Service user engagement by ethnicity groups at a children’s gender identity service in the UK

Abstract

Objectives

Gender service utilisation according to ethnicity is largely under-researched. The present research looked at demographics and service user-engagement according to ethnicity of young people accessing a gender service for children.

Method

A total of 2063 (M = 14.19 years, SD = 2.59, assigned male = 556, 1495 assigned female = 1495, no-specification=12) referrals were included in the analysis. Self-defined ethnicity in financial years (FY) 2016–2017, 2018–2019, and referrer-defined ethnicity in FY 2020–2021 were compared between years, to the national UK-population, and child and adolescent mental health service (CAMHS) averages. Numbers of offered, attended and non-attended appointments were compared across the White and the ethnic minority population (EMP).

Results

Across years 93.35% young people identified as White (higher than the CAMHS and national population averages); 6.65% as EMP. Service utilisation was similar in FY 2016–2017. In FY 2018–2019, the EMP subgroup was offered and attended more appointments compared to the White subgroup, ‘did not attended’ average was similar.

Conclusions

The majority of young people self-identified with a White ethnic-background. Service engagement was comparable between the EMP and White ethnicity subgroups in 2016–2017, while the EMP group was offered and attended more appointments in 2018–2019. Due to the low EMP group numbers, findings need to be interpreted with caution.

Keywords

Gender identity gender diversity ethnicity ethnic minority populations children adolescents

Introduction

The rise in international referrals to child and adolescent gender services over recent years (Aitken et al., 2015; de Graaf et al., 2019; Kaltiala-Heino et al., 2018) has increased research interest in adolescent transgender health. However, little has been explored regarding service user engagement in relation to ethnicity. Literature acknowledges the diverse understandings of gender held across ethnic communities that have developed through years of cultural practice and/or interpretations of religious texts; however, research lacks in recording the diversity of ethnicity referred to services, and the experiences of gender diverse people from ethnic minority population (EMP) groups (Budge & Pankey, 2016).

Gender and ethnicity are two important aspects of our identity that influence how we perceive the world around us (Frable, 1997). Present notions of cis- and binary gender identification are rooted in Western society, and likely contribute to social stigma, prejudice, and bullying in gender diverse people. These experiences have been linked to associated difficulties such as high levels of distress, anxiety, depression, low mood, and self-harm in some gender diverse young people (de Vries et al., 2011; Di Ceglie et al., 2002; Holt et al. 2016; Skagerberg, Davidson & Carmichael, 2013). Indeed, the theory of intersectionality (Crenshaw, 1990) suggests that our socially constructed identities implicate our experiences of oppression, discrimination, privilege or power. The minority stress model (Levitt & Ippolito, 2014) states that the sum of cumulative effects of such stress can negatively impact the physical and mental health of stigmatised groups of people. Thus, EMP groups who occupy multiple minority identities simultaneously may be exposed to an increased risk of experiencing multiple and cumulative effects of oppression and discrimination (Cyrus, 2017).

The differences in the meaning of gender across different ethnicities and cultures are sometimes conceptualised through two principal philosophies: Western (or ‘White’) and Eastern (or ‘non-White’) (Fernando, 2012). However, complex constructs such as gender could not be fairly represented in such simplistic divisions without diluting the richness of individual differences within these ‘West’ and ‘East’ categories (Fernando, 2012).

Ecklund (2012) illustrated the differences of gender identity development between the Western and Eastern cultures in a case report which reflected on the multiple intersecting identities of a six-year-old assigned male at birth who identified as female, and whose native Korean enculturation by his parents restricted the expressions of his gender diverse feelings while his adopted American cultural identity allowed this (see also Bussey, 2011; Jensen, 2011; Newman, 2002). The parents’ own gender identities and perspectives were based on their own enculturation through Eastern philosophy which emphasises stability, harmony, and interdependence through the establishing and maintaining of the outer world of relationships Dwivedi & Verma, 1996;Fernando, 2012. Such enculturation by parents or caregivers may cause young people from EMP groups to encounter barriers in accessing gender services out of perceived fear of stigma, discrimination, and prejudice from their community. By contrast, the child’s adopted culture placed them at the centre of attention and care (Fernando, 2012) through Western philosophy which is mostly centralised around individualism, independence, self-sufficiency, and assertiveness (Dwivedi and Verma, 1996; Fernando, 2012), this may be a contributing factor to the higher number of young people from White ethnicities seen at Services (as has been previously reported e.g., de Graaf et al., 2019).

