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| Name | Class |
|---|---|
| Monash Health | OTHER |
| St Vincent's Hospital Melbourne | OTHER |
| Uniting Vic Tas | OTHER |
| Star Health |
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Cognitive biases contribute to the difficulty experienced by heavy drinkers wishing to reduce their alcohol use. Recent interventions designed to reduce cognitive biases demonstrate efficacy for Approach Bias Modification (ApBM). Reductions in the likelihood of relapse have been found after ApBM in Alcohol Use Disorder (AUD) patients during residential treatment. Current methods of ApBM are usually delivered by computer and joystick and come with several limitations, including accessibility. If ApBM could be shown to be feasible in other settings, such as outpatient treatment, it could benefit a much larger population with AUD.
This randomised controlled trial will test the efficacy of a recently-developed ApBM smartphone app called "AAT-App" ("Alcohol Avoidance Training App"). We aim to test whether AAT-App, relative to a minimal version of the app which excludes ApBM training, is effective at reducing alcohol use, cravings, severity of dependence, and approach bias (a measure of a person's automatic tendency to automatically approach alcohol-related stimuli), and to explore user experiences of AAT-App to guide future improvements to the app and its implementation.
Aims:
We aim to determine whether providing the "active" version of AAT-App (including ApBM) to people accessing outpatient alcohol treatment from AOD services, is effective, relative to a minimal version of the app which does not include ApBM training, at reducing alcohol use, cravings, and severity of dependence. We also aim to test the psychometric properties of the mobile phone approach bias measure we developed, and whether engaging in AAT-App significantly reduces approach bias, relative to the minimal control condition. We also aim to explore user experiences of AAT-App's, perceived alignment with treatment, and suggested improvements, using qualitative interviews in a subset of participants, to guide further future improvements to the app and its implementation.
Design & Setting:
We will conduct a double-blind, randomised, parallel-group controlled superiority trial with alcohol treatment outpatients in Melbourne, Victoria. Participants will be randomised to one of 2 groups with a 1:1 allocation ratio. Both participants and researchers completing the follow-up interviews will be unaware (blinded) of the condition to which they have been randomly allocated.
Recruitment:
Staff at participating services will briefly explain the opportunity to participate in a study testing a "brain-training" app to clients who they believe may meet eligibility criteria. To preserve blinding, no specific details will be provided regarding approach bias modification, and participants will merely be informed that the study tests "a new smartphone 'brain-training app'" that "involves doing brief game-like tasks on your phone each week for 4 weeks". Clients who are interested will need to provide consent to be contacted by the research team, who will conduct screening for eligibility, provide more complete participant information, and conduct recruitment.
Screening:
Research staff will phone clients who have provided consent to be contacted to confirm eligibility (administering the Alcohol Use Disorders Identification Test (AUDIT), checking age and phone operating system, confirming that they have no plans to enter residential/inpatient treatment in the next month, confirming absence of past-month residential rehabilitation and any past-week inpatient treatment (e.g., hospitalisation or residential withdrawal), as well as asking about number of days spent in inpatient treatment in the past month if the person underwent any inpatient treatment prior to the previous week).
Randomisation and blinding of allocation:
Six computer-generated randomisation sequences (one for each recruitment site) will be produced by a data scientist who is not otherwise involved in recruitment or data collection, processing, or analysis, using a 1:1 allocation ratio, based on blocks of variable size (ranging from 2-6). As such, randomisation will be stratified by site. The app developers (ANT Development Studios Ltd.) will provide the data scientist with two lists of app access codes which will direct participants to either the intervention or minimal version of AAT-App when they first download and open the app. Using these lists and the randomisation sequence, the data scientist will generate a separate spreadsheet of access codes for each site (based on the site-stratified randomisation sequence). Researchers will send these codes to participants as they are recruited from each respective site. Researchers involved in recruitment will only have access to a spreadsheet displaying a single list of codes to be sent to participants at each respective site, while the randomisation sequence will be stored in a password-protected file provided to the trial statistician and to one research officer who will remain unblinded to assist with coordinating qualitative interviews. Neither the randomisation file, nor its password will be provided to any other staff involved in recruitment or in pursuing follow-ups or quantitative data management until all data analysis is complete.
