Mental health-related service contact amongst young people with a possible eating problem in the English national child mental health surveys

Mental health-related service contact amongst young people with a possible eating problem in the English national child mental health surveys | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Mental health-related service contact amongst young people with a possible eating problem in the English national child mental health surveys Benjamin Geers, Helen Bould, Tamsin Ford, Tamsin Newlove-Delgado This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8886674/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract Objective: To describe patterns of service contact among adolescents screening positive for possible eating problems. Methods: Secondary analysis of the Mental Health of Children and Young People in England 2017 survey, a national stratified probability sample. Possible eating problems were identified using Development and Wellbeing Assessment (DAWBA) eating disorder screening items in adolescents aged 11–19. Individuals answered questions regarding contact with sources of help for any mental health concern. Results: Overall, 36.4% of adolescents screened positive for a possible eating problem, of whom 60.7% reported no contact with sources of mental health support. Among those reporting contact with formal and specialist services, a substantial proportion screened positive for possible eating problems, including half of those reporting contact with mental health specialists. In weighted multinomial logistic regression restricted to screen-positive adolescents, older age (17–19 years) and presence of a DSM-5 diagnosis on the DAWBA were associated with higher likelihood of contact across informal, formal, and secondary healthcare sources. Adolescents from minoritised ethnic backgrounds were less likely to report secondary healthcare contact than White peers. Conclusion: Despite high numbers of adolescents screening positive for possible eating problems, rates of help seeking in this group were low. Within this subgroup, service contact varies by age, ethnicity, and clinical comorbidity. Differences in service contact in this subgroup should be further explored. disordered eating eating problems service contact help seeking Figures Figure 1 Figure 2 Figure 3 Introduction Eating disorders, including anorexia nervosa, bulimia nervosa and binge-eating disorder, are the third most common chronic illness in adolescence and are associated with high psychiatric morbidity and mortality, with over half of individuals not achieving recovery[ 1 – 4 ]. They have significant economic burden: in 2020, the total cost of eating disorders in the UK was £9.4 billion[ 5 ]. Prevalence of eating disorders in children and young people appears to be increasing over time: the Mental Health of Children and Young People (MHCYP) in England 2023 survey found the prevalence of any eating disorder was 2.6% in 11 to 16 year olds and 12.5% in 17 to 19 year olds, a substantial increase from 2017, although methodological differences between the surveys should be noted[ 6 ]. Early intervention in eating disorders has been shown to improve outcomes. Optimal outcomes are associated with treatment commencing within the first three years of illness onset and shorter duration of untreated eating disorders [ 7 , 8 ]. Thus, early identification and treatment is central to improving chances of recovery[ 9 ]. Those with less severe or sub-clinical eating difficulties may still experience distress or impairment and may benefit from identification and support, including assessment or treatment for co-occurring physical or mental health problems associated with eating difficulties, such as depression, anxiety and substance misuse[ 10 – 12 ]. However, many studies assessing help-seeking and service contact in eating difficulties focus on adult populations, only include those with a medical diagnosis of eating disorders (and thus do not account for low rates of help-seeking), or rely on retrospective reports of those who have already sought help[ 13 , 14 ]. Consequently, there is a gap in the evidence regarding help-seeking and eating problems amongst young people in population samples. Estimates of help-seeking among adolescents with eating disorders or eating problems vary. A 2022 scoping review reported that many young people who met criteria for a clinical or subclinical eating disorder were not receiving help and did not intend to seek it, with help-seeking rates ranging from 10% to 85%[ 15 ]. However, direct comparison between studies was limited due to methodological heterogeneity. Research suggests that adolescents with eating problems often seek support from informal rather than professional sources. For example, studies in Ireland and Australia have found that family, friends or self-help were more commonly utilised than professional sources for support for eating problems[ 16 , 17 ]. Given the importance of early intervention, it is crucial to understand which sources of support adolescents with possible eating problems are in contact with. This can inform efforts to identify those who might benefit from further assessment and treatment, and ensure that professionals who may be in contact with such young people have the appropriate training. This is especially important as adolescents with eating disorders may not be aware that they have a problem in the early stages of their illness, when treatment may be most beneficial. Research question and objectives Our primary objective was to examine patterns of reported service contact in a national probability sample of young people in England with a possible eating problem, assessed using the Development and Wellbeing Assessment (DAWBA) Eating Disorder Module screening questions[ 18 ]. Methods Study population We used data from the NHS England Mental Health of Children and Young People in England 2017 survey of 9,117 children and young people aged 2 to 19 years and their parents and teachers across England. The sample was recruited through a stratified multistage random probability sample of 18,029 addresses of children from the NHS Patient Register, designed to be representative of the population. Of the 18,029 addresses issued, 2% were ineligible. Of the eligible addresses (n = 17,636) 28% refused, 12% had no further contact and 8% were classed as ‘other unproductive’. Data was successfully collected from 9,117 (52%) households, resulting in 9,117 children and young people interviewed. For this analysis, we included participants aged 11 to 19 (n = 4,057), as this group is more at risk of eating difficulties[ 19 , 20 ]. Procedure Each young person and one of their parents were invited to complete a face-to-face interview with a trained lay interviewer. For children aged 16 and younger, parents were interviewed first, and then parental consent was sought to interview their child; for 17 to 19 year-olds, consent was requested from the young person and subsequently sought from them to interview their parents. Further information about the Mental Health of Children and Young People 2017 cohort and sampling process is available in the NHS Digital report[ 21 ]. Measures The key measures used in our secondary analysis are described below: The Development and Wellbeing Assessment The Development and Wellbeing Assessment (DAWBA) was used to assess mental health conditions in participants[ 18 ]. The DAWBA is a standardised diagnostic assessment in which modules map to most common childhood mental health conditions. Participants complete “screening items” for each module, and individuals who report any difficulties related to the relevant disorder go on to complete the rest of the module, in which structured questions relate directly to diagnostic criteria while semi-structured questions probe context and impairment. Individuals who do not report potential difficulties when responding to the screening questions are moved onto the next module, reducing responder burden. A team of expert clinical raters reviewed data from informants assigning diagnoses according to both DSM-5 and ICD-10 criteria. Responses to the screening questions of the Eating Disorders module of the DAWBA were used to define ‘possible eating problems’ (Table I). Table I: DAWBA screening module questions DAWBA full statements Corresponding Fig. 1 Labels Have you deliberately made yourself vomit (throw up)? Purging Have you ever thought you were fat when other people told you that you were very thin Thought fat Do your worried about eating (What? Where? How much?) really interfere with your life? Eating worries If you eat too much, do you blame yourself a lot? Self-blame Would you be ashamed if other people knew how much you eat? Shame Young people were classified as having a possible eating problem (i.e. ‘screen positive’) using standard cut-off thresholds (Supplementary material SI, [ 22 ]) of answering yes to one or more items, or their parent answering yes to two or more parent-reported items. The threshold for screening positive for a possible eating problem is lower for self-reported symptoms, due to the commonly secretive nature of eating disorder symptoms[ 23 ]. A previous test accuracy study reported that for 11–16 year olds, the DAWBA screening items had a sensitivity of 100% and specificity of 55%. In 17 to 19 year olds, sensitivity was 100% and specificity was 48% [ 24 ]. Service contact Respondents were asked if they (or their child for parents) had contact with a range of informal support and professional services for any mental health