Assisting Digital HEalth REtention (ADHERE Trial): Protocol for a Study Within a Trial (SWAT)
Phase: NA
Conditions: Low Back Pain
Sponsor: Neuroscience Research Australia

ADHERE SWAT Protocol 
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STATISTICAL ANALYSIS PLAN 
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Assisting Digital HEalth REtention (ADHERE Trial): protocol for a 
study within a trial (SWAT) 
 
 
 
 
 
 
 
 
Authors: Filipe Luis Souza, Isha Mishra, Rodrigo Rossi Nogueira Rizzo, James McAuley  
 
 
 
 
 
 
 
 
 
 
 
 

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SUMMARY 
1. 
ADMINISTRATIVE INFORMATION ......................................................................... 4 
2. 
ABSTRACT ...................................................................................................................... 5 
3. 
BACKGROUND .............................................................................................................. 6 
4. 
OBJECTIVE .................................................................................................................... 7 
5. 
HYPOTHESES ................................................................................................................ 7 
6. 
METHODS ....................................................................................................................... 8 
6.1 Trial design ..................................................................................................... 8 
6.2 Participants .................................................................................................... 8 
6.3 Settings........................................................................................................... 8 
6.4 Recruitment .................................................................................................... 8 
6.5 Interventions .................................................................................................. 9 
6.6 Outcomes ..................................................................................................... 10 
6.7 Moderation analysis ...................................................................................... 10 
6.8 Sample Size .................................................................................................. 11 
6.9 Randomisation and Allocation procedure ........................................................ 11 
6.10 Implementation ........................................................................................... 12 
6.12 Patient withdrawal ...................................................................................... 12 
6.13 Blinding ...................................................................................................... 12 
6.14 Statistical Analysis ....................................................................................... 12 
7. 
ETHICS .......................................................................................................................... 14 
7.1 Informed consent .......................................................................................... 14 
7.2 Confidentiality .............................................................................................. 14 
7.3 Autonomy ..................................................................................................... 14 
7.4 Beneficence ................................................................................................... 14 
7.5 Non-maleficence ............................................................................................ 14 
7.6 Justice .......................................................................................................... 15 
7.7 Data Consistency ........................................................................................... 15 
7.8 Quality Control and Assurance ...................................................................... 15 
7.9 Trial Sponsorship and Financing .................................................................... 15 
7.10 Indemnity ................................................................................................... 15 
8. APPENDIX ......................................................................................................................... 17 

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8.1. CRediT (Contribution Roles Taxonomy) ........................................................ 17 
8.2. Sample Size Calculation Code (R Version 4.5.1) .............................................. 18 
9. REFERENCES ................................................................................................................... 20 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

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1. ADMINISTRATIVE INFORMATION 
Trial registration: This trial will be prospectively registered on ClinicalTrials.gov.  
 
Version: 0.10 (September 25, 2025) 
 
Funding: 2021 Primary Health Care Digital Innovations - Medical Research Future Funding 
(MRFF) project grant (ID# 2023373 - 2023).   
 
Authors: Filipe Luis Souzaa, b, Isha Mishraa, b, Rodrigo Rossi Nogueira Rizzoa, b, James 
McAuleya, b  
 
Affiliation: 
aCentre for Pain IMPACT, Neuroscience Research Australia (NeuRA), Sydney, Australia. 
bSchool of Health Sciences, Faculty of Medicine, University of New South Wales, Sydney, 
Australia.  
 
Contributor roles (see Appendix for roles descriptions)  
Conceptualisation: F.L.S. and R.R.N.R. 
Data curation: F.L.S. and R.R.N.R. 
Formal analysis: F.L.S., I.M. and R.R.N.R. 
Funding Acquisition: R.R.N.R. and J.M. 
Investigation: F.L.S., I.M. and R.R.N.R. 
Methodology: F.L.S., R.R.N.R. and J.M. 
Project administration: F.L.S., R.R.N.R. and J.M.  
Supervision: R.R.N.R. and J.M. 
Visualisation: F.L.S., R.R.N.R. and J.M. 
Writing – Original Draft Preparation: F.L.S.  
Writing – Review & Editing: I.M., R.R.N.R. and J.M. 
 