Data collection windows for post-intervention and follow up assessments:
Statistical analyses:
Primary outcome: A linear mixed-effects model (LMM) will be used to compare change in mean standard drinks consumed per week between groups across 4 time points (baseline, post-intervention, 1-month follow-up, and 3-month follow-up). This model will test the main effects of time and group and (most crucially for determining efficacy) the group x time interaction. Planned follow-up comparisons between groups at post-intervention, 1-month follow-up, and 3-month follow-up time-points will be conducted using t-tests, with post-intervention being the primary endpoint. A secondary sensitivity analysis will be conducted excluding a participant's data from any time-point where they had been in residential/inpatient treatment in the past week (i.e., restricting analyses to time-points where a participant's opportunity to drink had not been limited by hospitalisation, rehabilitation, etc.). If a difference between groups is found post-intervention, a secondary LMM analysis of difference between groups in change in weekly standard drinks during the intervention period (i.e., 5 levels of time: Baseline, week 1, week 2, week 3, post-intervention) will be conducted to examine how quickly differences between groups emerge, with t-tests used to compare groups at week 1, 2, 3, and post-intervention time-points. This secondary analysis will be conducted excluding participants who had engaged in any residential/inpatient treatment within the intervention period.
Secondary outcomes: Continuous outcome variables (Craving Experience Questionnaire frequency scale (CEQ-F) scores, Severity of Dependence Scale scores, AUDIT scores, past-week heavy drinking days (HDDs), past-month drinking days, Australian Treatment Outcome Profile quality of life items, and approach bias) will be analysed in a similar manner to the primary analysis described above. Sensitivity analysis of past-week drinking days to control for the possible effect of past-week residential/inpatient treatment will be conducted as described for the primary outcome. Past-month drinking days will be expressed as a percentage of the total number of days on which a participant had the opportunity to drink (i.e., if a participant was in residential/inpatient treatment for 10 days at a certain time point, then for that time point, their past-month drinking days will be expressed as a proportion of the remaining 18 days on which they had the opportunity to drink), although data will be excluded at any time point where the participant did not have at least 14 days on which they had the opportunity to drink alcohol (i.e., if they were within residential/inpatient treatment on 15 or more days). For CEQ-F, secondary analyses will be conducted for each of its 3 subscales. Analyses of AUDIT scores will use 2 levels of time (baseline, 3-month follow-up). Approach bias analyses will also use 2 levels of time (baseline, post-intervention) and approach bias scores will be analysed separately for alcohol and positive images. As past-month HDDs can only be calculated at 1 time point (post-intervention), they will simply be compared between groups using a t-test post-intervention after converting scores to a proportion of days on which the participant had an opportunity to drink (as described for past-month drinking days). Proportions of groups reporting complete past-week and past-month abstinence will be compared between groups at post-intervention, 1-month follow-up, and 3-month follow-up using Pearson's chi-squared. Mobile Application Rating Scale 'functionality', 'aesthetics', and 'subjective quality' scores, and participants' subjective ratings regarding AAT-App's effect on drinking and cravings will be explored within each group separately using descriptive data (e.g., mean, median, quartile cut-offs, percentages scoring above 3) to quantify typical ratings and proportions of participants providing favourable ratings. Where relevant, exploratory analyses will also compare mean scores of uMARS scales between groups using t-tests.