concern over the previous year. We then classified sources of help as informal, formal and secondary healthcare[ 25 ](see Table II). Table II: Categories of help, classified as Informal, Formal and Secondary healthcare Informal Formal Secondary healthcare Friends and Family, e.g. ‘someone in your family or a close friend’ Primary care professional, e.g. GP, health visitor, practice nurse or school nurse Mental health specialist, e.g. mental health nurse, psychiatrist, psychologist or counsellor Telephone help, e.g. Samaritans, NHS 111, Young Minds Textline Teacher, e.g. form tutor, head of year, head teacher or coordinator Child physical health specialist, e.g. hospital or community paediatrician, Self help, e.g. self help groups or organisations Additional educational support, e.g. educational psychologist, educational social worker or specialist teacher from outside of school Internet help, e.g NHS or government websites, charity websites, blogs, online communities Social care, e.g a social worker Youth justice services We classified service contact hierarchically. Individuals who reported contact with any informal, but no formal or secondary healthcare sources, were classified as having had contact with informal sources only. Individuals who reported contact with any formal sources of help but no contact with secondary healthcare were classified as having had contact with formal sources of help. Individuals who reported contact with mental health specialists or child health specialists were classified as having had contact with secondary healthcare. Measures of DSM-5 comorbidities We examined DSM 5 disorders[ 26 ] as assigned by the DAWBA to examine co-occurring anxiety, depression, behavioural, ADHD, autism spectrum disorder (ASD) and tic disorder diagnoses. Socio-demographic characteristics Baseline characteristics for these analyses included age, sex and ethnicity. Housing tenure was used as a measure of household socioeconomic position. Data analysis All data was analysed using Stata 17, using calibrated weights provided with the dataset which include weights for design and non-response[ 21 ]. Initially, we described the characteristics of participants screening positive (according to either parent or young person) for possible eating problems, including by age, sex, ethnicity, DSM-5 comorbidities and socioeconomic position. Due to the low frequency of ADHD diagnosis, ASD and tic disorders in the cohort, we did not analyse them individually; however, they were included when calculating the number of individuals with one or more DSM-5 diagnosis (see Table III). Subsequently, we examined reported sources of help-seeking by overall screening status (screen positive/negative), and by individual DAWBA screening item. Finally, we examined the proportion of those in contact with different types of services who screened positive. We used a multinomial logistic regression model to examine associations between sociodemographic characteristics and reported service contact in individuals who screened positive for a possible eating problem. Results are reported as relative risk ratios (RRRs) with associated 95% confidence intervals. The outcome variable was reported help-seeking category, defined using the previously described hierarchical classification system ((1) no help (ref); (2) informal help only; (3) formal help; and (4) secondary healthcare). The following predictor variables were included in the model and treated as categorical: age group (11 to 16 years, 17 to 19 years); sex (male, female); housing tenure (owner occupied, private rented, socially rented); and ethnicity (White, minoritised ethnic backgrounds). Calibrated survey weights accounting for clustering were applied using Stata’s ‘svy’ command. In the unweighted dataset, some service-contact categories had small cell counts (< 10 in one case; see Supplementary material Table SII). Therefore, ethnicity was modelled as a dichotomous variable to improve model stability. Strengths and limitations of this approach are discussed in the Discussion section. Ethical approval All secondary analyses were approved by the University of Exeter Medical School REC (Nov20/D/270), and the MHCYP2017 data were accessed under a data sharing agreement with NHS England (DARS-NIC-424336-T7K7T-). Data are reported using ONS statistical disclosure control guidance[27]. Results Overall, 1,430 (36.4%) children and young people aged 11 to 19 screened positive for a possible eating problem. In those aged 11 to 16, 32.0% (95% CI 30.1, 33.7) screened positive, compared with 45.1% (95% CI 41.8, 48.4) of those aged 17 to 19. Rates of possible eating problems were lower in young men (25.7%, 95% CI 23.7, 27.8) than young women (47.6%, 95% CI 45.3, 50). Of those meeting criteria for any DSM-5 disorder, around half (51.3%, 95% CI 47.3, 55.4) screened positive for a possible eating problem. This figure was higher for those with an anxiety disorder (63.8%, 95% CI 58.4, 68.8) or a depressive disorder (67.7%, 95% CI 59.3, 75.0). There was no significant difference based on ethnicity or housing tenure. Table III displays the characteristics of the MHCYP 2017 cohort by possible eating problem status. Table III: Cohort characteristics by possible eating problem screening status using the DAWBA eating disorder screening module (weighted row percentages; non-weighted n given) Variable Total Screen positive n, %(95% CI) Age 11 to 16 years 3,121 999 32.0% (30.3, 33.7) 17 to 19 years 936 427 45.1% (41.8, 48.4) Sex Male 2,032 511 25.7% (23.7, 27.8) Female 1,426 915 47.6% (45.3, 50.0) Ethnicity White 3,255 1,159 37.0% (35.2, 39.0) Black/Afro-Caribbean 162 48 30.9% (23.7, 39.0) Asian 406 131 33.6% (28.9, 38,7) Mixed 233 88 39.9% (33.3, 46.9) Tenure Owner of home 2,608 897 35.3% (33.3, 37.3) Private rented 610 219 38.0% (33.8, 42.2) Socially rented 770 271 36.1% (32.6, 40.0) Presence of DSM-5 disorder Any DSM diagnosis 686 332 51.3% (47.3, 55.4) Two or more DSM diagnoses 249 130 55.9% (49.3, 62.3) Anxiety disorders 372 223 63.8% (58.4, 68.8) Depressive disorders 148 95 67.7% (59.3, 75.0) ASD s* s* 17.9% (8.60, 33.5) Total N = 4,060 1,430 36.4% (34.8, 38.1) *Suppressed due to small numbers. Totals have been rounded to the nearest 5 according to statistical disclosure guidance. Reported service contact Among all participants, 68.2% (95% CI 66.6, 69.8) reported no contact for mental health concerns. Furthermore, 81.2% of those screening negative, and 73.8% of those screening positive for a possible eating problem reported no contact with professional services (formal or secondary health). Participants screening positive were more likely to report contact with each category of support (Table IV). For example, a higher proportion of young people screening positive (9.17%, 95% CI 7.67, 10.9) were in contact with specialist services compared to those screening negative (6.06%, 95% CI 5.15, 7.12). Table IV: Sources of help for mental health concerns amongst adolescents aged 11 to 19 with a possible eating problem (weighted row percentages, non-weighted n given) No contact (%, (95% CI)) Informal only (%, (95% CI)) Formal (%, (95% CI)) Secondary healthcare (%, (95% CI)) Total (n) Screen negative 72.6 (70.6, 74.4) N = 1,925 8.60 (7.40, 9.97) N = 182 12.8 (11.5, 14.2) N = 336 6.06 (5.15, 7.12) N = 161 2,604 Screen positive 60.7 (57.9, 63.4) N = 898 13.1 (11.2, 15.4) N = 149 17.0 (15.0, 19.3) N = 240 9.17 (7.67, 10.9) N = 134 1,421 Total (n & row%) 68.2 (66.6, 69.8) N = 2,823 10.3 (9.20, 11.4) N = 331 14.3 (13.2, 15.5) N = 576 7.20 (6.38, 8.11) N = 295 4,025 Help seeking and service contact by symptom type Figure 1 displays reported service contact among young people who endorsed each DAWBA eating disorder screening items, as outlined in Table I. All proportions and 95% confidence intervals for each category of help by screening item are provided in Supplementary material Table SIII. Among those endorsing each item the majority reported no help-seeking, apart from eating-related worries for which the proportion of individuals reporting no help-seeking was 48% (95% CI 42.8, 53.7). The item with the highest proportion reporting no-help seeking was thinking they were fat when others thought they were very thin (62.2%, 95% CI 59.4, 64.9). Young people who had any reported purging were more likely to have contact with professional or secondary healthcare services than with informal sources of help. However, 51.7% (95% CI 44.5, 58.9) of those reporting purging did not report contact with any source of help in the year prior to the survey. Figure 1: Help seeking by item Figure 1: Reported help-seeking and service contact over the past year among individuals with a positive response (parent or self-reported) to each DAWBA screening item (see Table I). Screening positive by source of help or service contact Figures 3 and 4 display the proportion of respondents with possible eating problems among all participants reporting contact with different sources of support. For most services (except child health), between 40% to 50% of young people reporting contact were screen positive; however, confidence intervals overlap for the majority of service types (see Supplementary material Table IV). Figure 2: Proportion of young people screening positive for a possible eating problem by category of help Figure 2: See Table II for details of each category. Note results are weighted; 95% CI. Figure 3: Proportion of young people screening positive for a possible eating problem by specific sources of help Figure 3: See Table II for details of help sources. Note results are weighted; 95% CI. Regression