“People Need to Know;We’re Part of the Community. We’re Here.”: Examining Experiences of Sharing Demographic Information for a Community-Based Diabetes Prevention Program

Abstract

Background

Collecting demographic data is critical for identifying inequities in healthcare services and delivery. Inaccurate collection of demographic data can make developing equitable health interventions and improving reach of existing interventions difficult. This study aimed to (a) examine experiences in completing a community-based type 2 diabetes prevention program Small Steps for Big Changes (SSBC) demographic questionnaire (SSBC-DQ) among adults from equity-owed groups, and (b) assess recommendations for improvement to the questionnaire.

Methods

Adults with no prior involvement in SSBC were recruited. Participants completed the SSBC-DQ online and then engaged in one-on-one structured interviews. Interview data was analyzed using interpretive description and coded using the APEASE criteria.

Results

Twelve participant interviews were included in analysis. Five principle themes were developed to capture the experiences of completing the SSBC-DQ: representation, comprehension, demographics are an emotional experience, the role that privilege plays, and beliefs about demographic data. Sixty suggested changes were coded using the APEASE criteria; six suggestions met the criteria for implementation, 20 did not meet the criteria, and 34 required further discussion with the research team.

Conclusions

Results from this study illustrate that people’s lived experiences can drive their reactions and interpretations to demographic questionnaires. Based on end-user suggestions, SSBC made changes to its demographic questionnaire to be more inclusive. Having a demographic questionnaire that is more inclusive can help SSBC better understand what populations it is and is not reaching in an acceptable and inclusive manner. This will help inform future directions regarding evaluating program reach and equity.

Keywords

health inequities demographic data equity monitoring accessibility program reach equity-owed populations

Introduction

In Canada, healthcare is not equitably distributed to all individuals. Demographic questionnaires provide valuable information on disparities in health status and access to resources by collecting information on personal characteristics inherent to the individual (i.e., sex, gender, ethnic origin, socioeconomic status etc.).¹ Demographic data is recognized as a critical tool for health equity measurement, however, best practices for collecting this data in healthcare settings are not well understood.^2–4

Healthcare practitioners and policymakers value demographic data for the development of equitable health interventions and improving reach of care^3,4; however, patients are more concerned about the harms of collecting data, including worries about maintaining privacy, fear of discrimination, and concerns about why this data was being collected.^2,4,5 It has been demonstrated that patients of equity-owed groups (i.e., groups who are historically, persistently, and systemically denied equal access, opportunities, and resources due to unearned disadvantage and discrimination) often do not want to disclose demographic information that could result in judgment or stereotyping, and therefore, are more likely to falsify answers or refrain from completing demographic questionnaires.^2,4,5 The dichotomy between healthcare leaders benefiting from demographic data and patients feeling uncomfortable providing this information leads to inaccurate and poorly collected data, reducing the certainty that policy makers and researchers have about what populations are and are not receiving care.

Recognizing the importance of collecting demographic data in an appropriate and respectful manner, British Columbia’s Office of the Human Rights Commissioner published a report to develop a policy framework for the collection of race-based, Indigenous, and other demographic data.¹ This report focuses on building community relationships and making space for the voices of equity-owed groups to be the experts of their own lived experiences. Human Rights Commissioners from across Canada have made a call to action for the development of a national strategy for the collection of demographic data that reduces stigmatization and advances health equity.^1,6–9

Small Steps for Big Changes (SSBC) is an evidence-based, diet and exercise counselling diabetes prevention program (DPP) delivered in communities.^10,11 In its initial years of implementation in community, SSBC’s client population was predominantly White, female and of middle income.¹² This is representative of the population of Kelowna, British Columbia, the initial program location, but is not in line with those most at risk for developing type 2 diabetes (T2D) including individuals of low socioeconomic status, immigrants and individuals of African, South Asian and Indigenous descent.^12,13 Other large scale DPPs which target diet and exercise behavior change have been shown to significantly reduce the risk for T2D; however, they rarely report demographics beyond participant sex, so it is unknown whether these DPPs are reaching the equity-owed groups most at risk for T2D.^14–16 Demographic data collection lacks a standardized approach, whereby the data being collected and reported varies between programs; potentially hindering the transferability of program findings to other communities/populations. Currently, most research on demographic data collection has been conducted in healthcare settings and has not examined end-user experiences or suggestions for improving collection practices, limiting the understanding of best practices for demographic data collection in community-based health programs such as DPPs. The purpose of this study was to (a) examine experiences in completing the SSBC Demographic Questionnaire (SSBC-DQ) among adults from equity-owed groups, and (b) assess recommendations for improvement of the SSBC-DQ.

Methods

Qualitative Paradigms

This study was guided by pragmatism and constructivist paradigms. Pragmatism prioritizes transferability and does not assume that the methods used make results solely context-specific, or generalizable; instead focusing on the applications of findings in real-world settings.¹⁷ A pragmatic paradigm encourages the use of an abductive approach whereby inductive and deductive methods are combined to draw connections between data and theory to better predict the utility of findings.¹⁷ This study employed both inductive methods, through thematic analysis to understand participants’ subjective experiences, and deductive methods, through coding suggestions using the APEASE framework to determine whether each suggestion was appropriate for the SSBC-DQ.

