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Trial registered on ANZCTR
Registration number
ACTRN12625000413426
Ethics application status
Approved
Date submitted
12/04/2025
Date registered
6/05/2025
Date last updated
6/05/2025
Date data sharing statement initially provided
6/05/2025
Type of registration
Retrospectively registered
Titles & IDs
Public title
The Pitjantjatjara ASSIST: A project aimed at assessing the validity, reliability and cultural appropriateness of the digital, translated and culturally-adapted Alcohol, Smoking and Substance Involvement Screening Test (ASSIST), for use in Aboriginal and Torres Strait Islander populations.
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Scientific title
The Pitjantjatjara ASSIST: An order-randomised study assessing the validity, reliability and cultural appropriateness of the digital, translated and culturally-adapted Alcohol, Smoking and Substance Involvement Screening Test (ASSIST), for use in Aboriginal and Torres Strait Islander populations.
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Secondary ID [1]
314199
0
None
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Universal Trial Number (UTN)
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Trial acronym
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Linked study record
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Health condition
Health condition(s) or problem(s) studied:
alcohol use disorder
337075
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hazardous alcohol use
337076
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harmful use of alcohol
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alcohol dependence
337078
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tobacco use disorder
337079
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hazardous nicotine use
337080
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harmful use of nicotine
337081
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nicotine dependence
337082
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cannabis use disorder
337083
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hazardous cannabis use
337084
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harmful use of cannabis
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cannabis dependence
337086
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methamphetamine use disorder
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hazardous stimulants use
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harmful use of stimulants
337089
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stimulants dependence
337090
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inhalants use disorder
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hazardous inhalants use
337092
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harmful use of inhalants
337093
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inhalants dependence
337094
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Condition category
Condition code
Mental Health
333510
333510
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0
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Addiction
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Public Health
333511
333511
0
0
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Epidemiology
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Public Health
333512
333512
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0
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Health promotion/education
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Intervention/exposure
Study type
Interventional
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Description of intervention(s) / exposure
Participant Involvement and Procedure:
Participants will complete the Pitjantjatjara ASSIST app, a culturally-adapted and translated 8-item questionnaire that assesses risk of harm from substance use disorders [1,2]. The app focuses on five substances of concern in Pitjantjatjara communities (alcohol, tobacco, cannabis, methamphetamine, and inhalants). Participants step through the instrument sequentially for each substance, with the ability to modify responses throughout the assessment until the final question is completed. After completion, participants receive personalized feedback on substance-specific risk levels and general health advice about reducing or stopping use. Following the receipt of feedback, participants are then asked to answer three user experience questions using a 5-point Likert Scale with emoji faces to evaluate cultural acceptability.
Time Requirement:
Based on internal pilot testing, the app takes approximately 10 minutes to complete, not including the variable time participants spend reviewing their feedback, which is not time-limited.
Administration:
The app is self-administered on an iPad tablet. Before beginning, participants receive a guided visual and tactile demonstration from a research team member (either a health worker or interpreter). Research team members remain nearby to address any questions or technical issues, but participants complete the assessment independently.
Frequency:
Participants will complete the app twice during the study period: once on the initial day (either before or after the diagnostic interview, depending on randomization) and again during a follow-up session 6-14 days later.
Fidelity and Adherence Monitoring:
The app's digital format ensures standardisation of the assessment process. All participants receive the same questions in the same sequence, with built-in controls that prevent modification of responses after completion.
Randomisation and follow-up
Participants will first be randomised to complete either the Pitjantjatjara ASSIST app or the diagnostic interview first. Those assigned to the app-first condition will complete the app as outlined, then be provided a 30-minute break before completing the diagnostic interview. Those assigned to the interview-first condition will complete the diagnostic interview first, then be given a 30-minute break before completing the app.
Both groups of participants will then be followed up 7-14 days later to complete the Pitjantjatjara ASSIST app a second time.
References:
1. World Health Organization Working Group. The Alcohol, Smoking and Substance Involvement Screening Test (ASSIST): development, reliability and feasibility. Addiction. 2002 Sep;97(9):1183-94.
2. Stevens MW, Barry D, Bertossa S, Thompson M, Ali R. First-Stage Development of the Pitjantjatjara Translation of the World Health Organization’s Alcohol, Smoking and Substance Involvement Screening Test (ASSIST). Journal of the Australian Indigenous HealthInfoNet. 2022;3(4):2.