analysis of help seeking in individuals screening positive for possible eating problems Table V displays the results of the weighted multinomial logistic regression examining reported help-seeking for mental health concerns among adolescents screening positive for possible eating problems. Model diagnostics were satisfactory (see Supplementary material SV to SXVI for details). Age, ethnicity, and presence of any DSM-5 diagnosis were significantly associated with patterns of help-seeking in this subgroup, whereas sex and household income were not. Compared with young people aged 11 to 16, those aged 17 to 19 were more likely to report contact with informal (RRR = 8.49, 95% CI 5.65, 12.8, p < 0.001), formal (RRR = 1.54, 95% CI 1.07, 2.21, p = 0.021) and secondary healthcare (RRR = 2.07, 95% CI 1.29, 3.30, p = 0.002) sources. Compared with White participants, those from minoritised ethnic backgrounds were less likely to report contact with secondary healthcare (RRR = 0.28, 95% CI 0.11, 0.68, p = 0.005). Young people with a DSM-5 diagnosis were more likely to report contact with informal (RRR = 1.84, 95% CI 1.08, 3.12, p = 0.024), formal (RRR = 4.22, 95% CI 2.91, 6.12, p < 0.001), and secondary healthcare (RRR = 21.4, 95% CI 12.8, 35.8, p < 0.001) sources, compared with those without. Informal only Professional Secondary healthcare Predictor RRR (95% CI) p RRR (95% CI) p RRR (95% CI) p Age group (ref = 11 to 16 years) 17 to 19 years 8.49 (5.65, 12.8) <0.001 1.54 (1.07, 2.21) 0.021 2.07 (1.29, 3.30) 0.002 Sex (ref = male) Female 0.74 (0.49, 1.12) 0.150 1.32 (0.93, 1.88) 0.118 1.53 (0.96, 2.45) 0.077 Housing tenure (ref = owned) Private rented 1.47 (8.46, 2.54) 0.172 1.09 (0.69, 1.72) 0.706 0.76 (0.39, 1.48) 0.415 Social rented 1.08 (0.62, 1.88) 0.789 0.94 (0.62, 1.44) 0.782 0.73 (0.41, 1.29) 0.278 Ethnicity (ref = White) Minoritised ethnic background 0.63 (0.36, 1.10) 0.107 0.64 (0.40, 1.01) 0.057 0.28 (0.11, 0.68) 0.005 DSM diagnosis (ref = No concurrent diagnosis) Any DSM5 comorbidity 1.84 (1.08, 3.12) 0.024 4.22 (2.91, 6.12) <0.001 21.4 (12.8, 35.8) <0.001 Table V: Estimates are relative risk ratios (RRRs) from multinomial logistic regression model. See Methods for model specification. Bold values indicate p F < 0.001. Table V: Multinomial regression analysis of help seeking Discussion This study used a nationally representative probability sample of children and young people to examine (a) contact with sources of help among those screening positive for a possible eating problem and (b) prevalence of possible eating problems among those reporting contact with sources of help for any mental health concern. Throughout this discussion, help-seeking and service contact refer to reported contact for any mental health concern, and “possible eating problems” denotes those screening positive on DAWBA screening items rather than a clinical diagnosis. Overall, those with a possible eating problem were more likely than those without to report contact with sources of help, although almost three-quarters did not report any contact with a professional service (Table 3). Notably, around one-third of those who reported no contact with sources of help screened positive for a possible eating problem. Approximately half of young people reporting contact with a mental health specialist and almost half of those reporting contact with teachers or primary care screened positive. Among those screening positive, older adolescents (17 to 19 years) and those with a DSM-5 comorbidity were significantly more likely to report contact across all categories of support, while those from minoritised ethnic backgrounds were markedly less likely to report secondary healthcare contact. We found no association between help-seeking and sex or housing tenure (Table 6). Older adolescents (17 to 19 years) were more likely to report contact with all categories of mental health support compared with those aged 11 to 16 years. This contrasts with previous analysis of MHCYP 2017 data, which showed that while rates of professional service contact were similar across these age groups in the full sample (21.5% vs 22.0%), older adolescents with a DSM-5 diagnosable mental disorder were less likely than younger adolescents to report service contact[25]. Further work is needed to understand possible explanations for this finding; for example, whether disordered eating in older adolescents is associated with greater symptom salience, distress, or functional impairment that prompts help-seeking. Greater service contact among those with a DSM-5 diagnosis likely reflects the recognised link between clinical complexity and increased help-seeking. This finding is consistent with international evidencethat psychiatric comorbidity is linked to increased service use[28,29]. Controlling for DSM-5 diagnostic status in our model ensures associations between age, ethnicity, and help-seeking are not explained by differences in diagnosable mental health conditions. Among young people screening positive for a possible eating problem, those from minoritised ethnic backgrounds were less likely to report secondary-healthcare contact. This finding is consistent with previous analyses of the MHCYP 2017 dataset, which found that children from Black and Asian backgrounds were less likely than White peers to report contact with professional mental health services, after adjustment for DSM-5 disorder status and sociodemographic factors[30]. A Canadian study reported similar findings among immigrant, refugee, racial and ethnic minoritised youth, after adjusting for symptom severity and perceived need[31]. Together, these findings suggest that ethnic disparities in service use are not explained by clinical need and may reflect structural or cultural barriers to accessing care. Although possible eating problems were more common in females than males, sex was not significantly associated with help-seeking or service contact among those screening positive. This aligns with previous analyses of the MHCYP 2017 dataset, which also found comparable rates of professional contact in females (20.0%) and males (22.2%)[25]. These findings suggest that the greater proportion of females in eating disorder populations may primarily reflect underlying sex differences in prevalence rather than disparities in help-seeking. We found no evidence that housing tenure was associated with help-seeking among adolescents with possible eating problems.This contrasts with previous analyses of MHCYP 2017 data, which found that 11 to 16 year-olds living in private or socially rented housing had significantly lower odds of specialist mental health contact compared with those in owner-occupied homes[30], but aligns with previous studies reporting no consistent association between socioeconomic position and help-seeking for eating disorders[32–34]. Of note, young people with ASD were less likely to screen positive for possible eating problems. Emerging literature suggests that eating difficulties in young people with ASD may be more closely associated with sensory processing and “feeding problems”, rather than preoccupation with food, eating or body image, which the DAWBA screening module primarily assesses[35,36]. However, given the low numbers in this sample, (Table III), the dataset is underpowered to support reliable population-level inference. Our findings add to the relatively sparse literature on help-seeking and eating problems amongst young people. Estimated rates of help-seeking from other studies vary from around 8% to 66%[37] , likely due to how help seeking is defined and measured. Our finding of a help-seeking rate of 39.3% among those with a possible eating problem sits within this range. One reason for low rates of mental health related service contact in individuals who screen positive for eating problems could be that these young people do not ‘need’ help. A recent study reports the positive predictive value of screening positive for a clinical eating disorder using the DAWBA to be very low, so the majority who screen positive are unlikely to meet full criteria for an eating disorder [24]. Furthermore, as we used survey data from one time point, difficulties may have been transitory. However, some young people with eating problems may experience distress or impairment and therefore benefit from identification and support. It is concerning that over half of individuals who reported purging reported no contact with any source of support for a mental health concern in the past year. A review by the UK charity Beat found that the average length of time between someone developing an eating disorder and realizing they had an eating disorder was 69 weeks, followed by 39 weeks before seeking help from a GP[38]. Reported barriers to help seeking include stigma and fear of disclosure, low self-perceived severity of eating behaviors, minimal support from family and friends, and experiences with healthcare providers who lacked knowledge about eating disorders or dismissed parental concerns[15]. Relatively high proportions of young people who reported contact with professional services screened positive for possible eating problems. It is therefore important for professionals to have awareness of eating difficulties and disorders, the difference between the two, and the potential for “atypical” presentations.Recent findings from England’s national child mental health surveys indicate the prevalence of ‘other’ eating disorders have risen over time[6]. Despite this, education and assessment on eating disorders remain limited in UK medical education, prompting initiatives like Beat’s