Qualitative study:
Interview transcripts will be subjected to a thematic qualitative analysis in order to identify underlying themes and patterns within each respondent's discourse. Thematic analysis will proceed according to the six stage process described by Braun and Clark. The coding process will be primarily conducted by two researchers, and a third researcher will oversee and verify coding decisions to ensure agreement and consistency throughout the process. The digital qualitative data analysis software NVivo 11.4.0 will be used to facilitate qualitative data analysis. Free-text responses to app acceptability questions in the post-intervention survey will be reviewed primarily to identify reports of functionality issues (e.g., "bugs" in the app) and safety issues (e.g., reports of triggering). Any such issues will be catalogued to inform further improvements to the app (if necessary) and its delivery/implementation in future research and/or treatment contexts.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Active AAT-App | Experimental | Participants will receive the active AAT-App. |
|
| Minimal AAT-App | Sham Comparator | Participants will receive the minimal version of AAT-App. |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| AAT-App | Behavioral | Participants will receive the active AAT-App on their smartphone, which includes ApBM training, and prompted to engage with the app during the 28-day intervention period. |
| Measure | Description | Time Frame |
|---|---|---|
| Number of Standard Drinks Consumed Per Week | Participants will estimate the number of standard drinks of alcohol consumed on each day within the past week, using a timeline follow-back assessment. Participants will select a number, ranging from 0-80, to estimate how many standard drinks they consumed on each day in that week. Past-week standard drinks will be calculated using the sum of values for each of the past 7 days. | Baseline, 4 weeks after commencing app use, 8 weeks after commencing app use, and 16 weeks after commencing app use |
| Measure | Description | Time Frame |
|---|---|---|
| Past-Week Frequency of Alcohol Cravings (as Measured by the Craving Experience Questionnaire Frequency Scale - CEQ-F) | The Craving Experience Questionnaire frequency scale (CEQ-F) is a validated, 10-item scale, with each item rated on a scale of 0-10. Total scores are calculated based on the mean of individual items. Higher scores indicate more frequent craving experiences. Three subscale scored can also be calculated: "intensity" (3 items), "imagery" (4 items), and "intrusiveness" (3 items). Secondary analyses will be conducted for each of its 3 subscales. |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Affiliation | Role |
|---|---|---|
| Victoria Manning | Turning Point | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Uniting Vic Tas | Coburg | Victoria | 3058 | Australia | ||
| Monash Health (Addiction Medicine Unit) |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 23218805 | Background | Eberl C, Wiers RW, Pawelczack S, Rinck M, Becker ES, Lindenmeyer J. Approach bias modification in alcohol dependence: do clinical effects replicate and for whom does it work best? Dev Cogn Neurosci. 2013 Apr;4:38-51. doi: 10.1016/j.dcn.2012.11.002. Epub 2012 Nov 14. | |
| 27488392 | Background | Manning V, Staiger PK, Hall K, Garfield JB, Flaks G, Leung D, Hughes LK, Lum JA, Lubman DI, Verdejo-Garcia A. Cognitive Bias Modification Training During Inpatient Alcohol Detoxification Reduces Early Relapse: A Randomized Controlled Trial. Alcohol Clin Exp Res. 2016 Sep;40(9):2011-9. doi: 10.1111/acer.13163. Epub 2016 Aug 4. |
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There is no plan to grant general public access to the dataset. Researchers interested in accessing deidentified individual-level participant data may contact the coordinating principal investigator, Victoria Manning. Granting access to other researchers to use deidentified data will require additional approval by the Saint Vincent's Hospital Melbourne Human Research Ethics Committee, and seeking these approvals will be the responsibility of the researchers seeking access to the dataset.
Researchers interested in accessing individual participant data may contact the coordinating principal investigator after the primary outcome has been published. Note that data will only be stored for 7 years following publication of the last peer-reviewed publication arising from this study, or 7 years after the final report to the ethics committee, or 7 years after final reporting of outcomes on the clinical trials registry, whichever occurs latest. After this 7 year retention period, individual participant data may not be available.
Reasonable requests to access individual participant data will be considered by the coordinating principal investigator
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After providing informed consent to participate, participants (N=82) were sent a link to download the app. 3 participants who were enrolled did not download and install the app, hence the final sample assigned to groups comprised 79 participants.
Recruitment commenced on May 25, 2022 and ended on January 22, 2024. Recruitment was open to people receiving outpatient treatment for alcohol problems in the state of Victoria, Australia.