Trial sponsor  
Name: Neuroscience Research Australia (NeuRA) 
E-mail: pain@neura.edu.au 
Phone: +61 02 9399 1121 

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2. ABSTRACT 
Background: Digital health interventions are increasingly recognised as promising tools to 
expand access to care and reduce healthcare costs, particularly for individuals with chronic 
conditions. While randomised controlled trials (RCTs) remain the gold standard for 
evaluating such interventions, few studies have investigated adherence to digital psychosocial 
treatments for chronic pain—despite adherence being a key determinant of both clinical and 
economic outcomes. A key challenge in digital health trials is low adherence, especially in 
behavioural interventions, where participant engagement is central to treatment effectiveness. 
Dropout rates tend to be higher in interventions delivered digitally among individuals with 
chronic conditions. This compromises statistical power and threatens the internal validity of 
RCTs, with dropout rates ranging from 19% to 45%. Strategies such as phone calls may 
improve adherence; however, the evidence remains limited. To address these gaps, we 
embedded a Study Within a Trial (SWAT) into a host RCT to evaluate whether proactive 
phone calls or text messages can improve adherence to a digital psychosocial intervention for 
chronic pain. Methods: This SWAT will be embedded into an ongoing host RCT evaluating 
an 8-week app-based clinical hypnosis intervention for adults with chronic low back pain. 
Participants allocated to the intervention arm of the host trial will be randomly assigned 
(1:1:1 ratio via REDCap) to receive either standard app notifications alone (control), 
notification plus up to two text messages or notifications plus up to two telephone calls from 
the study investigators. Each contact via phone or text will be spaced at least one week apart. 
The primary outcome is the mean number of completed sessions during the 8-week 
intervention period. Secondary outcomes include the proportion of completers, responder 
rates, and dropout rates in the host trial. Outcome assessors and statisticians will remain 
blinded to SWAT allocation. Results: Analyses will compare the mean number of completed 
sessions between groups, with 95% confidence intervals and standard deviation. Secondary 
outcomes will be analysed descriptively and inferentially. Conclusion: Findings from this 
SWAT will provide empirical evidence to inform the design of future RCTs delivered 
digitally for various chronic conditions, particularly regarding the use of telephone support to 
improve adherence. Although no cost-effectiveness analysis will be conducted, the results can 
help researchers weigh the operational costs of implementing phone-based support against 
the expected benefits in adherence when planning future trials. 
 
 
 
 
 
 
 
 
 
 
Keywords: SWAT; Study Within A Trial; Adherence methods; Embedded Randomised 
Controlled Trial 