From a healthcare perspective, literature shows that EMP groups generally face multiple barriers in accessing relevant healthcare services (Szczepura, 2005), including not being represented enough in healthcare research (e.g. mental health; Brown et al., 2014). This may result in poorer health outcomes, possibly due to the interventions being largely formulated for white ethnic populations (Browne et al., 2014; Cooper et al., 2013; Memon et al., 2016). High numbers of missed appointments (referred to as ‘Did Not Attends’ (DNAs) in healthcare settings) have been well documented in services throughout the National Health Service (NHS) and in Child and Adolescent Mental Health Services (CAMHS) (Abdinasir, 2017; Minty & Anderson, 2004; Mitchell & Selmes, 2007). Non-attendance to clinical sessions may be an important indicator of the barriers experienced by young people and their caregivers. However, there remains a paucity of research looking specifically at DNA rates across different ethnic groups, largely due to poor ethnicity data gathering across healthcare services (Psoinos et al., 2011). Thus, research attending to the intersections of ethnicity and gender of EMP service users, and engagement with gender services is needed.

There is currently no data on the utilisation of gender services according to ethnicity. Therefore, this paper aims to assess the self-defined ethnicity of under 18 year olds who have and who are accessing the children’s NHS Gender Identify Development Service (GIDS), and chart the potential differences in service user engagement between the White and EMP groups. Referrer-defined ethnicity will also be reviewed for newer referrals to the Service.

Method

In this retrospective chart review, referrals accepted by the GIDS in the 2016–2017 and 2018–2019 financial years (1st April-31st March) were assessed to determine self-defined ethnicity and service engagement using the Service’s demographics form provided at the start of attending the Service. For referrals made during the 2020–2021 financial year, referrer-defined ethnicity was used owing to self-defined ethnicity data not yet being available for this group.

All data was anonymised prior to analysis, thus exemption for ethics was confirmed by external and local ethics committees affiliated with the Tavistock and Portman NHS Research and Development Department.

Demographics form

Three versions of the demographics form were used to collect the ethnicity data. Prior to 2018, the GIDS distributed an ethnicity demographics form approved locally by the Trust. This was updated in 2018 to include the same standardised “16+1” ethnicity code list that was used throughout the NHS; a more extensive ethnicity form was adopted again in 2020 (Figure 1). Due to their differences, the ethnicity categories in this paper have been coded based on the standardised “16+1” list. Thus, there were nine instances where the ethnicities collected from the pre-2018 form which did not fall under the “16+1” coding, and so were re-categorised accordingly.

Further demographic information including each young person’s assigned gender at birth, date of birth, year of referral and age at referral to the GIDS was gathered from the Service’s electronic patient record system. Data was also collected on the total number of appointments offered and attended, and the number of DNAs for the 2016–2017 and 2018-2019 groups; this data was not yet available for the 2020–2021 cohort as they were newly referred and had not started attending appointments at the Service at the time of analysis.

Demographic information on religion was available for the 2018–2019 cohort through the newer demographics forms, and therefore was captured as supplementary data.

Descriptive analysis

Categorical data was summarised by providing percentages of young people in each ethnicity category across the three financial years, and compared to the available data held across sectors in the UK (Office of National Statistics, 2011) and in CAMHS (Children’s Commissioner Report, 2016).

Results

Participant demographics

A combined total of 4050 referrals were accepted by the GIDS in the 2016–2017 (n=856) and the 2018–2019 (n=425) groups. Participant demographics are summarised in Table 1, and Figure 2 provides a breakdown of the included and excluded data. Breakdown of assigned gender at birth and of age by ethnicity was similar across White and EMP groups in the 2016–2017 cohort, but the 2018–2019 cohort showed some differences (Figure 3). It is important to note that from 2018, young people aged 17.6+ years were offered a clinical telephone conversation to discuss their referral and options. Thus, the demographics form return rate for this sub-group was relatively low in 2018–2019.

Table 1.

Participant demographics of included referrals across the 2016–2017 and 2018–19 financial year groups.

Year	Referrals	Assigned gender at birth		Age
Year	Referrals	Male	Female	Adolescents (15.0–17.96 y)	Children (12.0–14.9 y)	Under 12, y
2016–2017	N = 856	29.67% (M = 13.71, SD = 3.01)	70.33% (M = 14.24, SD = 2.36)	45.21	39.72	15.07
2018–2019	N = 425	25.71% (M=12.40, SD=3.37)	74.29% (M = 13.9, SD = 1.96)	24.76	58.73	16.51

Ethnicity breakdown

Table 2 details the self-defined ethnicities from the 2016–2017 and 2018–2019 cohorts, and the referrer-defined ethnicities from the 2020-2021 group. The vast majority of the young people self-identified with a White ethnicity background both in the 2016–2017 (93.34%) and 2018–2019 (93.87%) cohorts while only 6.66% and 6.13%, respectively, identified from an EMP group. The referrer-defined 2020-2021 group (N = 783) also showed a similar pattern, with 92.85% identified as White and a slightly higher percentage for the EMP group (7.15%). The 2020-2021 group totalled 1274 accepted referrals, from which ethnicity data was missing for 491 referrals; additionally, errors in ethnicity notation may be expected owing to this data being referrer-defined, and potentially not verified with the service users.