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| ID | Title | Description |
|---|---|---|
| FG000 | Active AAT-App | Participants will receive the active AAT-App. AAT-App: Participants will receive the active AAT-App on their smartphone, which includes ApBM training, and prompted to engage with the app during the 28-day intervention period. |
| FG001 | Minimal AAT-App | Participants will receive the minimal version of AAT-App. Minimal AAT-App: Participants will receive the minimal version of AAT-App, which does not include ApBM training, on their smartphone and prompted to engage with the app during the 28-day intervention period. |
| Title | Milestones | Reasons Not Completed | |||||||||||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Overall Study |
|
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| ID | Title | Description |
|---|---|---|
| BG000 | Active AAT-App | Participants will receive the active AAT-App. AAT-App: Participants will receive the active AAT-App on their smartphone, which includes ApBM training, and prompted to engage with the app during the 28-day intervention period. |
| BG001 | Minimal AAT-App |
| Units | Counts |
|---|---|
| Participants |
|
| Title | Description | Population Description | Parameter Type | Dispersion Type | Unit of Measure | Calculate Percentage | Denominator Units Selected | Denominators | Classes |
|---|---|---|---|---|---|---|---|---|---|
| Age, Continuous | Mean |
| Type | Title | Description | Population Description | Reporting Status | Anticipated Posting Date | Parameter Type | Dispersion Type | Unit of Measure | Calculate Percentage | Time Frame | Units Analyzed | Denominator Units Selected | Arm/Group Information | Denominators | Classes | Analyses | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Primary | Number of Standard Drinks Consumed Per Week | Participants will estimate the number of standard drinks of alcohol consumed on each day within the past week, using a timeline follow-back assessment. Participants will select a number, ranging from 0-80, to estimate how many standard drinks they consumed on each day in that week. Past-week standard drinks will be calculated using the sum of values for each of the past 7 days. | The numbers describe how many participants were included in the linear mixed model (i.e., providing valid alcohol use data fro at least one time point). Numbers varied across time points (Baseline: 37 Active, 40 Minimal; Week 4: 29 Active, 32 Minimal; Week 8: 27 Active, 30 Minimal; Week 16: 20 Active, 27 Minimal), however, these were analysed using a single linear mixed-effects model which calculated estimated marginal means. | Posted | Mean | Standard Error | standard drinks (10 grams alcohol) | Baseline, 4 weeks after commencing app use, 8 weeks after commencing app use, and 16 weeks after commencing app use |
|
Since this trial tested a brief behavioural training task delivered in a smartphone app, we did not actively assess adverse events. We were prepared to record if participants spontaneously reported significant emotional distress (e.g., feeling triggered, or experiencing strong cravings, during or after app use) at any time during their participation (up to the final 16-week follow-up), but none reported any adverse events.
We were prepared to record if participants spontaneously reported significant emotional distress (e.g., feeling triggered, or experiencing strong cravings, during or after app use) at any time during the trial, but none did.
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| ID | Title | Description | Deaths (Affected) | Deaths (At Risk) | Serious Events (Affected) | Serious Events (At Risk) | Other Events (Affected) | Other Events (At Risk) |
|---|---|---|---|---|---|---|---|---|
| EG000 | Active AAT-App | Participants will receive the active AAT-App. AAT-App: Participants will receive the active AAT-App on their smartphone, which includes ApBM training, and prompted to engage with the app during the 28-day intervention period. |
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| Title | Organization | Phone | Extension | |
|---|---|---|---|---|
| Dr Joshua B. B. Garfield | Monash University | +61 3 8413 8711 | joshuag@turningpoint.org.au |
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| Type | Includes Protocol | Includes SAP | Includes ICF | Document Label | Document Date | Document Uploaded Date | Document File Name |
|---|---|---|---|---|---|---|---|
| Prot_SAP | Yes | Yes | No | Study Protocol and Statistical Analysis Plan | Jul 6, 2022 | Aug 1, 2024 | Prot_SAP_000.pdf |
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| ID | Term |
|---|---|
| D000437 | Alcoholism |
| D016739 | Behavior, Addictive |
| ID | Term |
|---|---|
| D019973 | Alcohol-Related Disorders |
| D019966 | Substance-Related Disorders |
| D064419 | Chemically-Induced Disorders |
| D001523 | Mental Disorders |
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| OTHER |
| Odyssey House | OTHER |
A double-blind, randomised, parallel-group controlled superiority trial with alcohol treatment outpatients will be conducted. Participants will be randomised to one of 2 groups with a 1:1 allocation ratio.
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Participants, investigators, and outcomes assessors will be unaware (blinded) of the condition to which participants have been randomly allocated.