training for medical students and foundation doctors[39,40]. It is important that professionals are aware that they are likely to be in contact with adolescents with possible eating problems and are equipped to appropriately identify and refer individuals needing further assessment. This study has several strengths, notably it uses a national probability sample of 11 to 19 year-olds, thus allowing the study of both those who are, and are not, in contact with services. It also includes self-reported and parent-reported symptoms through use of the DAWBA. The DAWBA screening module was designed to rule out eating disorders, and as such it has a high sensitivity[24]. However it has low specificity and a low positive predictive value (2.4% for children aged 11 to 16 and 2.5% for those aged 17 to 19 years)[24]. As such, the DAWBA is well suited for our aim to examine service contact and possible eating problems in a population sample of young people. However, due to the focus on symptoms characteristic of anorexia nervosa and bulimia nervosa[24], the DAWBA screening questions may not be as good at identifying other eating disorders or conditions such as binge eating or purging disorder. Additionally, the self-reported and retrospective nature of service contact data may introduce bias. For those aged 11 to 16, we used parent-reported service contact, which may be limited by the parent’s knowledge of their child’s help-seeking. Importantly, we do not know whether participants sought help regarding eating concerns, or a different mental health concern, or what happened subsequently. Despite the large population sample, we used a dichotomised measure of ethnicity to improve the stability of our regression model. Whilst this allows a less nuanced assessment of the relationship between ethnicity and service contact, it allowed us to include ethnicity in our model and is consistent with how data on ethnicity from MHCYP has previously been used [25]. The use of longitudinal linked data could help address these limitations in future research. Linking primary and secondary care data would allow symptoms, service contact and referral pathways to be tracked over time, including pre-and post-pandemic. Qualitative studies may further understanding of what enables and hinders help-seeking among adolescents with eating problems. Longitudinal population studies should also investigate long-term trajectories and outcomes of adolescents with eating difficulties, including progression to eating disorders or other conditions, and broader health outcomes. Conclusion A high proportion of adolescents in this nationally representative English survey screen positive for a possible eating problem. Most of those screening positive did not report any contact with sources of mental health support. Around half of those in contact with specialist mental health services and almost half of those in contact with teachers or primary care for mental health concerns reported eating difficulties; clinicians and teachers should be alert to these problems as they may not be disclosed. Within the subgroup of young people with possible eating problems, older adolescents, and those with a comorbid DSM-5 disorder were more likely to report contact with informal, formal, and secondary-care sources, while those from minoritised ethnic backgrounds were less likely to report contact with secondary care. Future work should examine the clinical course and treatment journeys of adolescents with possible eating problems. Declarations Author contributions All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by BG and TND. The first draft of the manuscript was written by BG and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. Data availability The MHCYP 2017 dataset is archived with the UK Data Service. Approval for access to the MHYCP data can be obtained through the UK Data Service Data Access Request Service. Rights retention For the purpose of open access, the author has applied a Creative Commons Attribution (CC BY) license to any Author Accepted Manuscript version arising from this submission. Competing interests: BG, HB, TF and TND have no relevant financial or non-financial interests to disclose. This report is independent research. HB was supported by an NIHR Advanced Fellowship (302271). BG was supported by an NIHR Academic Clinical Fellowship (ACF-2024-23-010) . TF’s research group receives funding from Place2Be, a third sector organisation that provides mental health training and interventions in UK schools. All research at the Department of Psychiatry in the University of Cambridge is supported by the NIHR Cambridge Biomedical Research Centre (NIHR203312) and the NIHR Applied Research Collaboration East of England. The views expressed in this publication are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care. Acknowledgements BG would like to acknowledge the support of the Royal College of Psychiatrists Faculty of Eating Disorders Psychiatry for awarding him a research bursary to support presenting this work and related projects. Ethic approval The MHCYP-2017 survey received approvals from the West London & GTAC Research Ethics Committee (reference: 16/LO/0155) and the Health Research Authority Confidentiality Advisory Group (reference: 16/CAG/0016) [18]. TND obtained ethical approval for secondary analysis of the MHCYP-2017 data via the University of Exeter College of Medicine and Health Research Ethics Committee (reference: Nov20/D/270). The study was performed in accordance with the ethical standards as laid down in the 1964 Declaration of Helsinki and its later amendments. References Arcelus J, Mitchell AJ, Wales J et al (2011) Mortality rates in patients with anorexia nervosa and other eating disorders. A meta-analysis of 36 studies. Arch Gen Psychiatry 68:724–731. https://doi.org/10.1001/archgenpsychiatry.2011.74 Gonzalez A, Kohn MR, Clarke SD (2007) Eating disorders in adolescents. Aust Fam Physician 36:614–619 Hoang U, Goldacre M, James A (2014) Mortality following hospital discharge with a diagnosis of eating disorder: national record linkage study, England, 2001–2009. 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Euro Eat Disorders Rev 29:329–345. https://doi.org/10.1002/erv.2745 Royal College of Psychiatrists (2019) Position statement on early intervention for eating disorders Herpertz-Dahlmann B, Wille N, Hölling H et al (2008) Disordered eating behaviour and attitudes, associated psychopathology and health-related quality of life: results of the BELLA study. Eur Child Adolesc Psychiatry 17:82–91. https://doi.org/10.1007/s00787-008-1009-9 Steinhausen H-C, Gavez S, Winkler Metzke C (2005) Psychosocial correlates, outcome, and stability of abnormal adolescent eating behavior in community samples of young people. Int J Eat Disord 37:119–126. https://doi.org/10.1002/eat.20077 Kärkkäinen U, Mustelin L, Raevuori A et al (2018) Do Disordered Eating Behaviours Have Long-term Health-related Consequences? Eur Eat Disord Rev 26:22–28. https://doi.org/10.1002/erv.2568 Hart LM, Granillo MT, Jorm AF et al (2011) Unmet need for treatment in the eating disorders: A systematic review of eating disorder specific treatment seeking among community cases. Clin Psychol Rev 31:727–735. https://doi.org/10.1016/j.cpr.2011.03.004 Mond JM, Hay PJ, Rodgers B et al (2007) Health service utilization for eating disorders: Findings from a community-based study. Intl J Eat Disorders 40:399–408. https://doi.org/10.1002/eat.20382 Nicula M, Pellegrini D, Grennan L et al (2022) Help-seeking attitudes and behaviours among youth with eating disorders: a scoping review. J Eat Disord 10:21. https://doi.org/10.1186/s40337-022-00543-8 McNicholas F, O’Connor C, McNamara N et al (2018) Eating disorder services for young people in Ireland: perspectives of service providers, service users and the general adolescent population. Ir J Psychol Med 35:301–309. https://doi.org/10.1017/ipm.2015.66 Sparti C, Santomauro D, Cruwys T et al (2019) Disordered eating among Australian adolescents: Prevalence, functioning, and help received. Intl J Eat Disorders 52:246–254. https://doi.org/10.1002/eat.23032 Goodman R, Ford T, Richards H et al (2000) The Development and Well-Being Assessment: description and initial validation of an integrated assessment of child and adolescent psychopathology. J Child Psychol Psychiatry 41:645–655 Volpe U, Tortorella A, Manchia M et al (2016) Eating disorders: What age at onset? Psychiatry Res 238:225–227. https://doi.org/10.1016/j.psychres.2016.02.048 Ward ZJ, Rodriguez P, Wright DR et al (2019) Estimation of Eating Disorders Prevalence by Age and Associations With Mortality in a Simulated Nationally Representative US Cohort. JAMA Netw Open 2:e1912925. https://doi.org/10.1001/jamanetworkopen.2019.12925 NHS Digital (2018) Mental Health of Children and Young People in England, 2017 Moya T, Fleitlich-Bilyk B, Goodman R et al (2005) The Eating Disorders Section of the Development and Well-Being Assessment (DAWBA): development and validation. Braz J Psychiatry 27:25–31. https://doi.org/10.1590/s1516-44462005000100008 Lydecker JA, Grilo CM (2019) I Didn’t Want Them to See: Secretive Eating among Adults with Binge-Eating Disorder. Int J Eat Disord 52:153–158. https://doi.org/10.1002/eat.23002 O’Logbon J, Newlove-Delgado T, McManus S et al (2022) How does the increase in eating difficulties according to the Development and Well-Being Assessment screening items relate to the population prevalence of eating disorders? An analysis of the 2017 Mental Health in Children and Young People survey. Int J Eat Disord 