A constructivist worldview is rooted in the belief that individuals create meaning from their lived experiences, and environmental context; therefore, multiple, subjective realities exist.¹⁸ Neither the participants nor the researchers can be separated from their own subjective understandings.²⁰

In line with the theoretical underpinnings of this study, it is important to acknowledge the positionality of the authors.¹⁹ SC is a cis-gender heterosexual woman of White settler-colonial ancestry without disability. JS is a cis-gender woman of White settler-colonial origins. KC is a cis-gender heterosexual woman of both White settler-colonial and Southeast Asian origins. MJ is a second-generation Canadian of Asian and European origins, and identifies as a cis-gender heterosexual woman. All authors recognize that their privilege shapes their research, worldview, and life experiences, and aim to center and amplify voices that are often left out of academia and health. Positionality, biases, experiences and emotions were reflected upon throughout the study process through reflexive journaling and in conversations with the research team – an essential process when generating themes and interpreting meaning.^19–21

Participants

Adults with no prior involvement with SSBC were recruited to participate in the study by social media posts, emails to special interest groups, posters, and word of mouth. Special attention was paid to recruiting individuals from equity-owed groups including persons of colour, 2SLGBTQIA+, Indigenous peoples, and individuals with disabilities. We aimed to recruit a heterogeneous sample across diverse and intersecting demographics to capture a broad range of experiences and to best represent the clients SSBC intends to reach. Participants included in this study were 18 years of age or older, able to read, write, and speak English, currently residing in Canada, and consented to audio recording. Participants received a $30 Amazon e-gift card honorarium as compensation for their study involvement.

Procedures

Participants expressed interest in the study by reaching out to the first author via email. An option was given to participate in-person or virtually via Zoom. Participants were informed of the purpose of the study and potential discussion topics, and provided free, informed consent. First, the SSBC-DQ (Supplemental file 1) was completed in its entirety on Qualtrics, ranging in completion time from 3.1 to 31.8 minutes (mean = 9.95 min, SD = 10.1 min). All participants were given verbal instructions to take their time in completing the questionnaire in its entirety to the best of their abilities. If a participant asked a question while completing the questionnaire the above message was reaffirmed, and no specific advice or answers were provided. The mean completion time is in line with the estimated time of completion of 10 minutes. Participants then engaged in a one-on-one structured interview with SC.

The interview guide (Supplemental file 2) was developed with the goal of understanding participants’ thought processes when completing the SSBC-DQ and to gather suggested changes to the SSBC-DQ. The interview guide was informed by cognitive interviewing methodology, an evidence-based method used to evaluate the mental processing and context in which survey questions are understood and experienced.^22–24 Similar interview methodology has been used to evaluate demographic questionnaires in the United States, United Kingdom, and New Zealand.^25–27 Key questions included participants’ emotional reaction to SSBC-DQ (e.g., ‘Can you describe your level of comfort in answering this question?’); comprehension of the SSBC-DQ (e.g., ‘Were there any parts of the question or responses you did not understand?’); thoughts on the inclusivity of the SSBC-DQ questions (e.g., “Do you think there’s a better response option that could be provided?’); and suggestions on the SSBC-DQ (e.g., “Do you have any thoughts, comments, or suggestions on the questionnaire?”). Interviews ranged in length from 18.9 to 41.0 minutes (Mean = 27.1 min; SD = 7.1 min). Interviews were audio recorded, transcribed verbatim using Otter.AI and checked for accuracy by SC.

Data related to suggestions about the SSBC-DQ was extracted from transcripts for deductive coding using the APEASE (affordability, practicability, effectiveness, acceptability, safety and equity) criteria.²⁸ The APEASE criteria is a widely used^29–32 framework designed to help make informed decisions as to what ideas (e.g., program or intervention components) might be best suited for implementation.²⁸ The use of APEASE aligns with our pragmatic paradigm and our values for equity. We used the APEASE criteria in attempt to pragmatically and respectfully apply participant suggestions to improve the SSBC-DQ. For the purpose of this study, the APEASE criteria was defined as: affordability – the cost of implementing the demographic questionnaire suggestions, including human resources; practicability – participant burden, comprehension and readability; effectiveness – the fit of the suggestions with the aims of the SSBC program; acceptability – the acceptability for SSBC clients, SSBC program, and the scientific community; safety – whether suggestions were supportive of emotional, mental and spiritual well-being of clients; and equity – whether the suggestions would improve or decline questionnaire equity.

Data Analysis

Data was managed using Microsoft Word^TM and Excel^TM. Interpretive description, a theoretically flexible method of analyzing qualitative data to develop practical applications, was utilized for its alignment with pragmatic and constructivist paradigms.^33–36 Congruent with the method of interview, inductive analysis was employed. Analysis moved from specific to general with each individual interview being treated as the unit of analysis to account for the context in which they experienced the SSBC-DQ.^19,33 SC and JS immersed themselves in the data to develop themes, becoming integrated in the generation of knowledge.²⁰ Both researchers engaged in reflexive journaling and critically discussed their findings with each other throughout the analysis.

Initial analysis began with SC and JS each reading the first three interviews to develop initial reflections and create common themes. The initial analysis was consolidated to generate a thematic template, a method found to be beneficial when following interpretive description methodology.^34,37 Interviews were analyzed and consolidated in sets of three and data was compiled into the thematic template. Initial themes and comments were refined throughout in an iterative process. In line with constructivism, themes were not created based on frequency of data, but on the depth of the experience to the overall findings.¹⁸ KC acted as a critical friend and was consulted after analysis of interviews 1-3, 4-6, and again at 7-12 to provide critical suggestions.