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3. BACKGROUND 
Digital health interventions are increasingly recognised as promising tools for improving 
access to care and reducing healthcare costs, particularly for patients with chronic conditions 
(Steinhubl et al., 2013). To evaluate the effectiveness of such interventions, randomised 
controlled trials (RCTs) are considered the gold standard (Hariton & Locascio, 2018). 
However, for people living with chronic pain, there is a lack of high-quality RCTs assessing 
the effects of digital psychosocial interventions, either on pain reduction or healthcare cost 
mitigation (Rosser et al., 2023). Despite known challenges, digital tools continue to show 
promise in advancing healthcare across multiple domains. 
A persistent issue in RCTs investigating digital health interventions is low adherence. This 
problem is exacerbated in non-pharmacological or behavioural interventions, where 
individual behaviour change is a critical mechanism for treatment effect. These trials tend to 
show higher dropout rates (Middleton et al., 2013; Vancampfort et al., 2024), which increase 
further when interventions are delivered digitally (Hasnan et al., 2022; Forbes et al., 2023; 
Giebel et al., 2023), and particularly among patients with chronic conditions (Macea et al., 
2010; Moshe et al., 2022; Kidman et al., 2024). Still, the scalability and convenience of 
digital delivery have encouraged growing interest from both patients and researchers. 
The internal validity of RCTs is frequently questioned when attrition exceeds 15%, as 
emphasised by critical appraisal tools (Maher et al., 2003; Cashin & McAuley, 2020). High 
dropout rates can compromise statistical power, introduce bias, and lead to the inefficient use 
of research resources. Notably, dropout rates in digital trials range from 19% to 45% (Enock 
et al., 2014; Ivanova et al., 2016; Pham et al., 2016), underscoring the need for strategies to 
boost adherence. 
Multiple factors contribute to low adherence in digital trials, including limited motivation, 
low digital literacy, psychological distress, perceived low benefit, and lack of human support 
(van Gaalen et al., 2022; Moshe et al., 2022). To counteract these, interventions like text 
messaging and phone calls have been tested. Meta-analyses suggest that text messaging 
improves adherence to antiretroviral therapy (Finitsis et al., 2014) and cardiovascular 
medication regimens (Park et al., 2014). Similarly, phone calls have been shown to support 
patients with mental health conditions (Aku et al., 2024), enhance medication adherence 
among cancer patients (Akerley, 2021), and increase engagement with digital treatments 
(Gardner et al., 2022). 
Nevertheless, high-quality evidence on the comparative effectiveness of these strategies in 
digital psychosocial trials remains limited, particularly in chronic pain populations. To 
address this limitation, this paper will embed s Study Within a Trial (SWAT; Treweek et al., 
2018) in a larger RCT, aiming to test whether proactive phone calls, compared to no 
additional support, can enhance adherence to a digital intervention for chronic pain. 
This SWAT evaluates the hypothesis that phone calls will lead to higher treatment adherence 
compared to app notifications alone. These findings may inform future digital health trial 
designs and guide the development of strategies to optimise participant engagement in 
behavioural research. 
 
 
 

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4. OBJECTIVE 
Research question 
Do phone calls or text messages increase adherence compared to app notifications in patients 
receiving a digital health intervention for chronic back pain? 
 
5. HYPOTHESES 
a) We hypothesise that the phone calls, compared to standard app notifications alone, 
will result in greater adherence in the mobile app at the 8-week time point after 
randomisation. 
b) We hypothesise that the text messages, compared to standard app notifications alone, 
will result in greater adherence in the mobile app at the 8-week time point after 
randomisation. 
c) We hypothesise that the phone calls, compared to text message notifications alone, 
will result in greater adherence to the mobile app at the 8-week time point after 
randomisation. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

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6. METHODS 
The study will be reported in accordance with the Guideline for Reporting the Results of 
Randomised Studies Within a Trial (SWATs; Arundel et al., 2024) and the Consolidated 
Standards of Reporting Trials (CONSORT 2025; Hopewell et al., 2025). 
 
6.1 Trial design 
This protocol will be prospectively registered as a randomised controlled trial (RCT) within a 
trial (SWAT) (Treweek et al., 2018), characterised as a type of clinical research in which 
participants are randomised into a group after having been previously randomised into an 
intervention group in a host trial (NOTUS trial). The study will randomly allocate 
participants from the intervention group of the NOTUS Trial into one of three parallel arms in 
a 1:1:1 ratio. 
 
6.2 Participants 
Participants in this SWAT will be individuals who meet the eligibility criteria of the host trial 
and were allocated to the mobile app intervention. Eligible participants are adults (≥18 years 
old) residing in Australia who consult a general practitioner for chronic low back pain (LBP). 
LBP is defined as pain persisting for at least 12 weeks in the region between the 12th rib and 
the buttock crease. Participants must report a mean pain intensity of ≥3/10 on the Numeric 
Rating Scale (NRS) in the past week and at least a moderate level of pain interference with 
normal activities based on question 8 on the SF-36 physical functioning component. 
Additional inclusion criteria include the ability to understand English (both written and audio 
materials), access to a mobile device with at least 300MB available for app download, and a 
stable internet connection.  
 
6.3 Settings 
Participants from the host trial intervention group will receive pain education and clinical 
hypnosis via a mobile app for managing chronic LBP. Only outpatients will be recruited for 
the study. The trial will be coordinated from Neuroscience Research Australia (NeuRA; 
Sydney, AU). The data of interest (i.e., sessions completed) for this SWAT will be monitored 
in real time by our research team via the app platform (Mindset Health - app infrastructure 
provider; Victoria, AU). 
 