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Intervention code [1]
330802
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Early detection / Screening
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Intervention code [2]
330803
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Diagnosis / Prognosis
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Intervention code [3]
330865
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Lifestyle
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Comparator / control treatment
Procedure:
Participants will complete a diagnostic interview based on the modified DIS-SAM that identifies clinical symptoms for both ICD-11 and DSM-5 substance use disorders. The interview follows a semi-structured "yarning"-style discussion framework and covers substance use over both 3-month and 12-month intervals. Each participant will complete this interview once, on the same day they complete the Pitjantjatjara ASSIST app, with the order determined by their randomization group (app-first or interview-first).
Time Requirement:
The interview is designed to be completed within 30 minutes or less.
Administration:
The interview will be conducted by a gender-matched health professional who understands Pitjantjatjara culture and context but may not be Aboriginal or fluent in the language. An Aboriginal person of the same gender as the participant will always be present during the interview to aid with interpretation and cultural context. This dual-professional approach is designed to help mitigate potential impacts of cultural differences on assessment quality.
Frequency:
Participants will complete the diagnostic interview only once during the study period. In contrast, they will complete the Pitjantjatjara ASSIST app twice: once on the initial day (either before or after the interview, depending on randomisation) and again during a follow-up session 7-14 days later.
Fidelity and Adherence Monitoring:
The interview is standardised through implementation in REDCap, ensuring that all participants receive the same questions in the same order, depending on their level of substance involvement. This standardisation, combined with the dual-professional approach (Aboriginal and non-Indigenous healthcare workers), helps maintain consistency across all interviews while allowing for culturally appropriate "yarning"-style discussions. The structured digital format in REDCap also facilitates consistent documentation and data collection across all participants.
Randomisation and follow-up:
As above, participants assigned to receive the interview first will complete the diagnostic interview with the health professional and translator, then be given a 30-minute break before completing the Pitjantjatjara ASSIST app.
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Control group
Active
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Outcomes
Primary outcome [1]
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Discriminant validity.
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Assessment method [1]
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ASSIST substance specific involvement (SSI) scores for alcohol, tobacco, cannabis, methamphetamine, inhalants will be compared to outcomes from clinical interview (determining diagnosis of DSM-5 [substance use disorder] and ICD-11 [hazardous use, harmful use, dependence] conditions). To assess discriminant validity, i.e., the ability of the ASSIST to discriminate between diagnostic outcomes, ASSIST SSI scores for participants grouped by DSM-5 and ICD-11 diagnoses will be compared for group differences using one-way ANOVA. Post-hoc pairwise tests will assess where group differences lie.
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Timepoint [1]
341084
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Only responses obtained on the first day of assessment (both ASSIST and interview) will be used to determine this outcome.
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Primary outcome [2]
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Concurrent validity. Concurrent validity captures the extent to which a test aligns with the current gold-standard.
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Assessment method [2]
341085
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To assess concurrent validity, i.e., the ability of ASSIST score ratings to align with risk severity of the gold-standard, ASSIST SSI scores for each substance will be compared to the number of DSM-5 and ICD-11 symptoms endorsed using generalised linear models.
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Timepoint [2]
341085
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Only responses obtained on the first day of assessment (both ASSIST and interview) will be used to determine this outcome.
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Primary outcome [3]
341087
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Reliability (test-retest)
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Assessment method [3]
341087
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ASSIST SSI scores for each substance will be compared at two time points using Cohen's chance-corrected kappa, and intraclass correlation coefficients.
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Timepoint [3]
341087
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baseline and 7-14 day follow-up
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Secondary outcome [1]
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Internal consistency reliability
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Assessment method [1]
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ASSIST substance-specific items (for alcohol, tobacco, cannabis, methamphetamine, inhalants) will be assessed for internal consistency using McDonald's Omega.
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Timepoint [1]
446175
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Only responses obtained on the first day of assessment (ASSIST only) will be used to determine this outcome.