Suggested changes to the SSBC-DQ were independently coded using the APEASE criteria by SC, JS, and KC using Excel^TM. Each APEASE criteria was evaluated using the codes yes – met criteria, no – did not meet criteria, and depends – suggestions dependent on the context it would be applied. Disagreements were discussed among the three authors to reach consensus with MJ being consulted when consensus could not be reached. A priori plans for implementation were set as follows: Suggestions that met all APEASE criteria would be immediately incorporated into the SSBC-DQ, suggestions that did not meet at least one APEASE criterion would not be added to the SSBC-DQ, and suggestions with at least one “depends” were to be discussed with the broader SSBC research team, and then re-examined to determine if they did or did not meet criteria.

Results

Participant Characteristics

Twelve participants (n = 12) between 19 and 35 years of age (Mean = 25 years; SD = ±5.9 years) completed the study. Additional demographic information is in Table 1.

Table 1.

Demographic information for participants (n = 12).

Variable	Values n (%)
Sex
Male	5 (41.7)
Female	7 (58.3)
Gender
Female or primarily feminine	6 (50.0)
Male or primarily masculine	6 (50.0)
Ethnic origin
African, Western European	1 (8.3)
East Asian	1 (8.3)
Western European	5 (41.7)
Latin(x), South American	1 (8.3)
South Asian	2 (16.7)
East Asian, Southeast Asian	1 (8.3)
Prefer not to say	1 (8.3)
Visible minority, or person of colour
Yes	6 (50.0)
No	6 (50.0)
Disability
Yes	5 (41.7)
No	5 (41.7)
Prefer not to say	2 (16.7)
Type of disability^a
Communications	1 (20.0)
Learning	1 (20.0)
Mental health related	1 (20.0)
Mobility, mental health related	1 (20.0)
Another option	1 (20.0)
Education level
High school	1 (8.3)
Currently in some university or college	6 (50.0)
College, CEGEP, or non-university certification or diploma	1 (8.3)
University certificate, diploma, or degree	4 (33.3)
Occupation
Only student	4 (38.3)
Student, working part-time	3 (25.0)
Working occasionally/contract work, working part-time	1 (8.3)
Only working full-time	4 (33.3)
Total family income
$0-$29,999	2 (16.7)
$30,000-$59,999	4 (33.3)
$90,000-$119,999	1 (8.3)
$120,000-$149,999	1 (8.3)
Do not know	4 (33.3)
Marital status
Single	9 (75.0)
Married	1 (8.3)
Another option	1 (8.3)
Prefer not to say	1 (8.3)
Tobacco use in past 30 days
Yes	2 (16.7)
No	10 (83.3)

^a% values are out of 5 (the number of people having a disability).

Interpretive Description

Inductive analysis led to the development of five principle themes that illustrate the experiences from completing the SSBC-DQ: (1) Representation, (2) Comprehension, (3) Completing demographic questionnaires is an emotional experience, (4) The role that privilege plays, and (5) Beliefs about demographic data. These themes captured suggestions on the SSBC-DQ that expressed both positive attributes and where there was room for improvement. The principal themes are described below. Participants’ personal characteristics and lived experiences influenced how they experienced the questionnaire; therefore, select demographic information for each participant is presented to add context to the selected quotes (Supplemental file 3). Quotes linked to the principal themes are identified with an anonymous identification number corresponding to the participant (Table 2).

Table 2.

Themes associated with experiences completing the Small Steps for Big Changes Demographic Questionnaire.

Theme	Description	Quote
Representation	Feeling seen in the questionnaire response options. Not only seeing response option that fit given identity, but also autonomy to select multiple options, specify beyond options given, or to choose not to respond.	“I’m racially mixed…in the past, …you could only ever pick one option…I didn’t like just clicking the mixed race because that seemed just like bunching everyone together…so I really like that I get to pick all that apply.” (P2 about ethnic origin)
		“People identify in multivariable ways. I think also like, this route itself in the binary, like, the option neither male nor female...it feels like you’re not in the binaries, or you’re outside of the binary.” (P10 about gender identity)
		“Not very easy…normally it’s either…Latino and Ecuador…I don’t know to what extent there’s a difference between Central America, South America and Latino…I find it somewhat odd that it’s Latino, South American and Latino Central American but there’s no Latino North American…what if a Latin person was born in North America?” (P12 about ethnic origin)
		“I am proud of my ancestry. I’m proud that my parent’s came from China, I don’t necessarily hide the fact” (P8 about visible minority)
Comprehension	The ease of questionnaire completion. Participant’s understanding of what questions were asking, and the meaning of response options provided.	“The first thought I had was usually where you’re born. And then I guess the secondary thought is what culture you most identify with” (P11 about ethnic origin)
		“I fail to realize why like, that racial component of perceptions of race affects diabetes…so if it’s given to me without any context in a questionnaire, I would be…confused as to why I’m being asked that” (P10 about visible minority)
		“I know some people might hesitate whether their vape counts as tobacco. I don’t even know how that works” (P12 about tobacco use)
Emotional experience	Completing a demographic questionnaire elicits a host of emotions all along the positive to negative spectrum.	“You know, who wants to accept that label? Right? Because then it hobbles you or it could potentially hobble you” (P6 about disability)
		“there’s very direct correlations with diabetes within the [South Asian] region and the intergenerational passing down of diabetes…so I feel very comfortable checking it off because I think more stronger connections need to be made with ethnic origins and diabetes.” (P10 about ethnic origin)
Not wanting to ‘mess up'	Negative emotions were particularly strong when there was a feeling that the question could be answered ‘wrong'	“There was hesitation and whether or not I should select that, I didn’t, but I don’t know if it counts” (P7 about disability)
		“I kept having to search each answer and making sure that I was picking the right one.” (P11 about education)
Role that privilege plays	Emotions strongly tied to sociocultural systems of oppression highlighted that the privilege one holds or doesn’t hold influences the emotional experience of completing a demographic questionnaire	“I get a lot of guilt. If I’m saying like, yes, I do have a disability. But it’s like, on the grand scheme of things in my mind, it’s like a super minor one…when compared to someone that may have one that’s a greater effect on their lives.” (P2 about DQ concerns)
		“I just usually just look for the single option that’s either Western European, or Caucasian or European. And I just kind of select that and move on. I know, the option is always going to be there” (P7 about ethnic origin)
		“I’m transgender. And I would only be comfortable answering questions like that in a context where I know it couldn’t be linked back to me personally, in the sense of I don’t want to put myself in a position…that may be um not good for me.” (P5 about gender identity)
Beliefs about demographic data	The importance or value one places on demographic data specific to their overall beliefs about the purpose of demographic data collection in healthcare settings.
Equity monitoring	Beliefs that demographic data was important for seeing who programs are or are not reaching as a whole to know where gaps in reach are.	“Knowing who’s in your community and what needs they may have is like the most important thing that any community organization should know…if you don’t know who’s out there, you can’t help them. (P4 overall comment)
		“There are a lot of communities that are underrepresented, especially in a lot of healthcare settings. So this is a really good way to sort of get a grasp at what levels we’re able to reach.” (P10 overall comment)
		“It’s valuable to know as a whole…what groups might suffer from these conditions and then use government funding to appropriately…look into those problems and address those issues” (P8 about DQ importance)
Point of care	Beliefs that demographic data was important for individualizing treatment directly for patients and that individual’s demographics affect their health journeys.	“I think that demographic information…and all their life experiences really shapes an individual’s health…it’s like super, super important because every health promotion strategy has to be somewhat tailored to the individual.” (P2 about DQ importance)
		“Quality of treatment based on those criteria, like I hear indigenous people are often treated worse just because of their race. So stuff like that. Or health care for trans people” (P9 about DQ concerns)
		“I would also worry if the information I’m being given is going to kind of negatively impact how I’m perceived in that setting” (P11 about DQ concerns)
Divisiveness	Beliefs that demographic data is a divisive practice that unnecessarily labels people and puts them into categories.	“Divisiveness, that they want to put everybody into categories. When I don’t think that’s necessary for overall health. If health is the goal, I don’t see how it benefits people to do that.” (P6 about DQ concerns)