6.4 Recruitment 
Participants with chronic LBP will be recruited from general practices using the 
BetterConsult pre-consultation tool in Australia. This digital platform collects patients’ 
demographic and clinical details and summarises this information for GPs during 
consultations. The tool includes a question assessing the patient’s interest in receiving an 
SMS after the consultation, containing information about a clinical trial that evaluates the 
effectiveness of digital health interventions. Individuals who express interest in participating 
will receive, via SMS, details of the study and the Participant Information Statement Form 
(PISF). After 24 hours, participants will be invited to complete an eligibility screening. 
Eligible participants who complete the required questionnaires will provide electronic 

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consent, complete baseline assessments, and then be contacted by an investigator for 
randomisation and allocation. The investigator will guide participants on how to access and 
initiate the digital intervention. 
Participants who are randomised to the NOTUS mobile app will be randomly allocated to one 
of the SWAT study groups (phone calls, SMS or app notifications) (Figure 1):  
 
Figure 1 – ADHERE Trial flowchart based on CONSORT2025. 
 
6.5 Interventions 
a. Control group: Participants will receive the standard app notifications. Reminders 
are automatically sent at 8pm each day. A user can change the time of their reminder 
or turn off reminders in the app. The purpose of the app notifications is to increase 
motivation to complete the app sessions. An example app notification is: Your path to 
pain management is just a session away. Have you listened today? 
b. Phone calls: Participants will receive standard app notifications, and if they do not 
engage with the intervention for more than three consecutive days, they will be 
contacted for adherence with up to two phone calls or voice messages, one week 
apart. The purpose of these calls will be to increase motivation and assess whether 
participants are experiencing any difficulties using the app or completing the sessions. 
We expect the calls to last no longer than five minutes. The phone call will include the 
following communication: Hi [Name], it's [Researcher] from Neuroscience Research 
Australia calling about the NOTUS back pain trial. I saw that you've done a few 
sessions on the NOTUS app - great job! We haven’t seen you in the Relio app lately, 
so I wanted to check in and see if everything is working okay or if you need any help 
with anything. We look forward to seeing you back on the app as you continue 
retraining your pain system. 
c. Text messages: Participants will receive the standard app notifications, and if they do 
not engage with the intervention for more than three consecutive days, they will be 
contacted for adherence with up to two SMS reminders, one week apart. The purpose 

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of these SMS will be to increase motivation and assess whether participants are 
experiencing any difficulties using the app or completing the sessions. The text 
messages will include the following: Hey [Name], this is [Researcher] from 
Neuroscience Research Australia. I saw that you've done a few sessions on the 
NOTUS app - great job! We haven’t seen you in the Relio app lately, so I wanted to 
check in and see if everything is working okay or if you need any help with anything. 
We look forward to seeing you back on the app as you continue retraining your pain 
system. 
 
6.6 Outcomes 
Primary outcome measure 
Number of sessions completed: Mean difference of the number of sessions completed over 
8 weeks between groups. 
This outcome pertains to the number of sessions (new or repeated) that participants 
completed over the 8-week treatment period. Although participants receive a treatment 
consisting of 42 different audio scripts, they are informed immediately after randomisation to 
the mobile app that they may skip sessions or repeat those they find most effective or 
enjoyable. 
 
Secondary outcome measures 
Adherence rate (completer vs. non-completer): Participants will be classified as 
“completers” if they have attended at least 24 sessions (new or repeated) during the 8-week 
treatment period of the host trial. This threshold represents an average of three clinical 
sessions per week over 8 weeks. 
Missing follow-up rate: Participants will be classified as “follow-up completer” when they 
completed all primary, secondary and intermediate measures or as “follow-up missing” when 
they did not complete all primary, secondary and intermediate measures at the 8-week 
follow-up. 
Withdrawal rate: Participants will be classified as “withdrawal” if they formally withdrew 
consent, or as “non-withdrawal” if they remained enrolled in the trial at the 8-week follow-
up. 
Cost-effectiveness: The mean difference in costs and adherence between groups will be used 
to calculate the incremental cost-effectiveness ratio (ICER), representing the average 
additional cost (expressed in Australian dollars - AUD) required to achieve one additional 
completed session. This outcome reflects the economic efficiency of each engagement 
strategy (SMS or phone call) compared to others. 
 
