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This guidance aims to help staff and students determine whether they need to be collecting diversity monitoring data and provides recommended question structures based on best practice in the sector.
This guidance was approved by UCL’s Equality, Diversity and Inclusion Committee (EDIC) in February 2024.
Contents
1. Purpose of data collection
2. Definition of personal data
3. Design of data collection
4. General Data Protection Regulation (GDPR) Principles
Accuracy: Take ‘reasonable measures’ to have the most accurate data possible
Data minimisation: Only gather and keep the exact amount of data that is needed
Purpose limitation: Only process personal data for the purpose it was intended for
5. Example question structures
General good practice
Age
Disability and long-term health conditions
Ethnicity
Gender
Gender identity
Sexual orientation
Caring responsibilities
Religion or belief
Marriage and civil partnerships
Socio-economic background
1. Purpose of data collection
Collecting diversity monitoring data can play a vital role in identifying inequalities and implementing initiatives to address them. The collection of diversity monitoring data may also be required for academic research, student projects or internal university projects like staff and student surveys.
2. Definition of personal data
As outlined in the Data Protection Act 2018, personal data is any information relating to an identified or identifiable living person (known as a ‘data subject’). This includes special category personal data such as: personal data about an individual’s race; ethnic origin; sexual orientation; religion or belief; disability; political opinions; trade union membership; genetic data; and/or biometric data.
3. Design of data collection
The design of diversity monitoring questions needs to align with relevant statutory reporting requirements while also ensuring that staff and students can, as far as possible, describe themselves in ways that reflect how they identify. This guidance is drawn from best practice in the sector, such as Advance HE’s Guidance on the collection of diversity monitoring data, and the Diversity and Inclusion Survey (DAISY) Question guidance designed by the Equality, Diversity and Inclusion in Science and Health and the Wellcome Trust. The guidance has also been developed to align to UCL’s values such as openness and inclusion, and the Higher Education Statistics Agency's (HESA) reporting requirements, and demonstrates our ongoing commitment to the principles of the Transformed Athena Swan Charter and Race Equality Charter.
Please note, this is guidance and is not a definitive position on the gathering of diversity monitoring data, and is subject to periodic review. This guidance acknowledges that it may not be practical or most effective to adopt the same approach to diversity monitoring across all activities. If you have any questions regarding the collection of diversity monitoring data, please contact the EDI Team.
4. General Data Protection Regulation (GDPR) Principles
When determining what data you may need to gather for a specific purpose, it is important to consider the following key principles of the GDPR:
Accuracy: Take ‘reasonable measures’ to have the most accurate data possible
Consider whether the data you are requesting is sufficient to allow for an accurate response from all individuals. For example, asking a question about gender identity, rather than sex, may be better as it more accurately reflects how a survey respondent lives and identifies. Similarly, in certain situations, sex may be the more appropriate information to collect.
Data minimisation: Only gather and keep the exact amount of data that is needed
We should not gather and hold more personal data than is required for a specific purpose. Consider what information is needed to fulfil the specific purpose at hand. If something is ‘nice to have’ but not necessary, do not request it. This can include commonly used categories such as title, job title or grade.
Collecting only the essential data not only respects individuals' privacy but also streamlines the user experience by minimising the information required and the time required to provide this. This ensures that your data collection practices align with the principle of data minimisation.
For example, if you're conduction a survey regarding fitness app usage. This may require only essential data such as fitness brand, usage, GPS info and non-essential data would be asking for title, job and address which is not relevant for this purpose.
Purpose limitation: Only process personal data for the purpose it was intended for
Personal data should only be collected for specified, explicit and legitimate purposes, and not be further processed in a manner that is incompatible with those purposes. You should specify the purpose in your privacy notice. For example, if you collect personal data for doing an analysis for one project, you cannot then use the data for a different, unrelated project.
Please see ‘Understanding Data Protection at UCL’ for further information.
When dealing with sensitive information such as special category personal data, the first question you should ask yourself is whether you need the data at all. For example, collecting certain data, such as someone’s age, sex or gender, is often standard practice when collecting data from people but it may not be relevant or required for the work. On the other hand, it may be important for you to be able to analyse whether there are any differences in the responses by sex or gender, but not for both. Personal data should always be treated with care as there are significant risks that incorrect handling and processing of data can lead to disclosure or discrimination. You should therefore identify what potential risks there are with using sensitive personal data and consider completing a Data Protection Impact Assessment (DPIA) to mitigate potential risks to privacy and compliance with data protection law.