Table 2.

Ethnicities of children and adolescents, as referrals accepted by the GIDS during the 2016–2017, 2018–2019 and 2020–2021 financial years.

Ethnicity	2016-2017 FY		2018-2019 FY		2020-2021 FY
	Self-defined ethnicity		Self-defined ethnicity		Referrer-defined ethnicity
	n	%	n	%	n	%
White	799	93.34	398	93.87	727	92.85
White British	763	89.14	378	89.15	672	85.82
White Irish	5	0.58	3	0.71	8	1.02
Any other white background	31	3.62	17	4.01	47	6
Black or black British	5	0.58	0	0	4	0.51
Black African	0	0	0	0	0	0
Black Caribbean	3	0.35	0	0	3	0.38
Any other black background	2	0.23	0	0	1	0.13
Asian or Asian British	4	0.47	5	1.18	10	1.28
Indian	2	0.23	2	0.47	3	0.38
Pakistani	1	0.12	0	0	1	0.13
Bangladeshi	0	0	0	0	2	0.26
Any other Asian background	1	0.12	3	0.71	4	0.51
Mixed heritage	47	5.49	21	4.95	34	4.34
White and Asian	18	2.10	0	0	8	1.02
White and black African	5	0.58	3	0.71	2	0.26
White and black Caribbean	11	1.29	7	1.65	9	1.15
Any other mixed background	13	1.52	7	1.65	15	1.92
Chinese and Any other background	1	0.12	0	0	8	1.02
Chinese	0	0	0	0	0	0
Any other background	1	0.12	0	0	8	1.02
Total	856	100.00	424	100.00	783	100

When compared to the latest available national UK child and adolescent population (N = 11,970,367; range=0–17 years) (Office of National Statistics, 2011), and CAMHS figures (N = 248,264; range=0–18 years) (Children’s Commissioner Report, 2016), the overall EMP group across our three cohorts was found to be underrepresented at the GIDS, while the White ethnicity group was overrepresented (Figure 4). As noted by de Graaf et al. (2019), while the ethnicity data in the UK child and adolescent population and the CAMHS reports were presented according to the NHS “16+1” ethnicity standards, we acknowledge that each source has gathered its data at different time points. Plus, the method of collecting ethnicity information is unclear for the CAMHS report. We recommend these limitations are considered when interpreting the data.

Religion breakdown

Table 3 provides a percentage breakdown of the religion demographics captured from the 2018-2019 group data, and its comparison to the national UK population average (Office of National Statistics, 2011). At 65.0%, ‘no religion’ was overrepresented at the GIDS, as compared to the 74.1% affiliation with a religion in the national UK population.

Table 3.

Religion breakdown, as referrals accepted by the GIDS during the 2018–2019 financial year, compared to the national UK population average.

Religion	GIDS, %	National UK, %
Christian	12.90	59.30
Muslim	0.00	4.80
Buddhist	0.00	0.40
Sikh	0.00	0.80
Hindu	0.70	1.50
Jewish	0.20	0.50
None	65.00	25.10
Other	6.80	0.40
Prefer not to say/Missing	14.40	7.20
Total	100.00	100.00

Average number of appointments offered, attended and not attended in 2016–2017 and 2018-2019 groups

Table 4 provides a breakdown of the average number of appointments offered to, attended by and not attended by the 2016–2017 and 2018–2019 cohorts, based on ethnicity. The 2018–2019 cohort included 519 (20.47%) one-off telephone appointments made to young people aged 17.6+ years who would not be seen at the GIDS; so, they were not included in the following analyses.

Table 4.

Mean number and range of appointments offered, attended and not attended young people accessing the gender service, by ethnicity and financial year.

2016–2017	Offered		Attended		Did not Attend^a
2016–2017	M	SD	M	SD	M	SD
White	10.91	5.92	8.21	4.81	0.57	0.90
Black or black British	12.40	6.88	9.40	5.68	1.00	1.00
Asian or Asian British	7.25	3.30	4.50	3.79	0.50	0.41
Mixed heritage	10.89	5.53	8.26	4.23	0.66	0.94
Chinese and other	8.00	0.00	9.00	0.00	0.00	0.00
2018–2019	Offered		Attended		Did not Attend^a
2018–2019	M	SD	M	SD	M	SD
White	7.77	5.97	6.59	2.27	0.55	0.92
Asian or Asian British	11.00	10.12	10.00	8.51	0.20	0.40
Mixed heritage	10.57	5.56	8.90	4.49	1.05	1.44

^aThe DNA rate does not reflect appointments which may have been cancelled and/or rescheduled by the Service.

