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Trial registered on ANZCTR


Registration number
ACTRN12617000722392
Ethics application status
Approved
Date submitted
16/05/2017
Date registered
18/05/2017
Date last updated
13/11/2019
Date data sharing statement initially provided
13/11/2019
Date results information initially provided
13/11/2019
Type of registration
Retrospectively registered

Titles & IDs
Public title
Beverage Choice Decisions (BCD) study
Scientific title
Estimating the impact of an increase in sugar-sweetened beverage (SSB) price and educational messages on adult consumer behaviour
Secondary ID [1] 291947 0
None
Universal Trial Number (UTN)
Trial acronym
BCD Study
Linked study record
None

Health condition
Health condition(s) or problem(s) studied:
Obesity 303293 0
Dental decay 303294 0
Condition category
Condition code
Diet and Nutrition 302722 302722 0 0
Obesity
Oral and Gastrointestinal 302758 302758 0 0
Other diseases of the mouth, teeth, oesophagus, digestive system including liver and colon
Public Health 302759 302759 0 0
Health promotion/education

Intervention/exposure
Study type
Interventional
Description of intervention(s) / exposure
The BCD study uses a discrete choice experiment approach to explore the effect of changing beverage prices and exposure to educational messaging on participants' selection of sugary and non-sugary beverages.

It does not use a traditional allocation of treatment and control groups but rather the experiment allows subsequent modelling of predicted effect at a population level of changes in beverage prices and volumes.

Study participants will complete an online experiment in which they will be given a series of 20 hypothetical non-alcoholic beverage purchasing tasks in a convenience store setting. In each task, participants will choose between seven sugary and non-sugary beverage alternatives (energy drink, plain low-fat milk, flavoured milk, bottled water, regular soft drink, diet soft drink, fruit juice, no beverage) and a no beverage alternative that will be described by attributes of those alternatives (price and volume). Prices and volumes which varied between scenarios with four generic volume levels (200mL, 330mL, 460mL, 600mL) and four alternative-specific price levels as follows:

Energy drink: $2.00, $3.30, $4.60, $5.90
Plain low-fat milk: $1.00, $2.30, $3.70, $5.00
Flavoured milk: $2.00, $3.50, $5.00, $6.50
Bottled water: $1.00, $2.30, $3.70, $5.00
Regular soft drink: $2.00, $3.50, $5.00, $6.50
Diet soft drink: $2.00, $3.50, $5.00, $6.50
Fruit juice: $2.00, $3.30, $4.60, $5.90

As this is not a traditional trial, a total of 160 choice scenarios were generated using NGene software to minimize the correlation between displayed prices and volumes (in order to isolate the effect of changing each). Each participant was randomly allocated to complete one of eight blocks of 20 choice scenarios.

The responses from participants will be incorporated into a discrete choice model, which will then allow generation of the predicted impact of hypothetical beverage price changes on population purchases of sugary and non-sugary beverages.

Approximately half of participants will also be shown an educational message discouraging sugary drink consumption, prior to completing the choice scenarios, from the rethinksugary drink campaign (Copyright held by Cancer Council Victoria). The graphic message describes the sugar content of a selection of common SSBs accompanied by the message "you wouldn't eat 16 teaspoons of sugar". The message will be displayed on the screen within the online experiment for 5 seconds.
Intervention code [1] 298072 0
Behaviour
Comparator / control treatment
This is not a traditional RCT. Therefore while no individual participant can be said to be a 'control', many participants will complete choice scenarios with prices and volumes that approximate usual prices and volumes in real-world convenience stores.

Approximately half of participant will not be exposed to an educational message.

In the modelling of predicted population purchases of beverage under differing pricing scenarios, the 'baseline' scenario will be the mean price and volume of beverages reported to be most recently purchased in convenience stores by participants, without exposure to an educational message.
Control group
Active