55:1777–1787. https://doi.org/10.1002/eat.23833 Mathews F, Ford TJ, White S et al (2024) Children and young people’s reported contact with professional services for mental health concerns: a secondary data analysis. Eur Child Adolesc Psychiatry 33:2647–2655. https://doi.org/10.1007/s00787-023-02328-z American Psychiatric Association (2013) Diagnostic and statistical manual of mental disorders, 5th edn. American Psychiatric Publishing Office for National Statistics Disclosure control https://www.ons.gov.uk/methodology/methodologytopicsandstatisticalconcepts/disclosurecontrol . Accessed 30 September 2025 Merikangas KR, He J, Burstein M et al (2011) Service utilization for lifetime mental disorders in U.S. adolescents: results of the National Comorbidity Survey-Adolescent Supplement (NCS-A). J Am Acad Child Adolesc Psychiatry 50:32–45. https://doi.org/10.1016/j.jaac.2010.10.006 Costello EJ, He J, Sampson NA et al (2014) Services for adolescent psychiatric disorders: 12-month data from the National Comorbidity Survey-Adolescent. Psychiatr Serv 65:359–366. https://doi.org/10.1176/appi.ps.201100518 Trethewey SP, Mathews F, Russell A et al (2025) Socio-demographic and clinical characteristics associated with mental health-related support and service contact in children and young people aged 5–16 in England. Eur Child Adolesc Psychiatry 34:2599–2608. https://doi.org/10.1007/s00787-025-02666-0 Kamali M, Edwards J, Anderson LN et al (2023) Social Disparities in Mental Health Service Use Among Children and Youth in Ontario: Evidence From a General, Population-Based Survey. Can J Psychiatry 68:596–604. https://doi.org/10.1177/07067437221144630 Fatt SJ, Mond J, Bussey K et al (2020) Help-seeking for body image problems among adolescents with eating disorders: findings from the EveryBODY study. Eat Weight Disord 25:1267–1275. https://doi.org/10.1007/s40519-019-00759-9 Regan P, Cachelin FM, Minnick AM (2017) Initial treatment seeking from professional health care providers for eating disorders: A review and synthesis of potential barriers to and facilitators of first contact. Int J Eat Disord 50:190–209. https://doi.org/10.1002/eat.22683 Huryk KM, Drury CR, Loeb KL (2021) Diseases of affluence? A systematic review of the literature on socioeconomic diversity in eating disorders. Eat Behav 43:101548. https://doi.org/10.1016/j.eatbeh.2021.101548 Baraskewich J, von Ranson KM, McCrimmon A et al (2021) Feeding and eating problems in children and adolescents with autism: A scoping review. Autism 25:1505–1519. https://doi.org/10.1177/1362361321995631 Nadon G, Feldman DE, Dunn W et al (2011) Association of Sensory Processing and Eating Problems in Children with Autism Spectrum Disorders. Autism Res Treat 2011:541926. https://doi.org/10.1155/2011/541926 Ali K, Radunz M, McLean SA et al (2025) The Unmet Treatment Need for Eating Disorders: What Has Changed in More Than 10 Years? An Updated Systematic Review and Meta-Analysis. Int J Eat Disord 58:46–65. https://doi.org/10.1002/eat.24306 Beat (2017) Delaying for years, denied for months Ayton A, Ibrahim A (2018) Does UK medical education provide doctors with sufficient skills and knowledge to manage patients with eating disorders safely? Postgrad Med J 94:374–380. https://doi.org/10.1136/postgradmedj-2018-135658 Beat Training for Medical Students and Foundation Doctors https://www.beateatingdisorders.org.uk/get-information-and-support/training-for-professionals/training-for-healthcare-clinical-professionals/eating-disorders-training-for-medical-students-and-foundation-doctors/ . Accessed 13 October 2021 Additional Declarations Competing interest reported. BG, HB, TF and TND have no relevant financial or non-financial interests to disclose. This report is independent research. HB was supported by an NIHR Advanced Fellowship (302271). BG was supported by an NIHR Academic Clinical Fellowship (ACF-2024-23-010). TF’s research group receives funding from Place2Be, a third sector organisation that provides mental health training and interventions in UK schools. All research at the Department of Psychiatry in the University of Cambridge is supported by the NIHR Cambridge Biomedical Research Centre (NIHR203312) and the NIHR Applied Research Collaboration East of England. The views expressed in this publication are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care. Supplementary Files SupplementarymaterialMentalhealthrelatedservicecontactamongstyoungpeoplewithapossibleeatingproblemintheEnglishnationalchildmentalhealthsurveys.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 14 May, 2026 Reviews received at journal 08 May, 2026 Reviews received at journal 14 Apr, 2026 Reviewers agreed at journal 09 Apr, 2026 Reviewers agreed at journal 30 Mar, 2026 Reviewers agreed at journal 29 Mar, 2026 Reviewers invited by journal 28 Mar, 2026 Editor assigned by journal 17 Feb, 2026 Submission checks completed at journal 17 Feb, 2026 First submitted to journal 15 Feb, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8886674","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":614307109,"identity":"da210a88-824d-4a38-8ebd-2dbc752692d4","order_by":0,"name":"Benjamin Geers","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA4UlEQVRIiWNgGAWjYBACAygthyzITJQWYyBmbCBJS2ID0VrMGdgvPvi4py69XyL5OJDBIM/fwGNsgE+LZQNPseGMZ4dzZ/YcS2yc8YzBcMYBHuMEvA47wJMmzXPgQO6G4z2GzTwHGBg3MPAYHyCgJf33nwN16faH+T82/znAYE+EFvZjzAwHmBMM2HsYmxkOMCSCtOB1mGUzD7Nkz4HDhjPOHDOc2XNAInnGYbZivN43Z29/+OHHgTp5/hnJD4AMG9v+9ubNEvi0MDDzoBgpQShWQID9AUElo2AUjIJRMMIBAKFqSUNIeP1eAAAAAElFTkSuQmCC","orcid":"","institution":"University of Exeter","correspondingAuthor":true,"prefix":"","firstName":"Benjamin","middleName":"","lastName":"Geers","suffix":""},{"id":614307111,"identity":"4a83d9a0-fdc5-4b83-b49d-89baa9397549","order_by":1,"name":"Helen Bould","email":"","orcid":"","institution":"NIHR Bristol Biomedical Research Centre","correspondingAuthor":false,"prefix":"","firstName":"Helen","middleName":"","lastName":"Bould","suffix":""},{"id":614307112,"identity":"ca9ac745-f6ff-424f-8d38-ec513c47e687","order_by":2,"name":"Tamsin Ford","email":"","orcid":"","institution":"University of Cambridge","correspondingAuthor":false,"prefix":"","firstName":"Tamsin","middleName":"","lastName":"Ford","suffix":""},{"id":614307113,"identity":"06664d5b-c41c-47e7-bb65-be5a4ef7f412","order_by":3,"name":"Tamsin Newlove-Delgado","email":"","orcid":"","institution":"University of Exeter","correspondingAuthor":false,"prefix":"","firstName":"Tamsin","middleName":"","lastName":"Newlove-Delgado","suffix":""}],"badges":[],"createdAt":"2026-02-15 14:38:10","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8886674/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8886674/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":106058063,"identity":"26bc9e15-d2b2-4156-99f5-342b117b7532","added_by":"auto","created_at":"2026-04-03 02:15:54","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":74956,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eHelp seeking by item\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eReported help-seeking and service contact over the past year among individuals with a positive response (parent or self-reported) to each DAWBA screening item (see Table I).\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8886674/v1/ac672748649d6de64e2329ed.png"},{"id":106058065,"identity":"8bbbb8f0-28ca-420c-b876-38c7cb7f8fe7","added_by":"auto","created_at":"2026-04-03 02:15:54","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":60661,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eProportion of young people screening positive for a possible eating problem by category of help\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSee Table II for details of each category. Note results are weighted; 95% CI.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-8886674/v1/71fb835953c7179caacc4340.png"},{"id":106058064,"identity":"586375f9-245e-432e-bece-3b2416436214","added_by":"auto","created_at":"2026-04-03 02:15:54","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":68142,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eProportion of young people screening positive for a possible eating problem by specific sources of help\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSee Table II for details of help sources. Note results are weighted; 95% CI.