COVID-19 studies are our top priority.

For new and updated trial submissions, we are processing trials as quickly as possible and appreciate your patience. We recommend submitting your trial for registration at the same time as ethics submission.

The safety and scientific validity of this study is the responsibility of the study sponsor and investigators. Listing a study does not mean it has been endorsed by the ANZCTR. Before participating in a study, talk to your health care provider and refer to this information for consumers
Trial registered on ANZCTR


Registration number
ACTRN12619000906156
Ethics application status
Approved
Date submitted
18/06/2019
Date registered
27/06/2019
Date last updated
3/10/2019
Date data sharing statement initially provided
27/06/2019
Type of registration
Prospectively registered

Titles & IDs
Public title
The effect of weight stigma and the polycystic ovary syndrome (PCOS) disease label and causal explanations on intention to eat healthier and perceived personal control over weight: A randomised online study in reproductive aged women
Scientific title
The effect of weight stigma and the polycystic ovary syndrome (PCOS) disease label and causal explanations on intention to eat healthier and perceived personal control over weight: A randomised online study in reproductive aged women
Secondary ID [1] 297303 0
None
Universal Trial Number (UTN)
Trial acronym
Linked study record

Health condition
Health condition(s) or problem(s) studied:
Polycystic Ovary Syndrome 311393 0
Overweight/obesity 311394 0
Condition category
Condition code
Reproductive Health and Childbirth 310026 310026 0 0
Other reproductive health and childbirth disorders
Diet and Nutrition 310027 310027 0 0
Obesity
Renal and Urogenital 311869 311869 0 0
Other renal and urogenital disorders
Metabolic and Endocrine 311870 311870 0 0
Other endocrine disorders

Intervention/exposure
Study type
Interventional
Description of intervention(s) / exposure
The intervention at Time 1 will be delivered as a hypothetical scenario online using Qualtrics survey software and will take approximately 15-20 minutes to complete.

Intervention materials: A hypothetical scenario of a doctor's visit - female, reproductive aged participants will be asked to imagine they have been putting on weight easily and finding it hard to lose it, having irregular periods and more pimples than usual, and they go to their doctor to see if there is anything to be concerned about.

The first independent variable is label given ("you are experiencing these symptoms because you have PCOS" vs. "you are experiencing these symptoms because of your weight") and the second independent variable is the explanation given ("genes (DNA) play a major role" vs. "diet and other health behaviours play a major role")

Participants will be randomised to receive one of four hypothetical scenarios.
1) PCOS label + genetic explanation
2) Weight label + genetic explanation
3) PCOS label + environmental explanation
4) Weight label + environmental explanation

The full intervention reads:

Imagine that for the past year you have been putting on weight easily and finding it hard to lose it. You have also noticed that your periods have become quite irregular and you have had more pimples than usual. You visit your general practitioner (GP) to see if there is anything to be concerned about.

Your GP asks about your symptoms, measures your height and weight, and says… “I think you are experiencing these symptoms because [of your weight/you have Polycystic Ovary Syndrome (PCOS)].” -1st IV

“This is likely due to a mix of factors. However, we now know from recent research that [genes (DNA)/diet and other health behaviours] -2nd IV- play a major role.”

Your GP further explains… “[Being above your healthy weight range/Having PCOS] increases your risk of high blood pressure, reduced fertility and type II diabetes.

You ask your GP what you should do. “Well… guidelines recommend making healthy lifestyle changes to try to lose weight and reduce these risks.”

“I would suggest the first step is to focus on your diet to try to lose weight. This includes eating more fruit and vegetables and less foods high in sugar and saturated fats. For example, less sugary drinks, cakes and pastries, cereals, fatty meat and cream.”

“If this doesn’t work, we can then try a medication to help you lose weight. But first, focus on your diet”
Intervention code [1] 313556 0
Behaviour
Comparator / control treatment
Active control: no PCOS diagnosis, weight advice alone
Control group
Active