Outcomes
Primary outcome [1] 302115 0
Proportion of sample predicted to purchase a sugar sweetened beverage (%) as assessed by predicted probability based on discrete choice models developed using participant responses.
Timepoint [1] 302115 0
Hypothetical scenario generated in predicted probability analysis post discrete choice experiment: 20% price increase on sugar sweetened beverages (without an educational message, at baseline beverage volumes)
Primary outcome [2] 302116 0
Proportion of sample predicted to purchase a sugar sweetened beverage (%) as assessed by predicted probability based on discrete choice models developed using participant responses.
Timepoint [2] 302116 0
Hypothetical scenario generated in predicted probability analysis post discrete choice experiment: At baseline beverage prices and volumes with exposure to an educational message designed to reduce purchases of sugary beverages
Primary outcome [3] 302117 0
Proportion of sample predicted to purchase a sugar sweetened beverage (%) as assessed by predicted probability based on discrete choice models developed using participant responses.
Timepoint [3] 302117 0
Hypothetical scenario generated in predicted probability analysis post discrete choice experiment: Combined 20% price increase on sugar sweetened beverages and exposure to an educational message (at baseline volumes)
Secondary outcome [1] 334846 0
Proportion of sample predicted to purchase a non-sugar sweetened beverage (%) as assessed by predicted probability based on discrete choice models developed using participant responses.
Timepoint [1] 334846 0
Hypothetical scenario generated in predicted probability analysis post discrete choice experiment: 20% price increase on sugar sweetened beverages (without an educational message, at baseline beverage volumes)
Secondary outcome [2] 334847 0
Proportion of sample predicted to purchase a non-sugar sweetened beverage (%) as assessed by predicted probability based on discrete choice models developed using participant responses.
Timepoint [2] 334847 0
Hypothetical scenario generated in predicted probability analysis post discrete choice experiment: At baseline beverage prices and volumes with exposure to an educational message designed to reduce purchases of sugary beverages
Secondary outcome [3] 334848 0
Proportion of sample predicted to purchase a non-sugar sweetened beverage (%) as assessed by predicted probability based on discrete choice models developed using participant responses.
Timepoint [3] 334848 0
Hypothetical scenario generated in predicted probability analysis post discrete choice experiment: Combined 20% price increase on sugar sweetened beverages and exposure to an educational message (at baseline volumes)

Eligibility
Key inclusion criteria
Income, gender and age quotas will be applied, These are representative of the Australian age and gender distribution in the following age categories (according to the 2011 Australian census): 18-29 years, 30-44 years, 45-59 years, 60-74 years, 75+ years. 650 from each household income group of low (<$44,000), middle ($44,000- $94,000), high (>$94,000).
Minimum age
18 Years
Maximum age
No limit
Sex
Both males and females
Can healthy volunteers participate?
Yes
Key exclusion criteria
Those under 18years will be excluded as this study is interested in adult SSB purchasing behaviour.

Study design
Purpose of the study
Prevention
Allocation to intervention
Randomised controlled trial
Procedure for enrolling a subject and allocating the treatment (allocation concealment procedures)
Central randomisation by computer to one of 16 choice scenario blocks (8 blocks for each of the sub-samples who were and were not exposed to the educational message)
Methods used to generate the sequence in which subjects will be randomised (sequence generation)
Simple randomisation using a randomisation table created by computer software.
The sequence generation for the combination of prices and volumes per block was developed using NGene experimental design software [version 1.1.2, Choice Metrics, Australia]. An orthogonal simultaneous design was developed which minimises the correlation between the coefficients of different alternative (price and volume) levels. Simple randomisation using a randomisation table created by computer software was used to determine the order in which participants within each block saw the difference choice scenarios (each participant saw the scenarios in a unique order).
Masking / blinding
Blinded (masking used)
Who is / are masked / blinded?
The people receiving the treatment/s
The people administering the treatment/s
The people assessing the outcomes
Intervention assignment
Other
Other design features
As described above, no individual participant can be said to be allocated to an intervention or control group. Across the 20 choice sets that each participant completes, they will see a range of prices and volumes of beverages, some of which will be higher and some lower than baseline or 'real-world' prices and volumes.
Phase
Not Applicable
Type of endpoint/s
Efficacy
Statistical methods / analysis
Discrete choice models will be estimated using random utility theory. Observed heterogeneity and scale will be explored via the inclusion of respondent characteristics with unobserved preference and scale heterogeneity (SE) explored using mixed logit, logit-het, latent class analysis and/or GMNL models. Tradeoffs respondents are prepared to make across attributes will be investigated via the calculation of the marginal rates of substitution. Predicted probability analysis will be undertaken to explore predicted beverage purchases. This will be used to explore a number of policy relevant scenarios including testing various tax rates (e.g. 10%, 20%, 30% SSB price increase and 10%, 20%, 30% non-SSB price decrease, combined SSB price increases and non-SSB price decreases, and the effect of educational messages and their impact on predicted purchases of SSBs and non-SSBs. Predicted purchase results will be used to calculate own and cross price elasticities. Heterogeneity in such results will be explored over key characteristics of consumers such as income, gender, age and baseline SSB consumption.

Recruitment
Recruitment status
Completed
Date of first participant enrolment
Anticipated
Actual
Date of last participant enrolment
Anticipated
Actual
Date of last data collection
Anticipated
Actual
Sample size
Target
Accrual to date
Final
Recruitment in Australia
Recruitment state(s)
ACT,NSW,NT,QLD,SA,TAS,WA,VIC