6.7 Moderation analysis 
To explore whether the effect of group allocation on adherence differs across participant 
characteristics, we will conduct moderation analyses using linear regression models. 

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The primary outcome will be the number of sessions completed over 8 weeks. The main 
predictor will be group allocation (e.g., SWAT intervention vs control), and candidate 
moderators will include age, gender, pain intensity, disability, occupational status, digital 
literacy, depression, and anxiety (Fuhr et al., 2018; Gutierrez & Sakulbumrungsil, 2021). 
Each model will include: 
 
• 
Main effects of the group and the moderator 
 
• 
A group × moderator interaction term 
 
6.8 Sample Size 
The objective of the host trial is to recruit a total of 720 patients, providing 90% power, 
αௗ=ௗ0.025 (adjusted for co-primary outcomes), to detect a standardised mean difference 
(SMD) of 0.3 between the (fixed) groups at the primary endpoint at 8 weeks post-
randomisation. Randomised studies within trials commonly do not include a formal statistical 
power calculation (Liu et al., 2018; Bensaaud et al., 2020; Woodford et al., 2020; Coleman et 
al., 2021), as their sample size is determined by the number of participants randomised in the 
host trial. This SWAT will be incorporated into the intervention arm of the NOTUS trial, 
which is currently ongoing. Eligible participants will be continuously recruited as they are 
randomised to the mobile app arm. Not all 360 participants originally projected for this 
intervention will be available for inclusion in this SWAT. Participants will be randomised in a 
1:1:1 ratio to receive either phone calls, SMS or app notifications only (control group).  
Based on consensus after discussing unpublished pilot data, an average difference of 4 
completed sessions between groups was estimated (SD = 8). Although this difference was not 
defined according to a formally established minimal clinically important difference (MCID), 
due to the absence of a known MCID in the literature, the calculated difference and 
variability were based on expertise (Schmidt et al., 2018), providing a solution for the lack of 
prior data in the literature on mobile app interventions for chronic back pain. Thus, a 
between-group difference of four sessions would represent approximately one fewer week of 
app use. Using a significance level of 0.05 and a statistical power of 80%, it is estimated that 
at least 258 participants (86 per arm) would be required to detect this effect (Cohen’s d = 0.5 
or 4 sessions between groups; calculation also available in Appendix, see 8.2 section).  
Given that the projected number of participants to be recruited for the intervention arm of the 
host trial exceeds this value (N = 258), the SWAT is adequately powered to detect the 
hypothesised difference. This effect size (d = 0.5) is typically classified as moderate, 
suggesting that the study is sufficiently powered to detect modest differences in session 
completion rates between groups. The analysis was performed using R (version 4.5.1; see 
Appendix 8.2 details). 
 
6.9 Randomisation and Allocation 
Participants of the host trial will be randomised automatically using block randomisation (4 
to 6 per block) using REDCap. The SWAT randomisation will use "Realtime-randomisation" 
integrated with REDCap. The investigator or research assistant will click the "randomise" 
button on REDCap. REDCap will use the hidden Excel spreadsheet to allocate participants to 
the group code with the pre-built randomisation spreadsheet. At this stage, the investigator or 
research assistant will know the group participant was randomised. For the adherence of the 

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intervention, an investigator will access the REDCap randomisation page and contact 
participants via telephone or SMS. 
 
6.10 Procedure 
In the host trial, participants will be recruited via an automated referral process through 
HealthShare (Sydney, NSW). This external partner organisation sends patients an SMS with 
the trial advertisement after their GP consultation. Participants will access the Participant 
Information Statement Form (PISF), complete the screening and consent forms and baseline 
questionnaires before randomisation. Participants can be randomised into one of two groups 
(factsheet or mobile app) via the REDCap. Participants allocated to the mobile app 
intervention will be automatically randomised to one of the three interventions of the SWAT 
trial via REDCap in a 1:1:1 ratio.  
 
