretation bias would be greater in the SBT than the AffeCT group (H2c). Improvements in affective control would be associated with baseline to post-training changes in emotion regulation (H3a) and improvements in affective control and interpretation bias would be associated with lower depressive and anxiety symptoms (H3b). Materials and Methods This study was approved by the University of New South Wales Human Research Executive Committee (HC230164) and a protocol was pre-registered prior to participant recruitment ( https://osf.io/preprints/psyarxiv/rpvh9 ). For sample size calculation, eligibility criteria, and participant exclusions, please see supplementary materials. Consent and Assent Before completing the study, prospective participants provided informed consent from their parent or guardian. Parents/guardians could follow a URL to access study information and the consent procedure on Qualtrics ( https://www.qualtrics.com ). Eligible participants with parental/guardian consent were invited to complete an informed assent procedure on Gorilla Experiment Builder ( https://gorilla.sc ), after which they were given access to the baseline assessment. During baseline and post-training assessments, participants were reminded that they could withdraw consent at any time before, during, or after the study with no consequences, and that they would receive up to AUD60 (GBP30) reimbursement for all parts of the study completed up to withdrawal. Participants The final sample size used for data analysis comprised 144 participants recruited in 2023 through schools, social media advertisement, the MQ participate and Children Helping Science websites, and advertisements on the research lab website and the community (Table 1 ). While advertisements and recruitment efforts were targeted at participants from Australia and the UK, where the lead researchers were based, some participants from the USA and India signed up for the study through online recruitment platforms. If these participants obtained parental consent and met all other eligibility requirements, they were included in the study. Table 1 Sample characteristics (N = 144), means and standard deviations of variables Mean (SD)/N (%) Age (years) 14.77 (1.12) SES 2.81 (0.31) Gender Female 69 (47.92%) Male 73 (50.69%) Non-binary 2 (1.39%) Country Australia 77 (53.47%) United Kingdom 48 (33.33%) United States of America 17 (11.81%) India 2 (1.39%) Ethnicity Aboriginal or Torres Strait Islander 2 (1.39%) Asian 22 (15.28%) Black 7 (4.86%) White 98 (68.06%) Mixed 10 (6.94%) Other 4 (2.78%) Prefer not to say 1 (0.69%) Education Current student 142 (%) Prefer not to say 2 (%) Note . SES = socio-economic status, derived from the average level of parental education for up to 2 parents (1 = primary school; 2 = high school, professional/vocational training; 3 = university). Allocation Procedure Eligible participants who completed the baseline questionnaires were randomised to either the SBT ( N = 77) or the AffeCT ( N = 67) group (see supplementary materials for randomization procedure). Measures For details on all self-report measures please see supplementary materials. Means and standard deviations of measures are presented in Table 2 . Participant Characteristics A brief questionnaire was used to measure demographic characteristics (e.g., age, gender, ethnicity), history of mental health and learning and neurodevelopmental disorders. To explore whether training increased overall screentime use, participants were also asked for their average daily screentime usage (indicated within their device settings). These measures were all assessed at baseline, with screentime assessed again at post-training. Mental Health and Functioning Participants completed measures of anxiety (Generalized Anxiety Disorder Scale; ( 39 ); baseline: ωT = .94; post: ωT = .94; follow-up: ωT = .96), depression (Patient Health Questionnaire – Adolescent; ( 40 ); baseline: ωT = .94; post: ωT = .95; follow-up: ωT = .96), functional impairment (modified - see supplementary for details - version of the Child Anxiety Life Interference Scale; ( 41 ); baseline: ωT = .90; post-training: ωT = .90; follow-up: ωT = .93). All measures showed good reliability in the current sample at baseline, post-training and follow-up. Mechanisms of change Self-report measures. Emotion regulation, specifically reappraisal, was assessed with the reappraisal subscale of the Emotion Regulation Questionnaire – child and adolescent version (( 42 ); baseline: ωT = .90; post: ωT = .93; follow-up: ωT = .91) and rumination was assessed with the Repetitive Thinking Questionnaire (( 43 ); baseline: ωT = .92; post: ωT = .93; follow-up: ωT = .93). Pre-registered exploratory moderators social sensitivity (Online and Offline Social Sensitivity Scale; ( 44 ); baseline: ωT = .90; post: ωT = .92; follow-up: ωT = .87) and social risk concern (social subscale of the Health and Social Risk Questionnaire; ( 45 ); baseline: ωT = .78; post: ωT = .84; follow-up: ωT = .80) were also measured. Interpretation bias. Interpretation bias was measured through a scrambled sentences task (SST) developed for adolescents ( 46 ). The task comprises 40 trials reflecting general and social anxiety-related concerns. Twenty trials were completed at baseline, and 20 at post-training (counterbalanced across participants). Each trial required participants to unscramble a scrambled statement. Statements could be unscrambled to hold a positive or negative meaning. Each trial required participants to include five of six available words in a statement within 30s. For example, “people, dislike, new, enjoy, meeting, I” could be unscrambled to “I enjoy/dislike meeting new people”, with the selection of enjoy or dislike rendering the statement positive or negative, respectively. In the present study, the statement “relaxed with tense I’m children older ” was modified to “relaxed with tense I’m people other ”, to ensure all sentences were age appropriate for our sample. Additionally, each administration of the task contained one neutral sentence (e.g., “I read like books to magazines”) as a baseline response for the task. That is, the current version included twenty-one trials at baseline and post-intervention. The task was performed under a cognitive load, with participants required to hold a 4-digit number in mind throughout the task. The cognitive load was introduced to the task to disrupt volitional efforts to supress, modify or edit thoughts ( 46 ). Interpretation bias was operationalised as the proportion of sentences completed correctly with a negative valence, such that higher scores indicated greater negative interpretation bias. The inclusion of the neutral sentences as a covariate in the analyses did not change the pattern of results and is therefore not reported in the current manuscript. Affective control. Affective control was assessed with a 2-back task ( 47 ). Participants indicated via button press whether the word they were currently seeing was the same as the word presented two-words-back. The task was completed twice, once with 22 neutral words (e.g., stair) and once with 22 affective words (e.g., rude) from the English lemmas database ( 48 ). Trials (i.e., words) progressed if no response was given after 2,500ms. Affective control was operationalised as average reaction time (RT) on correct trials of the affective minus neutral 2-back conditions, with more negative scores indicating greater affective control. Acceptability Intervention acceptability measures (i.e., completion rate and the app’s perceived helpfulness, ease of use and likeability) were adapted from an existing smartphone acceptability measure ( 49 ) and assessed at post-training. Table 2 Means and standard deviations of variables of interest across time points Variable Baseline mean (SD) Post-training mean (SD) Follow-up mean (SD) Affective Control -4.35 (235.95) 12.40 (199.09) N/A Interpretation Bias 0.30 (0.24) 0.21 (0.21) N/A Emotion Regulation 27.08 (6.13) 28.00 (6.91) 27.37 (6.95) Rumination 29.93 (8.80) 27.58 (9.22) 26.38 (8.95) Depression 6.65 (6.61) 5.14 (5.94) 5.73 (6.67) Anxiety 6.44 (6.06) 4.76 (5.28) 5.29 (5.95) Social Sensitivity 25.19 (9.95) 24.48 (11.16) 23.33 (9.20) Social Risk Concern 41.18 (18.06) 39.28 (16.29) 39.46 (16.00) Affective Control Change (baseline to post-training) N/A -20.13 (238.55) N/A Interpretation Bias Change (baseline to post-training) N/A 0.05 (0.18) N/A Note . Affective Control = average RT on correct trials of the emotional 2-back task minus average RT on correct trials of the neutral 2-back task. Interpretation Bias = proportion of negative grammatically correct sentences in the Scrambled Sentences Task. Emotion Regulation = total score on ERQ reappraisal subscale. Rumination = total score on RTQ. Depression = total score on PHQ. Anxiety = total score on GAD. Social Sensitivity = total score on O 2 S 3 . Social Risk Concern = Average score of HSRQ rating scales. Affective Control Change = change in average RT on correct trials of the emotional minus neutral 2-back task from baseline to post-training. Interpretation Bias Change = Change in proportion of negative grammatically correct sentences in the SST from baseline to post-training. Training Programs Participants completed 12 training sessions of either SBT or AffeCT over a 15-day period. To promote training completion, participants received training reminders at 8am and 5pm each day. Training was self-paced, as total time training was one of the outcomes of interest. Once all 12 sessions were completed, participants could opt to repeat any previously completed session. Means and standard deviations of training variables are presented in Table 3 . Social Brain Train In the SBT each training session began with four brief questions about participants’ mood (ranging from very unhappy to very happy ), affect regulatory intentions (e.g., avoidance, acceptance), social context (e.g., alone, with friends/family), and current activity. Participants then alternated between the affective control (5 blocks), CBM-I (7 scenarios) and psychoeducation (1 brain and 1 mental health fact) components (Fig. 2). At the end of each training session, participants had the option to continue training on the affective control component, however the next training session could not be accessed until the following day. Figure 2 Depiction of One Training Session of the SBT Note Figure 2 shows the structure of one training session of the SBT. Participants first completed four brief questions (~ 30s) about their mood, affect regulatory intentions, social context, and current activity. Participants then alternated between completing five blocks of affective control training (~ 1-1.5mins per block) and seven ambiguous social interaction scenarios (~ 10-20s per scenario). Within each training session, participants unlocked facts about mental health and the social and emotional brain (~ 40s per fact) after block two and four of affective control training. Participants also received points after completing each block of affective control training (1 point: ≤ 50% correct; 10 points: 51–80% correct; 30 points: ≥ 81% correct), and 2 additional points for each social interaction scenario completed correctly (i.e., scenarios where the positive resolution was selected). Upon session completion, the app flow locked and participants were unable to access the next training session until the following day, but could still complete as many extra blocks of affective control training as they wished. Affective Control Training. The affective dual n -back task comprised 15 + n trials where the image of a face (appearing on a 4x4 grid for 500ms) and a spoken word were presented simultaneously (Fig. 3). Participants were asked to indicate whether the stimuli were the same (words) or appeared in the same location (faces) as the stimuli presented n -trials back (for details on stimuli, please see 50). Responses were indicated via button press ( no match , location match , word match , or both match ), with feedback provided after each trial. Participants had 2500ms to respond before the next word/face pair appeared, with responses marked as incorrect if no selection was made within this time. At the start of training (i.e., the first training session), n was set to one. For each subsequent training session, the starting level of n was the final n achieved the previous session minus two. The level of n within a training session was titrated to performance. When performance reached ≥ 70% accuracy, n increased by one, while n decreased by one when accuracy was ≤ 30%. Figure 3 Depiction of the affective control training components Note Figure 3 depicts a block of 15 + n trials of the affective control training component of the SBT where n = 1. Participants were therefore asked to indicate whether the location of the face presented in the current trial matched the location of the face presented in the previous trial, and whether the word presented in the current trial was also presented in the previous trial. Target trials (i.e., trials with a location and/or a word match) are depicted with a yellow background. Participants indicated whether either or both stimuli matched the stimuli presented n -trials back within 2500ms from the onset of the stimuli. After a response was made or the time expired, the next word-image pairing then appeared. Cognitive interpretation bias modification . The CBM-I component comprised seven ambiguous social interaction scenarios (trials) per training session. The ambiguous social interaction scenarios were presented in four interactive ways: 1) text message scenarios (Fig. 4A), a missing text fragment; 2) audio scenarios (Fig. 4B), a missing fragment from a voicemail recording; 3) narrative vignette scenarios (Fig. 4C), missing letters in a word fragment; and 4) emotion detection scenarios (Fig. 4D), where participants identified the emotional content of an image. Participants were required to resolve each scenario positively within 7s, with feedback provided after each trial. Researchers have previously shown that adolescents can learn to positively resolve ambiguous social interaction scenarios ( 35 ). Figure 4 Depiction of the Ambiguous Social Interaction Scenarios Note Figure 4 depicts the four different ways the CBM-I scenarios were presented throughout training. Panel A shows the text message format. Participants were first shown the text message interaction, then asked to choose between one of two options to resolve a missing fragment of the text message interaction, before then being shown the scenario resolution and receiving feedback. Panel B shows the audio format. Participants were first given a brief description of the context of the voicemail, then listened to the voicemail (they could also follow a transcript at the bottom of the screen), before being asked to choose between two of the options to resolve a missing fragment of the voicemail. On the final screen, the scenario was resolved and participants received feedback. Panel C shows the narrative vignette format. Participants first read about the narrative ambiguous social interaction scenario, before being asked to complete a missing word fragment to resolve the scenario, and lastly being shown the scenario resolution and receiving feedback. Panel D shows the emotion detection format. Participants were first asked to identify the emotional content of an image, before then being shown the scenario resolution and receiving feedback. In all four formats, a correct response was indicated by a green tick, while an incorrect response was indicated by a red cross. Gamification and Incentivization. To incentivise participation, several gamification components were built into the app. Participants could choose one of 45 brain avatars after downloading the app (Fig. 5A) and were awarded “brain points” based on their task performance throughout training (Fig. 5B). During each training session participants also unlocked one fact about the human brain, and one fact about mental health (four facts on days 11 and 12). The 28 brain and mental health facts were designed to present psychoeducation content, including concepts such as neuroplasticity, in engaging text and video-based formats. Within each session, participants reached “brain stations” (Fig. 5C) as they progressed through the app, and after completing a training session in full they received “brain badges” (Fig. 5D). These stations and badges thematically matched the corresponding day’s brain/mental health facts and contained a code to unlock a linked webpage with additional resources related to that day’s brain/mental health topic (e.g., additional information on neuroplasticity). Once unlocked, badges remained accessible in a participant’s app profile for the duration of training. Figure 5 Depiction of Gamification Components Note Figure 5 depicts the gamification components of the SBT. Panel A shows the avatars participants could choose after downloading the app. Panel B shows an example of the “brain points” participants could receive for completing the affective control and CBM-I components of training. Panel C depicts an example of the “brain stations” participants reached at the end of each training session. Panel D shows some examples of the “brain badges” participants unlocked as they completed each training session. Affective Control Training Like the SBT, each AffeCT session started with 4 questions about mood, affect regulation, social context and current activity. AffeCT ( 51 ) then included the same dual n -back task as per the SBT. The only differences in the AffeCT dual n -back were that each block contained 20 + n trials, and each session was made up of 30 blocks. Participants were able to end each training session any time from 10 minutes onwards, and there was no limit on the number of training sessions participants could complete within a day. The first day of AffeCT training started at n = 1, with the level of n for each subsequent day of training starting at the average n achieved in the previous day’s training session. Table 3 Means and standard deviations of variables of interest across training groups Variable