Variation in the number of appointments offered to the 2016–2017 cohort (White ethnicity N = 799; EMP N = 57) suggested that the White ethnicity group were offered, on average, a similar number of appointments to the EMP group (White ethnicity: M = 10.91, SD = 5.92; EMP: M = 10.74, SD = 5.5). The two subgroups also attended a similar number of appointments (White ethnicity: M = 8.21, SD = 4.81; EMP: M = 8.09, SD = 4.35). Thus, a comparable attendance rate was observed, out of the offered appointments, between the White ethnicity group (75.29%) and the EMP group (75.33%). The average number of DNAs was also similar between the White ethnic group (M = 0.57, SD = 0.9; 5.22% of offered appointments) and the EMP group (M = 0.67, SD = 0.9; 6.21% of offered appointments).

In the 2018–2019 cohort (White ethnicity N=398; EMP N=26), the EMP group were offered (M = 10.65, SD = 6.42) and attended (M = 9.12, SD = 5.29) more appointments compared to the White ethnicity group on average (M = 7.77, SD = 5.97 and M = 6.59, SD = 2.27, respectively). A similar attendance rate, out of the number of appointments offered, between the two subgroups was observed (White ethnicity: 84.83%; EMP: 85.56%). In terms of DNA appointments, the White (M = 0.55, SD = 0.92; 7.12% of offered appointments) and the EMP (M = 0.88, SD = 1.36; 8.30% of offered appointments) subgroups also had comparable averages.

The relatively low DNAs found in the overall dataset may be partly explained by the unique positioning of the Service as the only service of its kind in the UK. Individuals are required to attend if they are seeking nationally funded specialist support for gender identity exploration, and, in some cases, physical treatment, which is not typically accessible through solely attending primary healthcare services. Comparing the figures across all ethnicity groups, lower DNA rates were observed in the 2018–2019 cohort compared to the 2016–2017 cohort. This may be due to a move to telemedicine appointments owing to the COVID-19 pandemic, potentially increasing accessibility in attending appointments.

Discussion

This research aimed to understand service user engagement in a UK child and adolescent gender service based on ethnicity demographics. The results suggest that the majority of young people accessing the Service were of a White ethnicity background. This is higher than the national youth population and the CAMHS averages (Office of National Statistics, 2011; Children’s Commissioner Report, 2016). The average numbers of appointments offered, attended, and not attended were found to be similar across the White and EMP groups in the 2016-2017 group; while in the 2018-2019 group, the EMP group were offered and attended more appointments compared to the White ethnicity group, but the average DNA rates were similar.

It is important to note in the present research the low rates of young people from EMP groups referred and attending the gender service as compared to other CAMHS. de Graaf et al. (2019) suggested differences may be due to ‘help-seeking’ and ‘help-needing’ behaviours; feelings of shame and/or stigma, and cross-cultural differences in the conceptualisation of gender may contribute towards the under-representation of several EMP groups seen in GIDS. For instance, caregivers of young people might act as ‘gatekeepers’ to specialist gender services based on their understanding and interpretation of their child’s difficulties in light of their core values and beliefs (Arai et al., 2014; de Graaf et al., 2019). However, in the absence of research comparing parental attitudes towards gender diverse young people between and within different ethnicity groups (including White, and White British ethnicities), it should not be assumed that this potential barrier applies only to gender diverse young people from EMP groups.

The model of healthcare in the UK may act as an additional barrier for young people in EMP groups seeking gender-based care. Typically, primary care providers, such as general practitioners (GPs), act as referrers into specialist services, but individuals from EMP groups may experience difficulties in accessing specialist services through such a pathway. Literature suggests individuals from EMP groups are less likely to be registered with primary care services and seek professional treatment less frequently than the White ethnicity groups due to, for example, attitudinal barriers and fear of discrimination (Bhui & Bhugra, 2002; Bhui et al., 2003; Bradby et al., 2007). This is concerning as evidence suggests individuals from EMP groups may be more susceptible to certain mental health difficulties and least likely to access support (Goodman et al., 2008; Grey et al., 2013; Weich et al., 2004). Consistent with the minority stress model, young people occupying a dual minority status are at an increased risk of experiencing micro- and macro-aggressions that may, in some cases, effectuate mental health difficulties (Balsam et al., 2011; Meyer, 2003). Moreover, individuals from EMP groups may experience challenges in terms of their gender exploration due to cultural, ethnic and or community beliefs and values regarding gender appropriate behaviour (de Graaf et al., 2019).