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Secondary outcome [2]
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Diagnostic accuracy - Sensitivity
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Assessment method [2]
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ROC curve analysis will determine cut-off scores (using Youden's J). Cut-off scores will then be used to comparing SSI classifications predicted by the ASSIST (index screening tool) versus the clinical interview (gold-standard reference). True positive (TP), true negative (TN), false positive (FP) and false negative (FN) are calculated using a 2x2 matrix. Sensitivity is the proportion of true positive cases among total positive cases (TP/[TP+FN])
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Timepoint [2]
446636
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Only responses obtained on the first day of assessment (both ASSIST and interview) will be used to determine this outcome.
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Secondary outcome [3]
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Diagnostic accuracy - Specificity
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Assessment method [3]
446637
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ROC curve analysis will determine cut-off scores (using Youden's J). Cut-off scores will then be used to comparing SSI classifications predicted by the ASSIST (index screening tool) versus the clinical interview (gold-standard reference). True positive (TP), true negative (TN), false positive (FP) and false negative (FN) are calculated using a 2x2 matrix. Specificity is the proportion of true negative cases among total negative cases (TN/[TN+FP])
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Timepoint [3]
446637
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Only responses obtained on the first day of assessment (both ASSIST and interview) will be used to determine this outcome.
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Secondary outcome [4]
446638
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Diagnostic accuracy - positive predictive value (PPV)
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Assessment method [4]
446638
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ROC curve analysis will determine cut-off scores (using Youden's J). Cut-off scores will then be used to comparing SSI classifications predicted by the ASSIST (index screening tool) versus the clinical interview (gold-standard reference). True positive (TP), true negative (TN), false positive (FP) and false negative (FN) are calculated using a 2x2 matrix. PPV is the proportion of true positives among all positive test results (TP/[TP+FP])
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Timepoint [4]
446638
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Only responses obtained on the first day of assessment (both ASSIST and interview) will be used to determine this outcome.
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Secondary outcome [5]
446639
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Diagnostic accuracy - negative predictive value (NPV)
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Assessment method [5]
446639
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ROC curve analysis will determine cut-off scores (using Youden's J). Cut-off scores will then be used to comparing SSI classifications predicted by the ASSIST (index screening tool) versus the clinical interview (gold-standard reference). True positive (TP), true negative (TN), false positive (FP) and false negative (FN) are calculated using a 2x2 matrix. NPV is the proportion of true negatives among all negative test results (TN/[TN+FN]).
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Timepoint [5]
446639
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Only responses obtained on the first day of assessment (both ASSIST and interview) will be used to determine this outcome.
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Secondary outcome [6]
446640
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Positive likelihood ratio (LR+)
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Assessment method [6]
446640
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Likelihood ratio for positive tests (LR+) is the ratio of true cases to false cases, which can be calculated by the following formula: Sensitivity / (1 - Specificity). As above, Sensitivity is the proportion of true positive cases among total positive cases (TP/[TP+FN]); while Specificity is the proportion of true negative cases among total negative cases (TN/[TN+FP]). These values are calculated using the ASSIST app (index) and clinical interview data (reference).
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Timepoint [6]
446640
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Only responses obtained on the first day of assessment (both ASSIST and interview) will be used to determine this outcome.
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Secondary outcome [7]
446641
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Negative likelihood ratio (LR-)
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Assessment method [7]
446641
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The likelihood ratio for negative tests (LR-) is the likelihood of true non-cases to false non-cases which can be calculated by the following formula: (1 - Sensitivity) / Specificity As above, Sensitivity is the proportion of true positive cases among total positive cases (TP/[TP+FN]); while Specificity is the proportion of true negative cases among total negative cases (TN/[TN+FP]). These values are calculated using the ASSIST app (index) and clinical interview data (reference).
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Timepoint [7]
446641
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Only responses obtained on the first day of assessment (both ASSIST and interview) will be used to determine this outcome.
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Secondary outcome [8]
446642
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Clinical utility index (positive)
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Assessment method [8]
446642
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the clinical utility index for positive tests (CUI+) is the product of sensitivity and PPV As above, Sensitivity is the proportion of true positive cases among total positive cases (TP/[TP+FN]); while PPV is the proportion of true positives among all positive test results (TP/[TP+FP]). These values are calculated using the ASSIST app (index) and clinical interview data (reference).
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Timepoint [8]
446642
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Only responses obtained on the first day of assessment (both ASSIST and interview) will be used to determine this outcome.