SBT ( n = 77) mean (SD) AffeCT ( n = 67) mean (SD) App usage 59.73 (67.24) 40.58 (81.84) App sessions 6.61 (7.27) 3.61 (7.08) N-back usage 82.37 (51.54) 110.62 (101.80) Max N 3.81 (2.07) 4.29 (2.87) Mean N 2.31 (1.23) 2.42 (1.32) CBMI usage 44.31 (50.90) N/A CBMI RT 3889.267 (654.79) N/A CBMI accuracy 51.47(35.54) N/A Psychoed usage 20.51 (24.70) N/A Note . App usage = average time (mins) spent in the assigned training app in total. App sessions = average number of times participants engaged in a training session in the assigned training app in total (a new engagement was counted each time there was a break longer than 5 minutes between the end of the previous engagement and the start of the next engagement). N-back usage = amount of time (mins) spent training on the n-back task of the assigned training app. Max N = maximum N level reached across all trials of the assigned training app. Mean N = average N level reached across all trials of the assigned training app. CBMI usage = total time (mins) spent on CBMI tasks in the SBT app across all SBT app sessions. CBMI RT = average RT (ms) on correct CBMI trials across all SBT app sessions. CBMI accuracy = total correct CBMI trials across all SBT app sessions. Psychoed usage = total time (mins) spent on psychoeducation components in the SBT app across all SBT app sessions. Procedure All study components were completed online. After completing consent and assent procedures, participants completed all baseline assessments. They were then allocated to complete either AffeCT or SBT across two weeks, receiving an email from the research lab detailing how to download and access their assigned app to complete the training. Throughout the two weeks of training, participants with notifications enabled received daily alerts from their training app to complete training, the first sent at 8am and the second at 5pm. Following the training, participants completed the post-training assessments (as baseline) and one-month follow-up assessment. All baseline, post-training and follow-up assessments were conducted using Gorilla Experiment Builder ( https://gorilla.sc ). Through the inbuilt participant messaging system within the Gorilla platform, participants were emailed links to complete the assessments at each time point. Those who did not complete the assessment at a given time point received two reminders to do so, the first sent 3 days after the initial email, and the second sent 7 days after the initial email. Participants were reimbursed with an AUD50 (GBP25) voucher for completing baseline, training and post-training assessments, and received an additional AUD10 (GBP5) voucher for completing the follow-up assessment. For a schematic overview of all measures and when they were administered, see Figure S2. Analyses All statistical analyses were conducted using R version 4.2.1 ( 52 ). See supplementary materials for a list of R packages used. Training groups (SBT vs. AffeCT) were compared on baseline characteristics and changes over time on the outcomes of interest prior to hypothesis testing. Hypothesis 1 was tested with a general linear model, with training group entered as a predictor and minutes spent training as the outcome. Exploratory analyses were also run with app sessions and n-back usage separately added as the outcome in the model testing H1. App sessions were operationalised as the average number of times participants engaged in a training session in their assigned app, while n-back usage was operationalised as the average amount of time (minutes) participants spent on the n-back task of their assigned training app. Prior to testing hypotheses 2–3, exploratory analyses were run to investigate the effects of time (baseline vs post-training) on mental health, interpretation bias and affective control using mixed models, a Bonferroni correction of p ≤ .003 (.05/16) was applied to account for 16 additional comparisons. Hypotheses 2 and 3 were tested using linear mixed models, with time (baseline vs post-training) as a fixed within-subjects factor and Participant ID as a random effect. For models that included training group (SBT vs AffeCT), this was added as a fixed between-subjects factor. As recommended for mixed effects models, effect sizes were calculated using r squared ( 53 ). App usage (mins) was added as a predictor of affective control (H2a) and interpretation bias (H2b). To investigate H2c, training group (SBT vs AffeCT) was added as a predictor to the model testing H2b. Hypothesis a was tested with training group (SBT vs AffeCT) and baseline to post-training change in affective control as predictors of emotion regulation (as measured by the reappraisal subscale of the ERQ-CA and by the RTQ, entered into separate analyses). To test H3b, baseline to post-training changes in affective control and interpretation bias were separately added along with training group (SBT vs AffeCT) as predictors of depression and anxiety respectively. To investigate the pre-registered exploratory analyses, assessing whether social sensitivity and concern for social risk would moderate improvements in affective control, social sensitivity and concern for social risk were separately added as fixed effects to the models testing H3 (first just as an interaction with time (baseline vs post-training), then as an interaction with time (baseline vs post-training) and training group (SBT vs AffeCT). Data and Code Availability On publication of the manuscript, de-identified data, syntax, and code supporting the conclusions of this article will be made available at the Open Science Framework ( https://osf.io/preprints/psyarxiv/rpvh9 ). Study materials will not be made available, as most of the included images are licensed to the authors. Results Randomisation Checks Participants were randomly assigned to one of two training groups, SBT or AffeCT. Analyses of variance (ANOVA; continuous variables) and chi-squared tests (categorical variables) showed no group differences in baseline characteristics (see supplementary materials), except for self-rated emotion regulation ( F (1, 140) = 4.33, p = .039), which was lower at baseline in the SBT compared to the AffeCT group. App Acceptability There were no significant differences in ratings of app helpfulness ( F (1, 96) = 0.02, p = .896), ease of use ( F (1, 96) = 0.18, p = .669), or likeability ( F (1, 96) = 0.91, p = .342) between the training apps (Table 4 ) . Table 4 App acceptability variables means and standard deviations SBT mean (SD) AffeCT mean (SD) App helpfulness 2.07 (1.32) 2.10 (1.21) App ease of use 2.95 (1.14) 2.85 (1.20) App likeability 2.12 (1.27) 1.87 (1.22) Note . App helpfulness = how helpful participants found their assigned training app. App ease of use = how easy to use participants found their assigned training app. App likeability = how much participants liked using their assigned training app. All measures were rated from 0 ( not at all ) to 4 ( very ). App Engagement A chi-squared test indicated that participants who were assigned to the SBT ( n = 48 began training) app were significantly more likely to begin training than participants assigned to the AffeCT ( n = 24 began training) app ( χ 2 (1, N = 144) = 9.12, p = .003). Additionally, an independent samples t -test indicated that of those who began training, SBT ( M = 6.61; SD = 7.27) participants engaged with significantly more training sessions on average than AffeCT ( M = 3.61; SD = 7.08) participants ( t (286) = -3.53, p < .001, 95% CI [-4.67, -1.33]). Contrary to our hypothesis (H1), however, we did not observe a significant difference in amount of time (in minutes) spent training on the SBT compared to the AffeCT ( R 2 = 0.01, F (1, 142) = 2.36, p = .127). Similarly, there was no significant difference in amount of time (in minutes) spent completing affective control training in the SBT compared to the AffeCT ( R 2 = -0.00, F (1, 142) = 0.85, p = .357). However, exploratory analyses indicated a significant difference between number of training sessions participants engaged with in the SBT compared to the AffeCT ( R 2 = .04, F (1, 142) = 6.20, p = .014), with the SBT group engaging in more training sessions (Fig. 6). Figure 6 Number of training sessions engaged with Note Effect of training group (SBT vs AffeCT) on average number of sessions participants engaged with on their assigned training app. Training-related changes in affective control and interpretation bias Across all participants, interpretation bias was reduced from baseline to post-training ( R 2 m = 0.02, R 2 c = 0.70, F = 15.51, df = 115.71, p < .001). While affective control defined as the difference in RT for correct trials on the affective versus neutral condition of the 2-back task did not significantly differ from baseline to post-training ( R 2 m = 0.00, R 2 c = 0. 38, F = 0.63, df = 126.19, p = .429), participants did get better at the task across conditions, as shown by a significant effect of time on RT on the 2-back task ( R 2 m = 0.03, R 2 c = 0.64, F = 43.95, df = 383.00, p < .001). This indicates that when looking at RT generally, participants showed significant improvements in affective control from baseline to post-training. However, in contrast with hypotheses H2a/b time spent training did not interact with time (baseline vs post-training) to predict improvements in affective control ( p = .361; Table S1 ) or interpretation bias ( p = .142; Table S2), though time spent training was significantly associated with improvements in interpretation bias after controlling for time point ( p = .023; Table S2). Furthermore, there was no interaction between training group (SBT vs AffeCT), time (baseline vs post-training) and training time on interpretation bias (H2c; p = .106; Table S3). The exploratory analysis including RT on correct trials of the untrained 2-back task (across the affective and neutral conditions) as outcome, show a significant improvement across time and greater improvement with more training time (Table S4). However there was no significant time x training time interaction. Training-related changes in mental health and emotion regulation Exploratory analyses investigating baseline to post-training and follow-up changes in mental health showed no significant changes in symptoms of depression (Tables S5C-6C) and anxiety (Tables S5D-6D). While there were no significant changes in reappraisal (Tables S5A-6A), participants’ rumination decreased significantly from baseline to follow-up (Table S6B; Figure S3). These effects were consistent across training groups (i.e., no significant training group x time interaction; Tables S8-9). In contrast with our third hypothesis, changes in affective control were not associated with changes in emotion regulation (Table S9) or mental health (Table S10). These non-significant associations made the pre-registered exploratory analyses obsolete, however for completeness the code for these analyses is available with the code of the included analyses. Discussion In this pre-registered study, we aimed to investigate the merits of introducing gamification components, such as badges and points, to standard affective control training paradigms to improve training uptake and adherence in an adolescent sample. We hypothesised that gamification would increase adolescent engagement with cognitive control training in affective contexts (i.e., affective control training), thus leading to improved affective control and, in turn, emotion regulation. We also directly trained emotion regulation abilities by targeting interpretation biases, aiming to decrease these and, by extension, improve mental health symptoms in adolescents. The results showed no significant differences in minutes spent training across the gamified and non-gamified training. However, exploratory analyses showed participants were twice as likely to start training when assigned to SBT compared to AffeCT training, and that participants engaged more with the gamified SBT (more sessions) compared to the AffeCT training. While training time was not associated with baseline to post-training improvements in affective control, when looking at overall performance on the 2-back task (i.e., neutral and affective condition) there was a significant change from baseline to post-intervention and there was a significant effect of training time. Similarly, interpretation bias improved from baseline to post-intervention and was associated with time spent training. Moreover, while training was not associated with significant changes in depression or anxiety symptoms and reappraisal capacity, there was a significant baseline to post-intervention reduction in rumination, which was maintained at follow-up. Gamification did not lead to increased training time, as there was no difference in the amount of training time between the SBT and AffeCT groups. However, participants assigned to the SBT did engage in significantly more sessions than those assigned to the AffeCT. This is in line with previous research findings that gamification increased engagement with training (for a review, see 28), as despite not increasing the total time spent on the app, participants did seem to return to the gamified app more frequently than those who were engaging with its non-gamified counterpart. Importantly, training engagement was entirely self-motivated in the present study, as participants did not receive any additional monetary rewards for completing more training. It is unclear, however, which specific components of the SBT may have led participants to return to it more often than those completing the AffeCT training. The two training apps did not differ in participants’ ratings of helpfulness, ease of use, or even likeability. Overall, training uptake and retention in the present study was quite low across the two apps. Of the 67 participants assigned to AffeCT, only 24 participants began training, and similarly only 48 of the 77 participants assigned to SBT began training. Furthermore, out of the minimum 12 sessions required for successful training completion across the two apps, participants only begun an average of 4 sessions in the AffeCT app and an average of 7 sessions in the SBT app. These differences are promising for the hypothesis that gamification may increase training engagement, as they indicate that participants were almost twice as likely to begin training and engaged on average with approximately twice as many sessions of training when assigned to the gamified SBT compared to the non-gamified AffeCT training. However, these findings are also in line with previous findings that cognitive training uptake in adolescents is quite low ( 24 , 25 ), suggesting that the gamified factors included in the present study may still not be enough to fully incentivise participants to complete cognitive control training. Future studies aiming to incorporate gamification components into training programs should explicitly assess which components participants find most engaging. There was no effect of increased training and interpretation bias or affective control across time in the present study. However, interpretation bias generally was reduced from baseline to post-training, and while affective control measured as the difference between affective and neutral trials did not improve with training, affective and cognitive control as measured with overall task performance on the untrained 2-back also improved from baseline to post-intervention. Additionally, we observed significant effects of training time on interpretation bias and general performance of cognitive and affective control across baseline and post-training. These findings suggest that despite the low training uptake, engaging with the training apps may have still had some effects on overall improvements in interpretation bias and affective and cognitive control performance (i.e., combined performance across neutral and affective trials) from baseline to post-training. This is in line with existing literature on cognitive control training studies, as researchers have previously found that cognitive training improves affective control (e.g., 33) and cognitive control (e.g., 24). The n -back task used to train cognitive control across both training groups in the present study was modelled after a similar n-back task that has previously been shown to significantly improve affective control ( 51 ). Similarly, CBM-I training has been shown to successfully reduce interpretation bias ( 54 – 56 ), and the present task was modelled after a previously validated task ( 35 ). Affective control training has also been associated with emotion regulation improvements ( 23 ), which may underly interpretation bias ( 57 ). Interestingly, we also observed overall reductions in rumination from baseline that persisted over a one-month follow-up period. It has been hypothesised that reduced cognitive control may underly ruminative tendencies, with researchers finding associations between increased rumination and reduced cognitive control ( 58 , 59 ). However, previous studies employing 6 sessions of dual n -back training over a one week period, with the hope of increasing cognitive control and decreasing rumination as with the present study, did not find associations between training and cognitive improvements or differential effects of training on rumination ( 60 ). The researchers proposed that this may have been due to insufficient training time, as they did observe a relationship between increased training time and decreased depressive symptomatology, which is closely associated with rumination ( 61 ), over time ( 60 ). Indeed, in a study where participants completed 27 sessions of training involving multiple tasks, including a dual n -back task, over a period of 4 weeks, researchers observed improvements in negative mood in the cognitive control training group ( 62 ), a factor that is closely linked to rumination ( 63 , 64 ). Other studies have similarly found that cognitive training decreased ruminative tendencies (e.g., 65,66). Together, these findings suggest that the observed effect of reduced rumination over time in the present study may indeed have been a preliminary result of cognitive