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-8886674/v1/0135cc946c8b8566e402124f.png"},{"id":106402372,"identity":"deb1c8b5-dd7b-4924-8d3b-b91aafa77054","added_by":"auto","created_at":"2026-04-08 09:11:53","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1553030,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8886674/v1/447db46d-3e0c-473c-a468-c3fea9d0bed0.pdf"},{"id":106058062,"identity":"fd517a1c-fdbe-420e-9737-0a9ab342e3df","added_by":"auto","created_at":"2026-04-03 02:15:54","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":93399,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementarymaterialMentalhealthrelatedservicecontactamongstyoungpeoplewithapossibleeatingproblemintheEnglishnationalchildmentalhealthsurveys.docx","url":"https://assets-eu.researchsquare.com/files/rs-8886674/v1/296407181edf59b66b76849c.docx"}],"financialInterests":"Competing interest reported. BG, HB, TF and TND have no relevant financial or non-financial interests to disclose. This report is independent research. HB was supported by an NIHR Advanced Fellowship (302271). BG was supported by an NIHR Academic Clinical Fellowship (ACF-2024-23-010). TF’s research group receives funding from Place2Be, a third sector organisation that provides mental health training and interventions in UK schools. All research at the Department of Psychiatry in the University of Cambridge is supported by the NIHR Cambridge Biomedical Research Centre (NIHR203312) and the NIHR Applied Research Collaboration East of England. The views expressed in this publication are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care.","formattedTitle":"Mental health-related service contact amongst young people with a possible eating problem in the English national child mental health surveys","fulltext":[{"header":"Introduction","content":"\u003cp\u003eEating disorders, including anorexia nervosa, bulimia nervosa and binge-eating disorder, are the third most common chronic illness in adolescence and are associated with high psychiatric morbidity and mortality, with over half of individuals not achieving recovery[\u003cspan additionalcitationids=\"CR2 CR3\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. They have significant economic burden: in 2020, the total cost of eating disorders in the UK was \u0026pound;9.4 billion[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Prevalence of eating disorders in children and young people appears to be increasing over time: the Mental Health of Children and Young People (MHCYP) in England 2023 survey found the prevalence of any eating disorder was 2.6% in 11 to 16 year olds and 12.5% in 17 to 19 year olds, a substantial increase from 2017, although methodological differences between the surveys should be noted[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eEarly intervention in eating disorders has been shown to improve outcomes. Optimal outcomes are associated with treatment commencing within the first three years of illness onset and shorter duration of untreated eating disorders [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Thus, early identification and treatment is central to improving chances of recovery[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Those with less severe or sub-clinical eating difficulties may still experience distress or impairment and may benefit from identification and support, including assessment or treatment for co-occurring physical or mental health problems associated with eating difficulties, such as depression, anxiety and substance misuse[\u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eHowever, many studies assessing help-seeking and service contact in eating difficulties focus on adult populations, only include those with a medical diagnosis of eating disorders (and thus do not account for low rates of help-seeking), or rely on retrospective reports of those who have already sought help[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Consequently, there is a gap in the evidence regarding help-seeking and eating problems amongst young people in population samples.\u003c/p\u003e \u003cp\u003eEstimates of help-seeking among adolescents with eating disorders or eating problems vary. A 2022 scoping review reported that many young people who met criteria for a clinical or subclinical eating disorder were not receiving help and did not intend to seek it, with help-seeking rates ranging from 10% to 85%[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. However, direct comparison between studies was limited due to methodological heterogeneity. Research suggests that adolescents with eating problems often seek support from informal rather than professional sources. For example, studies in Ireland and Australia have found that family, friends or self-help were more commonly utilised than professional sources for support for eating problems[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eGiven the importance of early intervention, it is crucial to understand which sources of support adolescents with possible eating problems are in contact with. This can inform efforts to identify those who might benefit from further assessment and treatment, and ensure that professionals who may be in contact with such young people have the appropriate training. This is especially important as adolescents with eating disorders may not be aware that they have a problem in the early stages of their illness, when treatment may be most beneficial.\u003c/p\u003e\n\u003ch3\u003eResearch question and objectives\u003c/h3\u003e\n\u003cp\u003eOur primary objective was to examine patterns of reported service contact in a national probability sample of young people in England with a possible eating problem, assessed using the Development and Wellbeing Assessment (DAWBA) Eating Disorder Module screening questions[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e"},{"header":"Methods","content":" \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy population\u003c/h2\u003e \u003cp\u003eWe used data from the NHS England Mental Health of Children and Young People in England 2017 survey of 9,117 children and young people aged 2 to 19 years and their parents and teachers across England. The sample was recruited through a stratified multistage random probability sample of 18,029 addresses of children from the NHS Patient Register, designed to be representative of the population. Of the 18,029 addresses issued, 2% were ineligible. Of the eligible addresses (n\u0026thinsp;=\u0026thinsp;17,636) 28% refused, 12% had no further contact and 8% were classed as \u0026lsquo;other unproductive\u0026rsquo;. Data was successfully collected from 9,117 (52%) households, resulting in 9,117 children and young people interviewed. For this analysis, we included participants aged 11 to 19 (n\u0026thinsp;=\u0026thinsp;4,057), as this group is more at risk of eating difficulties[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \n\u003ch3\u003eProcedure\u003c/h3\u003e\n\u003cp\u003e Each young person and one of their parents were invited to complete a face-to-face interview with a trained lay interviewer. For children aged 16 and younger, parents were interviewed first, and then parental consent was sought to interview their child; for 17 to 19 year-olds, consent was requested from the young person and subsequently sought from them to interview their parents.\u003c/p\u003e \u003cp\u003eFurther information about the Mental Health of Children and Young People 2017 cohort and sampling process is available in the NHS Digital report[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eMeasures\u003c/h3\u003e\n\u003cp\u003eThe key measures used in our secondary analysis are described below:\u003c/p\u003e\n\u003ch3\u003eThe Development and Wellbeing Assessment\u003c/h3\u003e\n\u003cp\u003eThe Development and Wellbeing Assessment (DAWBA) was used to assess mental health conditions in participants[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. The DAWBA is a standardised diagnostic assessment in which modules map to most common childhood mental health conditions. Participants complete \u0026ldquo;screening items\u0026rdquo; for each module, and individuals who report any difficulties related to the relevant disorder go on to complete the rest of the module, in which structured questions relate directly to diagnostic criteria while semi-structured questions probe context and impairment. Individuals who do not report potential difficulties when responding to the screening questions are moved onto the next module, reducing responder burden. A team of expert clinical raters reviewed data from informants assigning diagnoses according to both DSM-5 and ICD-10 criteria. Responses to the screening questions of the Eating Disorders module of the DAWBA were used to define \u0026lsquo;possible eating problems\u0026rsquo; (Table I).\u003c/p\u003e \u003cp\u003e \u003cb\u003eTable I: DAWBA screening module questions\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDAWBA full statements\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCorresponding Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e1\u003c/span\u003e Labels\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHave you deliberately made yourself vomit (throw up)?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePurging\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHave you ever thought you were fat when other people told you that you were \u003cem\u003every\u003c/em\u003e thin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThought fat\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDo your worried about eating (What? Where? How much?) really interfere with your life?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEating worries\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIf you eat too much, do you blame yourself a lot?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSelf-blame\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWould you be ashamed if other people knew how much you eat?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eShame\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eYoung people were classified as having a possible eating problem (i.e. \u0026lsquo;screen positive\u0026rsquo;) using standard cut-off thresholds (Supplementary material SI, [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]) of answering yes to one or more items, or their parent answering yes to two or more parent-reported items. The threshold for screening positive for a possible eating problem is lower for self-reported symptoms, due to the commonly secretive nature of eating disorder symptoms[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. A previous test accuracy study reported that for 11\u0026ndash;16 year olds, the DAWBA screening items had a sensitivity of 100% and specificity of 55%. In 17 to 19 year olds, sensitivity was 100% and specificity was 48% [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eService contact\u003c/h3\u003e\n\u003cp\u003eRespondents were asked if they (or their child for parents) had contact with a range of informal support and professional services for any mental health concern over the previous year. We then classified sources of help as informal, formal and secondary healthcare[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e](see Table II).