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Secondary outcome [9]
446643
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Clinical utility index (negative)
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Assessment method [9]
446643
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clinical utility index for negative tests (CUI-) is the product of specificity and NPV. As above, Specificity is the proportion of true negative cases among total negative cases (TN/[TN+FP]); while NPV is the proportion of true negative cases among all negative test results (TN/[TN+FN]). These values are calculated using the ASSIST app (index) and clinical interview data (reference).
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Timepoint [9]
446643
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Only responses obtained on the first day of assessment (both ASSIST and interview) will be used to determine this outcome.
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Secondary outcome [10]
446644
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Cultural acceptability
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Assessment method [10]
446644
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three questions rated on a 5-point Likert scale, using facial expression emojis, ranging from 0 (frown) to 5 (smile). The three questions are: “How easy was it to use this iPad to answer our questions?”, “Was it okay for us to ask these questions?”, and “Were the questions easy to understand?” Responses will be quantified and used to assess acceptability, together with the time taken to complete the app.
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Timepoint [10]
446644
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baseline and 7-14 day follow up
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Eligibility
Key inclusion criteria
Must self-identify as Pitjantjatjara- or English-speaking Anangu (meaning ‘people’ in Pitjantjatjara-Yankunytjatjara, the Traditional Owners of the APY-lands across South Australia, Northern Territory, and Western Australia)
Since participants are also required to conduct a diagnostic interview (which will be conducted in English with the aid of a translator), fluency in either (spoken or written) English or Pitjantjatjara is required.
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Minimum age
18
Years
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Maximum age
65
Years
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Sex
Both males and females
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Can healthy volunteers participate?
Yes
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Key exclusion criteria
Participants who appear intoxicated at the time of the interview will not be eligible to participate in the study, but will still be able to try out app should they choose
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Study design
Purpose of the study
Diagnosis
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Allocation to intervention
Randomised controlled trial
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Procedure for enrolling a subject and allocating the treatment (allocation concealment procedures)
Participants are first approached by the research assistant to gauge interest/suitability for participation. Those interested to participate are then randomised into either condition first, ahead of providing informed consent. Information about the study is provided to the participants through the iPad at the beginning of both the app (as part of the app's onboarding process) or the interview (as part of the interview orientation).
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Methods used to generate the sequence in which subjects will be randomised (sequence generation)
A link to our randomisation sequence generator (located on a centralised website:https://assistportal.com.au/randomiser/) has been embedded within each iPad. The researcher initiates the randomisation sequence on the iPad, and depending on the allocated group, obtains informed consent via the app or at the beginning of the interview.
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Masking / blinding
Blinded (masking used)
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Who is / are masked / blinded?
The people analysing the results/data
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Intervention assignment
Crossover
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Other design features
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Phase
Not Applicable
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Type of endpoint/s
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Statistical methods / analysis
Statistical approach:
The primary outcomes from this study include the app’s reliability, validity, diagnostic accuracy. Reliability will be assessed according to internal consistency and test-retest, using McDonald’s omega, and Cohen’s chance-corrected kappa. Validity will be assessed according to both concurrent and discriminative validity against a gold-standard clinical interview. Concurrent validity will be assessed using linear regression, while discriminant validity will be assessed using one-way ANOVA. A small subset of participants will also receive an independent evaluation from a Specialist Addiction Medicine Registrar, which will form the basis of an additional check for concurrent validity, which will be assessed using logistic regression. Diagnostic accuracy of the instrument will be assessed based on a range of indices and receiver operating characteristics (ROC) curve analysis.
SAMPLE SIZE CALCULATIONS
Since the app focuses on these five substances only, and uses existing ASSIST cut-off scores to determine three corresponding levels of risk for each (i.e., low, moderate or high), there are a total of 15 (5x3) possible substance/risk combinations. We will aim to recruit a minimum of 40 individuals to satisfy each of those outcomes (e.g., 40 participants each for low, moderate and high-risk, for each of the substances This could require up to 600 participants, though the total will likely be lower since many use multiple substances.
For the validity assessments, a series of power calculations were conducted to determine the minimum sample size needed to detect a large between-groups effect, with type-I, and type-II error rates of 5% (corresponding to a=.05), and 10% (corresponding to an a priori power of 90%) respectively. Where possible, we will also aim to recruit a 1:1 ratio of participants for each group (i.e., positive/negative cases), and so a 1:1 ratio of participants was used here. Using these parameters as default, we conducted the following power calculations in G-power [1].