You can find more information on the Data Protection Impact Assessment webpage.
5. Example question structures
The following question structures are based on established best practice and recommendations in the sector. If you want to align your questions to UCL’s HESA data collection, please contact the Workforce Reporting and Analytics Team (staff data) or Student Data Team (student data).
As best practice continues to develop in this area and UCL becomes aware of different perspectives and experiences, our ideas may change – we always welcome feedback or suggestions for updates. These questions have been designed in consultation with UCL stakeholders, including the central EDI Team, Legal Services, Data Protection, UCL’s Pro-Provost (Equity & Inclusion).
General good practice
- If you are using a form or survey, ensure your content is accessible. UCL’s Digital Accessibility Team provides guidance on forms, survey tools and accessibility.
- List your response options in alphabetical order; this can ensure you avoid appearing to prioritise certain responses, e.g., by putting “White English” or “Heterosexual or straight” first. However, options such as “prefer not to say” and “prefer to self-describe” don’t need to be alphabetised and are typically included at the end.
This guidance was last reviewed on 25 March 2024
Age
Considerations
There is not one ‘best’ approach when asking participants for their age. It is therefore recommended that you consider the likely age of respondents and adapt your response categories accordingly.
However, do not make assumptions; for example, that all PhD students are in their 20s, or that everyone in employment is under the age of 65. If you want to compare with existing data, ensure your response categories align with those used in previous data collection or reporting.
Finally, if you require more granular information, or are investigating a specific age group, it could be preferable to ask about an individual’s age or year or date of birth.
Suggested question structure:
How old are you?
- 19 and under
- 20 – 24
- 25 – 29
- 30 – 34
- 35 – 39
- 40 – 44
- 45 – 49
- 50 – 54
- 55 – 59
- 60 – 64
- 65 and over
- Prefer not to say
Disability and long-term health conditions
Considerations
There is no single definition of disability. Defining disability is complicated as it is a complex, dynamic, and multidimensional concept and there are many schools of thought. It is important to recognise that at UCL we follow the Social Model of Disability, which considers how people are disabled by barriers put in place by society, not by an individual’s impairment, health condition or difference. Due to disability being hard to define, respondents are often unsure about how to answer monitoring questions about disability, which leads to inaccuracy, so it is important to ensure you are providing information in the question to help respondents answer as accurately as possible.
For the purposes of data monitoring, UCL is required to collect data for HESA returns that identify people as disabled if they meet the definition of Disability under the Equality Act 2010. When collecting data on disability, it is important to consider what you need the data for. For example, if you need data you collect to align with UCL staff or student disability data, then you should phrase the question in a way which provides information on the definition of disability under the Equality Act 2010 (suggested question 1(a) below). HESA requirements also include a breakdown of disability categories, which UCL also collects information on (suggested question 1(b) below). You should only collect information on disability categories if you need this information for analysis (GDPR data minimisation principle) as these numbers may be small and may risk identifying individuals. It is also important to ensure that people can select multiple categories as individuals may have several types of disabilities.
If, for the purposes of your data collection, you do not need to align your data with UCL’s HESA data, then you may wish to ask the question in an alternative way – one that more accurately reflects the Social Model of Disability. Some examples are provided in questions 2 and 3.
Suggested question structure:
- (a) Do you have a disability that meets the definition under the Equality Act 2010*?
- Yes
- No
- Prefer not to say
*A disability is defined in law as a physical or mental impairment that has a ‘substantial’ and ‘long-term’ negative effect on your ability to do normal daily activities.
Please note, you are automatically considered disabled under the Equality Act 2010 from the point of diagnosis for the following conditions: cancer, multiple sclerosis, HIV, registered as blind or sight impaired, or have a severe, long-term disfigurement.
Visit this link for more information.
(b) Please indicate which of the following applies to you*?