\u003c/p\u003e \u003cp\u003e \u003cb\u003eTable II: Categories of help, classified as Informal, Formal and Secondary healthcare\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Tabb\" border=\"1\"\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInformal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFormal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSecondary healthcare\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFriends and Family, e.g. \u0026lsquo;someone in your family or a close friend\u0026rsquo;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrimary care professional, e.g. GP, health visitor, practice nurse or school nurse\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMental health specialist, e.g. mental health nurse, psychiatrist, psychologist or counsellor\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTelephone help, e.g. Samaritans, NHS 111, Young Minds Textline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTeacher, e.g. form tutor, head of year, head teacher or coordinator\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eChild physical health specialist, e.g. hospital or community paediatrician,\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSelf help, e.g. self help groups or organisations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAdditional educational support, e.g. educational psychologist, educational social worker or specialist teacher from outside of school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInternet help, e.g NHS or government websites, charity websites, blogs, online communities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSocial care, e.g a social worker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYouth justice services\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eWe classified service contact hierarchically. Individuals who reported contact with any informal, but no formal or secondary healthcare sources, were classified as having had contact with informal sources only. Individuals who reported contact with any formal sources of help but no contact with secondary healthcare were classified as having had contact with formal sources of help. Individuals who reported contact with mental health specialists or child health specialists were classified as having had contact with secondary healthcare.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eMeasures of DSM-5 comorbidities\u003c/h2\u003e \u003cp\u003eWe examined DSM 5 disorders[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e] as assigned by the DAWBA to examine co-occurring anxiety, depression, behavioural, ADHD, autism spectrum disorder (ASD) and tic disorder diagnoses.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSocio-demographic characteristics\u003c/h3\u003e\n\u003cp\u003eBaseline characteristics for these analyses included age, sex and ethnicity. Housing tenure was used as a measure of household socioeconomic position.\u003c/p\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eData analysis\u003c/h2\u003e \u003cp\u003eAll data was analysed using Stata 17, using calibrated weights provided with the dataset which include weights for design and non-response[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eInitially, we described the characteristics of participants screening positive (according to either parent or young person) for possible eating problems, including by age, sex, ethnicity, DSM-5 comorbidities and socioeconomic position. Due to the low frequency of ADHD diagnosis, ASD and tic disorders in the cohort, we did not analyse them individually; however, they were included when calculating the number of individuals with one or more DSM-5 diagnosis (see Table III). Subsequently, we examined reported sources of help-seeking by overall screening status (screen positive/negative), and by individual DAWBA screening item. Finally, we examined the proportion of those in contact with different types of services who screened positive.\u003c/p\u003e \u003cp\u003eWe used a multinomial logistic regression model to examine associations between sociodemographic characteristics and reported service contact in individuals who screened positive for a possible eating problem. Results are reported as relative risk ratios (RRRs) with associated 95% confidence intervals.\u003c/p\u003e \u003cp\u003eThe outcome variable was reported help-seeking category, defined using the previously described hierarchical classification system ((1) no help (ref); (2) informal help only; (3) formal help; and (4) secondary healthcare).\u003c/p\u003e \u003cp\u003eThe following predictor variables were included in the model and treated as categorical: age group (11 to 16 years, 17 to 19 years); sex (male, female); housing tenure (owner occupied, private rented, socially rented); and ethnicity (White, minoritised ethnic backgrounds). Calibrated survey weights accounting for clustering were applied using Stata\u0026rsquo;s \u0026lsquo;svy\u0026rsquo; command. In the unweighted dataset, some service-contact categories had small cell counts (\u0026lt;\u0026thinsp;10 in one case; see Supplementary material Table SII). Therefore, ethnicity was modelled as a dichotomous variable to improve model stability. Strengths and limitations of this approach are discussed in the Discussion section.\u003c/p\u003e \u003c/div\u003e\u003cp\u003e\u003cstrong\u003eEthical approval\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll secondary analyses were approved by the University of Exeter Medical School REC (Nov20/D/270), and the MHCYP2017 data were accessed under a data sharing agreement with NHS England (DARS-NIC-424336-T7K7T-). Data are reported using ONS statistical disclosure control guidance[27].\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eOverall, 1,430 (36.4%) children and young people aged 11 to 19 screened positive for a possible eating problem. In those aged 11 to 16, 32.0% (95% CI 30.1, 33.7) screened positive, compared with 45.1% (95% CI 41.8, 48.4) of those aged 17 to 19. Rates of possible eating problems were lower in young men (25.7%, 95% CI 23.7, 27.8) than young women (47.6%, 95% CI 45.3, 50). Of those meeting criteria for any DSM-5 disorder, around half (51.3%, 95% CI 47.3, 55.4) screened positive for a possible eating problem. This figure was higher for those with an anxiety disorder (63.8%, 95% CI 58.4, 68.8) or a depressive disorder (67.7%, 95% CI 59.3, 75.0). There was no significant difference based on ethnicity or housing tenure. Table III displays the characteristics of the MHCYP 2017 cohort by possible eating problem status.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable III: Cohort characteristics by possible eating problem screening status using the DAWBA eating disorder screening module (weighted row percentages; non-weighted n given)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"700\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eScreen positive n, %(95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e11 to 16 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e3,121\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e999\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e32.0% (30.3, 33.7)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e17 to 19 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e936\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e427\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e45.1% (41.8, 48.4)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e2,032\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e511\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e25.7% (23.7, 27.8)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e1,426\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e915\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e47.6% (45.3, 50.0)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEthnicity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003eWhite\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e3,255\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e1,159\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e37.0% (35.2, 39.0)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003eBlack/Afro-Caribbean\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e162\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e30.9% (23.7, 39.0)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003eAsian\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e406\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e131\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e33.6% (28.9, 38,7)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003eMixed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e233\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e39.9% (33.3, 46.9)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;Tenure\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003eOwner of home\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e2,608\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e897\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e35.3% (33.3, 