6.12 Patient withdrawal 
Participants have the right to withdraw from the host trial at any time. Participants wishing to 
withdraw will be sent an online withdrawal form in REDCap. If participants in the host trial 
refuse to complete the withdrawal form, research assistants will withdraw participants as 
soon as the intention to withdraw is expressed. The SWAT will not be affected by the number 
of patients who drop out, since this data (number of dropouts) is one of the study outcomes. 
 
6.13 Blinding 
General practitioners and statisticians will be blind to group allocation. Blinding will be 
maintained for the entire duration of the trial until all data have been collected, and data 
analysis and interpretation have been completed. The personnel involved in the daily 
operations of the trial (e.g., research assistants and investigators who will provide possible 
technical support to participants and trial managers) will be unblinded to group allocation and 
will not be involved in the analyses. 
 
6.14 Statistical Analysis 
 Primary outcome: The effectiveness data will be analysed by a statistician blinded to 
group allocation, comparing the mean number of sessions completed by the 
participants in each group over 8 weeks, using R software (version 4.5.1). The 
analysis will follow the intention-to-treat (ITT) principle, including all randomised 
participants for analysis. As this outcome is a count variable and based on pilot data, 
overdispersion is expected to be present in the research.  
 
A negative binomial regression model will be used to compare the mean number of 
sessions completed between the three study arms (Hilbe, 2011). The model will 
include group assignment as a categorical predictor. If relevant baseline covariates 
(e.g., age, baseline motivation) are meaningfully unbalanced across groups, we will 
conduct adjusted analyses including these covariates. Model fit and assumptions will 

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be evaluated, and estimated incidence rate ratios (IRRs) with 95% confidence 
intervals and standard deviation (SD) will be reported. 
 
 Secondary outcome: Binary categorical variables will be analysed using binary 
logistic regression models. These include adherence rate, follow-up completion rate, 
and dropout rate at the 8-week follow-up period. Each model will include the 
intervention group (telephone calls, SMS, or control) as the primary predictor. Odds 
ratios (ORs) and corresponding 95% confidence intervals will be reported to quantify 
the likelihood of each outcome occurring in the intervention arms compared to the 
control group. 
 
The economic evaluation will be conducted from the trialist or provider perspective, 
expressed in AUD. To estimate costs, published guidelines will be followed (Russell 
et al., 2021). Costs will include all resources required to deliver the each of the 
interventions. The costs for the control group will be considered zero, and the costs 
regarding the phone calls and SMS will include expenses related to equipment (e.g. 
mobile phones), computer platforms (e.g. NOTION, San Francisco), staff (e.g. 
research assistant), incentives (e.g. gift cards), and supplies for each group per 
participant. 
 
As performed by previous SWATs (Bracken et al., 2019), the difference in mean costs 
per participant between the groups (incremental costs or ΔC) will be calculated (i.e., 
control – phone calls; control – SMS; phone calls – SMS). The difference in the mean 
adherence (ΔE) between the two groups for each comparison will also be calculated. 
Incremental cost-effectiveness ratios (ICERs) will be determined as ICER = ΔC / ΔE, 
which indicates the additional AUD per extra session completed. If ΔE ≤ 0, the 
intervention will be interpreted as providing no improvement (ΔE = 0) or being less 
effective (ΔE < 0) than the comparator. If ΔE < 0, the intervention will be interpreted 
as performing worse. If there is a difference greater than one, trialists or providers will 
be encouraged to calculate the Net Benefit (NB) considering their willingness-to-pay 
values (λ) per extra session (NB = λ * ΔE – ΔC). A positive NB indicates that the 
intervention is cost-effective at the chosen λ. NB will be calculated for each bootstrap 
replication to generate cost-effectiveness acceptability curves (CEACs) showing the 
probability that each intervention is cost-effective across the range of λ values. 
 