Representation

Participants expressed the value of feeling seen in the SSBC-DQ. They described feeling that the questionnaire response options fit with their identity, and that they had the autonomy to select multiple response options, expand beyond response options provided, or choose not to respond at all. Overall, participants felt that the SSBC-DQ was inclusive and that most questions provided thorough response options. There was overwhelming appreciation for the ability to express their identity in words through the ‘another option’ choice provided, recognizing that even with a thorough list of response options it is difficult to capture all individuality that is evolving and being understood. Representation came through strongest in disability, gender identity, occupation and ethnic origin questions. Representation was described by participants as being important so that programs are representative of the community they are serving.

Comprehension

Majority of participants had a positive experience with the SSBC-DQ, describing it as “easy”, “straight forward”, and “second nature”. The language used and questions presented were not new to participants, who expressed a familiarity with questionnaires of this nature. Including definitions and extra clarification was found to be helpful (e.g., “The Accessible Canada Act definition really helps to clarify” - P2 about disability), while ambiguous terminology hindered comprehension (e.g., “I don’t know if that’s the actual definition of visible minority…I also group in visible physical disabilities.” - P7 about visible minority). Comprehension was influenced by participants’ lived experiences and their stage of life (e.g., household income when living with roommates vs with a spouse).

Completing Demographic Questionnaires is an Emotional Experience

Participants expressed a host of emotions experienced while completing the SSBC-DQ ranging all along the positive to negative spectrum. Anonymity and confidentiality strongly influenced participants’ emotions towards demographic questionnaires expressing concerns about potential data leaks and being able to maintain their personal safety. The emotional experiences were context dependent; participants stated that their comfort in responding to a demographic questionnaire would depend on the nature of the questionnaire, why the data was being collected and who was collecting the information. Lived experiences including family upbringing, community involvement and education contributed to emotions of completing the SSBC-DQ. The sub-theme, not wanting to ‘mess up’, was developed relating to the emotional experience of completing demographics questionnaires.

Not Wanting to ‘Mess Up’

Participants expressed strong negative emotions when they felt there was a right or wrong way to complete the questionnaire. These emotions were framed around a lack of confidence and included feelings of nervousness, hesitation and ‘not being sure’. Having definitions and specificity was suggested for questions where there was uncertainty, to remove participant doubt.

The Role that Privilege Plays

Emotions relating to the sociocultural systems which place individuals in positions of unearned privilege or unearned oppression are described within this theme. Demographic questionnaires are commonly written and framed by Whiteness and other systems of oppression, such that identifying as having privilege allowed participants to have more positive or neutral emotions, while belonging to an equity-owed group caused more negative emotions related to demographics. It was strongly recognized that the privilege one holds or does not hold influenced their emotional experience when completing the demographic questionnaire. This was particularly apparent in participants who lacked privilege in some systems and held privilege in others, with emotions varying based on whether they lacked or held privilege within each system. The role that privilege plays extended beyond recognizing one’s own privilege, and included acknowledging that others’ emotions may be different if they lacked privilege.

Beliefs About Demographic Data

Participants described the importance they placed on demographic data, specific to their overall beliefs about demographic data collection practices; not to be conflated with the experience of completing the SSBC-DQ. The majority of participants viewed demographic data collection as important. Participants expressed that being transparent and honest about why data is being collected and what the data will be used for is critical. Additionally, there was concern about using demographic data to make conclusions and decisions based on a small sample of people. There were three distinctly different beliefs about demographic data that were identified as sub-themes: equity monitoring, point of care, and divisiveness.