Of particular note, it is vital to consider the difficulties for EMP groups in engaging with service providers. Language barriers and concerns around practitioners of a different ethnicity have been raised as important. For instance, some EMP individuals have voiced concerns around the capacity of practitioners of different ethnicities to relate to their experiences (Kovandžić et al., 2011). This may be linked to stereotypical views perceived to be held by care providers, and minority ethnic group experiences of racism within the healthcare setting. This is reflected in increased utilisation, lower drop-out rates, favourable treatment outcomes and higher satisfaction in some EMP service users assigned to healthcare professionals of their own ethnicity (for example, LaVeist & Nuru-Jeter, 2002; Meghani et al., 2009; Memon et al., 2016; Ziguras et al., 2003). However, this may prove difficult when accessing care through the NHS, where 79.2% of staff self-identify as having a white ethnicity (NHS Workforce, 2020). It is important to note that these studies were not carried out in relation to gender identity, and discussing gender with healthcare professionals holding the same ethnic identity may instead potentially close down exploration for fear of judgement owing to possible shared cultural and/or ethnic values and beliefs. It is also important to note that, although lower numbers of EMP young people were seen to attend the gender service, those that did were offered and attended a similar number of appointments to White ethnicity groups.

Limitations and future directions

While this retrospective chart review is the first of its kind, the low numbers of individuals within each EMP group means that the findings should be interpreted with caution. Statistical analysis on this data was not possible due to the small numbers within each EMP group, and so only descriptive analysis are presented. Future research using larger samples of EMP groups including statistical testing and comparisons with CAMHS populations to further explore distinctions between groups is warranted.

The data was categorised based on the “16 + 1” system used by the NHS; this information is collected based on ‘self-defined’ ethnicity directly from service users (NHS Data Model and Dictionary, 2020). Ethnicity is defined using several variables (das Nair and Thomas, 2012a). A lack of a standardised definition (Phinney, 1990) can not only make ethnicity a difficult construct to measure (McKenzie and Crowcroft, 1994), but also reduces the accuracy and reliability of collected data; for example, four in 100 people changed their answer regarding their ethnicity between the 2001 and 2011 Census (Jivraj & Simpson, 2015). In the case of data presented here, we are mindful that the ethnicity categories reported on conceal detail regarding the diversity of individuals within each group (Fernando, 2012). For example, the overrepresentation of the White ethnicity group may be due to this category being interpreted more as a broad ‘racial’ identity rather than specifically related to ethnicity (de Graaf et al., 2019); therefore, it is highly likely that this group includes other White minority or marginalised (or ‘invisible’) groups. Equally, the EMP sub-categories also cluster together individuals who likely have a broad range of cultural and ethnic backgrounds, religious beliefs and personal values. Future studies investigating the detailed variability within each ethnicity group which could contribute towards a better understanding gender identity development are required.

Work around the relationship between gender identity and ethnicity of young people from a mixed heritage is also needed. Highlighting the works of others, Sewell (2008) noted that people from some categories of Mixed Heritage have considerably poorer experiences within the prominent context of complexities in identity development, parental ambivalence about ethnic identity, family conflict, dislocation within society, and overlooked identity. Qualitative studies assessing what gender identity means for the children and young people from EMP backgrounds, especially in terms of their enculturation and their experiences of accessing gender based care, are called for.

It is important for healthcare professionals to consider the impact of Western gender labels and norms, identity markers, or references for EMP groups accessing gender services, especially if EMP groups cannot relate to these (das Nair and Butler, 2012). It is equally important to consider that cultural identity in thinking about gender may be important for some EMP youth exploring gender, but not for others. For EMP young people who feel that ethnicity is not a factor in their gender exploration, suggestions for qualitative studies exploring other identities, such as religion, have been proposed (Charmaraman & Grossman, 2010).

The socio-economic status (SES) of the cohort reviewed in this work was also not known. Data exists showing that poorer health outcomes for EMP groups are linked to lower SES (Jivraj & Simpson, 2015; Mason, 2000). This may act as a contributing factor to some young people’s experience in accessing specialist gender services. Future research is required to understand the link between SES, EMP groups and access to gender services in young people.

Lastly, the dynamic between religion and gender identity development was not explored here but should be considered in future research. Despite being a separate construct, religion can be a component of a definition of ethnicity and can form an important part of one’s identity. For some gender diverse people their religion can be a great source of comfort and support; but for others these identities may be at conflict, causing further psychological distress (das Nair and Thomas, 2012b).

Conclusion

Data from the present study indicate that the majority of young people accessing the GIDS were identified with a White ethnicity background compared to an EMP background across three different financial year cohorts. Regarding service engagement, the average number of offered, attended and not attended appointments were comparable between the White and EMP subgroups in the 2016–2017 cohort. In the 2018–2019 cohort, the EMP subgroup was offered and attended more appointments on average, but the not attended appointment rate was similar to the White ethnicity group. However, due to the smaller sample size of the EMP group across both the analysed financial year cohorts, these findings need to be taken with caution. Further research is recommended to explore why EMP groups may be accessing gender services less than the White ethnicity group.