| Minimal AAT-App | Behavioral | Participants will receive the minimal version of AAT-App, which does not include ApBM training, on their smartphone and prompted to engage with the app during the 28-day intervention period. |
|
| Baseline, 4 weeks after commencing app use, 8 weeks after commencing app use, and 16 weeks after commencing app use |
| Severity of Dependence Scale (SDS) Scores | The Severity of Dependence Scale (SDS) is a validated, 5-item scale, with each item scored 0-3. Total scores are calculated by summing individual item scores. Higher scores indicate more severe psychological dependence on the drug being enquired about (i.e., alcohol in this study) | Baseline, 4 weeks after commencing app use, 8 weeks after commencing app use, and 16 weeks after commencing app use |
| Total Scores on the Alcohol Use Disorders Identification Test (AUDIT) | The Alcohol Use Disorders Identification Test (AUDIT) is a validated, 10-item scale, with each item scored 0-4. Total scores are calculated based on the sum of individual item scores. Given the AUDIT usually enquires about drinking and related problems in the past year, wording of instructions and questions was modified to ask participants to base answers on the past 3 months so that equivalent, non-overlapping periods were assessed at both baseline and the final follow-up. | Baseline and 16 weeks after commencing app use |
| Past-week Heavy Drinking Days (HDDs) | Participants estimated the number of standard drinks of alcohol consumed on each day within the past week. Any day when they estimate they consumed at least 5 standard drinks in a day was considered an HDD. | Baseline, 4 weeks after commencing app use, 8 weeks after commencing app use, and 16 weeks after commencing app use |
| Past-Month Drinking Days | At baseline, participants will complete the past-week drinking assessment described above and also report number of drinking days in each of the 3 weeks preceding the past week. 1-month and 3-month follow-up assessments will be identical to the baseline assessment. | Baseline, 8 weeks after commencing app use, and 16 weeks after commencing app use |
| Proportion of Past-Week Complete Abstinence at Post-Intervention and Follow Up Assessments | Past-week complete abstinence will be defined as zero days in the past week on which any alcohol was consumed. Predicted proportions from the linear mixed-effects model are entered using a measure type of "mean", as advised by the trial statistician, because the model produces predicted means from the data (after coding abstinence as 1 and non-abstinence as 0) after the model accounts for complexities in the data, such as the repeated measures of the data, imbalances in group sizes, and assumptions regarding error correlation, random effects, fixed effects. | Baseline, 4 weeks after commencing app use, 8 weeks after commencing app use, and 16 weeks after commencing app use |
| Proportion of Past-Month Complete Abstinence at Post-Intervention and Follow Up Assessments | Participants reporting zero drinking days in the past month will be classified as past-month abstinent. Predicted proportions from the linear mixed-effects model are entered using a measure type of "mean", as advised by the trial statistician, because the model produces predicted means from the data (after coding abstinence as 1 and non-abstinence as 0) after the model accounts for complexities in the data, such as the repeated measures of the data, imbalances in group sizes, and assumptions regarding error correlation, random effects, fixed effects. | Baseline, 8 weeks after commencing app use, and 16 weeks after commencing app use |
| Scores for Quality of Life and Health Items on the Australian Treatment Outcomes Profile (ATOP) | 3 items will be adapted from the Australian Treatment Outcomes Profile (ATOP) assessing psychological health, physical health, and overall quality of life over the past 28 days. Each item will be rated on a scale from zero to ten, where zero is poor and ten is good. Each rating will be treated as a separate variable in analyses (i.e., no composite score will be derived from the 3 separate items). | Baseline, 4 weeks after commencing app use, 8 weeks after commencing app use, 16 weeks after commencing app use. |
| Approach Bias | Approach bias will be assessed within the app using an alcohol approach avoidance task. The approach avoidance task is a behavioural task designed to measure alcohol approach bias, which is the tendency to approach alcohol-related stimuli more quickly than avoiding them (relative to the same tendency for neutral stimuli). This is calculated from reaction time differences according to the formula: (RTalc-avoid - RTalc-approach) - (RTneu-avoid - RTneu-approach), where RTs are the mean reaction times for alcohol avoidance, alcohol approach, neutral stimulus avoidance, and neutral stimulus approach reactions, respectively. Thus, a positive approach bias score reflects a tendency to make an approach movement towards alcohol images more quickly than to make an avoidance, and for that tendency to be larger than the equivalent tendency for neutral images. Scores do not have specific minimum or maximum values. | Baseline and Post-Intervention (28 days after commencing app use) |