Equity Monitoring

Equity monitoring was described as the use of demographic data to see who programs are and are not reaching. Participants expressed the need to gather demographic data to identify gaps in program reach so that steps could be taken to “ensure the inclusivity and accessibility of the program” (P10 about DQ beliefs). There was a strong understanding from participants that the SSBC-DQ was used for accessibility and equity monitoring reasons as made clear by one participant, “demographics can provide important information on how to best target diabetes prevention” (P3 overall comment).

Point of Care

Separate from equity monitoring was the belief that demographic data was important directly at the point of care for individualizing treatment to the patient and influencing how the patient would be received in the setting. Participants described the need for programs to assess the health behaviours and intrinsic factors from patients’ demographic data to tailor the treatment/program to their needs. This was echoed by the idea that an individual’s demographics influenced their health journey (e.g., “certain groups have different needs particular to either their cultural, gender, or ethnic grouping.” – P8 overall comment). Another consideration was that providing demographic data may impact how the patient is perceived or treated within that setting. This was particularly strong when participants reflected on the sociocultural systems (i.e., racism, ableism, transphobia, settler-colonialism etc.) that continue to oppress certain groups of individuals.

Divisiveness

Majority of participants believed demographic data collection to be a useful and beneficial practice; however, there was one participant that stood apart, believing demographic data collection not to be important. They strongly expressed that demographic questionnaires unnecessarily label people and put them into segregated boxes making it a divisive process. They advocated for focusing on people and not worrying about what group they are in.

APEASE Coding

In addition to the information presented above, interviews contained suggestions for changes to the SSBC-DQ. APEASE coding aligned our pragmatic paradigm and values of respect and equity with applying the suggestions from participants to improve the SSBC-DQ. Suggestions focused on increasing question clarity, providing information about how questions link to diabetes (in the context of the SSBC-DQ), changing response selection to multiple selections or open text response, and including other aspects of individuals demographics that were not represented (Supplemental file 4).

A total of 60 suggestions were captured about the SSBC-DQ. Initial independent coding of each suggestion by the first three authors saw moderate agreement (kappa = 0.514, PABAK = 0.568).³⁸ Disagreements were discussed and consensus was reached by the three authors. To be implemented in the SSBC-DQ the suggestion had to be coded as ‘yes’ for all APEASE criteria. 10% of suggestions met all criteria for immediate implementation (Table 3). Coding as ‘no’ for at least one criterion excluded 33.3% of suggestions from implementation. The majority of suggestions (56.7%) received a code of ‘depends’ for at least one criterion. Suggestions coded as ‘depends’ were further examined among the three authors with consultation from the corresponding author; from which an additional 11 suggestions met the criteria for implementation (Table 3).

Table 3.

Participant suggestions that met APEASE criteria for implementation.

Add ‘exploring my gender identity’ to response options

Add option to select multiple options for gender identity question

Order ethnic origin response options by geographic region

Clarify if education is highest completed or highest currently engaged in

Add ‘prefer not to say’ response option to all questions

Add ‘do not know’ response option to tobacco usage question

Remove the term ‘minority’ from the questionnaire

Add what topics the questionnaire will discuss to introduction

Improve transparency about why data is being collected and how it will be used

Add definition of gender identity

Add definition of ethnic origin

Rephrase ‘less than high school’ response option

Add definition of household income

Replace ‘living as married’ response option to ‘common law partner’

Clarify if vaping counts as tobacco use

Add question about sexual orientation

Add definition of demographic data

Discussion

Using pragmatic and constructivist paradigms,^17,18 this study aimed to understand individuals of equity-owed groups experiences in completing the SSBC-DQ, and gather suggestions to develop recommendations for improving SSBC’s demographic data collection practices. Five principal themes were developed relating to SSBC-DQ experiences: Representation, Comprehension, Completing demographic questionnaires is an emotional experience, The role that privilege plays, and Beliefs about demographic data collection, which captured context for the elements in which the SSBC-DQ performs well and where there was room for improvement.

Our participant sample captured a diversity of demographic identities including 41.7% male sex, 50% female or primarily feminine gender, 50% persons of colour, and 42% with a disability. The sample age range is relatively young when compared to the age of adults typically engaging in DPPs. The young age range may be due to the nature of the city in which the study was conducted where 78.7% of its population is under the age of 65³⁹ and the fact that participants were not recruited from a DPP but rather from the general public.

The SSBC-DQ collected information in a familiar and understandable manner, inclusive of diverse and intersecting individuals. Comprehension was found to be weakest where terminology was ambiguous, such as ethnic origin and visible minority. This is consistent with previous research which found demographic questions about ethnicity and race to be challenging given the complex geographical and sociocultural representations of ethnicity and race.^3,40–42 Similar studies reported that individuals of mixed-race experienced uncertainty when demographic questionnaires allowed only single response options.^41,43 The SSBC-DQ found that including the ability to select multiple response options and specify beyond the options given reduced uncertainty surrounding mixed race.