training engagement, but more training may have been needed for training effects to be observed. The findings presented here should be considered within the study’s limitations. First, as the study’s aim was to demonstrate increased engagement with a training paradigm through gamification, there was no control group that completed non-affective control training. That is, observed effects could be due to placebo effects of engaging in cognitive training. However, if the observed effects are genuine, it suggests that even a limited amount of training can improve affective and cognitive control, interpretation bias, and rumination in adolescents. Future studies should seek to replicate these effects including a placebo-training group. A second limitation is the study’s follow-up period. Design and production of the SBT app began in early 2020. However, production of the app faced significant delays throughout the COVID-19 pandemic, and participant recruitment did not begin until mid-2023. Due to limitations with the grant expiry, the follow-up time point had to be changed from six-months to one-month post-training. Additionally, while recruitment and baseline assessments were originally proposed to be conducted in-person, the study had to be moved fully online and relied on social media advertisements to complete recruitment within the limited time left to conduct the study. While online recruitment benefitted the samples’ representativeness ( 67 ), it required the detection of fraudulent participants. The current study implemented a range of procedures to identify fraudulent participants, including attention check items, the Qualtrics fraudulent and duplicate response detection tools and identification of bulk response patterns. Conclusion Despite its limitations, this study does provide preliminary evidence that gamification may be a viable tool for increasing adolescent engagement with cognitive training. The results provide further tentative support for even limited amounts of affective control training’s potential to improve affective and cognitive control and reduce interpretation bias and rumination. If gamification effects can be further maximised to increase training adherence to apps such as the SBT, these apps have the potential to then be further developed as preventive interventions for adolescent mental health disorders and disseminated at larger scales, as the training is conducted online and at no cost to users. Research has shown that across 21 different countries, 90% of individuals under 24 years have access to the internet ( 68 ). Such interventions would therefore be easily accessible to youth worldwide, making them promising tools for targeting the leading cause of disability in adolescents. Abbreviations AffeCT Non-gamified Affective Control Training ANOVA Analysis of Variance CBM-I Cognitive Interpretation Bias Modification CI Confidence Interval ERQ Emotion Regulation Questionnaire – child and adolescent version GAD Generalized Anxiety Disorder Scale HSRQ Health and Social Risk Questionnaire M Mean O 2 S 3 Online and Offline Social Sensitivity Scale PHQ Patient Health Questionnaire - Adolescent RT Reaction Time RTQ Repetitive Thinking Questionnaire SBT Social Brain Train SD Standard Deviation SES socio-economic status SST Scrambled Sentences Task Declarations Ethics approval and consent to participate: The study received ethics approval by the university of New South Wales Human Research Executive Committee (HC230164) prior to data collection. Prior to data collection, Consent for publication: Not applicable. Competing interests: The authors declare that they have no competing interests to disclose. Funding: This work was supported by a National Health and Medical Research Council grant (GNT1184136). SS is supported by a Henry Wellcome fellowship (209127). AWS is supported by a NHMRC Investigator Grant (GNT1197074). SJB is funded by Wellcome (107496), the MRC, the Jacobs Foundation, the Wellspring Foundation and the University of Cambridge. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Author Contribution KG: Conceptualization, Data Curation, Formal Analysis, Investigation, Methodology, Project Administration, Resources, Software, Visualisation, Writing – original draft, Writing – reviewing and editing; SM: Conceptualization, Data Curation, Methodology, Project Administration, Resources, Software; JLA: Conceptualization, Methodology, Project Administration; AS: Conceptualization, Methodology, Writing – reviewing and editing; SJB: Funding Acquisition, Supervision; AKCC: Data Curation, Writing – reviewing and editing; JF: Project Administration; EF: Funding Acquisition; ABN: Project Administration; WR: Funding Acquisition; MR: Data Curation; AWS: Funding Acquisition, Supervision, Writing – reviewing and editing; SS: Conceptualization, Funding Acquisition, Methodology, Supervision, Writing – reviewing and editing. All authors read and approved the final manuscript. Acknowledgements: Not applicable. 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Supplementary Files SMGamifiedCognitiveTraining.docx Cite Share Download PDF Status: Published Journal Publication published 03 Jul, 2025 Read the published version in Child and Adolescent Psychiatry and Mental Health → Version 1 posted Editorial decision: Revision requested 13 Feb, 2025 Reviews received at journal 11 Feb, 2025 Reviewers agreed at journal 29 Jan, 2025 Reviews received at journal 29 Jan, 2025 Reviewers agreed at journal 29 Jan, 2025 Reviewers invited by journal 28 Jan, 2025 Editor assigned by journal 28 Jan, 2025 Submission checks completed at journal 27 Jan, 2025 First submitted to journal 25 Jan, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {\"props\":{\"pageProps\":{\"initialData\":{\"identity\":\"rs-5900018\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":false,\"archivedVersions\":[],\"articleType\":\"Research Article\",\"associatedPublications\":[],\"authors\":[{\"id\":408352119,\"identity\":\"1921e234-5c19-492d-99b1-16967dadef63\",\"order_by\":0,\"name\":\"Karina Grunewald\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"University of New South Wales\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Karina\",\"middleName\":\"\",\"lastName\":\"Grunewald\",\"suffix\":\"\"},{\"id\":408352120,\"identity\":\"5269aaed-466c-4005-a4e5-afa7ee2d7492\",\"order_by\":1,\"name\":\"Savannah Minihan\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"University of New South Wales\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Savannah\",\"middleName\":\"\",\"lastName\":\"Minihan\",\"suffix\":\"\"},{\"id\":408352121,\"identity\":\"4cb2b873-ee6a-45be-b4bd-31268821fa5a\",\"order_by\":2,\"name\":\"Jack L. Andrews\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"University of Oxford\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Jack\",\"middleName\":\"L.\",\"lastName\":\"Andrews\",\"suffix\":\"\"},{\"id\":408352122,\"identity\":\"b2dc76c7-5aa8-44f4-b935-d9808596a050\",\"order_by\":3,\"name\":\"Annabel Songco\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Black Dog Institute\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Annabel\",\"middleName\":\"\",\"lastName\":\"Songco\",\"suffix\":\"\"},{\"id\":408352123,\"identity\":\"b42a1a11-1a68-4de2-a551-a1b1d006d79b\",\"order_by\":4,\"name\":\"Sarah-Jayne Blakemore\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"University of Cambridge\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Sarah-Jayne\",\"middleName\":\"\",\"lastName\":\"Blakemore\",\"suffix\":\"\"},{\"id\":408352124,\"identity\":\"01ee50f7-b785-4ede-968b-5022824a4ab1\",\"order_by\":5,\"name\":\"Anson Kai Chun Chau\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"University of New South Wales\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Anson\",\"middleName\":\"Kai Chun\",\"lastName\":\"Chau\",\"suffix\":\"\"},{\"id\":408352125,\"identity\":\"da0221e0-b326-4a22-a17a-4e68d119b09c\",\"order_by\":6,\"name\":\"Jaimee Fischer\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"University of New South Wales\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Jaimee\",\"middleName\":\"\",\"lastName\":\"Fischer\",\"suffix\":\"\"},{\"id\":408352126,\"identity\":\"5df19106-bb2e-479d-ab6a-5743184e4c77\",\"order_by\":7,\"name\":\"Elaine Fox\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"University of Adelaide\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Elaine\",\"middleName\":\"\",\"lastName\":\"Fox\",\"suffix\":\"\"},{\"id\":408352127,\"identity\":\"cba32f4e-3aaf-4c3b-ade1-73a8a3e36499\",\"order_by\":8,\"name\":\"Alba Bruggeman Nelissen\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Catholic University of Leuven\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Alba\",\"middleName\":\"Bruggeman\",\"lastName\":\"Nelissen\",\"suffix\":\"\"},{\"id\":408352128,\"identity\":\"15eb55e2-8b46-422f-a2ac-75eb88a37838\",\"order_by\":9,\"name\":\"William Raffe\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"University of Technology Sydney\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"William\",\"middleName\":\"\",\"lastName\":\"Raffe\",\"suffix\":\"\"},{\"id\":408352129,\"identity\":\"579434df-de75-483d-9d1e-002be829d687\",\"order_by\":10,\"name\":\"Matthew Richards\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"University of Oxford\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Matthew\",\"middleName\":\"\",\"lastName\":\"Richards\",\"suffix\":\"\"},{\"id\":408352130,\"identity\":\"c68f9c91-c11f-4142-a5fe-031f1f7bd9d7\",\"order_by\":11,\"name\":\"Aliza Werner-Seidler\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Black Dog Institute\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Aliza\",\"middleName\":\"\",\"lastName\":\"Werner-Seidler\",\"suffix\":\"\"},{\"id\":408352131,\"identity\":\"78133593-c4b4-4650-bd56-99cb032588d2\",\"order_by\":12,\"name\":\"Susanne Schweizer\",\"email\":\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+ElEQVRIiWNgGAWjYJACZiDmAWLGB1ABA6K1MMOUEqcFBNgkiNIi38D+8HNhm42MfHvvs2reHXWJDezN2yQYag7j1GJwgMdYemZbGg9jz3Gz27xnDic28Bwrk2A4hkcLAw8bM++2wzzMEmlst3nbDuQ2SOSYSTCw4dYCdNgzoJb/PGzyz9iKedvqchvk3wC1/MOtheEAgxlQywEeHgk2oHVtzEBbeMwkGNvwOOww0C+8/5J5JHjSmCXnth2ub+NJK7ZI7EvH7bD29oefec7Y2cu3H2P88Latzpif/fDGGx++WeN2GDO6ABuISMCtYRSMglEwCkYBEQAAto1FN1iSkysAAAAASUVORK5CYII=\",\"orcid\":\"\",\"institution\":\"University of New South Wales\",\"correspondingAuthor\":true,\"prefix\":\"\",\"firstName\":\"Susanne\",\"middleName\":\"\",\"lastName\":\"Schweizer\",\"suffix\":\"\"}],\"badges\":[],\"createdAt\":\"2025-01-25 07:23:10\",\"currentVersionCode\":1,\"declarations\":\"\",\"doi\":\"10.21203/rs.3.rs-5900018/v1\",\"doiUrl\":\"https://doi.org/10.21203/rs.3.rs-5900018/v1\",\"draftVersion\":[],\"editorialEvents\":[{\"content\":\"https://doi.org/10.1186/s13034-025-00917-1\",\"type\":\"published\",\"date\":\"2025-07-03T15:57:13+00:00\"}],\"editorialNote\":\"\",\"failedWorkflow\":false,\"files\":[{\"id\":75360331,\"identity\":\"1f0345d9-e7d9-4c44-be38-de9ca822ed8c\",\"added_by\":\"auto\",\"created_at\":\"2025-02-03 17:43:55\",\"extension\":\"png\",\"order_by\":1,\"title\":\"Figure 1\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":205920,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cem\\u003eDepiction of One Training Session of the SBT\\u003c/em\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cem\\u003eNote\\u003c/em\\u003e. Figure 2 shows the structure of one training session of the SBT. Participants first completed four brief questions (~ 30s) about their mood, affect regulatory intentions, social context, and current activity. Participants then alternated between completing five blocks of affective control training (~ 1-1.5mins per block) and seven ambiguous social interaction scenarios (~ 10-20s per scenario). Within each training session, participants unlocked facts about mental health and the social and emotional brain (~40s per fact) after block two and four of affective control training. Participants also received points after completing each block of affective control training (1 point: ≤ 50% correct; 10 points: 51-80% correct; 30 points: ≥ 81% correct), and 2 additional points for each social interaction scenario completed correctly (i.e., scenarios where the positive resolution was selected). Upon session completion, the app flow locked and participants were unable to access the next training session until the following day, but could still complete as many extra blocks of affective control training as they wished.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage1.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-5900018/v1/f498897d019f1607ed25f905.png\"},{\"id\":75359686,\"identity\":\"e577028f-ff0a-4c77-872e-aa87dd51cbfc\",\"added_by\":\"auto\",\"created_at\":\"2025-02-03 17:35:54\",\"extension\":\"png\",\"order_by\":2,\"title\":\"Figure 2\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":115634,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cem\\u003eDepiction of the affective control training components\\u003c/em\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cem\\u003eNote\\u003c/em\\u003e. Figure 3 depicts a block of 15 + n trials of the affective control training component of the SBT where \\u003cem\\u003en\\u003c/em\\u003e = 1. Participants were therefore asked to indicate whether the location of the face presented in the current trial matched the location of the face presented in the previous trial, and whether the word presented in the current trial was also presented in the previous trial. Target trials (i.e., trials with a location and/or a word match) are depicted with a yellow background. Participants indicated whether either or both stimuli matched the stimuli presented \\u003cem\\u003en\\u003c/em\\u003e-trials back within 2500ms from the onset of the stimuli. After a response was made or the time expired, the next word-image pairing then appeared.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage2.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-5900018/v1/9b93c68a73c95a3f1401fc24.png\"},{\"id\":75359682,\"identity\":\"d17c2729-a4aa-4ec0-aaf8-c66955847233\",\"added_by\":\"auto\",\"created_at\":\"2025-02-03 17:35:54\",\"extension\":\"png\",\"order_by\":3,\"title\":\"Figure 3\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":345326,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cem\\u003eDepiction of the Ambiguous Social Interaction Scenarios\\u003c/em\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cem\\u003eNote\\u003c/em\\u003e. Figure 4 depicts the four different ways the CBM-I scenarios were presented throughout training. \\u003cstrong\\u003ePanel A\\u003c/strong\\u003e shows the text message format. Participants were first shown the text message interaction, then asked to choose between one of two options to resolve a missing fragment of the text message interaction, before then being shown the scenario resolution and receiving feedback. \\u003cstrong\\u003ePanel B\\u003c/strong\\u003e shows the audio format. Participants were first given a brief description of the context of the voicemail, then listened to the voicemail (they could also follow a transcript at the bottom of the screen), before being asked to choose between two of the options to resolve a missing fragment of the voicemail. On the final screen, the scenario was resolved and participants received feedback. \\u003cstrong\\u003ePanel C\\u003c/strong\\u003e shows the narrative vignette format. Participants first read about the narrative ambiguous social interaction scenario, before being asked to complete a missing word fragment to resolve the scenario, and lastly being shown the scenario resolution and receiving feedback. \\u003cstrong\\u003ePanel D\\u003c/strong\\u003eshows the emotion detection format. Participants were first asked to identify the emotional content of an image, before then being shown the scenario resolution and receiving feedback. In all four formats, a correct response was indicated by a green tick, while an incorrect response was indicated by a red cross.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage3.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-5900018/v1/94f685ab0ef7b0833b6925c9.png\"},{\"id\":75359692,\"identity\":\"770f62f4-2760-451b-b035-38e870a281ea\",\"added_by\":\"auto\",\"created_at\":\"2025-02-03 17:35:55\",\"extension\":\"jpeg\",\"order_by\":4,\"title\":\"Figure 4\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":133155,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cem\\u003eDepiction of Gamification Components\\u003c/em\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cem\\u003eNote\\u003c/em\\u003e. Figure 5 depicts the gamification components of the SBT. \\u003cstrong\\u003ePanel A\\u003c/strong\\u003e shows the avatars participants could choose after downloading the app. \\u003cstrong\\u003ePanel B\\u003c/strong\\u003e shows an example of the “brain points” participants could receive for completing the affective control and CBM-I components of training. \\u003cstrong\\u003ePanel C\\u003c/strong\\u003e depicts an example of the “brain stations” participants reached at the end of each training session. \\u003cstrong\\u003ePanel D\\u003c/strong\\u003e shows some examples of the “brain badges” participants unlocked as they completed each training session.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage4.jpeg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-5900018/v1/bff4522c2515a55514a8a7ba.jpeg\"},{\"id\":75359697,\"identity\":\"76dbdad6-eb74-4c9b-b9ec-e9c9a4674a8a\",\"added_by\":\"auto\",\"created_at\":\"2025-02-03 17:35:55\",\"extension\":\"png\",\"order_by\":5,\"title\":\"Figure 5\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":107155,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cem\\u003eNumber of training sessions engaged with\\u003c/em\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cem\\u003eNote\\u003c/em\\u003e. Effect of training group (SBT vs AffeCT) on average number of sessions participants engaged with on their assigned training app.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage5.