| Dandenong |
| Victoria |
| 3175 |
| Australia |
| St. Vincent's Hospital Melbourne (Department of Addiction Medicine) | Fitzroy | Victoria | 3065 | Australia |
| Odyssey House Victoria | Richmond | Victoria | 3121 | Australia |
| Turning Point | Richmond | Victoria | 3121 | Australia |
| Star Health | South Melbourne | Victoria | 3205 | Australia |
| 33146693 | Background | Manning V, Garfield JBB, Staiger PK, Lubman DI, Lum JAG, Reynolds J, Hall K, Bonomo Y, Lloyd-Jones M, Wiers RW, Piercy H, Jacka D, Verdejo-Garcia A. Effect of Cognitive Bias Modification on Early Relapse Among Adults Undergoing Inpatient Alcohol Withdrawal Treatment: A Randomized Clinical Trial. JAMA Psychiatry. 2021 Feb 1;78(2):133-140. doi: 10.1001/jamapsychiatry.2020.3446. |
| 30507226 | Background | Rinck M, Wiers RW, Becker ES, Lindenmeyer J. Relapse prevention in abstinent alcoholics by cognitive bias modification: Clinical effects of combining approach bias modification and attention bias modification. J Consult Clin Psychol. 2018 Dec;86(12):1005-1016. doi: 10.1037/ccp0000321. |
| 34110839 | Background | Salemink E, Rinck M, Becker E, Wiers RW, Lindenmeyer J. Does comorbid anxiety or depression moderate effects of approach bias modification in the treatment of alcohol use disorders? Psychol Addict Behav. 2022 Aug;36(5):547-554. doi: 10.1037/adb0000642. Epub 2021 Jun 10. |
| 21389338 | Background | Wiers RW, Eberl C, Rinck M, Becker ES, Lindenmeyer J. Retraining automatic action tendencies changes alcoholic patients' approach bias for alcohol and improves treatment outcome. Psychol Sci. 2011 Apr;22(4):490-7. doi: 10.1177/0956797611400615. Epub 2011 Mar 9. |
| Background | Braun V, Clarke V. Using thematic analysis in psychology. Qualitative Research in Psychology. 2006; 3(2): 77-101. |
| 41620760 | Derived | Manning V, Bell MCL, Garfield JBB, Paxie JCB, Rubenis A, Roxburgh AD, Piercy H, Whelan D, Lubman DI, Savic M. "A tool in a toolbox": patient engagement with a gamified and personalised approach bias modification app to reduce harmful alcohol consumption - a qualitative study. Addict Sci Clin Pract. 2026 Jan 31;21(1):22. doi: 10.1186/s13722-026-00646-6. |
| 40905156 | Derived | Garfield JBB, Rowland B, Liu SK, Piercy H, Bonomo Y, Whelan D, Manning V. Efficacy of a personalised alcohol approach bias modification smartphone app in people accessing outpatient alcohol use disorder treatment: A randomised controlled trial. Addiction. 2026 Jan;121(1):82-93. doi: 10.1111/add.70184. Epub 2025 Sep 4. |
Participants will receive the minimal version of AAT-App. Minimal AAT-App: Participants will receive the minimal version of AAT-App, which does not include ApBM training, on their smartphone and prompted to engage with the app during the 28-day intervention period. |
| BG002 | Total | Total of all reporting groups |
| years |
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| Sex: Female, Male | Count of Participants | Participants |
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| Race/Ethnicity, Customized | Count of Participants | Participants |
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| Region of Enrollment | Number | participants |
|
| Active AAT-App |
Participants will receive the active AAT-App. AAT-App: Participants will receive the active AAT-App on their smartphone, which includes ApBM training, and prompted to engage with the app during the 28-day intervention period. |
| OG001 | Minimal AAT-App | Participants will receive the minimal version of AAT-App. Minimal AAT-App: Participants will receive the minimal version of AAT-App, which does not include ApBM training, on their smartphone and prompted to engage with the app during the 28-day intervention period. |
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| Secondary | Past-Week Frequency of Alcohol Cravings (as Measured by the Craving Experience Questionnaire Frequency Scale - CEQ-F) | The Craving Experience Questionnaire frequency scale (CEQ-F) is a validated, 10-item scale, with each item rated on a scale of 0-10. Total scores are calculated based on the mean of individual items. Higher scores indicate more frequent craving experiences. Three subscale scored can also be calculated: "intensity" (3 items), "imagery" (4 items), and "intrusiveness" (3 items). Secondary analyses will be conducted for each of its 3 subscales. | All time points were analysed in a single linear mixed-effects model that included anyone who provided valid data for at least one time point. Estimated marginal means are shown below, along with numbers of participants providing data at each time point. | Posted | Mean | Standard Error | score on a scale | Baseline, 4 weeks after commencing app use, 8 weeks after commencing app use, and 16 weeks after commencing app use |
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| Secondary | Severity of Dependence Scale (SDS) Scores | The Severity of Dependence Scale (SDS) is a validated, 5-item scale, with each item scored 0-3. Total scores are calculated by summing individual item scores. Higher scores indicate more severe psychological dependence on the drug being enquired about (i.e., alcohol in this study) | A linear mixed model included all participants who provided valid data for at least one time point. Estimated marginal means and numbers providing data at each specific time point are reported below | Posted | Mean | Standard Error | score on a scale | Baseline, 4 weeks after commencing app use, 8 weeks after commencing app use, and 16 weeks after commencing app use |