A well-documented barrier to demographic data collection is participant discomfort, the emotional response to a question and willingness to provide a truthful response. The emotional response to a demographic question has been found to vary depending on participants’ perceived sensitivity of the information being requested,^43,44 consistent with the results discussed here. This may have to do with the phrasing of the question, the response options provided, and the context in which the information is being collected. For example, there was no discomfort among participants when answering a specific question designed to gather information on race and ethnicity in Toronto primary healthcare centers.⁴¹ The role that privilege plays in the experience of completing a demographic questionnaire came through very strongly in all of the 12 participant interviews. This is consistent with previous results which found emotions to differ among demographic groups, particularly in the negative emotions associated with disclosing race and ethnicity from participants of racially minoritized groups.^40,45

This study highlights that participants have a mixed understanding about the use of demographic data collection, similar to pervious findings.^41,43–45 Practitioners, policymakers, and researchers must do better at educating patients about why demographic data is being collected and how the data will be used to inform healthcare services. Furthermore, it is important to stress the role of demographic questionnaires as an equity monitoring tool aligned with provincial and federal human rights legislative frameworks.^1,8,46

There is considerable need for inclusive demographic data collection practices in community-based health programs, including DPPs, that lessen patient discomfort, reduce privacy concerns, and eliminate fear that disclosure will negatively affect care. Currently, there is no consolidated method for collecting demographic information in an inclusive and thoughtful manner. This leads programs to often report data that may not be representative of the population being reached, potentially inhibiting the ability to know who is and is not being reached. Without knowing who programs are and are not reaching it may be challenging to compare findings across programs or generalize findings to other populations. For example, there have been several widescale DPPs that have become landmark studies in diabetes prevention care, however, the characteristics of these study populations are largely unknown.^14–16 This is due to minimal and inconsistent reporting of demographic data between studies, such that it cannot be discerned if the program reach is equitable or if they are reaching those most at risk for T2D. Finally, health leaders must take responsibility for designing demographic questionnaires with the community in mind, as this study clearly demonstrates that a demographic questionnaire is not a simple list of boxes to be checked off but is linked to past experiences and emotions.

Limitations and Strengths

There are some limitations to this study. Importantly, most participants were students or staff from a university campus, and thus came from a position of higher education with possibly more exposure and education surrounding conversations on equity, diversity and inclusion. One limitation of self-selection bias is that it attracts participants that may be more interested in topics surrounding identity and equity advocacy. These topics may be more attractive to younger individuals as observed in the young age range of our sample. DPPs typically serve middle-age and older adults, thus the age-range of our sample may not represent the experiences of those most commonly engaging in DPPs. Furthermore, we were unable to capture experiences from all demographic identities in the questionnaire such as individuals with physical disabilities, those who identify as being of Indigenous or African descent.

Strengths of this study include the depth of information captured in participant interviews, including how participants linked past experiences to their feelings on the SSBC-DQ. Demographic questions are often thought of as simple to respond to, we provided insight not previously explored to the emotional context surrounding responding to demographic questions. Additionally, participants completed the SSBC-DQ in its entirety before the interview, as no previous studies had examined participants’ views of a demographic questionnaire in its entirety. Finally, although not all demographics represented in the SSBC-DQ were captured, we were able to achieve diversity among participants having recruited individuals from several different and intersecting groups.

Conclusions

This study represents action towards reducing inequities in community-based DPPs by understanding the experiences of a demographic questionnaire and exploring suggestions for which demographic data collection questions can be improved. The findings illustrate that people’s experiences of completing a health demographic questionnaire are driven by their lived experiences and environmental context. To our knowledge this is the first study to gather and evaluate end-user suggestions on demographic data collection for implementation. Results from this study were used to modify the original SSBC-DQ. Through use of the updated SSBC-DQ, this community-based program aims to improve feelings of representation for those who choose to enroll. This will allow SSBC to be more confident in the populations it is and is not reaching which will help inform future directions regarding improving program reach and equity.

Supplemental Material

Supplemental Material - “People Need to Know; we’re Part of the Community. We’re Here.”: Examining Experiences of Sharing Demographic Information for a Community-Based Diabetes Prevention Program

Supplemental Material for “People Need to Know; we’re Part of the Community. We’re Here.”: Examining Experiences of Sharing Demographic Information for a Community-Based Diabetes Prevention Program by Sarah A. Craven, Jenna A. P. Sim, Kaela D. Cranston, and Mary E. Jung in Community Health Equity Research & Policy.

Supplemental Material

Supplemental Material - “People Need to Know; we’re Part of the Community. We’re Here.”: Examining Experiences of Sharing Demographic Information for a Community-Based Diabetes Prevention Program

Supplemental Material

Supplemental Material - “People Need to Know; we’re Part of the Community. We’re Here.”: Examining Experiences of Sharing Demographic Information for a Community-Based Diabetes Prevention Program

Supplemental Material

Supplemental Material - “People Need to Know; we’re Part of the Community. We’re Here.”: Examining Experiences of Sharing Demographic Information for a Community-Based Diabetes Prevention Program

Footnotes

Acknowledgments

We respectfully acknowledge that the work and research conducted for this study were on the traditional, ancestral, and unceded territory of the syilx Nation. This research was possible due to the support of the Stober Foundation.

Authors’ Contributions

All authors contributed to the overall study design and conception. SC contributed to material preparation, data collection, data analysis, data interpretation and wrote the first draft of the manuscript. JS and KC contributed to data analysis and data interpretation. MJ contributed to data interpretation, data implementation, and critically revised manuscript for intellectual content. All authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: SC received financial support for this work from the Stober Foundation (Undergraduate Research Fellowship Award).

Ethical Statement

ORCID iDs

Kaela D. Cranston

Mary E. Jung

Supplemental Material

Supplemental material for this article is available online.

Appendix

Author Biographies

Sarah A. Craven is an undergraduate honours thesis and undergraduate research assistant.

Jenna A. P. Sim is a Master's student in the School of Health and Exercise Sciences at the University of British Columbia Okanagan.