Outcomes
Primary outcome [1] 319663 0
Intention to eat healthier measured using three items (adapted from Verhoeven et al., 2013, scale 1 = totally disagree to 7 = totally agree). "Please rate the extent to which you agree with the following statements, keeping in mind the scenario you read. As a result of what my GP has said…"
- I intend to eat a healthier diet
- I plan to eat a healthier diet
- I want to eat a healthier diet
Timepoint [1] 319663 0
Immediately after participants have read their respective hypothetical scenarios of the doctors visit at Time 1.
Primary outcome [2] 319664 0
Perceived personal control over weight measured using three items (adapted from Lebowitz & Appelbaum, 2017, scale 1 = completely disagree to 7 = completely agree). "Again thinking about what your GP has told you, please rate the extent to which you agree with the following statements."
- There are things I can do to overcome my weight
- I have control over my weight
- I have the ability to lose weight
Timepoint [2] 319664 0
After participants have read their respective hypothetical scenarios of the doctors visit at Time 1.
Secondary outcome [1] 369072 0
Weight stigma measured using three items as used by Major et al., 2014 (scale from 1 = strongly disagree to 7 = strongly agree). "Keeping in mind how you would feel in this situation, please rate the extent to which you agree with the following statements."
- I am concerned that I will not be treated fairly because of my weight
- I am concerned that others will reject me because of my weight
- When interacting with people, I am concerned that their opinion of me will be based on my weight
Timepoint [1] 369072 0
After participants have read their respective hypothetical scenarios of the doctors visit at Time 1.
Secondary outcome [2] 369073 0
Blameworthiness measured using a single item "Imagining you were in this situation, how much would you blame yourself for your weight?" (scale 1 = not at all to 9 = very much, adapted from Lebowitz & Appelbaum, 2017).
Timepoint [2] 369073 0
After participants have read their respective hypothetical scenarios of the doctors visit at Time 1.
Secondary outcome [3] 369074 0
Worry measured using a single item, "imagining you were in this situation... on a scale from 1 to 7, how much would you worry about your weight?" (scale from 1 = not at all to 7 = very much, adapted from Scherer et al., 2017).
Timepoint [3] 369074 0
After participants have read their respective hypothetical scenarios of the doctors visit at Time 1.
Secondary outcome [4] 369075 0
Perceived severity measured using a single item "Thinking about what your GP has said, please rate how much you agree or disagree with the following statement. I feel that my weight is a serious problem for me to have." (Adapted from Copp et al., 2017, scale from 1 = strongly disagree to 7 = strongly agree)
Timepoint [4] 369075 0
After participants have read their respective hypothetical scenarios of the doctors visit at Time 1.
Secondary outcome [5] 369076 0
Eight items adapted from the Brief Illness Perception questionnaire (Broadbent et al., 2006) used to measure cognitive and emotional representations of illness on a scale where 0 = lowest and 10 = highest for each question.
"Imagining you have just had this conversation with your GP..."
- How much do you think your weight would affect your life?
- How long do you think your weight would stay at this level?
- How much control do you feel you would have over your weight?
- How much do you think diet could help you to lose weight?
- How much do you think medicine could help you to lose weight?
- How concerned would you be about your weight?
- How well do you feel you understand your weight problem?
- How much would your weight affect you emotionally? (e.g. would it make you angry, scared, upset or depressed?)
Timepoint [5] 369076 0
After participants have read their respective hypothetical scenarios of the doctors visit at Time 1.
Secondary outcome [6] 369077 0
Belief diet will reduce risks measured using four items on a scale of 1 = strongly disagree to 6 = strongly agree. "Thinking about what your GP has said, to what extent would you agree with the following... A healthy diet will reduce my risk of..."
- High blood pressure
- Type 2 diabetes
- Weight gain
- Infertility
Timepoint [6] 369077 0
After participants have read their respective hypothetical scenarios of the doctors visit at Time 1.
Secondary outcome [7] 369078 0
Self-esteem, measured using the validated Rosenberg self-esteem scale (Strongly disagree to Strongly agree) (Rosenberg, 1965).
Timepoint [7] 369078 0
After participants have read their respective hypothetical scenarios of the doctors visit at Time 1.
Secondary outcome [8] 369079 0
Hypothetical lunch choice measured using a single item with 6 response options, as measured by Ahn & Lebowitz, 2018. "Imagine you are pre-ordering your lunch for a day-long meeting tomorrow and the following six meals are your options. Please select what you would order."
o Chicken Caesar salad wrap
o Pasta bake with three cheeses
o Cheeseburger
o Meatloaf with mashed potato
o Salad with grilled chicken
o Roasted turkey and avocado sandwich
Timepoint [8] 369079 0
After participants have read their respective hypothetical scenarios of the doctors visit at Time 1.

Eligibility
Key inclusion criteria
Participants will be Australian women aged 18-45 years with an adequate understanding of English and currently living in Australia.
Minimum age
18 Years
Maximum age
45 Years
Gender
Females
Can healthy volunteers participate?
Yes
Key exclusion criteria
n/a