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-5900018/v1/383578a629e92dbc912ea82f.png\"},{\"id\":86179110,\"identity\":\"809c591a-5486-4425-8f26-54ab788f0705\",\"added_by\":\"auto\",\"created_at\":\"2025-07-07 16:15:49\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":2421763,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"manuscript.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-5900018/v1/0b410d1c-f325-40c9-b323-10be5363d982.pdf\"},{\"id\":75359681,\"identity\":\"f027fc0b-4a72-4d1e-94c6-9ef385eb0202\",\"added_by\":\"auto\",\"created_at\":\"2025-02-03 17:35:53\",\"extension\":\"docx\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":1971168,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"SMGamifiedCognitiveTraining.docx\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-5900018/v1/a01364c66ee272e49593a2cb.docx\"}],\"financialInterests\":\"No competing interests reported.\",\"formattedTitle\":\"Investigating the effects of a novel gamified cognitive training on adolescent mental health\",\"fulltext\":[{\"header\":\"Introduction\",\"content\":\"\\u003cp\\u003eAdolescence (10\\u0026ndash;24 years; (\\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2\\u003c/span\\u003e)), is a sensitive period for the development of mental health disorders. Indeed, most mental health disorders first onset by 24 years, and often persist across the lifespan (\\u003cspan citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e3\\u003c/span\\u003e). Of these, emotional disorders including depression and anxiety are the most common (\\u003cspan citationid=\\\"CR4\\\" class=\\\"CitationRef\\\"\\u003e4\\u003c/span\\u003e). Yet, despite these disorders being the leading burden of disease in adolescence (\\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e5\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR6\\\" class=\\\"CitationRef\\\"\\u003e6\\u003c/span\\u003e), current psychological and pharmacological treatments often show limited efficacy. Meta-analytic evidence suggests that less than 40% of adolescents respond to psychological treatments for depression (\\u003cspan citationid=\\\"CR9\\\" class=\\\"CitationRef\\\"\\u003e9\\u003c/span\\u003e), and only 36% of adolescents receiving treatment for anxiety disorders were in remission post treatment (\\u003cspan citationid=\\\"CR10\\\" class=\\\"CitationRef\\\"\\u003e10\\u003c/span\\u003e). Adolescent responses to pharmacological treatments of depression have been similarly low (\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e). Identifying novel avenues for intervention and prevention of adolescent anxiety and depression that are deliverable at scale is therefore urgent.\\u003c/p\\u003e \\u003cp\\u003eResearchers have proposed that current interventions may be unsuccessful in treating emotional disorders, as they fail to target key risk factors underlying vulnerability to these disorders (\\u003cspan citationid=\\\"CR12\\\" class=\\\"CitationRef\\\"\\u003e12\\u003c/span\\u003e). One such risk factor is emotion regulation (\\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e), individuals\\u0026rsquo; ability to influence their emotions, where emotions refer to temporally limited, positively or negatively valenced and situationally-bound experiences (\\u003cspan citationid=\\\"CR14\\\" class=\\\"CitationRef\\\"\\u003e14\\u003c/span\\u003e). Difficulties in emotion regulation during adolescence have been robustly linked to the onset and maintenance of adolescent mental health problems (\\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e15\\u003c/span\\u003e), as well as treatment responsiveness (\\u003cspan citationid=\\\"CR16\\\" class=\\\"CitationRef\\\"\\u003e16\\u003c/span\\u003e). Developmental research shows that emotion regulation improves throughout adolescence (\\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e17\\u003c/span\\u003e), in tandem with its underlying cognitive (\\u003cspan citationid=\\\"CR18\\\" class=\\\"CitationRef\\\"\\u003e18\\u003c/span\\u003e) and neural (\\u003cspan citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e19\\u003c/span\\u003e) substrates. Successful emotion regulation has been proposed to rely on cognitive control (\\u003cspan citationid=\\\"CR20\\\" class=\\\"CitationRef\\\"\\u003e20\\u003c/span\\u003e), the ability to attend to and respond to goal-relevant stimuli while inhibiting attention and responses to goal-irrelevant stimuli (\\u003cspan citationid=\\\"CR21\\\" class=\\\"CitationRef\\\"\\u003e21\\u003c/span\\u003e). Especially, improvements in the application of cognitive control in affective contexts, \\u003cem\\u003eaffective control\\u003c/em\\u003e, may be central to the development of successful emotion regulation (\\u003cspan citationid=\\\"CR22\\\" class=\\\"CitationRef\\\"\\u003e22\\u003c/span\\u003e). Targeting these cognitive substrates has therefore been proposed as an effective means to intervene in the development and maintenance of emotional disorders (\\u003cspan citationid=\\\"CR23\\\" class=\\\"CitationRef\\\"\\u003e23\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003eEncouragingly, researchers have found that affective control is amenable to cognitive training, and training effects have been associated with improvements in emotion regulation and a range of clinical outcomes including depression and anxiety in adolescence (\\u003cspan citationid=\\\"CR23\\\" class=\\\"CitationRef\\\"\\u003e23\\u003c/span\\u003e). However, studies have found that cognitive training interventions have low engagement and adherence rates among adolescents (\\u003cspan additionalcitationids=\\\"CR25\\\" citationid=\\\"CR24\\\" class=\\\"CitationRef\\\"\\u003e24\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR26\\\" class=\\\"CitationRef\\\"\\u003e26\\u003c/span\\u003e), as adolescents often report finding low motivation for exerting effort to complete cognitive tasks (\\u003cspan citationid=\\\"CR27\\\" class=\\\"CitationRef\\\"\\u003e27\\u003c/span\\u003e). As a result, while improving affective control through cognitive training constitutes a promising avenue for intervention, low engagement limits its viability as an intervention or as a target for prevention.\\u003c/p\\u003e \\u003cp\\u003eOne way to effectively augment adolescents\\u0026rsquo; participation in cognitive training is gamification. Gamification, the use of game-like features such as narrative storylines and points systems, has been reliably shown to improve both attentional engagement with training and motivation to increase training time (\\u003cspan citationid=\\\"CR28\\\" class=\\\"CitationRef\\\"\\u003e28\\u003c/span\\u003e). It may be especially useful for interventions aimed at adolescents, as 90% of Australian adolescents report playing digital games regularly, averaging approximately 98 minutes of gameplay each day (\\u003cspan citationid=\\\"CR29\\\" class=\\\"CitationRef\\\"\\u003e29\\u003c/span\\u003e). Gamification also allows the creation of ecologically-valid content that is reflective of users\\u0026rsquo; real-world environments and experiences. As motivation and attentional capture are crucial for cognitive training success (\\u003cspan citationid=\\\"CR30\\\" class=\\\"CitationRef\\\"\\u003e30\\u003c/span\\u003e), and ecological validity improves the transferability of training gains to real-world problems (\\u003cspan citationid=\\\"CR31\\\" class=\\\"CitationRef\\\"\\u003e31\\u003c/span\\u003e), gamification appears to offer an existing opportunity to boost the uptake of cognitive training in adolescents.\\u003c/p\\u003e \\u003cp\\u003eThe current study aimed to explore the effectiveness of a novel gamified app-based affective control training program, the Social Brain Train (SBT). The SBT comprised three components: a standard affective control training component (affective dual \\u003cem\\u003en\\u003c/em\\u003e-back task), a cognitive interpretation bias modification (CBM-I) component and a psychoeducation component. The affective dual \\u003cem\\u003en\\u003c/em\\u003e-back task required flexible engagement (remembering emotional words) and disengagement (inhibiting the processing of the task-irrelevant emotional expressions) with affective information. This specific task has previously been shown to lead to improvements in affective control, emotion regulation, and mental health in adolescents and young adults (\\u003cspan citationid=\\\"CR26\\\" class=\\\"CitationRef\\\"\\u003e26\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR32\\\" class=\\\"CitationRef\\\"\\u003e32\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR33\\\" class=\\\"CitationRef\\\"\\u003e33\\u003c/span\\u003e). In the SBT, the affective \\u003cem\\u003en\\u003c/em\\u003e-back task was gamified, with points awarded for performance.\\u003c/p\\u003e \\u003cp\\u003e The CBM-I component required participants to solve ambiguous social \\u0026ldquo;puzzles\\u0026rdquo; in a positive way. CBM-I training has previously been shown to successfully reduce interpretation bias in adolescents (\\u003cspan citationid=\\\"CR34\\\" class=\\\"CitationRef\\\"\\u003e34\\u003c/span\\u003e), which is associated with adolescent depression and anxiety (\\u003cspan citationid=\\\"CR4\\\" class=\\\"CitationRef\\\"\\u003e4\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR35\\\" class=\\\"CitationRef\\\"\\u003e35\\u003c/span\\u003e). The CBM-I also introduced a new \\u0026ldquo;game\\u0026rdquo; element to the training and allowed participants to directly train the application of affective control, as adolescents had to override any prepotent negative response tendencies and regulate any affective responses that the scenarios may elicit to resolve the puzzles positively.\\u003c/p\\u003e \\u003cp\\u003eLastly, the SBT further promoted gamification through the inclusion of badges and fun facts about mental health and the human brain (i.e., psychoeducation component) that could be unlocked throughout training completion. Psychoeducation in itself has small but positive effects on emotional disorders (\\u003cspan citationid=\\\"CR36\\\" class=\\\"CitationRef\\\"\\u003e36\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR37\\\" class=\\\"CitationRef\\\"\\u003e37\\u003c/span\\u003e). Combining affective control training with CBM-I then increases opportunities to practice the application of affective control in real-world analogue scenarios. This intervention\\u0026rsquo;s optimisation was further enhanced by psychoeducation contents that provide a rationale to motivate participation in the training.\\u003c/p\\u003e \\u003cp\\u003eThe SBT\\u0026rsquo;s effectiveness was compared with a non-gamified affective control training (AffeCT). Participants were 13\\u0026ndash;16 years of age, as this age range precedes and includes the ages \\u0026ndash; 16\\u0026ndash;17 years (\\u003cspan citationid=\\\"CR38\\\" class=\\\"CitationRef\\\"\\u003e38\\u003c/span\\u003e) \\u0026ndash; at which a sudden rise in symptoms of emotional disorders is observed in epidemiological studies. The present study allowed us to investigate the following pre-registered hypotheses:\\u003c/p\\u003e \\u003cp\\u003e \\u003col\\u003e \\u003cspan\\u003e \\u003cli\\u003e \\u003cp\\u003eThe SBT group would spend more time training (in minutes) than the AffeCT group.\\u003c/p\\u003e \\u003c/li\\u003e \\u003c/span\\u003e \\u003cspan\\u003e \\u003cli\\u003e \\u003cp\\u003eTime spent training across groups would be associated with improved performance on a non-trained affective control task (H2a) and social interpretation bias (H2b); and the effect of training time on interpretation bias would be greater in the SBT than the AffeCT group (H2c).\\u003c/p\\u003e \\u003c/li\\u003e \\u003c/span\\u003e \\u003cspan\\u003e \\u003cli\\u003e \\u003cp\\u003eImprovements in affective control would be associated with baseline to post-training changes in emotion regulation (H3a) and improvements in affective control and interpretation bias would be associated with lower depressive and anxiety symptoms (H3b).\\u003c/p\\u003e \\u003c/li\\u003e \\u003c/span\\u003e \\u003c/ol\\u003e \\u003c/p\\u003e\"},{\"header\":\"Materials and Methods\",\"content\":\"\\u003cp\\u003eThis study was approved by the University of New South Wales Human Research Executive Committee (HC230164) and a protocol was pre-registered prior to participant recruitment (\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://osf.io/preprints/psyarxiv/rpvh9\\u003c/span\\u003e\\u003cspan address=\\\"https://osf.io/preprints/psyarxiv/rpvh9\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e). For sample size calculation, eligibility criteria, and participant exclusions, please see supplementary materials.\\u003c/p\\u003e \\u003cdiv id=\\\"Sec3\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eConsent and Assent\\u003c/h2\\u003e \\u003cp\\u003e Before completing the study, prospective participants provided informed consent from their parent or guardian. Parents/guardians could follow a URL to access study information and the consent procedure on Qualtrics (\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://www.qualtrics.com\\u003c/span\\u003e\\u003cspan address=\\\"https://www.qualtrics.com\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e). Eligible participants with parental/guardian consent were invited to complete an informed assent procedure on Gorilla Experiment Builder (\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://gorilla.sc\\u003c/span\\u003e\\u003cspan address=\\\"https://gorilla.sc\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e), after which they were given access to the baseline assessment. During baseline and post-training assessments, participants were reminded that they could withdraw consent at any time before, during, or after the study with no consequences, and that they would receive up to AUD60 (GBP30) reimbursement for all parts of the study completed up to withdrawal.\\u003c/p\\u003e \\u003c/div\\u003e\\n\\u003ch3\\u003eParticipants\\u003c/h3\\u003e\\n\\u003cp\\u003eThe final sample size used for data analysis comprised 144 participants recruited in 2023 through schools, social media advertisement, the MQ participate and Children Helping Science websites, and advertisements on the research lab website and the community (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e). While advertisements and recruitment efforts were targeted at participants from Australia and the UK, where the lead researchers were based, some participants from the USA and India signed up for the study through online recruitment platforms. If these participants obtained parental consent and met all other eligibility requirements, they were included in the study.\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab1\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 1\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eSample characteristics (N\\u0026thinsp;=\\u0026thinsp;144), means and standard deviations of variables\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"2\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eMean (SD)/N (%)\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eAge (years)\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e14.77 (1.12)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eSES\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e2.81 (0.31)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eGender\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eFemale\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e69 (47.92%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eMale\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e73 (50.69%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eNon-binary\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e2 (1.39%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eCountry\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAustralia\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e77 (53.47%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eUnited Kingdom\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e48 (33.33%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eUnited States of America\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e17 (11.81%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eIndia\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e2 (1.39%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eEthnicity\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAboriginal or Torres Strait Islander\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e2 (1.39%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAsian\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e22 (15.28%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eBlack\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e7 (4.86%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eWhite\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e98 (68.06%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eMixed\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e10 (6.94%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eOther\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e4 (2.78%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePrefer not to say\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1 (0.69%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eEducation\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eCurrent student\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e142 (%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePrefer not to say\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e2 (%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003ctfoot\\u003e \\u003ctr\\u003e\\u003ctd colspan=\\\"2\\\"\\u003e\\u003cem\\u003eNote\\u003c/em\\u003e. \\u003cb\\u003eSES\\u003c/b\\u003e\\u0026thinsp;=\\u0026thinsp;socio-economic status, derived from the average level of parental education for up to 2 parents (1\\u0026thinsp;=\\u0026thinsp;primary school; 2\\u0026thinsp;=\\u0026thinsp;high school, professional/vocational training; 3\\u0026thinsp;=\\u0026thinsp;university).