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| Secondary | Total Scores on the Alcohol Use Disorders Identification Test (AUDIT) | The Alcohol Use Disorders Identification Test (AUDIT) is a validated, 10-item scale, with each item scored 0-4. Total scores are calculated based on the sum of individual item scores. Given the AUDIT usually enquires about drinking and related problems in the past year, wording of instructions and questions was modified to ask participants to base answers on the past 3 months so that equivalent, non-overlapping periods were assessed at both baseline and the final follow-up. | A linear mixed model included all participants providing scores at baseline and/or follow-up. Estimates marginal means, and numbers of participants providing data at each time point, are provided below. | Posted | Mean | Standard Error | score on a scale | Baseline and 16 weeks after commencing app use |
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| Secondary | Past-week Heavy Drinking Days (HDDs) | Participants estimated the number of standard drinks of alcohol consumed on each day within the past week. Any day when they estimate they consumed at least 5 standard drinks in a day was considered an HDD. | All time points were analysed in a single linear mixed-effects model including all participants who provided valid data for at least one time point. Estimated marginal means and numbers of participants contributing data at each time point are reported below. | Posted | Mean | Standard Error | Heavy drinking days in a week | Baseline, 4 weeks after commencing app use, 8 weeks after commencing app use, and 16 weeks after commencing app use |
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| Secondary | Past-Month Drinking Days | At baseline, participants will complete the past-week drinking assessment described above and also report number of drinking days in each of the 3 weeks preceding the past week. 1-month and 3-month follow-up assessments will be identical to the baseline assessment. | A linear mixed-effects model analysing this outcome included all participants who provided data for at least one of the 3 time points at which it was measured. Numbers providing data at each time point, and predicted marginal means from the analysis, are reported below. | Posted | Mean | Standard Error | number of days any alcohol was consumed | Baseline, 8 weeks after commencing app use, and 16 weeks after commencing app use |
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| Secondary | Proportion of Past-Week Complete Abstinence at Post-Intervention and Follow Up Assessments | Past-week complete abstinence will be defined as zero days in the past week on which any alcohol was consumed. Predicted proportions from the linear mixed-effects model are entered using a measure type of "mean", as advised by the trial statistician, because the model produces predicted means from the data (after coding abstinence as 1 and non-abstinence as 0) after the model accounts for complexities in the data, such as the repeated measures of the data, imbalances in group sizes, and assumptions regarding error correlation, random effects, fixed effects. | A mixed effects logistic regression model included all participants who provided data for at least 1 time point. Numbers providing data at each individual time point and predicted proportions produced by the model are reported below. | Posted | Mean | 95% Confidence Interval | proportion of participants abstinent | Baseline, 4 weeks after commencing app use, 8 weeks after commencing app use, and 16 weeks after commencing app use |
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| Secondary | Proportion of Past-Month Complete Abstinence at Post-Intervention and Follow Up Assessments | Participants reporting zero drinking days in the past month will be classified as past-month abstinent. Predicted proportions from the linear mixed-effects model are entered using a measure type of "mean", as advised by the trial statistician, because the model produces predicted means from the data (after coding abstinence as 1 and non-abstinence as 0) after the model accounts for complexities in the data, such as the repeated measures of the data, imbalances in group sizes, and assumptions regarding error correlation, random effects, fixed effects. | The mixed effects logistic regression model included all participants who provided data for this outcome for at least one time point. Numbers providing data for each specific time point and predicted proportions who were past-month abstinent from the model are provided below. | Posted | Mean | 95% Confidence Interval | proportion of participants abstinent | Baseline, 8 weeks after commencing app use, and 16 weeks after commencing app use |