Footnotes

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) received no financial support for the research, authorship, and/or publication of this article.

ORCID iDs

Johanna K. Maninger

Una Masic

Author biographies

Ilham I. Manjra [BSc (Hons), MSc] has a special interest in how ethnicity and religion influence healthcare access and choices. From 2017 until 2021, she was based at the Tavistock and Portman NHS Foundation Trust as a Research Assistant for the Gender Identity Development Service, where she worked on exploring the relationship between gender diversity and ethnicity as well as contributing to other projects. She currently works for the Critical Care Research Team at Great Ormond Street Hospital for Children NHS Foundation Trust.

Ian Russell was a Research Assistant in the Gender Identity Development Service at the Tavistock and Portman NHS Foundation Trust. He worked in this service from 2017 until 2020 and contributed to a number of research projects that were undertaken at the time. Prior to this he completed an MSc in Affective Disorders at Kings College London University. Ian currently works for Sussex Partnership NHS Foundation Trust as a Clinical Audit and Quality Improvement Advisor.

Johanna-Katharina Maninger is a Research Assistant at the Gender Identity Developmental service at the Tavistock and Portman NHS Foundation Trust, where she contributes to various research projects. Previously she was placed at the Centre for Brain and Cognitive development where she aided in the conduction of experimental research procedures looking at child development. Currently she is also completing a master's degree in neuroscience, specialising in developmental neurobiology and stem cell research at King’s College London.

Una Masic is the head of research, data, and audit in the Gender Identity Development Service (GIDS) for Children and Adolescents at the Tavistock and Portman NHS Foundation Trust. Una has worked in the GIDS since 2018, after completing her Doctorate at the University of Sussex and post-doctoral work at the University of Liverpool. She leads a team of research assistants in the collection and dissemination of key data from one of the largest child gender services in the world as part of the GIDS’ continued responsibility to monitor the wellbeing of service users.

References

Abdinasir

(2017). Stick with us - tackling missed appointments in children’s mental health services. The Children’s Society.

Aitken

Steensma

T. D.

Blanchard

VanderLaan

D. P.

Wood

Fuentes

Spegg

Wasserman

Ames

Fitzsimmons

C. L.

Leef

J. H.

Lishak

Reim

Takagi

Vinik

Wreford

Cohen-Kettenis

P. T.

de Vries

A. L. C.

Kreukels

B. P. C.

Zucker

K. J.

(2015). Evidence for an altered sex ratio in clinic‐referred adolescents with gender dysphoria. The Journal of Sexual Medicine, 12(3), 756–763. https://doi.org/10.1111/jsm.12817

Arai

Stapley

Roberts

(2014). ‘Did not attends’ in children 0–10: A scoping review. Child: Care, Health and Development, 40(6), 797–805. https://doi.org/10.1111/cch.12111

Balsam

K. F.

Molina

Beadnell

Simoni

Walters

(2011). Measuring multiple minority stress: the LGBT People of Color Microaggressions Scale. Cultural Diversity and Ethnic Minority Psychology, 17(2), 163–174. https://doi.org/10.1037/a0023244

Bhui

Bhugra

(2002). Mental illness in Black and Asian ethnic minorities: Pathways to care and outcomes. Advances in Psychiatric Treatment, 8(1), 26–33. https://doi.org/10.1192/apt.8.1.26

Bhui

Stansfeld

Hull

Priebe

Mole

Feder

(2003). Ethnic variations in pathways to and use of specialist mental health services in the UK: systematic review. The British Journal of Psychiatry, 182(2), 105–116. https://doi.org/10.1192/bjp.182.2.105

Bradby

Varyani

Oglethorpe

Raine

White

Helen

(2007). British Asian families and the use of child and adolescent mental health services: A qualitative study of a hard to reach group. Social Science & Medicine, 65(12), 2413–2424. https://doi.org/10.1016/j.socscimed.2007.07.025

Browne

A. J.

Varcoe

C. M.

Wong

S. T.

Smye

V. L.

Khan

K. B.

(2014). Can ethnicity data collected at an organizational level be useful in addressing health and healthcare inequities? Ethnicity & Health, 19(2), 240–254. https://doi.org/10.1080/13557858.2013.814766

Brown

Marshall

Bower

Woodham

Waheed

(2014). Barriers to recruiting ethnic minorities to mental health research: A systematic review. International Journal of Methods in Psychiatric Research, 23(1), 36–48. https://doi.org/10.1002/mpr.1434

10.

Bussey

(2011). Gender identity development. Handbook of identity theory and research. Springer. 603–628. https://doi.org/10.1007/978-1-4419-7988-9_25

11.

Charmaraman

Grossman

J. M.

(2010). Importance of race and ethnicity: An exploration of Asian, Black, Latino, and multiracial adolescent identity. Cultural Diversity and Ethnic Minority Psychology, 16(2), 144–151. https://doi.org/10.1037/a0018668

12.