Study design
Purpose of the study
Educational / counselling / training
Allocation to intervention
Randomised controlled trial
Procedure for enrolling a subject and allocating the treatment (allocation concealment procedures)
Participants were sent an email link to access the Qualtrics survey by the researcher. The link directed participants to complete the online consent form. After completing the consent form participants were then randomised to one of the four hypothetical scenarios using Qualtrics survey software. The recruiting researcher was unaware of which condition participants would be randomised to, as randomisation occurred after participants had clicked on the link to complete the online intervention
Methods used to generate the sequence in which subjects will be randomised (sequence generation)
Participants were randomised automatically using the Randomizer function included in Qualtrics, which utilises the Mersenne Twister pseudorandom number generator.
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
Factorial
Other design features
Phase
Not Applicable
Type of endpoint(s)
Efficacy
Statistical methods / analysis
Sample size was calculated based on the primary outcome of intention, with anticipated effect sizes estimated from Copp et al (2017) and Verhoeven et al (2014), assuming a between-subject standard deviation of 1.48 units for intention ratings and an alpha level for significance of 0.05. A total of 280 participants randomised equally to the 4 groups (i.e., n = 70 per group) will provide 80% power to detect main effects of differences between labels (PCOS vs weight), and between explanations (genetic vs environmental) as small as 1/3 SDs (corresponding to small effect sizes of f=0.17). Small interaction effect sizes (as low asf=0.19) will also be detectable with > 85% power with a sample of this size. More than 90% power will also be afforded to detect main effects for perceived personal control (expected between-subject SD = 1.014, from Lebowitz & Appelbaum, 2017) between labels, and explanations, of 0.47 SDs (f = 0.25).

To test differences in outcomes between the four experimental conditions, we will use a two-way Analysis of Variance (ANOVA) using Statistical Package for the Social Sciences (SPSS) version 22.0, with an alpha level of .05 set for all statistical tests.

Recruitment
Recruitment status
Suspended
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] 301865 0
Government body
Name [1] 301865 0
National Health and Medical Research Council Program
Address [1] 301865 0
Level 1
16 Marcus Clarke Street
Canberra City
ACT 2600
Country [1] 301865 0
Australia
Primary sponsor type
University
Name
School of Public Health, University of Sydney
Address
Edward Ford Building (A27)
The University of Sydney
NSW 2006
Country
Australia
Secondary sponsor category [1] 303051 0
None
Name [1] 303051 0
Address [1] 303051 0
Country [1] 303051 0

Ethics approval
Ethics application status
Approved
Ethics committee name [1] 302559 0
The University of Sydney Human Research Ethics Committee
Ethics committee address [1] 302559 0
Human Ethics Office
Margaret Telfer Building (K07)
University of Sydney
NSW 2006
Ethics committee country [1] 302559 0
Australia
Date submitted for ethics approval [1] 302559 0
28/03/2019
Approval date [1] 302559 0
24/05/2019
Ethics approval number [1] 302559 0
2019/296

Summary
Brief summary
It is unknown whether knowing a diagnosis of PCOS encourages women to engage in recommended preventative activities for associated long-term implications, such as a healthy diet and exercise, and if this is more effective than giving advice regarding weight gain on its own. If genetic explanations for PCOS reduce personal agency/self-control and induce doubt about the effectiveness of non-biomedical treatments (lifestyle), this could have significant negative consequences. It is vital the potential impact of a PCOS diagnosis on lifestyle behaviours is explored. The aim of this study are threefold:
- What is the effect of the PCOS label on intention to eat healthier compared to a weight label?
- How does the PCOS label influence perceived personal control of weight compared to a weight label?
- Does this differ depending on whether an environmental or genetic explanation is given?
Trial website
Trial related presentations / publications
Public notes

Contacts
Principal investigator
Name 90650 0
A/Prof Jesse Jansen
Address 90650 0
126a Edward Ford Building (A27)
The University of Sydney
NSW 2006
Country 90650 0
Australia
Phone 90650 0
+61 02 9351 5178
Fax 90650 0
Email 90650 0
jesse.jansen@sydney.edu.au
Contact person for public queries
Name 90651 0
Mrs Jenna Smith
Address 90651 0
Room 128C Edward Ford Building (A27)
The University of Sydney
NSW 2006
Country 90651 0
Australia
Phone 90651 0
+61 02 8627 0095
Fax 90651 0
Email 90651 0
jenna.smith@sydney.edu.au
Contact person for scientific queries
Name 90652 0
Mrs Jenna Smith
Address 90652 0
Room 128C Edward Ford Building (A27)
The University of Sydney
NSW 2006
Country 90652 0
Australia
Phone 90652 0
+61 02 8627 0095
Fax 90652 0
Email 90652 0
jenna.smith@sydney.edu.au

Data sharing statement
Will individual participant data (IPD) for this trial be available (including data dictionaries)?
Yes
What data in particular will be shared?
All individual participant data collected during the trial can be made available in de-identified csv or excel datasets, along with the data dictionary.
When will data be available (start and end dates)?
Data will be made available once the manuscript outlining results from the study has been published for up to 5 years after publication.
Available to whom?
Data will be made available upon request to anyone wishing to access it who provides a methodologically sound proposal to the principal investigator.
Available for what types of analyses?
Replication and meta-analysis.
How or where can data be obtained?
Data will be made available upon direct contact with the principal investigator. Contact details of the principal investigator are: jesse.jansen@sydney.edu.au
What supporting documents are/will be available?
No other documents available
Summary results
No Results