 Moderation analysis: Moderation analyses will be conducted to explore whether the 
effect of group allocation on the number of sessions completed varies according to 
participant characteristics. These analyses will use negative binomial regression 
models including main effects and a group × moderator interaction term. As the study 
is not powered to detect moderation effects, these analyses will be interpreted with 
caution and considered exploratory. The characteristics to be examined will include 
age, gender, pain severity, baseline level of disability and occupational status. 
 
 
 
 
 

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7. ETHICS 
The proposed study will adhere to the ethical principles for conducting research on humans: 
informed consent, confidentiality, autonomy, beneficence, non-maleficence, and justice 
(Bošnjak, 2001) and will be conducted in accordance with Good Clinical Practice (GCP) 
guidelines (NHMRC, 2018). Recruitment will not commence until ethical approval has been 
granted for the project. 
 
7.1 Informed consent 
Participants will be given a participant information sheet outlining the details of the study and 
asked to provide informed consent by signing the informed consent form. 
 
7.2 Confidentiality 
All participants will be provided with a unique identification number. All data will be coded 
with this number so that any data collected will only be identifiable by the code. All analyses 
will be done using de-identified data. Results will be disseminated using group data to ensure 
confidentiality is preserved. The participants’ privacy will be protected according to NeuRA’s 
privacy policy available on https://neura.edu.au/resources/common/COM03-Privacy-Policy-
v2.2.pdf. 
 
7.3 Autonomy 
Participants will take part in the study willingly without being unduly persuaded. Should the 
participants wish to withdraw from the study, they will be allowed to do so without any 
punitive consequences. Participants wishing to withdraw will be sent an online withdrawal 
form in REDCap. Should participants decline to complete the withdrawal form, research 
assistants will withdraw participants once the intention to withdraw is expressed. 
 
7.4 Beneficence 
High-quality systematic reviews of randomised controlled trials have shown that patients 
benefit from interventions aimed at improving their treatment adherence, as this behaviour 
increases their chances of reducing the primary treatment target symptoms (Kim et al., 2025; 
MacLean et al., 2025) 
 
7.5 Non-maleficence 
The treatments in the host trial involve self-management approaches and have a very low 
risk. The responsible investigators will ensure that the study is completed in accordance with 
the guidelines in: 
 
 Australian Clinical Trials Handbook guidance on conducting clinical trials in 
Australia using ‘unapproved’ therapeutic goods (Version 2.2 October 2018). 
 The National Statement on Ethical Conduct in Human Research 2007 (updated 2018). 

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 International Council for Harmonisation (ICH) Guidelines for Good Clinical Practice 
(GCP).  
 
NOTUS/ADHERE SWAT researchers accept responsibility for the accuracy of the 
information provided in this application and ensure that the qualifications and/or experience 
of all members of the NOTUS/ADHERE SWAT research team involved with the project are 
appropriate to their role. NOTUS/ADHERE SWAT researchers will maintain valid ICH-GCP 
certification for the duration of the trial. 
 
7.6 Justice 
Participants will be treated in an unbiased, fair, and just manner, despite their race, gender, 
ethnicity, or socio-economic status. In this study, there will be an equitable distribution of 
clinical resources to all participants at no cost. 
 
7.7 Data Consistency 
Participant data will be self-entered and recorded online directly to REDCap. REDCap is a 
data capture software that ensures the curation of data via the use of standardised data 
collection. REDCap’s electronic capture and pre-defined fields ensure data consistency. 
 
7.8 Quality Control and Assurance 
Any amendments will be submitted to the Health Research Ethics Committee (HREC) and 
the ADHERE SWAT Steering Committee for review prior to implementation as per HREC 
guidelines. 
 
7.9 Trial Sponsorship and Financing 
The trial Sponsor is Neuroscience Research Australia. The host trial is funded by the 2021 
Primary Health Care Digital Innovations Medical Research Future Funding (MRFF) project 
grant (ID# 2023373 - 2023). The costs being covered include: 
 Research staff salaries 
 Adaptation of the intervention into the digital infrastructure  
 Delivery of the mobile app intervention 
 Recruitment and costs (e.g., advertising) 
 Data collection platform 
 
7.10 Indemnity 
We are taking reasonable precautions against harm by having the research team monitor 
adverse events for the duration of the study. All serious adverse events will be reviewed by 
the steering committee within 48 hours. 