Kaela D. Cranston is a PhD student in the School of Health and Exercise Sciences at the University of British Columbia Okanagan. Kaela completed her Master’s of Science in the School of Health and Exercise Sciences July 2019.

Mary E. Jung is an Associate Professor at UBC in the School of Health and Exercise Sciences at the University of British Columbia Okanagan Campus and the Director of the Diabetes Prevention Research Group (DPRG). Mary’s passion is researching the self-regulation of health behaviours, primarily the promotion and adherence to physical activity and health diets in people living with, or at risk of, type 2 diabetes. Dr. Jung strives to see evidence-based lifestyle interventions implemented in the community to serve those in need.

References

British Columbia’s Office of the Human Rights Commissioner . Disaggregated demographic data collection in British Columbia: the grandmother perspective. https://epe.lac-bac.gc.ca/100/200/300/bcohrc/disaggregated/BCOHRC_Sept2020_Disaggregated-Data-Report.pdf (2020, accessed 12 July 2022).

Browne

Varcoe

Wong

, et al.

Can ethnicity data collected at an organizational level be useful in addressing health and healthcare inequities?

Ethn Health 2014; 19(2): 240–254. DOI: 10.1080/13557858.2013.814766.

Moscrop

Ziebland

Roberts

, et al. A systematic review of reasons for and against asking patients about their socioeconomic contexts. Int J Equity Health 2019; 18(1): 112. DOI: 10.1186/s12939-019-1014-2.

Varcoe

Browne

Wong

, et al. Harms and benefits: collecting ethnicity data in a clinical context. Soc Sci Med 2009; 68(9): 1659–1666. DOI: 10.1016/j.socscimed.2009.02.034.

Williams-Roberts

Neudorf

Abonyi

, et al. Facilitators and barriers of sociodemographic data collection in Canadian health care settings: a multisite case study evaluation. Int J Equity Health 2018; 17(1): 186. DOI: 10.1186/s12939-018-0903-0.

Bates

Roche

Cheff

, et al. Wellesley institute works in research and policy to improve health and health equity in the GTA through action on the social determinants of health. Toronto: Wellesley Institute, 2017, p. 26.

Canadian Institute for Health Information . Guidance on the use of standards for race-based and indigenous identity data collection and health reporting in Canada. Ottawa, ON: CIHI, 2022, p. 33.

Ontario Human Rights Commission . Count me in! Collecting human rights-based data, Ontario human rights commission. https://www.ohrc.on.ca/en/count-me-collecting-human-rights-based-data (2009, accessed 10 April 2023).

Toronto Public Health . We-ask-because-we-care: the tri-hospital & TPH health equity data collection research project report. https://torontohealthequity.ca/wp-content/uploads/2017/05/We-Ask-Because-We-Care-Report.pdf (2013, accessed 10 April 2023).

10.

Bourne

Ivanova

Gainforth

, et al. Mapping behavior change techniques to characterize a social cognitive theory informed physical activity intervention for adults at risk of type 2 diabetes mellitus. Transl Behav Med 2020; 10(3): 705–715. DOI: 10.1093/tbm/ibz008.

11.

Locke

Bourne

Beauchamp

, et al. High-intensity interval or continuous moderate exercise: a 24-week pilot trial. Med Sci Sports Exerc 2018; 50(10): 2067–2075. DOI: 10.1249/MSS.0000000000001668.

12.

Bean

Dineen

Locke

, et al. An evaluation of the reach and effectiveness of a diabetes prevention behaviour change program situated in a community site. Can J Diabetes 2021; 45(4): 360–368. DOI: 10.1016/j.jcjd.2020.10.006.

13.

Diabetes Canada . Diabetes in Canada: 2022 backgrounder. Ottawa: Diabetes Canada, 2022.

14.

Knowler

Barrett-Connor

Fowler

, et al. Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin. N Engl J Med 2002; 346(6): 393–403. DOI: 10.1056/NEJMoa012512.

15.

Lindström

Louheranta

Mannelin

, et al. The Finnish Diabetes Prevention Study (DPS): lifestyle intervention and 3-year results on diet and physical activity. Diabetes Care 2003; 26(12): 3230–3236. DOI: 10.2337/diacare.26.12.3230.

16.

Pan

, et al. Effects of diet and exercise in preventing NIDDM in people with impaired glucose tolerance: the Da qing IGT and diabetes study. Diabetes Care 1997; 20(4): 537–544. DOI: 10.2337/diacare.20.4.537.

17.

Morgan

. Paradigms lost and pragmatism regained: methodological implications of combining qualitative and quantitative methods. J Mix Methods Res 2007; 1(1): 48–76. DOI: 10.1177/2345678906292462.

18.

Tamminen

Poucher

. Research philosophies. In: Hackfort

Schinke

(eds). The Routledge international encyclopedia of sport and exercise psychology. 1st ed. Milton Park: Routledge, 2020, pp. 535–549. DOI: 10.4324/9781315187259-39.

19.

Sparkes

Smith

. What is qualitative research. Qualitative research methods in sport, exercise and health: From process to product. 1st ed. Routledge, 2013, pp. 6–32. https://doi.org/10.4324/9780203852187

20.

Braun

Clarke

. Using thematic analysis in psychology. Qual Res Psychol 2006; 3: 77–101. DOI: 10.1191/1478088706qp063oa.

21.

Braun

Clarke

. One size fits all? What counts as quality practice in (reflexive) thematic analysis? Qual Res Psychol 2021; 18(3): 328–352. DOI: 10.1080/14780887.2020.1769238.

22.

