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Trial registered on ANZCTR
Registration number
ACTRN12625000505404p
Ethics application status
Not yet submitted
Date submitted
23/04/2025
Date registered
22/05/2025
Date last updated
22/05/2025
Date data sharing statement initially provided
22/05/2025
Type of registration
Prospectively registered
Titles & IDs
Public title
Effects of A Sit Less and Move More (SLAMM) App on Sedentary and Physical Activity Behaviours
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Scientific title
Effects of A Mobile App-based Sit Less and Move More (SLAMM) Intervention on Sedentary and Physical Activity Behaviours Among Australian Adults
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Secondary ID [1]
314263
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None
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Universal Trial Number (UTN)
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Trial acronym
SLAMM
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Linked study record
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Health condition
Health condition(s) or problem(s) studied:
Physical Inactivity
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Sedentary Behaviour
337202
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Condition category
Condition code
Public Health
333610
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0
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Other public health
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Intervention/exposure
Study type
Interventional
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Description of intervention(s) / exposure
A single-arm 12-week digital intervention study will be conducted using a mobile application-based behaviour change platform called SLAMM (Sit Less And Move More). The intervention combines real-time activity tracking with context-aware, semi-personalised behavioural support.
Objectives:
To evaluate the feasibility, usability, and preliminary effects of a progressive digital health intervention aimed at reducing sedentary behaviour (SB) and promoting light-to-moderate physical activity (PA).
Aims:
1- To assess changes in sedentary behaviour and physical activity over 12 weeks.
2- To evaluate user perceptions of feasibility, usability, and acceptability of the SLAMM intervention.
3- To explore how personalised and contextually adapted behavioural strategies influence daily movement behaviour (sitting time, active time, exercise time).
Participants:
Participants will be community-dwelling adults who are at high-, medium-high-, medium- or low-medium risk for cardiovascular health. The risk level is determined via a SIT-ACT risk matrix, which considers sedentary hours and physical activity minutes combined.
Intervention Components:
Participants will be classified into movement behaviour levels (Sit Less, Move More, and Exercise) based on their sedentary and activity levels using a risk assessment tool (i.e. the Sit-Act Matrix). Sit Less Group: receives only Sit Less messages. Move More Group: receives both Sit Less and Move More components. Exercise Group: receives all components, including an exercise program. Participants can progress to a higher group (risk level) on a weekly basis based on their behavioural data captured by the mobile app. Messages include:
- Sit Less: Motivational messages to interrupt sitting, adapted to time of day, weather, and work status.
- Move More: Prompts encouraging walking or light movement integrated with daily routines.
- Exercise: Semi-automated coaching with light-to-moderate intensity exercise prescriptions.
Participants will receive up to six messages per day. These messages are designed to prompt behavioural changes and are data-driven, meaning they are triggered by prolonged sitting periods or relevant activity patterns (moving or exercising). Potential time points will include morning, lunchtime, afternoon and evening,
Examples of messages:
Sit Less: “Stuck inside because of bad weather? Stay active indoors by climbing stairs or pacing between rooms.”
Move More: “Been sitting too much? Break up your day with a lunchtime walk with a coworker.”
Exercise: “Swimming for 40 minutes from 7:00 to 7:40 am; the intensity level: moderate [select via app].”
Exercises prescribed to the Exercise Group include activities such as swimming, or cycling, tailored to light-to-moderate intensity. This will be measured using the Borg Rating of Perceived Exertion (RPE) scale.
Adherence:
Adherence to the intervention will be assessed by interaction with the app (logging activities and app screen time). App analytics will thus provide ongoing monitoring of participant engagement and intervention fidelity.
Technology:
Participants will use the SLAMM mobile app, which integrates with Fitbit or a personal activity tracker to collect real-time movement and sedentary data. The app also accesses contextual data (e.g., weather) to deliver adaptive prompts.
Decision Logic:
Messages are dynamically generated based on participant availability, movement levels, contextual factors, and behavioural trends.