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The sponsor, Neuroscience Research Australia, is covered by UniMutual Clinical trials 
Protection insurance to the value of $30M. Neuroscience Research Australia adheres to the 
principles outlined in the Medicines Australia Guidelines for Compensation for Injury 
Resulting from Participation a Company-Sponsored Clinical Trial 
(https://www.medicinesaustralia.com.au). 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

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8. APPENDIX 
8.1. CRediT (Contribution Roles Taxonomy) 
 Conceptualization: Ideas; formulation or evolution of overarching research goals and 
aims; 
 Data Curation: Management activities to annotate (produce metadata), scrub data and 
maintain research data (including software code, where it is necessary for interpreting 
the data itself) for initial use and later reuse; 
 Formal Analysis: Application of statistical, mathematical, computational, or other 
formal techniques to analyse or synthesize study data; 
 Funding Acquisition: Acquisition of the financial support for the project leading to 
this publication; 
 Investigation: Conducting a research and investigation process, specifically 
performing the experiments, or data/evidence collection; 
 Methodology: Development or design of methodology; creation of models; 
 Project Administration: Management and coordination responsibility for the research 
activity planning and execution; 
 Supervision: Oversight and leadership responsibility for the research activity planning 
and execution, including mentorship external to the core team; 
 Visualization: Preparation, creation and/or presentation of the published work, 
specifically visualization/data presentation; 
 Writing – Original Draft Preparation: Creation and/or presentation of the published 
work, specifically writing the initial draft (including substantive translation); and 
 Writing – Review & Editing: Preparation, creation and/or presentation of the 
published work by those from the original research group, specifically critical review, 
commentary or revision – including pre- or post-publication stages. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

ADHERE SWAT Protocol 
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8.2. Sample Size Calculation Code (R Version 4.5.1) 
 
## ===== Pairwise planning with Bonferroni (3-arm RCT) ===== 
## Goal: detect a mean difference of 4 (SD = 8) between any two arms 
## Power = 80%, FWER alpha = 0.05 (two-sided), k = 3 
 
# install.packages("pwr")  # uncomment if needed 
library(pwr) 
## Inputs 
delta       <- 4        # minimal detectable difference 
sd          <- 8        # standard deviation 
power_goal  <- 0.80 
alpha_fwer  <- 0.05 
k           <- 3 
attrition   <- 0      
 
## Bonferroni per-test alpha (3 pairwise comparisons) 
m_pairs         <- k * (k - 1) / 2 
alpha_per_test  <- alpha_fwer / m_pairs 
 
## Effect size for two-sample t-test 
d <- delta / sd  # Cohen's d 
 
## Required sample size per arm (analyzable), using noncentral t 
res <- pwr.t.test(d = d, 
                  sig.level = alpha_per_test, 
                  power = power_goal, 
                  type = "two.sample", 
                  alternative = "two.sided") 

ADHERE SWAT Protocol 
Version 0.10 – Date: 25 September 2025 
 
n_per_arm_analyzable <- ceiling(res$n) 
 
## Optional: adjust for attrition 
n_per_arm_recruit <- ceiling(n_per_arm_analyzable / (1 - attrition)) 
total_recruit     <- n_per_arm_recruit * k 
 
## Report 
cat("Pairwise Bonferroni planning (k=3)\n", 
    "Delta:", delta, "| SD:", sd, "| d:", round(d, 3), "\n", 
    "FWER alpha:", alpha_fwer, "| per-test alpha:", signif(alpha_per_test, 4), "\n", 
    "Power:", power_goal, "\n\n", 
    "Per arm (analyzable):", n_per_arm_analyzable, "\n", 
    "Per arm to recruit (attrition =", attrition, "):", n_per_arm_recruit, "\n", 
    "Total to recruit:", total_recruit, "\n") 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

ADHERE SWAT Protocol 
Version 0.10 – Date: 25 September 2025 
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