\\u003c/td\\u003e\\u003c/tr\\u003e \\u003c/tfoot\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e\\n\\u003ch3\\u003eAllocation Procedure\\u003c/h3\\u003e\\n\\u003cp\\u003eEligible participants who completed the baseline questionnaires were randomised to either the SBT (\\u003cem\\u003eN\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;77) or the AffeCT (\\u003cem\\u003eN\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;67) group (see supplementary materials for randomization procedure).\\u003c/p\\u003e\\n\\u003ch3\\u003eMeasures\\u003c/h3\\u003e\\n\\u003cp\\u003eFor details on all self-report measures please see supplementary materials. Means and standard deviations of measures are presented in Table\\u0026nbsp;\\u003cspan refid=\\\"Tab2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e.\\u003c/p\\u003e \\u003cdiv id=\\\"Sec7\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eParticipant Characteristics\\u003c/h2\\u003e \\u003cp\\u003eA brief questionnaire was used to measure demographic characteristics (e.g., age, gender, ethnicity), history of mental health and learning and neurodevelopmental disorders. To explore whether training increased overall screentime use, participants were also asked for their average daily screentime usage (indicated within their device settings). These measures were all assessed at baseline, with screentime assessed again at post-training.\\u003c/p\\u003e \\u003c/div\\u003e\\n\\u003ch3\\u003eMental Health and Functioning\\u003c/h3\\u003e\\n\\u003cp\\u003eParticipants completed measures of anxiety (Generalized Anxiety Disorder Scale; (\\u003cspan citationid=\\\"CR39\\\" class=\\\"CitationRef\\\"\\u003e39\\u003c/span\\u003e); baseline: ωT\\u0026thinsp;=\\u0026thinsp;.94; post: ωT\\u0026thinsp;=\\u0026thinsp;.94; follow-up: ωT\\u0026thinsp;=\\u0026thinsp;.96), depression (Patient Health Questionnaire \\u0026ndash; Adolescent; (\\u003cspan citationid=\\\"CR40\\\" class=\\\"CitationRef\\\"\\u003e40\\u003c/span\\u003e); baseline: ωT\\u0026thinsp;=\\u0026thinsp;.94; post: ωT\\u0026thinsp;=\\u0026thinsp;.95; follow-up: ωT\\u0026thinsp;=\\u0026thinsp;.96), functional impairment (modified - see supplementary for details - version of the Child Anxiety Life Interference Scale; (\\u003cspan citationid=\\\"CR41\\\" class=\\\"CitationRef\\\"\\u003e41\\u003c/span\\u003e); baseline: ωT\\u0026thinsp;=\\u0026thinsp;.90; post-training: ωT\\u0026thinsp;=\\u0026thinsp;.90; follow-up: ωT\\u0026thinsp;=\\u0026thinsp;.93). All measures showed good reliability in the current sample at baseline, post-training and follow-up.\\u003c/p\\u003e\\n\\u003ch3\\u003eMechanisms of change\\u003c/h3\\u003e\\n\\u003cp\\u003e \\u003cb\\u003eSelf-report measures.\\u003c/b\\u003e Emotion regulation, specifically reappraisal, was assessed with the reappraisal subscale of the Emotion Regulation Questionnaire \\u0026ndash; child and adolescent version ((\\u003cspan citationid=\\\"CR42\\\" class=\\\"CitationRef\\\"\\u003e42\\u003c/span\\u003e); baseline: ωT\\u0026thinsp;=\\u0026thinsp;.90; post: ωT\\u0026thinsp;=\\u0026thinsp;.93; follow-up: ωT\\u0026thinsp;=\\u0026thinsp;.91) and rumination was assessed with the Repetitive Thinking Questionnaire ((\\u003cspan citationid=\\\"CR43\\\" class=\\\"CitationRef\\\"\\u003e43\\u003c/span\\u003e); baseline: ωT\\u0026thinsp;=\\u0026thinsp;.92; post: ωT\\u0026thinsp;=\\u0026thinsp;.93; follow-up: ωT\\u0026thinsp;=\\u0026thinsp;.93). Pre-registered exploratory moderators social sensitivity (Online and Offline Social Sensitivity Scale; (\\u003cspan citationid=\\\"CR44\\\" class=\\\"CitationRef\\\"\\u003e44\\u003c/span\\u003e); baseline: ωT\\u0026thinsp;=\\u0026thinsp;.90; post: ωT\\u0026thinsp;=\\u0026thinsp;.92; follow-up: ωT\\u0026thinsp;=\\u0026thinsp;.87) and social risk concern (social subscale of the Health and Social Risk Questionnaire; (\\u003cspan citationid=\\\"CR45\\\" class=\\\"CitationRef\\\"\\u003e45\\u003c/span\\u003e); baseline: ωT\\u0026thinsp;=\\u0026thinsp;.78; post: ωT\\u0026thinsp;=\\u0026thinsp;.84; follow-up: ωT\\u0026thinsp;=\\u0026thinsp;.80) were also measured.\\u003c/p\\u003e \\u003cp\\u003e\\u003cb\\u003eInterpretation bias.\\u003c/b\\u003e Interpretation bias was measured through a scrambled sentences task (SST) developed for adolescents (\\u003cspan citationid=\\\"CR46\\\" class=\\\"CitationRef\\\"\\u003e46\\u003c/span\\u003e). The task comprises 40 trials reflecting general and social anxiety-related concerns. Twenty trials were completed at baseline, and 20 at post-training (counterbalanced across participants). Each trial required participants to unscramble a scrambled statement. Statements could be unscrambled to hold a positive or negative meaning. Each trial required participants to include five of six available words in a statement within 30s. For example, \\u0026ldquo;people, dislike, new, enjoy, meeting, I\\u0026rdquo; could be unscrambled to \\u0026ldquo;I enjoy/dislike meeting new people\\u0026rdquo;, with the selection of enjoy or dislike rendering the statement positive or negative, respectively. In the present study, the statement \\u0026ldquo;relaxed with tense I\\u0026rsquo;m \\u003cem\\u003echildren older\\u003c/em\\u003e\\u0026rdquo; was modified to \\u0026ldquo;relaxed with tense I\\u0026rsquo;m \\u003cem\\u003epeople other\\u003c/em\\u003e\\u0026rdquo;, to ensure all sentences were age appropriate for our sample. Additionally, each administration of the task contained one neutral sentence (e.g., \\u0026ldquo;I read like books to magazines\\u0026rdquo;) as a baseline response for the task. That is, the current version included twenty-one trials at baseline and post-intervention.\\u003c/p\\u003e \\u003cp\\u003e The task was performed under a cognitive load, with participants required to hold a 4-digit number in mind throughout the task. The cognitive load was introduced to the task to disrupt volitional efforts to supress, modify or edit thoughts (\\u003cspan citationid=\\\"CR46\\\" class=\\\"CitationRef\\\"\\u003e46\\u003c/span\\u003e). Interpretation bias was operationalised as the proportion of sentences completed correctly with a negative valence, such that higher scores indicated greater negative interpretation bias. The inclusion of the neutral sentences as a covariate in the analyses did not change the pattern of results and is therefore not reported in the current manuscript.\\u003c/p\\u003e \\u003cp\\u003e \\u003cb\\u003eAffective control.\\u003c/b\\u003e Affective control was assessed with a 2-back task (\\u003cspan citationid=\\\"CR47\\\" class=\\\"CitationRef\\\"\\u003e47\\u003c/span\\u003e). Participants indicated via button press whether the word they were currently seeing was the same as the word presented two-words-back. The task was completed twice, once with 22 neutral words (e.g., stair) and once with 22 affective words (e.g., rude) from the English lemmas database (\\u003cspan citationid=\\\"CR48\\\" class=\\\"CitationRef\\\"\\u003e48\\u003c/span\\u003e). Trials (i.e., words) progressed if no response was given after 2,500ms. Affective control was operationalised as average reaction time (RT) on correct trials of the affective minus neutral 2-back conditions, with more negative scores indicating greater affective control.\\u003c/p\\u003e \\u003cdiv id=\\\"Sec10\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eAcceptability\\u003c/h2\\u003e \\u003cp\\u003eIntervention acceptability measures (i.e., completion rate and the app\\u0026rsquo;s perceived helpfulness, ease of use and likeability) were adapted from an existing smartphone acceptability measure (\\u003cspan citationid=\\\"CR49\\\" class=\\\"CitationRef\\\"\\u003e49\\u003c/span\\u003e) and assessed at post-training.\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab2\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 2\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eMeans and standard deviations of variables of interest across time points\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"4\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eVariable\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eBaseline\\u003c/p\\u003e \\u003cp\\u003e\\u003cem\\u003emean (SD)\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003ePost-training\\u003c/p\\u003e \\u003cp\\u003e\\u003cem\\u003emean (SD)\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eFollow-up\\u003c/p\\u003e \\u003cp\\u003e\\u003cem\\u003emean (SD)\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAffective Control\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e-4.35 (235.95)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e12.40 (199.09)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eN/A\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eInterpretation Bias\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.30 (0.24)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.21 (0.21)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eN/A\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eEmotion Regulation\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e27.08 (6.13)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e28.00 (6.91)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e27.37 (6.95)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eRumination\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e29.93 (8.80)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e27.58 (9.22)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e26.38 (8.95)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eDepression\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e6.65 (6.61)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e5.14 (5.94)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e5.73 (6.67)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAnxiety\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e6.44 (6.06)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e4.76 (5.28)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e5.29 (5.95)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eSocial Sensitivity\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e25.19 (9.95)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e24.48 (11.16)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e23.33 (9.20)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eSocial Risk Concern\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e41.18 (18.06)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e39.28 (16.29)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e39.46 (16.00)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAffective Control Change (baseline to post-training)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eN/A\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e-20.13 (238.55)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eN/A\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eInterpretation Bias Change (baseline to post-training)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eN/A\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.05 (0.18)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eN/A\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003ctfoot\\u003e \\u003ctr\\u003e\\u003ctd colspan=\\\"4\\\"\\u003e\\u003cem\\u003eNote\\u003c/em\\u003e. \\u003cb\\u003eAffective Control\\u003c/b\\u003e\\u0026thinsp;=\\u0026thinsp;average RT on correct trials of the emotional 2-back task minus average RT on correct trials of the neutral 2-back task. \\u003cb\\u003eInterpretation Bias\\u003c/b\\u003e\\u0026thinsp;=\\u0026thinsp;proportion of negative grammatically correct sentences in the Scrambled Sentences Task. \\u003cb\\u003eEmotion Regulation\\u003c/b\\u003e\\u0026thinsp;=\\u0026thinsp;total score on ERQ reappraisal subscale. \\u003cb\\u003eRumination\\u003c/b\\u003e\\u0026thinsp;=\\u0026thinsp;total score on RTQ. \\u003cb\\u003eDepression\\u003c/b\\u003e\\u0026thinsp;=\\u0026thinsp;total score on PHQ. \\u003cb\\u003eAnxiety\\u003c/b\\u003e\\u0026thinsp;=\\u0026thinsp;total score on GAD. \\u003cb\\u003eSocial Sensitivity\\u003c/b\\u003e\\u0026thinsp;=\\u0026thinsp;total score on O\\u003csup\\u003e2\\u003c/sup\\u003eS\\u003csup\\u003e3\\u003c/sup\\u003e. \\u003cb\\u003eSocial Risk Concern\\u003c/b\\u003e\\u0026thinsp;=\\u0026thinsp;Average score of HSRQ rating scales. \\u003cb\\u003eAffective Control Change\\u003c/b\\u003e\\u0026thinsp;=\\u0026thinsp;change in average RT on correct trials of the emotional minus neutral 2-back task from baseline to post-training. \\u003cb\\u003eInterpretation Bias Change\\u003c/b\\u003e\\u0026thinsp;=\\u0026thinsp;Change in proportion of negative grammatically correct sentences in the SST from baseline to post-training.\\u003c/td\\u003e\\u003c/tr\\u003e \\u003c/tfoot\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec11\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eTraining Programs\\u003c/h2\\u003e \\u003cp\\u003eParticipants completed 12 training sessions of either SBT or AffeCT over a 15-day period. To promote training completion, participants received training reminders at 8am and 5pm each day. Training was self-paced, as total time training was one of the outcomes of interest. Once all 12 sessions were completed, participants could opt to repeat any previously completed session. Means and standard deviations of training variables are presented in Table\\u0026nbsp;\\u003cspan refid=\\\"Tab3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec12\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eSocial Brain Train\\u003c/h2\\u003e \\u003cp\\u003eIn the SBT each training session began with four brief questions about participants\\u0026rsquo; mood (ranging from \\u003cem\\u003every unhappy\\u003c/em\\u003e to \\u003cem\\u003every happy\\u003c/em\\u003e), affect regulatory intentions (e.g., avoidance, acceptance), social context (e.g., alone, with friends/family), and current activity. Participants then alternated between the affective control (5 blocks), CBM-I (7 scenarios) and psychoeducation (1 brain and 1 mental health fact) components (Fig.\\u0026nbsp;2). At the end of each training session, participants had the option to continue training on the affective control component, however the next training session could not be accessed until the following day.\\u003c/p\\u003e \\u003cp\\u003e \\u003cb\\u003eFigure 2\\u003c/b\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec13\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eDepiction of One Training Session of the SBT\\u003c/h2\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003e \\u003cstrong\\u003eNote\\u003c/strong\\u003e \\u003cp\\u003eFigure\\u0026nbsp;2 shows the structure of one training session of the SBT. Participants first completed four brief questions (~\\u0026thinsp;30s) about their mood, affect regulatory intentions, social context, and current activity. Participants then alternated between completing five blocks of affective control training (~\\u0026thinsp;1-1.5mins per block) and seven ambiguous social interaction scenarios (~\\u0026thinsp;10-20s per scenario). Within each training session, participants unlocked facts about mental health and the social and emotional brain (~\\u0026thinsp;40s per fact) after block two and four of affective control training. Participants also received points after completing each block of affective control training (1 point: \\u0026le; 50% correct; 10 points: 51\\u0026ndash;80% correct; 30 points: \\u0026ge; 81% correct), and 2 additional points for each social interaction scenario completed correctly (i.e., scenarios where the positive resolution was selected). Upon session completion, the app flow locked and participants were unable to access the next training session until the following day, but could still complete as many extra blocks of affective control training as they wished.\\u003c/p\\u003e \\u003c/p\\u003e \\u003cp\\u003e\\u003cb\\u003eAffective Control Training.\\u003c/b\\u003e The affective dual \\u003cem\\u003en\\u003c/em\\u003e-back task comprised 15\\u0026thinsp;+\\u0026thinsp;\\u003cem\\u003en\\u003c/em\\u003e trials where the image of a face (appearing on a 4x4 grid for 500ms) and a spoken word were presented simultaneously (Fig.\\u0026nbsp;3). Participants were asked to indicate whether the stimuli were the same (words) or appeared in the same location (faces) as the stimuli presented \\u003cem\\u003en\\u003c/em\\u003e-trials back (for details on stimuli, please see 50). Responses were indicated via button press (\\u003cem\\u003eno match\\u003c/em\\u003e, \\u003cem\\u003elocation match\\u003c/em\\u003e, \\u003cem\\u003eword match\\u003c/em\\u003e, or \\u003cem\\u003eboth match\\u003c/em\\u003e), with feedback provided after each trial. Participants had 2500ms to respond before the next word/face pair appeared, with responses marked as incorrect if no selection was made within this time.\\u003c/p\\u003e \\u003cp\\u003eAt the start of training (i.e., the first training session), \\u003cem\\u003en\\u003c/em\\u003e was set to one. For each subsequent training session, the starting level of \\u003cem\\u003en\\u003c/em\\u003e was the final \\u003cem\\u003en\\u003c/em\\u003e achieved the previous session minus two. The level of \\u003cem\\u003en\\u003c/em\\u003e within a training session was titrated to performance. When performance reached\\u0026thinsp;\\u0026ge;\\u0026thinsp;70% accuracy, \\u003cem\\u003en\\u003c/em\\u003e increased by one, while \\u003cem\\u003en\\u003c/em\\u003e decreased by one when accuracy was \\u0026le;\\u0026thinsp;30%.\\u003c/p\\u003e \\u003cp\\u003e \\u003cb\\u003eFigure 3\\u003c/b\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec14\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eDepiction of the affective control training components\\u003c/h2\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003e \\u003cstrong\\u003eNote\\u003c/strong\\u003e \\u003cp\\u003eFigure\\u0026nbsp;3 depicts a block of 15\\u0026thinsp;+\\u0026thinsp;n trials of the affective control training component of the SBT where \\u003cem\\u003en\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;1. Participants were therefore asked to indicate whether the location of the face presented in the current trial matched the location of the face presented in the previous trial, and whether the word presented in the current trial was also presented in the previous trial. Target trials (i.e., trials with a location and/or a word match) are depicted with a yellow background. Participants indicated whether either or both stimuli matched the stimuli presented \\u003cem\\u003en\\u003c/em\\u003e-trials back within 2500ms from the onset of the stimuli. After a response was made or the time expired, the next word-image pairing then appeared.