Data Collection:
Objective data will include sedentary hours. activity minutes, exercise minutes, self-reported questionnaires and post-intervention interviews will assess usability, satisfaction, and behavioural awareness.
Sample Size:
A total of 38 community-dwelling adults will be recruited to evaluate preliminary effects and feasibility metrics. Results will guide future iterations and a larger-scale randomised trial.
Recruitment Timeframe:
Start Date: Recruitment is expected to commence in mid-July 2025.
End Date: Recruitment will conclude in early July 2026, or once the target sample size of 38 participants is reached, allowing time for replacements if any participant withdraws.
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Intervention code [1]
330876
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Lifestyle
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Comparator / control treatment
No Control Group
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Control group
Uncontrolled
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Outcomes
Primary outcome [1]
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Average daily sedentary time (hours)
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Assessment method [1]
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Activity Tracker
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Timepoint [1]
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Continuous/ everyday for 12 weeks post-intervention commencement
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Primary outcome [2]
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Average daily exercise time (minutes)
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Assessment method [2]
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Activity Tracker
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Timepoint [2]
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Various times during the week for 12 weeks post-intervention commencement (assigned by the participant)
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Primary outcome [3]
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Average daily physical activity time (minutes)
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Assessment method [3]
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Activity Tracker
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Timepoint [3]
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Continuous/ everyday for 12 weeks post-intervention commencement
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Secondary outcome [1]
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Acceptability
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Assessment method [1]
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user satisfaction and perceived usefulness (composite measure) via a one-on-one online interview using a semi-structured questionnaire
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Timepoint [1]
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Post-intervention (week 12)
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Secondary outcome [2]
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Awareness and perception of behaviour change (composite measure)
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Assessment method [2]
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Questionnaire (designed specifically for this study)
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Timepoint [2]
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Post-intervention (week 12)
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Secondary outcome [3]
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Technical issues
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Assessment method [3]
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Number of user-reported issues (user-reported via phone call) Frequency of repeated issues (user-reported via phone call) Type of issue (e.g., app crash, slow load, login failure, sync error; user-reported via phone call)
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Timepoint [3]
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Everyday two weeks post-intervention commencement via phone call
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Secondary outcome [4]
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Usability
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Assessment method [4]
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SUS questionnaire
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Timepoint [4]
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Post-intervention (week 12)
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Secondary outcome [5]
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Participant recruitment rate
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Assessment method [5]
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Participant recruitment log
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Timepoint [5]
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Post-intervention (week 12)
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Secondary outcome [6]
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retention
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Assessment method [6]
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study logs
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Timepoint [6]
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Post-intervention (Week 12)
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Eligibility
Key inclusion criteria
Eligible participants will be Australian adults, aged 20 years or older, own a smartphone (compatible with our app) and currently interact or engage with apps, have no limitation (including physical problems and medical complications) to engage in low-intensity and intensity PA, those who will not be identified to be at low-risk level, having a compatible wearable activity device, can communicate in English, and can provide informed consent.
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Minimum age
18
Years
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Maximum age
No limit
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Sex
Both males and females
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Can healthy volunteers participate?
No
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Key exclusion criteria
Individuals who self-report being highly active (low-risk), as well as those unable or fail to provide informed consent, and refuse to grant permission to access built-in mobile weather app will be excluded from the study.
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Study design
Purpose of the study
Treatment
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Allocation to intervention
Non-randomised trial
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Procedure for enrolling a subject and allocating the treatment (allocation concealment procedures)
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Methods used to generate the sequence in which subjects will be randomised (sequence generation)
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Masking / blinding
Open (masking not used)
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Who is / are masked / blinded?
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Intervention assignment
Single group
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Other design features
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Phase
Not Applicable
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Type of endpoint/s
Efficacy
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Statistical methods / analysis
Descriptive Statistics:
Participant’s baseline data (e.g., age, BMI, baseline sedentary time) will be summarised using descriptive statistics (mean, median, standard deviation, interquartile range).
Longitudinal Analysis:
Mixed-effects models: changes in sedentary time, overall activity time, and exercise time over 12 weeks will be analysed, accounting for repeated measures within individuals. This model can handle missing data and variability in individual trajectories.