Children’s Commissioner (2016). Lightning review: access to child and adolescent mental health services. Children’s Commissioner

13.

Cooper

Spiers

Livingston

Jenkins

Meltzer

Brugha

Bebbington

(2013). Ethnic inequalities in the use of health services for common mental disorders in England. Social Psychiatry and Psychiatric Epidemiology, 48(5), 685–692. https://doi.org/10.1007/s00127-012-0565-y

14.

Crenshaw

(1990). Mapping the margins: Intersectionality, identity politics, and violence against women of color. Stan L Rev, 43(6), 1241. https://doi.org/10.2307/1229039

15.

Cyrus

(2017). Multiple minorities as multiply marginalized: Applying the minority stress theory to LGBTQ people of color. Journal of Gay & Lesbian Mental Health, 21(3), 194–202. https://doi.org/10.1080/19359705.2017.1320739

16.

das Nair

Butler

(Eds.). (2012). Intersectionality, sexuality and psychological therapies: working with lesbian, gay and bisexual diversity. BPS Blackwell.

17.

das Nair

Thomas

(2012a). Race and ethnicity. In das Nair

Butler

(Eds.). Intersectionality, Sexuality and psychological therapies, working with lesbian, gay and bisexual diversity. BPS Blackwell. 59–89. https://doi.org/10.1002/9781119967613.ch3

18.

das Nair

Thomas

(2012b). Religion. In das Nair

Butler

(Eds.). Intersectionality, Sexuality and psychological therapies, working with lesbian, gay and bisexual diversity. BPS Blackwell. 89–111. https://doi.org/10.1002/9781119967613.ch4

19.

de Graaf

N. M.

Manjra

I. I.

Hames

Zitz

(2019). Thinking about ethnicity and gender diversity in children and young people. Clinical Child Psychology and Psychiatry, 24(2), 291–303. https://doi.org/10.1177/1359104518805801

20.

de Vries

A. L.

Doreleijers

T. A.

Steensma

T. D.

Cohen‐Kettenis

P. T.

(2011). Psychiatric comorbidity in gender dysphoric adolescents. Journal of Child Psychology and Psychiatry, 52(11), 1195–1202. https://doi.org/10.1111/j.1469-7610.2011.02426.x

21.

Di Ceglie

Freedman

McPherson

Richardson

(2002). Children and adolescents referred to a specialist gender identity development service: Clinical features and demographic characteristics. International Journal of Transgenderism, 7(3), 423–432. https://doi.org/10.1177/1359104502007003009

22.

Dwivedi

K. N.

Varma

V. P.

(1996). Meeting the needs of ethnic minority children. A handbook for professionals. Jessica Kingsley Publishers.

23.

Ecklund

(2012). Intersectionality of identity in children: A case study. Professional Psychology: Research and Practice, 43(3), 256–264. https://doi.org/10.1037/a0028654

24.

Fernando

(2012). Race and culture issues in mental health and some thoughts on ethnic identity. Counselling Psychology Quarterly, 25(2), 113–123. https://doi.org/10.1080/09515070.2012.674299

25.

Frable

D. E.

(1997). Gender, racial, ethnic, sexual, and class identities. Annual Review of Psychology, 48(1), 139–162. https://doi.org/10.1146/annurev.psych.48.1.139

26.

Goodman

Patel

Leon

D. A.

(2008). Child mental health differences amongst ethnic groups in Britain: A systematic review. BMC Public Health, 8(1), 1–11. https://doi.org/10.1186/1471-2458-8-258

27.

Grey

Sewell

Shapiro

Ashraf

(2013). Mental health inequalities facing UK minority ethnic populations: Causal factors and solutions. Journal of Psychological Issues in Organizational Culture, 3(S1), 146–157. https://doi.org/10.1002/jpoc.21080

28.

Holt

Skagerberg

Dunsford

(2016). Young people with features of gender dysphoria: Demographics and associated difficulties. Clinical Child Psychology and Psychiatry, 21(1), 108–118. https://doi.org/10.1177/1359104514558431

29.

Jensen

L. A.

(Ed.). (2011). Bridging cultural and developmental approaches to psychology: New syntheses in theory, research, and policy. Oxford University Press.

30.

Jivraj

Simpson

(Eds.). (2015).. Policy Press.Ethnic identity and inequalities in Britain: The dynamics of diversity.

31.

Kaltiala-Heino

Bergman

Työläjärvi

Frisén

(2018). Gender dysphoria in adolescence: Current perspectives. Adolescent Health, Medicine and Therapeutics, 9, 31–41. https://doi.org/10.2147/AHMT.S135432

32.