For each regression model assessing concurrent validity, it was determined that a minimum of 111 participants are needed for each model (corresponding to line-of-best-fit slope of .3). For each logistic regression model assessing concurrent validity with the independent assessment, a total sample size of 62 using each substance was determined. The additional parameters used in this analysis included a probability of reaching diagnosis in the diagnosis present group of .70 (corresponding to a sensitivity of 70% and an Odds Ratio of 2.33 [.70/.30]), versus a chance probability (i.e., 50%) in the diagnosis absent group. These parameters yielded a total sample size of 62 individuals (approximately 31 in each group diagnosis present/absent assuming 1:1 sampling). For each ANOVA model assessing discriminant validity, a minimum of 96 participants using each substance are required to power the analysis (corresponding to a Cohen’s f>.40 [2). Furthermore, given there are three planned comparisons for each ANOVA model assessing discriminant validity, a Bonferroni correction was applied to the type-I error rate (i.e., .05/3). Thus the new corrected type-I error rate was reduced to .017. Therefore, the minimum number of participants to detect a large effect (Hedges’ g>.80 [3]) was 38 participants for each group. This corresponds to thirty-eight low risk, thirty-eight moderate risk, and thirty-eight high-risk individuals for each substance (which equals approximately 114 participants for each given substance). Therefore, the total sample size required for each group is 38 individuals.
For the reliability assessment, we also calculated the minimum sample size required to detect an omega coefficient of >.70, setting the type-I error rate to .05, with a minimum power of .90, with the number of scale items equal to 4 (tobacco) or 5 (all other substances). This method has been suggested previously [4,5] and has been used widely in health and medical research settings [6]. The result was a minimum sample size of 38 for a 5-item scale, and 40 for the 4-item scale. We elected to use 40 as the minimum sample size required for consistency.
REFERENCES
1. Faul, F., Erdfelder, E., Lang, A.-G., & Buchner, A. (2007). G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior Research Methods, 39, 175-191
2. Cohen, J. (2013). Statistical power analysis for the behavioral sciences. Routledge.
3. Hedges LV. Distribution theory for Glass's estimator of effect size and related estimators. journal of Educational Statistics. 1981 Jun;6(2):107-28. Journal of Educational Statistics, 6, 107–128.
4. Bonett, D. G. (2002). Sample size requirements for testing and estimating coefficient alpha. Journal of educational and behavioral statistics, 27(4), 335-340.
5. Streiner, D. L. (2003). Starting at the beginning: an introduction to coefficient alpha and internal consistency. Journal of personality assessment, 80(1), 99-103. https://doi.org/10.21315/mjms2018.25.6.9
6. Bujang, M. A., Omar, E. D., & Baharum, N. A. (2018). A Review on Sample Size Determination for Cronbach's Alpha Test: A Simple Guide for Researchers. The Malaysian journal of medical sciences: MJMS, 25(6), 85–99.