*Multiple answers can be selected
- A learning difference, for example dyslexia, dyspraxia or ADHD
- A mental health condition
- A physical impairment or mobility impairment
- Autism, Autistic Spectrum Disorder, or Asperger's Syndrome
- Blind or a serious visual impairment uncorrected by glasses
- D/deaf, partially deaf, or hard of hearing
- General learning disability such as Down's syndrome
- Long standing illness/condition e.g., cancer, HIV, diabetes, CHD, epilepsy, MS, ME, CFS
- Other disability, impairment or health condition not listed above
- Prefer not to say
2. (a) Do you experience barriers or limitations in your day-to-day activities related to any health conditions (including mental health), physical, sensory, or cognitive differences?
- Yes, substantial barriers or limitations
- Yes, some / small barriers or limitations
- No
(b) If yes, please describe what type of barriers or limitations you face? Please describe these in whatever way works for you, some examples are included below. Please do not include any identifying information.
For example, these might include:
- Altitudinal barriers e.g., discriminatory attitudes; negative or incorrect assumptions
- Physical barriers e.g., no step free access to buildings; physical expectations of participating
- Travel or transportation barriers e.g., lack of accessible transport and accommodation
- Communications barriers e.g., lack of information in different accessible formats, lack of BSL interpretation
- Organisational barriers e.g., length of time and when meetings are scheduled limits participation
- Social barriers e.g., expectations in social interactions
3. Do you identify as Disabled or Neurodivergent person?
- Yes
- No
- Prefer not to say
Ethnicity
Considerations
Ethnic group, cultural heritage and national identity are self-identification measures reflecting how people define themselves. These concepts are not universally defined.
Race is a social construct and will therefore be a product of the social context it is asked in.
Advance HE recommends asking about ‘ethnicity or ethnic background’ which, in the UK, is inclusive of racial (e.g., Black, white) groups. The government and the Office for National Statistics (ONS) now recommend not using the terms BAME (Black, Asian and minority ethnic) and BME (Black and minority ethnic). These terms highlight some groups and not others and are often used inconsistently. While it is important to be precise as we can in the language we use when describing different ethnic groups, be mindful of the expected sample size and the risk of identifying individuals at a more granular level of categorisation.
Response options should be listed alphabetically.
Collecting data solely on ethnicity might omit different experiences and/or inequalities arising from nationality (e.g., experiences of British staff and students might be different from those of international staff and students). You may therefore wish to ask an additional question on nationality.
Suggested question structure:
How would you describe your ethnicity or ethnic background?
- Arab
- Asian - other background
- Asian – Bangladeshi or Bangladeshi British
- Asian – Chinese or Chinese British
- Asian – Indian or Indian British
- Asian – Pakistani or Pakistani British
- Black – African or African British
- Black – Caribbean or Caribbean British
- Black - other background
- Mixed or multiple ethnic groups: White and Asian
- Mixed or multiple ethnic groups: White and Black African
- Mixed or multiple ethnic groups: White and Black Caribbean
- Mixed – Other Mixed or Multiple Ethnic Background
- White
- White – British
- White – Gypsy or Irish Traveller
- White - Irish
- White - Roma
- White - other background
- Not known
- Any other ethnic background
- Prefer not to answer
The question structure is aligned to UCL MyHR values and are UK-centric. We recommend referring to alternative categorisations for international studies and/or research.
Gender
Considerations
There is no legal definition of sex or gender.
The UK government describes sex as a set of biological attributes that is generally limited to male or female, and typically attributed to individuals at birth.
Gender, on the other hand, is a social construct related to behaviours and attributes, and is self-determined based on a person’s internal perception, identification, and experience. Therefore, a person’s gender may not be the same as the registered sex at birth, and it may also change over time.
We should only ask participants about their sex if this is pertinent to the research. Sometimes, questions are asked around sex because the Equality Act 2010 includes sex as a protected characteristic. For this reason, some specific data collection purposes require a dichotomous response of male, female, or prefer not to say. For example, pay gap reporting compares the gap between males and females, or some medical studies may require a question on sex. But if you are not collecting data for these purposes, you should not give dichotomous response options and should provide options typically associated with gender (including, but not limited to, non-binary and an option to self-describe).
Please note, case law suggests that the meaning of sex in the Equality Act 2010 is wider than biological sex, as someone with a Gender Recognition Certificate becomes for all purposes the sex of their acquired gender.
When asking a question about gender, it is best practice to use woman and man rather than male and female, which relate to sex.