Collaborating Center for Questionnaire Design and Evaluation Research . Q-bank: question evaluation for surveys. Centers for Disease Control and Prevention. https://wwwn.cdc.gov/qbank/Learn/CI-Standards.aspx#/Overview (2021, accessed June 27, 2022).

23.

Presser

Couper

Lessler

, et al. (eds). Methods for testing and evaluating survey questions. Hoboken, NJ: John Wiley & Sons, Ltd, 2004, Vol 68. DOI: 10.1093/poq/nfh008. (accessed 27 June 2022).

24.

Willis

Artino

. What do our respondents think we’re asking? Using cognitive interviewing to improve medical education surveys. J Grad Med Educ 2013; 5(3): 353–356. DOI: 10.4300/JGME-D-13-00154.1.

25.

Betts

. Developing survey questions on sexual identity: cognitive/in-depth interviews. Newport: Office for National Statistics, 2009.

26.

Miller

Willson

. Cognitive testing of NCHS race questions. National Center for Health Statistics, 2002. https://wwwn.cdc.gov/qbank/report.aspx?1018.

27.

Ministry of Health . HISO 10001: 2017 ethnicity data protocols. Ministry of Health, 2017.

28.

Michie

Atkins

West

. The behaviour change wheel: a guide to designing interventions. https://www.vlebooks.com/vleweb/product/openreader?id=Exeter&isbn=9781912141081 (2014, accessed 23 July 2022).

29.

Sinnott

Mercer

Payne

, et al. Improving medication management in multimorbidity: development of the MultimorbiditY COllaborative medication review and DEcision making (MY COMRADE) intervention using the behaviour change wheel. Implement Sci 2015; 10(1): 132. DOI: 10.1186/s13012-015-0322-1.

30.

Litton

Atkinson

Anstey

, et al. Optimising a targeted test reduction intervention for patients admitted to the intensive care unit: the Targeted Intensive Care Test Ordering Cluster Trial intervention. Aust Crit Care 2021; 34(5): 419–426. DOI: 10.1016/j.aucc.2020.11.003.

31.

MacPherson

Cranston

Locke

, et al. Using the behavior change wheel to develop text messages to promote diet and physical activity adherence following a diabetes prevention program. Transl Behav Med 2021; 11(8): 1585–1595. DOI: 10.1093/tbm/ibab058.

32.

Scott

May

Patel

, et al. A practitioner behaviour change intervention for deprescribing in the hospital setting. Age Ageing 2021; 50(2): 581–586. DOI: 10.1093/ageing/afaa169.

33.

Hunt

. Strengths and challenges in the use of interpretive description: reflections arising from a study of the moral experience of health professionals in humanitarian work. Qual Health Res 2009; 19(9): 1284–1292. DOI: 10.1177/1049732309344612.

34.

Thompson Burdine

Thorne

Sandhu

. Interpretive description: a flexible qualitative methodology for medical education research. Med Educ 2021; 55(3): 336–343. DOI: 10.1111/medu.14380.

35.

Thorne

Kirkham

MacDonald-Emes

. Interpretive description: a noncategorical qualitative alternative for developing nursing knowledge. Res Nurs Health 1997; 20(2): 169–177. DOI: 10.1002/(SICI)1098-240X(199704)20:2<169::AID-NUR9>3.0.CO;2-I.

36.

Thorne

Kirkham

O’Flynn-Magee

. The analytic challenge in interpretive description. Int J Qual Methods 2004; 3(1): 1–11. DOI: 10.1177/160940690400300101.

37.

Archibald

Lawless

Ambagtsheer

, et al. Older adults’ understandings and perspectives on frailty in community and residential aged care: an interpretive description. BMJ Open 2020; 10(3): e035339. DOI: 10.1136/bmjopen-2019-035339.

38.

Fleiss

. Measuring nominal scale agreement among many raters. Psychol Bull 1971; 76(5): 378–382. DOI: 10.1037/h0031619.

39.

Government of Canada SC . Census profile, 2016 Census - Kelowna. Victoria, BC: Government of Canada SC, 2017.

40.

Hasnain-Wynia

Baker

. Obtaining data on patient race, ethnicity, and primary language in health care organizations: current challenges and proposed solutions. Health Serv Res 2006; 41(4 Pt 1): 1501–1518. DOI: 10.1111/j.1475-6773.2006.00552.x.

41.

Kiran

Sandhu

Aratangy

, et al. Patient perspectives on routinely being asked about their race and ethnicity: qualitative study in primary care. Can Fam Physician 2019; 65(8): e363–e369.

42.

Moscou

Anderson

Kaplan

, et al. Validity of racial/ethnic classifications in medical records data: an exploratory study. Am J Publ Health 2003; 93(7): 1084–1086.

43.

Kirst

Shankardass

Bomze

, et al. Sociodemographic data collection for health equity measurement: a mixed methods study examining public opinions. Int J Equity Health 2013; 12(1): 75. DOI: 10.1186/1475-9276-12-75.

44.

Lofters

Shankardass

Kirst

, et al. Sociodemographic data collection in healthcare settings: an examination of public opinions. Med Care 2011; 49(2): 193–199.

45.

Baker

Hasnain-Wynia

Kandula

, et al. Attitudes toward health care providers, collecting information about patients’ race, ethnicity, and language. Med Care 2007; 45(11): 1034–1042. DOI: 10.1097/MLR.0b013e318127148f.

46.

R.S.C . Can hum rights advocate. Section 16. https://laws-lois.justice.gc.ca/PDF/H-6.pdf. (1985, accessed April 10, 2023).

Supplementary Material

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