Funding & Sponsors
Funding source category [1] 296459 0
University
Name [1] 296459 0
Monash Business School Interdisciplinary Grant, Monash University
Country [1] 296459 0
Australia
Primary sponsor type
Individual
Name
A/Prof Emily Lancsar
Address
Centre for Health Economics
Monash University
Building 75, 15 Innovation Walk
Monash University
Clayton, Victoria
Australia 3800
Country
Australia
Secondary sponsor category [1] 295415 0
Individual
Name [1] 295415 0
Dr Kathryn Backholer
Address [1] 295415 0
Deakin University
Centre for Population Health Research Deakin University
School of Health & Soc. Dev., Faculty of Health
Locked Bag 20000, Geelong, VIC 3220
Country [1] 295415 0
Australia
Secondary sponsor category [2] 295425 0
Individual
Name [2] 295425 0
Prof Anna Peeters
Address [2] 295425 0
Deakin University
Centre for Population Health Research Deakin University
School of Health & Soc. Dev., Faculty of Health
Locked Bag 20000, Geelong, VIC 3220
Country [2] 295425 0
Australia
Other collaborator category [1] 279572 0
Individual
Name [1] 279572 0
Miranda Blake
Address [1] 279572 0
Department of Epidemiology and Preventive Medicine
Monash University
553 St Kilda Rd
Melbourne VIC 3004
Country [1] 279572 0
Australia

Ethics approval
Ethics application status
Approved
Ethics committee name [1] 297684 0
Monash University Human Research Ethics Committee
Ethics committee address [1] 297684 0
Monash University, Room 111, Chancellery Building E
24 Sports Walk, Clayton Campus, Wellington Rd
Clayton VIC 3800, Australia
Ethics committee country [1] 297684 0
Australia
Date submitted for ethics approval [1] 297684 0
Approval date [1] 297684 0
05/11/2015
Ethics approval number [1] 297684 0
CF15/4153 - 2015001760
Ethics committee name [2] 297693 0
Deakin University Human Research Ethics Committee (DUHREC)
Ethics committee address [2] 297693 0
Deakin Research Integrity
Burwood Campus
Postal: 221 Burwood Highway
Burwood Victoria 3125 Australia
Ethics committee country [2] 297693 0
Australia
Date submitted for ethics approval [2] 297693 0
Approval date [2] 297693 0
06/02/2017
Ethics approval number [2] 297693 0
2017-035

Summary
Brief summary
Consumption of sugar sweetened beverages (SSBs) such as softdrinks, cordials, flavoured milks and sports drinks is linked to increased risk of becoming overweight or obese and developing Type 2 Diabetes and dental decay. Increasing sugar sweetened beverage prices by taxing them and discouraging people from buying them using educational messages have both been proposed as strategies to discourage consumption. This study aims to explore the characteristics of beverages that people consider when deciding which beverage to buy. It will also examine preferences for different educational messages and pricing changes designed to reduce purchasing of sugar sweetened beverages. In this Discrete Choice Experiment (DCE) participants will be asked to choose between different beverage options with variable prices, volumes and under different conditions including after seeing an educational message. We hypothesise that increasing the price of sugary drinks and showing participants an educational poster about the negative health effects of sugary drinks will both decrease the likelihood participants will select a sugary drink. The results will be relevant to government and policy makers, by helping them to understand which types and size of pricing strategies are useful in reducing sugar sweetened beverage consumption in different groups of consumers, for example those with low and high incomes.
Trial website
Trial related presentations / publications
Public notes
This research was funded by a Monash University Faculty of Business and Economics Interdisciplinary Grant. MB is supported by an Australian Government Research Training Program Scholarship and a Monash University Departmental Scholarship. KB is supported by a post-doctoral fellowship from the National Heart Foundation of Australia (PH 12 M 6824). AP is supported by a National Health and Medical Research Council (NHMRC) fellowship. EL is supported by an Australian Research Council (ARC) fellowship (DE140101260).

Contacts
Principal investigator
Name 74814 0
A/Prof Emily Lancasr
Address 74814 0
Centre for Health Economics
Building 75, 15 Innovation Walk
Monash University
Clayton, Victoria
Australia 3800
Country 74814 0
Australia
Phone 74814 0
+61 3 99050759
Fax 74814 0
Email 74814 0
Contact person for public queries
Name 74815 0
Dr Miranda Blake
Address 74815 0
Deakin University
221 Burwood Highway, Burwood, VIC 3125
Australia
Country 74815 0
Australia
Phone 74815 0
+61 3 9246 8487
Fax 74815 0
Email 74815 0
Contact person for scientific queries
Name 74816 0
Dr Miranda Blake
Address 74816 0
Deakin University
221 Burwood Highway, Burwood, VIC 3125
Australia
Country 74816 0
Australia
Phone 74816 0
+61 3 9246 8487
Fax 74816 0
Email 74816 0

Data sharing statement
Will individual participant data (IPD) for this trial be available (including data dictionaries)?
No
No/undecided IPD sharing reason/comment


What supporting documents are/will be available?

No Supporting Document Provided



Results publications and other study-related documents

Documents added manually
TypeIs Peer Reviewed?DOICitations or Other DetailsAttachment
Study results articleYes Blake MR, Lancsar E, Peeters A, Backholer K. Sugar... [More Details]
Study results articleYes Blake, M. R., Lancsar, E., Peeters, A., & Backhole... [More Details]

Documents added automatically
No additional documents have been identified.