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Recruitment
Recruitment status
Recruiting
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Date of first participant enrolment
Anticipated
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Actual
17/12/2024
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Date of last participant enrolment
Anticipated
17/12/2025
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Actual
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Date of last data collection
Anticipated
31/12/2025
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Actual
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Sample size
Target
600
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Accrual to date
30
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Final
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Recruitment in Australia
Recruitment state(s)
SA
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Funding & Sponsors
Funding source category [1]
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Government body
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Name [1]
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Department of Health and Aged Care, Australian Government
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Address [1]
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Country [1]
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Australia
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Primary sponsor type
University
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Name
The University of Adelaide
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Address
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Country
Australia
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Secondary sponsor category [1]
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None
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Name [1]
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Address [1]
321144
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Country [1]
321144
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Ethics approval
Ethics application status
Approved
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Ethics committee name [1]
317319
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Aboriginal Health Research Ethics Committee
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Ethics committee address [1]
317319
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https://ahcsa.org.au/research-and-ethics/ethical-review-ahrec
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Ethics committee country [1]
317319
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Australia
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Date submitted for ethics approval [1]
317319
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11/10/2023
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Approval date [1]
317319
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20/09/2024
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Ethics approval number [1]
317319
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04-23-1090
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Ethics committee name [2]
317323
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Southern Adelaide Clinical Human Research Ethics Committee
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Ethics committee address [2]
317323
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https://www.sahealth.sa.gov.au/wps/wcm/connect/Public%2BContent/SA%2BHealth%2BInternet/About%2Bus/Our%2BLocal%2BHealth%2BNetworks/Southern%2BAdelaide%2BLocal%2BHealth%2BNetwork/Research/For%2BResearchers/Southern%2BAdelaide%2BClinical%2BHuman%2BResearch%2BEthics%2BCommittee
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Ethics committee country [2]
317323
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Australia
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Date submitted for ethics approval [2]
317323
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01/03/2024
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Approval date [2]
317323
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21/05/2024
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Ethics approval number [2]
317323
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2024/HRE00063
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Ethics committee name [3]
317324
0
University of Adelaide Human Research Ethics Committee
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Ethics committee address [3]
317324
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https://www.adelaide.edu.au/research-services/ethics-compliance-integrity/human-research-ethics/human-research-ethics-committee
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Ethics committee country [3]
317324
0
Australia
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Date submitted for ethics approval [3]
317324
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21/05/2024
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Approval date [3]
317324
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02/10/2024
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Ethics approval number [3]
317324
0
39232
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Summary
Brief summary
Substance use significantly contributes to disease burden among Australians, with harms exacerbated among Aboriginal and Torres Strait Islander peoples by colonisation-related factors like stigma and trauma. Addressing this gap requires culturally acceptable, valid and reliable screening tools, available in a familiar language to the participant, to identify and provide support for those at-risk. This study aims to assess the validity, reliability and clinical utility of a culturally-adapted digital screening tool — the Alcohol, Smoking and Substance Involvement Screening Test (ASSIST) — translated into Pitjantjatjara, to detect risk of substance-related harm among Aboriginal Australians.
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Trial website
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Trial related presentations / publications
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Public notes
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Contacts
Principal investigator
Name
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A/Prof Robert Ali, AO
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Address
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Level 3, Helen Mayo South Building, 1 Frome Road, The University of Adelaide, Adelaide, South Australia, 5005
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Country
140686
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Australia
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Phone
140686
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+61 401124516
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Fax
140686
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Email
140686
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[email protected]
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Contact person for public queries
Name
140687
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Robert Ali, AO
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Address
140687
0
Level 3, Helen Mayo South Building, 1 Frome Road, The University of Adelaide, Adelaide, South Australia, 5005
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Country
140687
0
Australia
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Phone
140687
0
+61 401124516
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Fax
140687
0
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Email
140687
0
[email protected]
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Contact person for scientific queries
Name
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Robert Ali, AO
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Address
140688
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Level 3, Helen Mayo South Building, 1 Frome Road, The University of Adelaide, Adelaide, South Australia, 5005
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Country
140688
0
Australia
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Phone
140688
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+61 401124516
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Fax
140688
0
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Email
140688
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[email protected]
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Data sharing statement
Will the study consider sharing individual participant data?
Yes
Will there be any conditions when requesting access to individual participant data?
Persons/groups eligible to request access:
•
Anyone
Conditions for requesting access:
•
Yes, conditions apply:
•
Requires review on a case-by-case basis by the trial custodian, sponsor or data sharing committee
•
Requires a scientifically sound proposal or protocol
•
Requires approval by an ethics committee
•
Requires a data sharing agreement between data requester and trial custodian or sponsor
What individual participant data might be shared?
•
De-identified individual participant data:
•
Published results
•
Primary outcome(s)
What types of analyses could be done with individual participant data?
•
Systematic reviews and meta-analyses
•
Studies exploring new research questions
•
Health economic analyses
•
Studies testing whether findings can be repeated or confirmed
When can requests for individual participant data be made (start and end dates)?
From:
At the end of the study
To:
No end date
Where can requests to access individual participant data be made, or data be obtained directly?
•
Email of trial custodian, sponsor or committee:
contact should be made to the Chief Investigator,
[email protected]
Are there extra considerations when requesting access to individual participant data?
No
What supporting documents are/will be available?
No Supporting Document Provided
Results publications and other study-related documents
Documents added manually
No documents have been uploaded by study researchers.
Documents added automatically
No additional documents have been identified.
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