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| Secondary | Scores for Quality of Life and Health Items on the Australian Treatment Outcomes Profile (ATOP) | 3 items will be adapted from the Australian Treatment Outcomes Profile (ATOP) assessing psychological health, physical health, and overall quality of life over the past 28 days. Each item will be rated on a scale from zero to ten, where zero is poor and ten is good. Each rating will be treated as a separate variable in analyses (i.e., no composite score will be derived from the 3 separate items). | Linear mixed-effects models tested all time points in a single model for each of the 3 ATOP scores. These numbers reflect the number of participants who provided data for at least one time point. Predicted marginal means and numbers of participants providing data at each individual time point are presented below | Posted | Mean | Standard Error | units on a scale | Baseline, 4 weeks after commencing app use, 8 weeks after commencing app use, 16 weeks after commencing app use. |
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| Secondary | Approach Bias | Approach bias will be assessed within the app using an alcohol approach avoidance task. The approach avoidance task is a behavioural task designed to measure alcohol approach bias, which is the tendency to approach alcohol-related stimuli more quickly than avoiding them (relative to the same tendency for neutral stimuli). This is calculated from reaction time differences according to the formula: (RTalc-avoid - RTalc-approach) - (RTneu-avoid - RTneu-approach), where RTs are the mean reaction times for alcohol avoidance, alcohol approach, neutral stimulus avoidance, and neutral stimulus approach reactions, respectively. Thus, a positive approach bias score reflects a tendency to make an approach movement towards alcohol images more quickly than to make an avoidance, and for that tendency to be larger than the equivalent tendency for neutral images. Scores do not have specific minimum or maximum values. | A linear mixed-effects model was used to analyse this outcome and included all participants who provided valid data for at least one time point. Numbers providing data at each individual time point, and predicted marginal means are provided below | Posted | Mean | Standard Error | units on a scale | Baseline and Post-Intervention (28 days after commencing app use) |
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| 0 |
| 39 |
| 0 |
| 39 |
| 0 |
| 39 |
| EG001 | Minimal AAT-App | Participants will receive the minimal version of AAT-App. Minimal AAT-App: Participants will receive the minimal version of AAT-App, which does not include ApBM training, on their smartphone and prompted to engage with the app during the 28-day intervention period. | 0 | 40 | 0 | 40 | 0 | 40 |
Not provided
Not provided
| D003192 | Compulsive Behavior |
| D007175 | Impulsive Behavior |
| D001519 | Behavior |
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This is for the test of the CEQ-F Intensity subscale score
| Mixed Models Analysis |
| .411 |
This is for the time x group interaction for the intensity subscale |
| Slope |
| -0.033 |
| Standard Error of the Mean |
| 0.041 |
| 2-Sided |
| 95 |
| -0.11 |
| 0.05 |
| Superiority |
| Analysis of CEQ-F Imagery subscale score | Mixed Models Analysis | .808 | p value for the time x group interaction for Imagery subscale | Slope | -0.009 | Standard Error of the Mean | 0.036 | 2-Sided | 95 | -0.08 | 0.06 | Superiority |
| This is for the analysis of the CEQ-F Intrusiveness subscale score | Mixed Models Analysis | .886 | This is the p value for the time x group interaction for the Intrusiveness subscale score | Slope | -0.006 | Standard Error of the Mean | 0.041 | 2-Sided | 95 | -0.09 | 0.08 | Superiority |
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| Week 16 |
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| Week 4 psychological wellbeing |
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| Week 8 psychological wellbeing |
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| Week 16 psychological wellbeing |
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| Baseline physical wellbeing |
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| Week 4 physical wellbeing |
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| Week 8 physical wellbeing |
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| Week 16 physical wellbeing |
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| Baseline quality of life |
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| Week 4 quality of life |
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| Week 8 quality of life |
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| Week 16 quality of life |
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Linear mixed-effects model analysis of physical well-being ratings |
| Mixed Models Analysis |
| .425 |
This is the p value for the group x time interaction |
| Slope |
| -0.029 |
| Standard Error of the Mean |
| 0.036 |
| 2-Sided |
| 95 |
| -0.099 |
| 0.042 |
| Superiority |
| Linear mixed-effects model analysis of quality of life ratings | Mixed Models Analysis | .247 | This is the p value for the group x time interaction | Slope | -0.039 | Standard Error of the Mean | 0.034 | 2-Sided | 95 | -0.106 | 0.027 | Superiority |
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