\\u003c/p\\u003e \\u003c/p\\u003e \\u003cp\\u003e \\u003cb\\u003eCognitive interpretation bias modification\\u003c/b\\u003e. The CBM-I component comprised seven ambiguous social interaction scenarios (trials) per training session. The ambiguous social interaction scenarios were presented in four interactive ways: 1) text message scenarios (Fig.\\u0026nbsp;4A), a missing text fragment; 2) audio scenarios (Fig.\\u0026nbsp;4B), a missing fragment from a voicemail recording; 3) narrative vignette scenarios (Fig.\\u0026nbsp;4C), missing letters in a word fragment; and 4) emotion detection scenarios (Fig.\\u0026nbsp;4D), where participants identified the emotional content of an image. Participants were required to resolve each scenario positively within 7s, with feedback provided after each trial. Researchers have previously shown that adolescents can learn to positively resolve ambiguous social interaction scenarios (\\u003cspan citationid=\\\"CR35\\\" class=\\\"CitationRef\\\"\\u003e35\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003e \\u003cb\\u003eFigure 4\\u003c/b\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec15\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eDepiction of the Ambiguous Social Interaction Scenarios\\u003c/h2\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003e \\u003cstrong\\u003eNote\\u003c/strong\\u003e \\u003cp\\u003eFigure\\u0026nbsp;4 depicts the four different ways the CBM-I scenarios were presented throughout training. \\u003cb\\u003ePanel A\\u003c/b\\u003e shows the text message format. Participants were first shown the text message interaction, then asked to choose between one of two options to resolve a missing fragment of the text message interaction, before then being shown the scenario resolution and receiving feedback. \\u003cb\\u003ePanel B\\u003c/b\\u003e shows the audio format. Participants were first given a brief description of the context of the voicemail, then listened to the voicemail (they could also follow a transcript at the bottom of the screen), before being asked to choose between two of the options to resolve a missing fragment of the voicemail. On the final screen, the scenario was resolved and participants received feedback. \\u003cb\\u003ePanel C\\u003c/b\\u003e shows the narrative vignette format. Participants first read about the narrative ambiguous social interaction scenario, before being asked to complete a missing word fragment to resolve the scenario, and lastly being shown the scenario resolution and receiving feedback. \\u003cb\\u003ePanel D\\u003c/b\\u003e shows the emotion detection format. Participants were first asked to identify the emotional content of an image, before then being shown the scenario resolution and receiving feedback. In all four formats, a correct response was indicated by a green tick, while an incorrect response was indicated by a red cross.\\u003c/p\\u003e \\u003c/p\\u003e \\u003cp\\u003e \\u003cb\\u003eGamification and Incentivization.\\u003c/b\\u003e To incentivise participation, several gamification components were built into the app. Participants could choose one of 45 brain avatars after downloading the app (Fig.\\u0026nbsp;5A) and were awarded \\u0026ldquo;brain points\\u0026rdquo; based on their task performance throughout training (Fig.\\u0026nbsp;5B).\\u003c/p\\u003e \\u003cp\\u003eDuring each training session participants also unlocked one fact about the human brain, and one fact about mental health (four facts on days 11 and 12). The 28 brain and mental health facts were designed to present psychoeducation content, including concepts such as neuroplasticity, in engaging text and video-based formats.\\u003c/p\\u003e \\u003cp\\u003eWithin each session, participants reached \\u0026ldquo;brain stations\\u0026rdquo; (Fig.\\u0026nbsp;5C) as they progressed through the app, and after completing a training session in full they received \\u0026ldquo;brain badges\\u0026rdquo; (Fig.\\u0026nbsp;5D). These stations and badges thematically matched the corresponding day\\u0026rsquo;s brain/mental health facts and contained a code to unlock a linked webpage with additional resources related to that day\\u0026rsquo;s brain/mental health topic (e.g., additional information on neuroplasticity). Once unlocked, badges remained accessible in a participant\\u0026rsquo;s app profile for the duration of training.\\u003c/p\\u003e \\u003cp\\u003e \\u003cb\\u003eFigure 5\\u003c/b\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec16\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eDepiction of Gamification Components\\u003c/h2\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003e \\u003cstrong\\u003eNote\\u003c/strong\\u003e \\u003cp\\u003eFigure\\u0026nbsp;5 depicts the gamification components of the SBT. \\u003cb\\u003ePanel A\\u003c/b\\u003e shows the avatars participants could choose after downloading the app. \\u003cb\\u003ePanel B\\u003c/b\\u003e shows an example of the \\u0026ldquo;brain points\\u0026rdquo; participants could receive for completing the affective control and CBM-I components of training. \\u003cb\\u003ePanel C\\u003c/b\\u003e depicts an example of the \\u0026ldquo;brain stations\\u0026rdquo; participants reached at the end of each training session. \\u003cb\\u003ePanel D\\u003c/b\\u003e shows some examples of the \\u0026ldquo;brain badges\\u0026rdquo; participants unlocked as they completed each training session.\\u003c/p\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec17\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eAffective Control Training\\u003c/h2\\u003e \\u003cp\\u003eLike the SBT, each AffeCT session started with 4 questions about mood, affect regulation, social context and current activity. AffeCT (\\u003cspan citationid=\\\"CR51\\\" class=\\\"CitationRef\\\"\\u003e51\\u003c/span\\u003e) then included the same dual \\u003cem\\u003en\\u003c/em\\u003e-back task as per the SBT. The only differences in the AffeCT dual \\u003cem\\u003en\\u003c/em\\u003e-back were that each block contained 20\\u0026thinsp;+\\u0026thinsp;\\u003cem\\u003en\\u003c/em\\u003e trials, and each session was made up of 30 blocks. Participants were able to end each training session any time from 10 minutes onwards, and there was no limit on the number of training sessions participants could complete within a day. The first day of AffeCT training started at \\u003cem\\u003en\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;1, with the level of \\u003cem\\u003en\\u003c/em\\u003e for each subsequent day of training starting at the average \\u003cem\\u003en\\u003c/em\\u003e achieved in the previous day\\u0026rsquo;s training session.\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab3\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 3\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eMeans and standard deviations of variables of interest across training groups\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"3\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eVariable\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eSBT (\\u003cem\\u003en\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;77)\\u003c/p\\u003e \\u003cp\\u003e\\u003cem\\u003emean (SD)\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eAffeCT (\\u003cem\\u003en\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;67)\\u003c/p\\u003e \\u003cp\\u003e\\u003cem\\u003emean (SD)\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eApp usage\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e59.73 (67.24)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e40.58 (81.84)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eApp sessions\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e6.61 (7.27)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e3.61 (7.08)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eN-back usage\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e82.37 (51.54)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e110.62 (101.80)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eMax N\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e3.81 (2.07)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e4.29 (2.87)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eMean N\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e2.31 (1.23)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e2.42 (1.32)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eCBMI usage\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e44.31 (50.90)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eN/A\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eCBMI RT\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e3889.267 (654.79)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eN/A\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eCBMI accuracy\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e51.47(35.54)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eN/A\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePsychoed usage\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e20.51 (24.70)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eN/A\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003ctfoot\\u003e \\u003ctr\\u003e\\u003ctd colspan=\\\"3\\\"\\u003e\\u003cem\\u003eNote\\u003c/em\\u003e. \\u003cb\\u003eApp usage\\u003c/b\\u003e\\u0026thinsp;=\\u0026thinsp;average time (mins) spent in the assigned training app in total. \\u003cb\\u003eApp sessions\\u003c/b\\u003e\\u0026thinsp;=\\u0026thinsp;average number of times participants engaged in a training session in the assigned training app in total (a new engagement was counted each time there was a break longer than 5 minutes between the end of the previous engagement and the start of the next engagement). \\u003cb\\u003eN-back usage\\u003c/b\\u003e\\u0026thinsp;=\\u0026thinsp;amount of time (mins) spent training on the n-back task of the assigned training app. \\u003cb\\u003eMax N\\u003c/b\\u003e\\u0026thinsp;=\\u0026thinsp;maximum N level reached across all trials of the assigned training app. \\u003cb\\u003eMean N\\u003c/b\\u003e\\u0026thinsp;=\\u0026thinsp;average N level reached across all trials of the assigned training app. \\u003cb\\u003eCBMI usage\\u003c/b\\u003e\\u0026thinsp;=\\u0026thinsp;total time (mins) spent on CBMI tasks in the SBT app across all SBT app sessions. \\u003cb\\u003eCBMI RT\\u003c/b\\u003e\\u0026thinsp;=\\u0026thinsp;average RT (ms) on correct CBMI trials across all SBT app sessions. \\u003cb\\u003eCBMI accuracy\\u003c/b\\u003e\\u0026thinsp;=\\u0026thinsp;total correct CBMI trials across all SBT app sessions. \\u003cb\\u003ePsychoed usage\\u003c/b\\u003e\\u0026thinsp;=\\u0026thinsp;total time (mins) spent on psychoeducation components in the SBT app across all SBT app sessions.\\u003c/td\\u003e\\u003c/tr\\u003e \\u003c/tfoot\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec18\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eProcedure\\u003c/h2\\u003e \\u003cp\\u003eAll study components were completed online. After completing consent and assent procedures, participants completed all baseline assessments. They were then allocated to complete either AffeCT or SBT across two weeks, receiving an email from the research lab detailing how to download and access their assigned app to complete the training. Throughout the two weeks of training, participants with notifications enabled received daily alerts from their training app to complete training, the first sent at 8am and the second at 5pm. Following the training, participants completed the post-training assessments (as baseline) and one-month follow-up assessment. All baseline, post-training and follow-up assessments were conducted using Gorilla Experiment Builder (\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://gorilla.sc\\u003c/span\\u003e\\u003cspan address=\\\"https://gorilla.sc\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e). Through the inbuilt participant messaging system within the Gorilla platform, participants were emailed links to complete the assessments at each time point. Those who did not complete the assessment at a given time point received two reminders to do so, the first sent 3 days after the initial email, and the second sent 7 days after the initial email. Participants were reimbursed with an AUD50 (GBP25) voucher for completing baseline, training and post-training assessments, and received an additional AUD10 (GBP5) voucher for completing the follow-up assessment. For a schematic overview of all measures and when they were administered, see Figure S2.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec19\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eAnalyses\\u003c/h2\\u003e \\u003cp\\u003eAll statistical analyses were conducted using R version 4.2.1 (\\u003cspan citationid=\\\"CR52\\\" class=\\\"CitationRef\\\"\\u003e52\\u003c/span\\u003e). See supplementary materials for a list of R packages used. Training groups (SBT vs. AffeCT) were compared on baseline characteristics and changes over time on the outcomes of interest prior to hypothesis testing.\\u003c/p\\u003e \\u003cp\\u003e \\u003cstrong\\u003eHypothesis 1\\u003c/strong\\u003e \\u003cp\\u003ewas tested with a general linear model, with training group entered as a predictor and minutes spent training as the outcome. Exploratory analyses were also run with app sessions and n-back usage separately added as the outcome in the model testing H1. App sessions were operationalised as the average number of times participants engaged in a training session in their assigned app, while n-back usage was operationalised as the average amount of time (minutes) participants spent on the n-back task of their assigned training app.\\u003c/p\\u003e \\u003c/p\\u003e \\u003cp\\u003ePrior to testing hypotheses 2\\u0026ndash;3, exploratory analyses were run to investigate the effects of time (baseline vs post-training) on mental health, interpretation bias and affective control using mixed models, a Bonferroni correction of \\u003cem\\u003ep\\u003c/em\\u003e\\u0026thinsp;\\u003cspan type=\\\"Underline\\\" class=\\\"Underline\\\" name=\\\"Emphasis\\\"\\u003e\\u0026le;\\u003c/span\\u003e\\u0026thinsp;.003 (.05/16) was applied to account for 16 additional comparisons. Hypotheses 2 and 3 were tested using linear mixed models, with time (baseline vs post-training) as a fixed within-subjects factor and Participant ID as a random effect. For models that included training group (SBT vs AffeCT), this was added as a fixed between-subjects factor. As recommended for mixed effects models, effect sizes were calculated using r squared (\\u003cspan citationid=\\\"CR53\\\" class=\\\"CitationRef\\\"\\u003e53\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003eApp usage (mins) was added as a predictor of affective control (H2a) and interpretation bias (H2b). To investigate H2c, training group (SBT vs AffeCT) was added as a predictor to the model testing H2b.\\u003c/p\\u003e \\u003cp\\u003e \\u003cstrong\\u003eHypothesis\\u003c/strong\\u003e \\u003cp\\u003ea was tested with training group (SBT vs AffeCT) and baseline to post-training change in affective control as predictors of emotion regulation (as measured by the reappraisal subscale of the ERQ-CA and by the RTQ, entered into separate analyses). To test H3b, baseline to post-training changes in affective control and interpretation bias were separately added along with training group (SBT vs AffeCT) as predictors of depression and anxiety respectively.\\u003c/p\\u003e \\u003c/p\\u003e \\u003cp\\u003eTo investigate the pre-registered exploratory analyses, assessing whether social sensitivity and concern for social risk would moderate improvements in affective control, social sensitivity and concern for social risk were separately added as fixed effects to the models testing H3 (first just as an interaction with time (baseline vs post-training), then as an interaction with time (baseline vs post-training) and training group (SBT vs AffeCT).\\u003c/p\\u003e \\u003cdiv id=\\\"Sec20\\\" class=\\\"Section3\\\"\\u003e \\u003ch2\\u003eData and Code Availability\\u003c/h2\\u003e \\u003cp\\u003eOn publication of the manuscript, de-identified data, syntax, and code supporting the conclusions of this article will be made available at the Open Science Framework (\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://osf.io/preprints/psyarxiv/rpvh9\\u003c/span\\u003e\\u003cspan address=\\\"https://osf.io/preprints/psyarxiv/rpvh9\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e). Study materials will not be made available, as most of the included images are licensed to the authors.\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e\"},{\"header\":\"Results\",\"content\":\"\\u003cdiv id=\\\"Sec22\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eRandomisation Checks\\u003c/h2\\u003e \\u003cp\\u003eParticipants were randomly assigned to one of two training groups, SBT or AffeCT. Analyses of variance (ANOVA; continuous variables) and chi-squared tests (categorical variables) showed no group differences in baseline characteristics (see supplementary materials), except for self-rated emotion regulation (\\u003cem\\u003eF\\u003c/em\\u003e(1, 140)\\u0026thinsp;=\\u0026thinsp;4.33, \\u003cem\\u003ep\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;.039), which was lower at baseline in the SBT compared to the AffeCT group.