Correlation and Mediation Analysis:
Spearman or Pearson Correlation will be used to investigate relationships between sedentary time, overall activity time, exercise time, risk levels, and awareness and perception of change in sedentary behaviour and physical activity (e.g., have you thought more often about sitting less or moving more?).
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Recruitment
Recruitment status
Not yet recruiting
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Date of first participant enrolment
Anticipated
20/06/2025
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Actual
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Date of last participant enrolment
Anticipated
15/12/2025
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Actual
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Date of last data collection
Anticipated
16/03/2026
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Actual
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Sample size
Target
38
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Accrual to date
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Final
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Recruitment in Australia
Recruitment state(s)
ACT,NSW,NT,QLD,SA,TAS,WA,VIC
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Funding & Sponsors
Funding source category [1]
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University
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Name [1]
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Deakin University
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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
Deakin University (Institute for Physical Activity and Nutrition)
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Address
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Country
Australia
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Secondary sponsor category [1]
321228
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None
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Name [1]
321228
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Address [1]
321228
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Country [1]
321228
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Ethics approval
Ethics application status
Not yet submitted
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Ethics committee name [1]
317393
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Deakin University Human Research Ethics Committee (DUHREC)
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Ethics committee address [1]
317393
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https://www.deakin.edu.au/research/support-for-researchers/research-integrity?a=438168
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Ethics committee country [1]
317393
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Australia
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Date submitted for ethics approval [1]
317393
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28/05/2025
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Approval date [1]
317393
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Ethics approval number [1]
317393
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Summary
Brief summary
Prolonged sedentary behaviour (SB) has been linked to serious health conditions, including cardiovascular disease, diabetes, and poor mental health—even in individuals who meet exercise guidelines. Reducing sitting time and incorporating light physical activity, such as walking, into daily routines can significantly improve health outcomes and serve as a foundation for sustained behaviour change. The SLAMM (Sit Less And Move More) intervention uses a mobile app and wearable activity trackers (e.g., Fitbit) to help participants reduce sedentary behaviour and progressively increase physical activity. Based on real-time tracking and self-reported activity, users are classified via a risk assessment matrix (the Sit-Act Matrix) and will then be provided with tailored behavioural messages or semi-personalised exercise coaching. Contextual factors such as weather, time of day, and work schedule are used to adapt prompts dynamically. The study aims to evaluate the feasibility, usability, acceptability and preliminary efficacy of this 12-week intervention. Outcomes include changes in sedentary time, activity levels, and user perceptions, informing future large-scale trials.
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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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Prof Ralph Maddison
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Address
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221 Burwood Highway Burwood Victoria 3125 Institute for Physical Activity and Nutrition Deakin University
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Country
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Australia
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Phone
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+61392446218
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Fax
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Email
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[email protected]
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Contact person for public queries
Name
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Reza Daryabeygikhotbehsara
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Address
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221 Burwood Highway Burwood Victoria 3125 Institute for Physical Activity and Nutrition Deakin University
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Country
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Australia
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Phone
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+61392446108
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Fax
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Email
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[email protected]
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Contact person for scientific queries
Name
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Reza Daryabeygikhotbehsara
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Address
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221 Burwood Highway Burwood Victoria 3125 Institute for Physical Activity and Nutrition Deakin University
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Country
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Australia
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Phone
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+61392446108
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Fax
140916
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Email
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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:
•
Researchers
Conditions for requesting access:
•
Yes, conditions apply:
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Requires approval by an ethics committee
What individual participant data might be shared?
•
De-identified individual participant data:
•
All outcomes data
•
Published results
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Primary outcome(s)
What types of analyses could be done with individual participant data?
•
Systematic reviews and meta-analyses
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Studies exploring new research questions
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Health economic analyses
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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:
A finite period of:
15
years
Where can requests to access individual participant data be made, or data be obtained directly?
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Email of trial custodian, sponsor or committee:
Prof Ralph Maddison (
[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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