If separate questions are asked in relation to sex and gender, then all experiences are being captured and you may be better positioned to demonstrate that the approach being taken is a proportionate means of achieving a legitimate aim as well as allowing more details to be gathered from data.
Trans identity should always be explored as a separate follow-up question, separate from questions relating to sex and gender.
UCL includes a question on sex in equality data monitoring to ensure we fulfil our public duty under the Equality Act 2010, as sex is a protected characteristic. We are also required to return sex data when collecting staff data to be returned to His Majesty’s Revenue and Customs, and when returning staff and student data to the Higher Education Statistics Agency (HESA).
Suggested question structure:
Which of the following best describes your gender?
- Man
- Non-binary
- Woman
- Prefer to self-describe (please describe)
- Prefer not to say
Suggested question structure where asking about sex is pertinent to the research:
What is your sex?
- Female
- Male
- Prefer not to say
Gender identity
Considerations
Under the Equality Act 2010, gender reassignment is a protected characteristic. A person has the protected characteristic of gender reassignment if they are proposing to undergo, are undergoing, or have undergone a process (or part of a process) for the purpose of reassigning their sex by changing physiological or other attributes of sex.
Alternative wording such as gender identity is usually preferred.
Some questions ask people whether their gender identity matches their biological sex. However, unless this is crucial for your data collection, as may be the case within Healthcare Services or certain research studies, we recommend asking people whether they identify as trans as this is generally considered to be a less intrusive question. It is important to approach the collection of gender-related information with sensitivity, respect for privacy, and a clear understanding of the purpose behind the request. Additionally, providing individuals with options such as ‘prefer not to say’ can foster an inclusive and respectful environment. Always ensure that the collection and use of such data align with legal and ethical standards and be transparent about how the information will be handled.
Suggested question structure:
Do you identify as trans or do you have a trans history?
- Yes
- No
- Prefer not to say
Sexual orientation
Considerations
There are multiple dimensions of sexual orientation, including sexual identity, sexual attraction, and sexual behaviour. Research exploring these areas may choose to use different question structures and response options. The suggested question structure provided asks about sexual identity.
Familiarity and acceptability of the term ‘Queer’ has increased within higher and further education through established disciplinary fields such as queer theory, queer studies, and queer history. Although this term has now been reclaimed by many LGBTQ+ individuals, it is still viewed as derogatory by some.
Suggested question structure:
How would you describe your sexual orientation?
- Asexual
- Bisexual
- Gay and/or lesbian
- Heterosexual/straight
- In another way (please describe)
- Prefer not to say
Caring responsibilities
Considerations
The suggested structure includes options for “joint primary carer” as this reflects how some people describe their caring responsibilities. People should be able to tick multiple options. A primary carer is defined as an individual who plays a substantial role in the care for another person, who may or may not have multiple primary carers. ‘Primary’ can thus describe the level of responsibility to care for another person, rather than being the sole carer for that person.
Suggested question structure:
Do you have any caring responsibilities for a child/children and/or another adult/s?
- Yes
- No
- Prefer not to say
If yes, please select all that apply:
- Primary carer of a child or children (under 18)
- Joint primary carer of a child or children (under 18)
- Primary carer of a disabled child or children
- Joint primary carer of a disabled child or children
- Primary carer or assistant for a disabled adult (18 years or over)
- Joint primary carer or assistant for a disabled adult (18 years or over)
- Primary carer or assistant for an older person or people (65 and over)
- Joint primary carer or assistant for an older person or people (65 and over)
- Secondary carer (another person carries out the main caring role)
- I have caring responsibilities but prefer not to specify what these are
- Prefer not to say
Religion or belief
Considerations
Differences in the ways that questions about religion or belief are asked lead to substantial variability in reporting rates. The Equality Challenge Unit (ECU) has recommended the inclusion of ‘Spiritual’, defined as belief in the spiritual dimension of all life, which can be experienced directly and without the assistance of conventional religion.
Suggested question structure:
What is your religion or belief, if any?
- No religion
- Buddhist
- Christian
- Hindu
- Jewish
- Muslim
- Sikh
- Spiritual
- Any other religion or belief (please describe)
- Prefer not to say
Marriage and civil partnerships
Considerations
There is no legal requirement (outside of Northern Ireland) to collect data on marriage and civil partnerships. However, people may be collecting data on marriage and civil partnership to identify any impact of these characteristics.