\\u003c/p\\u003e \\u003cdiv id=\\\"Sec23\\\" class=\\\"Section3\\\"\\u003e \\u003ch2\\u003eApp Acceptability\\u003c/h2\\u003e \\u003cp\\u003eThere were no significant differences in ratings of app helpfulness (\\u003cem\\u003eF\\u003c/em\\u003e(1, 96)\\u0026thinsp;=\\u0026thinsp;0.02, \\u003cem\\u003ep\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;.896), ease of use (\\u003cem\\u003eF\\u003c/em\\u003e(1, 96)\\u0026thinsp;=\\u0026thinsp;0.18, \\u003cem\\u003ep\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;.669), or likeability (\\u003cem\\u003eF\\u003c/em\\u003e(1, 96)\\u0026thinsp;=\\u0026thinsp;0.91, \\u003cem\\u003ep\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;.342) between the training apps (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e) .\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab4\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 4\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eApp acceptability variables means and standard deviations\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"3\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eSBT mean (SD)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eAffeCT mean (SD)\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eApp helpfulness\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e2.07 (1.32)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e2.10 (1.21)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eApp ease of use\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e2.95 (1.14)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e2.85 (1.20)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eApp likeability\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e2.12 (1.27)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e1.87 (1.22)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003ctfoot\\u003e \\u003ctr\\u003e\\u003ctd colspan=\\\"3\\\"\\u003e\\u003cem\\u003eNote\\u003c/em\\u003e. \\u003cb\\u003eApp helpfulness\\u003c/b\\u003e\\u0026thinsp;=\\u0026thinsp;how helpful participants found their assigned training app. \\u003cb\\u003eApp ease of use\\u003c/b\\u003e\\u0026thinsp;=\\u0026thinsp;how easy to use participants found their assigned training app. \\u003cb\\u003eApp likeability\\u003c/b\\u003e\\u0026thinsp;=\\u0026thinsp;how much participants liked using their assigned training app. All measures were rated from 0 (\\u003cem\\u003enot at all\\u003c/em\\u003e) to 4 (\\u003cem\\u003every\\u003c/em\\u003e).\\u003c/td\\u003e\\u003c/tr\\u003e \\u003c/tfoot\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec24\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eApp Engagement\\u003c/h2\\u003e \\u003cp\\u003eA chi-squared test indicated that participants who were assigned to the SBT (\\u003cem\\u003en\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;48 began training) app were significantly more likely to begin training than participants assigned to the AffeCT (\\u003cem\\u003en\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;24 began training) app (\\u003cem\\u003eχ\\u003c/em\\u003e \\u003csup\\u003e\\u003cem\\u003e2\\u003c/em\\u003e\\u003c/sup\\u003e(1, \\u003cem\\u003eN\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;144)\\u0026thinsp;=\\u0026thinsp;9.12, \\u003cem\\u003ep\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;.003). Additionally, an independent samples \\u003cem\\u003et\\u003c/em\\u003e-test indicated that of those who began training, SBT (\\u003cem\\u003eM\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;6.61; \\u003cem\\u003eSD\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;7.27) participants engaged with significantly more training sessions on average than AffeCT (\\u003cem\\u003eM\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;3.61; \\u003cem\\u003eSD\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;7.08) participants (\\u003cem\\u003et\\u003c/em\\u003e(286) = -3.53, \\u003cem\\u003ep\\u003c/em\\u003e\\u0026thinsp;\\u0026lt;\\u0026thinsp;.001, 95% CI [-4.67, -1.33]).\\u003c/p\\u003e \\u003cp\\u003eContrary to our hypothesis (H1), however, we did not observe a significant difference in amount of time (in minutes) spent training on the SBT compared to the AffeCT (\\u003cem\\u003eR\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003e2\\u003c/em\\u003e\\u003c/sup\\u003e\\u0026thinsp;=\\u0026thinsp;0.01, \\u003cem\\u003eF\\u003c/em\\u003e\\u003csub\\u003e(1, 142)\\u003c/sub\\u003e\\u0026thinsp;=\\u0026thinsp;2.36, \\u003cem\\u003ep\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;.127). Similarly, there was no significant difference in amount of time (in minutes) spent completing affective control training in the SBT compared to the AffeCT (\\u003cem\\u003eR\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003e2\\u003c/em\\u003e\\u003c/sup\\u003e = -0.00, \\u003cem\\u003eF\\u003c/em\\u003e\\u003csub\\u003e(1, 142)\\u003c/sub\\u003e\\u0026thinsp;=\\u0026thinsp;0.85, \\u003cem\\u003ep\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;.357). However, exploratory analyses indicated a significant difference between number of training sessions participants engaged with in the SBT compared to the AffeCT (\\u003cem\\u003eR\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003e2\\u003c/em\\u003e\\u003c/sup\\u003e\\u0026thinsp;=\\u0026thinsp;.04, \\u003cem\\u003eF\\u003c/em\\u003e\\u003csub\\u003e(1, 142)\\u003c/sub\\u003e\\u0026thinsp;=\\u0026thinsp;6.20, \\u003cem\\u003ep\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;.014), with the SBT group engaging in more training sessions (Fig.\\u0026nbsp;6).\\u003c/p\\u003e \\u003cp\\u003e \\u003cb\\u003eFigure 6\\u003c/b\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec25\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eNumber of training sessions engaged with\\u003c/h2\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003e \\u003cstrong\\u003eNote\\u003c/strong\\u003e \\u003cp\\u003eEffect of training group (SBT vs AffeCT) on average number of sessions participants engaged with on their assigned training app.\\u003c/p\\u003e \\u003c/p\\u003e \\u003c/div\\u003e\\n\\u003ch3\\u003eTraining-related changes in affective control and interpretation bias\\u003c/h3\\u003e\\n\\u003cp\\u003eAcross all participants, interpretation bias was reduced from baseline to post-training (\\u003cem\\u003eR\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003e2\\u003c/em\\u003e\\u003c/sup\\u003e\\u003cem\\u003em\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;0.02, \\u003cem\\u003eR\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003e2\\u003c/em\\u003e\\u003c/sup\\u003e\\u003cem\\u003ec\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;0.70, \\u003cem\\u003eF\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;15.51, \\u003cem\\u003edf\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;115.71, \\u003cem\\u003ep\\u003c/em\\u003e\\u0026thinsp;\\u0026lt;\\u0026thinsp;.001). While affective control defined as the difference in RT for correct trials on the affective versus neutral condition of the 2-back task did not significantly differ from baseline to post-training (\\u003cem\\u003eR\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003e2\\u003c/em\\u003e\\u003c/sup\\u003e\\u003cem\\u003em\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;0.00, \\u003cem\\u003eR\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003e2\\u003c/em\\u003e\\u003c/sup\\u003e\\u003cem\\u003ec\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;0. 38, \\u003cem\\u003eF\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;0.63, \\u003cem\\u003edf\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;126.19, \\u003cem\\u003ep\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;.429), participants did get better at the task across conditions, as shown by a significant effect of time on RT on the 2-back task (\\u003cem\\u003eR\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003e2\\u003c/em\\u003e\\u003c/sup\\u003e\\u003cem\\u003em\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;0.03, \\u003cem\\u003eR\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003e2\\u003c/em\\u003e\\u003c/sup\\u003e\\u003cem\\u003ec\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;0.64, \\u003cem\\u003eF\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;43.95, \\u003cem\\u003edf\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;383.00, \\u003cem\\u003ep\\u003c/em\\u003e\\u0026thinsp;\\u0026lt;\\u0026thinsp;.001). This indicates that when looking at RT generally, participants showed significant improvements in affective control from baseline to post-training.\\u003c/p\\u003e \\u003cp\\u003eHowever, in contrast with hypotheses H2a/b time spent training did not interact with time (baseline vs post-training) to predict improvements in affective control (\\u003cem\\u003ep\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;.361; Table \\u003cspan refid=\\\"MOESM1\\\" class=\\\"InternalRef\\\"\\u003eS1\\u003c/span\\u003e) or interpretation bias (\\u003cem\\u003ep\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;.142; Table S2), though time spent training was significantly associated with improvements in interpretation bias after controlling for time point (\\u003cem\\u003ep\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;.023; Table S2). Furthermore, there was no interaction between training group (SBT vs AffeCT), time (baseline vs post-training) and training time on interpretation bias (H2c; \\u003cem\\u003ep\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;.106; Table S3).\\u003c/p\\u003e \\u003cp\\u003eThe exploratory analysis including RT on correct trials of the untrained 2-back task (across the affective and neutral conditions) as outcome, show a significant improvement across time and greater improvement with more training time (Table S4). However there was no significant time x training time interaction.\\u003c/p\\u003e \\u003cdiv id=\\\"Sec27\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eTraining-related changes in mental health and emotion regulation\\u003c/h2\\u003e \\u003cp\\u003eExploratory analyses investigating baseline to post-training and follow-up changes in mental health showed no significant changes in symptoms of depression (Tables S5C-6C) and anxiety (Tables S5D-6D). While there were no significant changes in reappraisal (Tables S5A-6A), participants\\u0026rsquo; rumination decreased significantly from baseline to follow-up (Table S6B; Figure S3). These effects were consistent across training groups (i.e., no significant training group x time interaction; Tables S8-9).\\u003c/p\\u003e \\u003cp\\u003eIn contrast with our third hypothesis, changes in affective control were not associated with changes in emotion regulation (Table S9) or mental health (Table S10). These non-significant associations made the pre-registered exploratory analyses obsolete, however for completeness the code for these analyses is available with the code of the included analyses.\\u003c/p\\u003e \\u003c/div\\u003e\"},{\"header\":\"Discussion\",\"content\":\"\\u003cp\\u003eIn this pre-registered study, we aimed to investigate the merits of introducing gamification components, such as badges and points, to standard affective control training paradigms to improve training uptake and adherence in an adolescent sample. We hypothesised that gamification would increase adolescent engagement with cognitive control training in affective contexts (i.e., affective control training), thus leading to improved affective control and, in turn, emotion regulation. We also directly trained emotion regulation abilities by targeting interpretation biases, aiming to decrease these and, by extension, improve mental health symptoms in adolescents. The results showed no significant differences in minutes spent training across the gamified and non-gamified training. However, exploratory analyses showed participants were twice as likely to start training when assigned to SBT compared to AffeCT training, and that participants engaged more with the gamified SBT (more sessions) compared to the AffeCT training. While training time was not associated with baseline to post-training improvements in affective control, when looking at overall performance on the 2-back task (i.e., neutral and affective condition) there was a significant change from baseline to post-intervention and there was a significant effect of training time. Similarly, interpretation bias improved from baseline to post-intervention and was associated with time spent training. Moreover, while training was not associated with significant changes in depression or anxiety symptoms and reappraisal capacity, there was a significant baseline to post-intervention reduction in rumination, which was maintained at follow-up.\\u003c/p\\u003e \\u003cp\\u003eGamification did not lead to increased training time, as there was no difference in the amount of training time between the SBT and AffeCT groups. However, participants assigned to the SBT did engage in significantly more sessions than those assigned to the AffeCT. This is in line with previous research findings that gamification increased engagement with training (for a review, see 28), as despite not increasing the total time spent on the app, participants did seem to return to the gamified app more frequently than those who were engaging with its non-gamified counterpart. Importantly, training engagement was entirely self-motivated in the present study, as participants did not receive any additional monetary rewards for completing more training.\\u003c/p\\u003e \\u003cp\\u003eIt is unclear, however, which specific components of the SBT may have led participants to return to it more often than those completing the AffeCT training. The two training apps did not differ in participants\\u0026rsquo; ratings of helpfulness, ease of use, or even likeability. Overall, training uptake and retention in the present study was quite low across the two apps. Of the 67 participants assigned to AffeCT, only 24 participants began training, and similarly only 48 of the 77 participants assigned to SBT began training. Furthermore, out of the minimum 12 sessions required for successful training completion across the two apps, participants only begun an average of 4 sessions in the AffeCT app and an average of 7 sessions in the SBT app. These differences are promising for the hypothesis that gamification may increase training engagement, as they indicate that participants were almost twice as likely to begin training and engaged on average with approximately twice as many sessions of training when assigned to the gamified SBT compared to the non-gamified AffeCT training. However, these findings are also in line with previous findings that cognitive training uptake in adolescents is quite low (\\u003cspan citationid=\\\"CR24\\\" class=\\\"CitationRef\\\"\\u003e24\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR25\\\" class=\\\"CitationRef\\\"\\u003e25\\u003c/span\\u003e), suggesting that the gamified factors included in the present study may still not be enough to fully incentivise participants to complete cognitive control training. Future studies aiming to incorporate gamification components into training programs should explicitly assess which components participants find most engaging.\\u003c/p\\u003e \\u003cp\\u003eThere was no effect of increased training and interpretation bias or affective control across time in the present study. However, interpretation bias generally was reduced from baseline to post-training, and while affective control measured as the difference between affective and neutral trials did not improve with training, affective and cognitive control as measured with overall task performance on the untrained 2-back also improved from baseline to post-intervention. Additionally, we observed significant effects of training time on interpretation bias and general performance of cognitive and affective control across baseline and post-training. These findings suggest that despite the low training uptake, engaging with the training apps may have still had some effects on overall improvements in interpretation bias and affective and cognitive control performance (i.e., combined performance across neutral and affective trials) from baseline to post-training.\\u003c/p\\u003e \\u003cp\\u003eThis is in line with existing literature on cognitive control training studies, as researchers have previously found that cognitive training improves affective control (e.g., 33) and cognitive control (e.g., 24). The \\u003cem\\u003en\\u003c/em\\u003e-back task used to train cognitive control across both training groups in the present study was modelled after a similar n-back task that has previously been shown to significantly improve affective control (\\u003cspan citationid=\\\"CR51\\\" class=\\\"CitationRef\\\"\\u003e51\\u003c/span\\u003e). Similarly, CBM-I training has been shown to successfully reduce interpretation bias (\\u003cspan additionalcitationids=\\\"CR55\\\" citationid=\\\"CR54\\\" class=\\\"CitationRef\\\"\\u003e54\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR56\\\" class=\\\"CitationRef\\\"\\u003e56\\u003c/span\\u003e), and the present task was modelled after a previously validated task (\\u003cspan citationid=\\\"CR35\\\" class=\\\"CitationRef\\\"\\u003e35\\u003c/span\\u003e). Affective control training has also been associated with emotion regulation improvements (\\u003cspan citationid=\\\"CR23\\\" class=\\\"CitationRef\\\"\\u003e23\\u003c/span\\u003e), which may underly interpretation bias (\\u003cspan citationid=\\\"CR57\\\" class=\\\"CitationRef\\\"\\u003e57\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003eInterestingly, we also observed overall reductions in rumination from baseline that persisted over a one-month follow-up period. It has been hypothesised that reduced cognitive control may underly ruminative tendencies, with researchers finding associations between increased rumination and reduced cognitive control (\\u003cspan citationid=\\\"CR58\\\" class=\\\"CitationRef\\\"\\u003e58\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR59\\\" class=\\\"CitationRef\\\"\\u003e59\\u003c/span\\u003e). However, previous studies employing 6 sessions of dual \\u003cem\\u003en\\u003c/em\\u003e-back training over a one week period, with the hope of increasing cognitive control and decreasing rumination as with the present study, did not find associations between training and cognitive improvements or differential effects of training on rumination (\\u003cspan citationid=\\\"CR60\\\" class=\\\"CitationRef\\\"\\u003e60\\u003c/span\\u003e). The researchers proposed that this may have been due to insufficient training time, as they did observe a relationship between increased training time and decreased depressive symptomatology, which is closely associated with rumination (\\u003cspan citationid=\\\"CR61\\\" class=\\\"CitationRef\\\"\\u003e61\\u003c/span\\u003e), over time (\\u003cspan citationid=\\\"CR60\\\" class=\\\"CitationRef\\\"\\u003e60\\u003c/span\\u003e). Indeed, in a study where participants completed 27 sessions of training involving multiple tasks, including a dual \\u003cem\\u003en\\u003c/em\\u003e-back task, over a period of 4 weeks, researchers observed improvements in negative mood in the cognitive control training group (\\u003cspan citationid=\\\"CR62\\\" class=\\\"CitationRef\\\"\\u003e62\\u003c/span\\u003e), a factor that is closely linked to rumination (\\u003cspan citationid=\\\"CR63\\\" class=\\\"CitationRef\\\"\\u003e63\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR64\\\" class=\\\"CitationRef\\\"\\u003e64\\u003c/span\\u003e). Other studies have similarly found that cognitive training decreased ruminative tendencies (e.g., 65,66). Together, these findings suggest that the observed effect of reduced rumination over time in the present study may indeed have been a preliminary result of cognitive training engagement, but more training may have been needed for training effects to be observed.