Kovandžić

Chew-Graham

Reeve

Edwards

Peters

Edge

Aseem

Gask

Dowrick

(2011). Access to primary mental health care for hard-to-reach groups: From ‘silent suffering’to ‘making it work. Social Science & Medicine, 72(5), 763–772. https://doi.org/10.1016/j.socscimed.2010.11.027

33.

L Budge

L Pankey

(2016). Ethnic differences in gender dysphoria. Current Psychiatry Reviews, 12(2), 175–180. https://doi.org/10.2174/1573400512666160316004616

34.

LaVeist

T. A.

Nuru-Jeter

(2002). Is doctor-patient race concordance associated with greater satisfaction with care? Journal of Health and Social Behavior, 43(3), 296–306. https://doi.org/10.2307/3090205

35.

Levitt

H. M.

Ippolito

M. R.

(2014). Being transgender: Navigating minority stressors and developing authentic self-presentation. Psychology of Women Quarterly, 38(1), 46–64. https://doi.org/10.1177/0361684313501644

36.

Mason

(2000). Race and ethnicity in modern Britain. Oxford University Press.

37.

McKenzie

K. J.

Crowcroft

N. S.

(1994). Race, culture and ethnicity. British Medical Journal, 309(6950), 286–287. https://doi.org/10.1136/bmj.309.6950.286

38.

Meghani

S. H.

Brooks

J. M.

Gipson-Jones

Waite

Whitfield-Harris

Deatrick

J. A.

(2009). Patient–provider race-concordance: Does it matter in improving minority patients’ health outcomes? Ethnicity & Health, 14(1), 107–130. https://doi.org/10.1080/13557850802227031

39.

Memon

Taylor

Mohebati

L. M.

Sundin

Cooper

Scanlon

de Visser

(2016). Perceived barriers to accessing mental health services among black and minority ethnic (BME) communities: A qualitative study in Southeast England. BMJ open, 6(11), Article e012337. https://doi.org/10.1136/bmjopen-2016-012337

40.

Meyer

I. H.

(2003). Prejudice, social stress, and mental health in lesbian, gay, and bisexual populations: Conceptual issues and research evidence. Psychological Bulletin, 129(5), 674–697. https://doi.org/10.1037/0033-2909.129.5.674

41.

Minty

Anderson

(2004). Non-attendance at initial out-patient appointments at a hospital-based child psychiatric clinic. Clinical Child Psychology and Psychiatry, 9(3), 403–418. https://doi.org/10.1177/1359104504043923

42.

Mitchell

A. J.

Selmes

(2007). Why don't patients attend their appointments? Maintaining engagement with psychiatric services. Advances in psychiatric treatment, 13(6), 423–434. https://doi.org/10.1192/apt.bp.106.003202

43.

Newman

L. K.

(2002). Sex, gender and culture: Issues in the definition, assessment and treatment of gender identity disorder. Clinical Child Psychology and Psychiatry, 7(3), 352–359. https://doi.org/10.1177/1359104502007003004

44.

NHS Data Model and Dictionary (2020). Ethnic category code 2001. NHS Data Model and Dictionary. https://datadictionary.nhs.uk/attributes/ethnic_category_code_2001.html

45.

NHS Workforce (2020). NHS Workforce. NHS Workforce. https://www.ethnicity-facts-figures.service.gov.uk/workforce-and-business/workforce-diversity/nhs-workforce/latest

46.

Office of National Statistics (2011). 2011 UK censuses. Office of National Statistics. https://www.ons.gov.uk/census/2011census/2011ukcensuses

47.

Phinney

J. S.

(1990). Ethnic identity in adolescents and adults: Review of research. Psychological Bulletin, 108(3), 499–514. https://doi.org/10.1037/0033-2909.108.3.499

48.

Psoinos

Hatzidimitriadou

Butler

Barn

(2011). Ethnic monitoring in healthcare services in the UK as a mechanism to address health disparities: a narrative review. London: Swan IPI.

49.

Sewell

(2008). Working with ethnicity, race and culture in mental health: A handbook for practitioners. Jessica Kingsley Publishers.

50.

Skagerberg

Davidson

Carmichael

(2013). Internalizing and externalizing behaviors in a group of young people with gender dysphoria. International Journal of Transgenderism, 14(3), 105-112.

51.

Szczepura

(2005). Access to health care for ethnic minority populations. Postgraduate Medical Journal, 81(953), 141–147. https://doi.org/10.1136/pgmj.2004.026237

52.

Weich

Nazroo

Sproston

McManus

Blanchard

Erens

Tyrer

(2004). Common mental disorders and ethnicity in England: the EMPIRIC study. Psychological medicine, 34(8), 1543-1551.

53.

Ziguras

Klimidis

Lewis

Stuart

(2003). Ethnic matching of clients and clinicians and use of mental health services by ethnic minority clients. Psychiatric Services, 54(4), 535-541.