Suggested question structure:
Are you currently? (Select all that apply)
- Co-habiting or living with a partner
- Married or in a civil partnership
- Separated, divorced or civil partnership dissolved
- Single
- Widowed or a surviving partner from a civil partnership
- Other (please describe)
- Prefer not to say
Socio-economic background
Considerations
Otherwise referred to as ‘social background’, asking questions about socio-economic background (SEB) is complex, and no single question can fully indicate a person’s SEB. It is important that you consider what aspects of SEB are most relevant in your context. A commonly used indicator in widening participation initiatives include students’ parental education. Additional indicators include measures of rates of participation in Higher Education in their local area (TUNDRA and POLAR4) and school type (state or fee-paying). There are different data quality considerations for each indicator. It is important to distinguish that socio-economic background is not a protected characteristic listed in the Equality Act 2010.
Parental education can rely on student recall and may result in a high proportion of refusals. TUNDRA is only available for students whose home address on application was in England, and POLAR4 is not available for students whose home address on application was in Northern Ireland. Where possible, you should ask multiple questions.
Suggested question structure (for the collection of data about undergraduate students):
Do any of your parents* have any higher education qualifications such as a degree, diploma or certification or higher education?
- Yes
- No
- I don’t know
- Prefer not to say
*This includes natural parents, adoptive parents, step-parents or guardians who have raised you.
This question structure is from Advance HE’s ‘Guidance on the collection of diversity monitoring data’
When you applied for your undergraduate studies, what postcode did you apply from?
- My postcode was:
- I can’t remember
- I was not living in the UK when I applied for my undergraduate studies
- Prefer not to say
What type of school(s) did you mainly attend between the ages of 11 and 18 years old?
- State-run or state-funded school in the UK, which was non-selective
- State-run or state-funded school in the UK, which was selective on academic, faith or other grounds
- Independent or fee-paying school in the UK
- Independent or fee-paying school in the UK (assisted or funded place)
- School outside of the UK
- Other (such as home schooled)
- I don’t know
- Prefer not to say
Suggested question structure (for collection of data of workforce socio-economic background):
What was the occupation of your main household earner when you were about aged 14?
• Modern professional & traditional professional occupations such as: teacher, nurse, physiotherapist, social worker, musician, police officer (sergeant or above), software designer, accountant, solicitor, medical practitioner, scientist, civil / mechanical engineer.
• Senior, middle or junior managers or administrators such as: finance manager, chief executive, large business owner, office manager, retail manager, bank manager, restaurant manager, warehouse manager.
• Clerical and intermediate occupations such as: secretary, personal assistant, call centre agent, clerical worker, nursery nurse.
• Technical and craft occupations such as: motor mechanic, plumber, printer, electrician, gardener, train driver.
• Routine, semi-routine manual and service occupations such as: postal worker, machine operative, security guard, caretaker, farm worker, catering assistant, sales assistant, HGV driver, cleaner, porter, packer, labourer, waiter/waitress, bar staff.
• Long-term unemployed (claimed Jobseeker’s Allowance or earlier unemployment benefit for more than a year).
• Small business owners who employed less than 25 people such as: corner shop owners, small plumbing companies, retail shop owner, single restaurant or cafe owner, taxi owner, garage owner.
• Other such as: retired, this question does not apply to me, I don’t know.
• I prefer not to say
What type of school did you attend for the majority of your time between the ages of 11-16?
In the UK
- A state-run or state-funded school in the UK – Non-selective
- A state-run or state-funded school in the UK – Selective on academic, faith or other grounds
- Independent or fee-paying school in the UK – where I received a means-tested bursary covering 90% or more of the total cost of attending throughout my time there
- Independent or fee-paying school in the UK
Outside the UK
- A state-run or state-funded school outside the UK – Non-selective
- A state-run or state-funded school outside the UK – Selective on academic, faith or other grounds
- Independent or fee-paying school outside the UK – where I received a means-tested bursary covering 90% or more of the total cost of attending throughout my time there
- Independent or fee-paying school outside the UK
- I don’t know
- Prefer not to say
If you finished school after 1980, were you eligible for free school meals at any point during your school years?
- Yes
- No
- Not applicable (finished school before 1980 or went to school overseas)
- I don’t know
- Prefer not to say