\\u003c/p\\u003e \\u003cp\\u003eThe findings presented here should be considered within the study\\u0026rsquo;s limitations. First, as the study\\u0026rsquo;s aim was to demonstrate increased engagement with a training paradigm through gamification, there was no control group that completed non-affective control training. That is, observed effects could be due to placebo effects of engaging in cognitive training. However, if the observed effects are genuine, it suggests that even a limited amount of training can improve affective and cognitive control, interpretation bias, and rumination in adolescents. Future studies should seek to replicate these effects including a placebo-training group.\\u003c/p\\u003e \\u003cp\\u003eA second limitation is the study\\u0026rsquo;s follow-up period. Design and production of the SBT app began in early 2020. However, production of the app faced significant delays throughout the COVID-19 pandemic, and participant recruitment did not begin until mid-2023. Due to limitations with the grant expiry, the follow-up time point had to be changed from six-months to one-month post-training. Additionally, while recruitment and baseline assessments were originally proposed to be conducted in-person, the study had to be moved fully online and relied on social media advertisements to complete recruitment within the limited time left to conduct the study. While online recruitment benefitted the samples\\u0026rsquo; representativeness (\\u003cspan citationid=\\\"CR67\\\" class=\\\"CitationRef\\\"\\u003e67\\u003c/span\\u003e), it required the detection of fraudulent participants. The current study implemented a range of procedures to identify fraudulent participants, including attention check items, the Qualtrics fraudulent and duplicate response detection tools and identification of bulk response patterns.\\u003c/p\\u003e\"},{\"header\":\"Conclusion\",\"content\":\"\\u003cp\\u003eDespite its limitations, this study does provide preliminary evidence that gamification may be a viable tool for increasing adolescent engagement with cognitive training. The results provide further tentative support for even limited amounts of affective control training\\u0026rsquo;s potential to improve affective and cognitive control and reduce interpretation bias and rumination. If gamification effects can be further maximised to increase training adherence to apps such as the SBT, these apps have the potential to then be further developed as preventive interventions for adolescent mental health disorders and disseminated at larger scales, as the training is conducted online and at no cost to users. Research has shown that across 21 different countries, 90% of individuals under 24 years have access to the internet (\\u003cspan citationid=\\\"CR68\\\" class=\\\"CitationRef\\\"\\u003e68\\u003c/span\\u003e). Such interventions would therefore be easily accessible to youth worldwide, making them promising tools for targeting the leading cause of disability in adolescents.\\u003c/p\\u003e\"},{\"header\":\"Abbreviations\",\"content\":\"\\u003cdiv class=\\\"DefinitionList\\\"\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003eAffeCT\\u003c/b\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eNon-gamified Affective Control Training\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003eANOVA\\u003c/b\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eAnalysis of Variance\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003eCBM-I\\u003c/b\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eCognitive Interpretation Bias Modification\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003eCI\\u003c/b\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eConfidence Interval\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003eERQ\\u003c/b\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eEmotion Regulation Questionnaire \\u0026ndash; child and adolescent version\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003eGAD\\u003c/b\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eGeneralized Anxiety Disorder Scale\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003eHSRQ\\u003c/b\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eHealth and Social Risk Questionnaire\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003eM\\u003c/b\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eMean\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003eO\\u003c/b\\u003e\\u003csup\\u003e\\u003cb\\u003e2\\u003c/b\\u003e\\u003c/sup\\u003e\\u003cb\\u003eS\\u003c/b\\u003e\\u003csup\\u003e\\u003cb\\u003e3\\u003c/b\\u003e\\u003c/sup\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eOnline and Offline Social Sensitivity Scale\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003ePHQ\\u003c/b\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003ePatient Health Questionnaire - Adolescent\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003eRT\\u003c/b\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eReaction Time\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003eRTQ\\u003c/b\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eRepetitive Thinking Questionnaire\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003eSBT\\u003c/b\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eSocial Brain Train\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003eSD\\u003c/b\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eStandard Deviation\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003eSES\\u003c/b\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003esocio-economic status\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003eSST\\u003c/b\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eScrambled Sentences Task\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003c/div\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003cp\\u003e \\u003cstrong\\u003eEthics approval and consent to participate:\\u003c/strong\\u003e \\u003cp\\u003eThe study received ethics approval by the university of New South Wales Human Research Executive Committee (HC230164) prior to data collection. Prior to data collection,\\u003c/p\\u003e \\u003c/p\\u003e \\u003cp\\u003e \\u003cstrong\\u003eConsent for publication:\\u003c/strong\\u003e \\u003cp\\u003eNot applicable.\\u003c/p\\u003e \\u003c/p\\u003e\\u003cp\\u003e \\u003ch2\\u003eCompeting interests:\\u003c/h2\\u003e \\u003cp\\u003eThe authors declare that they have no competing interests to disclose.\\u003c/p\\u003e \\u003c/p\\u003e\\u003ch2\\u003eFunding:\\u003c/h2\\u003e \\u003cp\\u003eThis work was supported by a National Health and Medical Research Council grant (GNT1184136). SS is supported by a Henry Wellcome fellowship (209127). AWS is supported by a NHMRC Investigator Grant (GNT1197074). SJB is funded by Wellcome (107496), the MRC, the Jacobs Foundation, the Wellspring Foundation and the University of Cambridge. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.\\u003c/p\\u003e\\u003ch2\\u003eAuthor Contribution\\u003c/h2\\u003e\\u003cp\\u003eKG: Conceptualization, Data Curation, Formal Analysis, Investigation, Methodology, Project Administration, Resources, Software, Visualisation, Writing \\u0026ndash; original draft, Writing \\u0026ndash; reviewing and editing; SM: Conceptualization, Data Curation, Methodology, Project Administration, Resources, Software; JLA: Conceptualization, Methodology, Project Administration; AS: Conceptualization, Methodology, Writing \\u0026ndash; reviewing and editing; SJB: Funding Acquisition, Supervision; AKCC: Data Curation, Writing \\u0026ndash; reviewing and editing; JF: Project Administration; EF: Funding Acquisition; ABN: Project Administration; WR: Funding Acquisition; MR: Data Curation; AWS: Funding Acquisition, Supervision, Writing \\u0026ndash; reviewing and editing; SS: Conceptualization, Funding Acquisition, Methodology, Supervision, Writing \\u0026ndash; reviewing and editing. All authors read and approved the final manuscript.\\u003c/p\\u003e\\u003ch2\\u003eAcknowledgements:\\u003c/h2\\u003e \\u003cp\\u003eNot applicable.\\u003c/p\\u003e\\u003ch2\\u003eData Availability\\u003c/h2\\u003e\\u003cp\\u003eOn publication of the manuscript, de-identified data and code necessary to reproduce the analyses presented here will be made publicly accessible at the following URL: https://osf.io/preprints/psyarxiv/rpvh9. The materials necessary to attempt to replicate the findings presented here are not publicly available, as most of the included images are licensed to the authors.\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\u003cli\\u003e\\u003cspan\\u003eBlakemore SJ, Mills KL. Is adolescence a sensitive period for sociocultural processing? Annu Rev Psychol. 2013/09/11 ed. 2014;65:187\\u0026ndash;207.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eSawyer SM, Azzopardi PS, Wickremarathne D, Patton GC. 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In: Psychological Experiments on the Internet. 2000. pp. 89\\u0026ndash;117.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eInternational Telecommunication Union. Measuring the Information Society [Internet]. International Telecommunication Union. 2013. Available from: \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://www.itu.int/en/ITU-D/Statistics/Documents/publications/mis2013/MIS2013_without_Annex_4.pdf\\u003c/span\\u003e\\u003cspan address=\\\"https://www.itu.int/en/ITU-D/Statistics/Documents/publications/mis2013/MIS2013_without_Annex_4.pdf\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e\\u003c/ol\\u003e\"}],\"fulltextSource\":\"\",\"fullText\":\"\",\"funders\":[],\"hasAdminPriorityOnWorkflow\":false,\"hasManuscriptDocX\":true,\"hasOptedInToPreprint\":true,\"hasPassedJournalQc\":\"\",\"hasAnyPriority\":false,\"hideJournal\":false,\"highlight\":\"\",\"institution\":\"\",\"isAcceptedByJournal\":true,\"isAuthorSuppliedPdf\":false,\"isDeskRejected\":\"\",\"isHiddenFromSearch\":false,\"isInQc\":false,\"isInWorkflow\":false,\"isPdf\":false,\"isPdfUpToDate\":true,\"isWithdrawnOrRetracted\":false,\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"child-and-adolescent-psychiatry-and-mental-health\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"caph\",\"sideBox\":\"Learn more about [Child and Adolescent Psychiatry and Mental Health](http://capmh.biomedcentral.com)\",\"snPcode\":\"13034\",\"submissionUrl\":\"https://submission.nature.com/new-submission/13034/3\",\"title\":\"Child and Adolescent Psychiatry and Mental Health\",\"twitterHandle\":\"@IACAPAP\",\"acdcEnabled\":true,\"dfaEnabled\":true,\"editorialSystem\":\"em\",\"reportingPortfolio\":\"BMC/SO AJ\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":true},\"keywords\":\"Mental health, Adolescent, Depression, Emotion Regulation, Cognitive training, Gamification\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-5900018/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-5900018/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003ch2\\u003eBackground\\u003c/h2\\u003e \\u003cp\\u003eAdolescence is a time of increased emotional volatility, with emotion regulation still developing. Training the cognitive substrate of successful emotion regulation has been shown to benefit adolescents\\u0026rsquo; mental health. However, cognitive training interventions often have low adherence rates in this age group. The current study therefore trialled a novel gamified cognitive training program in adolescents.\\u003c/p\\u003e\\u003ch2\\u003eMethods\\u003c/h2\\u003e \\u003cp\\u003eA longitudinal study was conducted throughout 2023 where 144 culturally diverse adolescents (13\\u0026ndash;16 years, 48% female) completed 12 days of either a novel gamified affective control training program, the Social Brain Train (SBT), or a standard non-gamified affective control training program (AffeCT). Participants also completed mental health and mechanisms of change questionnaires at baseline, post-training, and 1-month follow-up, as well as behavioural affective control and interpretation bias measures at baseline and post-training.\\u003c/p\\u003e\\u003ch2\\u003eResults\\u003c/h2\\u003e \\u003cp\\u003eThe total minutes spent training did not differ significantly across the two training groups. Participants assigned to SBT training, however, did engage in more training sessions than participants assigned to AffeCT training. Additionally, all participants showed improvements in affective control performance and a reduction in interpretation bias and rumination from baseline to post-training. The observed reduction in rumination persisted at 1-month follow-up.\\u003c/p\\u003e\\u003ch2\\u003eConclusions\\u003c/h2\\u003e \\u003cp\\u003eAs engagement is often the most difficult thing to achieve in cognitive training with adolescents, observing greater repeated engagement with the gamified cognitive training is promising, given training on these apps is entirely self-motivated. Observing benefits to affective and cognitive control performance and reduced interpretation bias and rumination tendencies after very limited training is also promising, as these factors have all been previously linked to improved mental health symptoms among adolescents. The present findings therefore suggest there may be merit in using gamification techniques to improve the design of future training programs, and employing these to improve affective, cognitive, and emotion regulation abilities in adolescents.\\u003c/p\\u003e\",\"manuscriptTitle\":\"Investigating the effects of a novel gamified cognitive training on adolescent mental health\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2025-02-03 17:35:47\",\"doi\":\"10.21203/rs.3.rs-5900018/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0},{\"type\":\"decision\",\"content\":\"Revision requested\",\"date\":\"2025-02-13T09:55:14+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorInvitedReview\",\"content\":\"\",\"date\":\"2025-02-11T13:13:14+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"326596823709142245627047216142615143431\",\"date\":\"2025-01-29T10:05:20+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"editorInvitedReview\",\"content\":\"\",\"date\":\"2025-01-29T07:12:53+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"15348321506907395737925345417648867132\",\"date\":\"2025-01-29T06:21:57+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewersInvited\",\"content\":\"\",\"date\":\"2025-01-28T07:36:47+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorAssigned\",\"content\":\"\",\"date\":\"2025-01-28T07:34:40+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"checksComplete\",\"content\":\"\",\"date\":\"2025-01-27T12:00:38+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"submitted\",\"content\":\"Child and Adolescent Psychiatry and Mental Health\",\"date\":\"2025-01-25T07:13:48+00:00\",\"index\":\"\",\"fulltext\":\"\"}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"child-and-adolescent-psychiatry-and-mental-health\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"caph\",\"sideBox\":\"Learn more about [Child and Adolescent Psychiatry and Mental Health](http://capmh.biomedcentral.com)\",\"snPcode\":\"13034\",\"submissionUrl\":\"https://submission.nature.com/new-submission/13034/3\",\"title\":\"Child and Adolescent Psychiatry and Mental Health\",\"twitterHandle\":\"@IACAPAP\",\"acdcEnabled\":true,\"dfaEnabled\":true,\"editorialSystem\":\"em\",\"reportingPortfolio\":\"BMC/SO AJ\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":true}}],\"origin\":\"\",\"ownerIdentity\":\"1a4b2e90-2ede-435d-ba29-38ca5de597b6\",\"owner\":[],\"postedDate\":\"February 3rd, 2025\",\"published\":true,\"recentEditorialEvents\":[],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"published-in-journal\",\"subjectAreas\":[],\"tags\":[],\"updatedAt\":\"2025-07-07T16:05:16+00:00\",\"versionOfRecord\":{\"articleIdentity\":\"rs-5900018\",\"link\":\"https://doi.org/10.1186/s13034-025-00917-1\",\"journal\":{\"identity\":\"child-and-adolescent-psychiatry-and-mental-health\",\"isVorOnly\":false,\"title\":\"Child and Adolescent Psychiatry and Mental Health\"},\"publishedOn\":\"2025-07-03 15:57:13\",\"publishedOnDateReadable\":\"July 3rd, 2025\"},\"versionCreatedAt\":\"2025-02-03 17:35:47\",\"video\":\"\",\"vorDoi\":\"10.1186/s13034-025-00917-1\",\"vorDoiUrl\":\"https://doi.org/10.1186/s13034-025-00917-1\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-5900018\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-5900018\",\"identity\":\"rs-5900018\",\"version\":[\"v1\"]},\"buildId\":\"8U1c8b4HqxoKbykW_rLl7\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}