37.3)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003ePrivate rented\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e610\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e219\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e38.0% (33.8, 42.2)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003eSocially rented\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e770\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e271\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e36.1% (32.6, 40.0)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"5\" valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePresence of DSM-5 disorder\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003eAny DSM diagnosis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e686\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e332\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e51.3% (47.3, 55.4)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003eTwo or more DSM diagnoses\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e249\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e130\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e55.9% (49.3, 62.3)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003eAnxiety disorders\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e372\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e223\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e63.8% (58.4, 68.8)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003eDepressive disorders\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e148\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e67.7% (59.3, 75.0)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e\u0026nbsp;ASD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003es*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003es*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e17.9% (8.60, 33.5)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003eN = 4,060\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e1,430\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e36.4% (34.8, 38.1)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003e*Suppressed due to small numbers. Totals have been rounded to the nearest 5 according to statistical disclosure guidance.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eReported service contact\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAmong all participants, 68.2% (95% CI 66.6, 69.8) reported no contact for mental health concerns. Furthermore, 81.2% of those screening negative, and 73.8% of those screening positive for a possible eating problem reported no contact with professional services (formal or secondary health). \u0026nbsp;Participants screening positive were more likely to report contact with each category of support (Table IV). For example, a higher proportion of young people screening positive (9.17%, 95% CI 7.67, 10.9) were in contact with specialist services compared to those screening negative (6.06%, 95% CI 5.15, 7.12).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable IV: Sources of help for mental health concerns amongst adolescents aged 11 to 19 with a possible eating problem (weighted row percentages, non-weighted n given)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003eNo contact\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(%, (95% CI))\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003eInformal only\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(%, (95% CI))\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003eFormal\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(%, (95% CI))\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003eSecondary healthcare\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(%, (95% CI))\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003eTotal (n)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003eScreen negative\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e72.6 (70.6, 74.4)\u003c/p\u003e\n \u003cp\u003eN = 1,925\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e8.60 (7.40, 9.97)\u003c/p\u003e\n \u003cp\u003eN = 182\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e12.8 (11.5, 14.2)\u003c/p\u003e\n \u003cp\u003eN = 336\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e6.06 (5.15, 7.12)\u003c/p\u003e\n \u003cp\u003eN = 161\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e2,604\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003eScreen positive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e60.7 (57.9, 63.4)\u003c/p\u003e\n \u003cp\u003eN = 898\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e13.1 (11.2, 15.4)\u003c/p\u003e\n \u003cp\u003eN = 149\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e17.0 (15.0, 19.3)\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eN = 240\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e9.17 (7.67, 10.9)\u003c/p\u003e\n \u003cp\u003eN = 134\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e1,421\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003eTotal (n \u0026amp; row%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e68.2 (66.6, 69.8)\u003c/p\u003e\n \u003cp\u003eN = 2,823\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e10.3 (9.20, 11.4)\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eN = 331\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e14.3 (13.2, 15.5)\u003c/p\u003e\n \u003cp\u003eN = 576\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e7.20 (6.38, 8.11)\u003c/p\u003e\n \u003cp\u003eN = 295\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e4,025\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eHelp seeking and service contact by symptom type\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFigure 1 displays reported service contact among young people who endorsed each DAWBA eating disorder screening items, as outlined in Table I. All proportions and 95% confidence intervals for each category of help by screening item are provided in Supplementary material Table SIII. Among those endorsing each item the majority reported no help-seeking, apart from eating-related worries for which the proportion of individuals reporting no help-seeking was 48% (95% CI 42.8, 53.7). The item with the highest proportion reporting no-help seeking was thinking they were fat when others thought they were very thin (62.2%, 95% CI 59.4, 64.9).\u003c/p\u003e\n\u003cp\u003eYoung people who had any reported purging were more likely to have contact with professional or secondary healthcare services than with informal sources of help. However, 51.7% (95% CI 44.5, 58.9) of those reporting purging did not report contact with any source of help in the year prior to the survey. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFigure 1: Help seeking by item\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFigure 1: Reported help-seeking and service contact over the past year among individuals with a positive response (parent or self-reported) to each DAWBA screening item (see Table I).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eScreening positive by source of help or service contact\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFigures 3 and 4 display the proportion of respondents with possible eating problems among all participants reporting contact with different sources of support. For most services (except child health), between 40% to 50% of young people reporting contact were screen positive; however, confidence intervals overlap for the majority of service types (see Supplementary material Table IV).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFigure 2: Proportion of young people screening positive for a possible eating problem by category of help\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFigure 2: See Table II for details of each category. Note results are weighted; 95% CI.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFigure 3: Proportion of young people screening positive for a possible eating problem by specific sources of help\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFigure 3: See Table II for details of help sources. Note results are weighted; 95% CI.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRegression analysis of help seeking in individuals screening positive for possible eating problems\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTable V displays the results of the weighted multinomial logistic regression examining reported help-seeking for mental health concerns among adolescents screening positive for possible eating problems. Model diagnostics were satisfactory (see Supplementary material SV to SXVI for details). Age, ethnicity, and presence of any DSM-5 diagnosis were significantly associated with patterns of help-seeking in this subgroup, whereas sex and household income were not. Compared with young people aged 11 to 16, those aged 17 to 19 were more likely to report contact with informal (RRR = 8.49, 95% CI 5.65, 12.8, p \u0026lt; 0.001), formal (RRR = 1.54, 95% CI 1.07, 2.21, p = 0.021) and secondary healthcare (RRR = 2.07, 95% CI 1.29, 3.30, p = 0.002) sources. Compared with White participants, those from minoritised ethnic backgrounds were less likely to report contact with secondary healthcare (RRR = 0.28, 95% CI 0.11, 0.68, p = 0.005). Young people with a DSM-5 diagnosis were more likely to report contact with informal (RRR = 1.84, 95% CI 1.08, 3.12, p = 0.024), formal (RRR = 4.22, 95% CI 2.91, 6.12, p \u0026lt; 0.001), and secondary healthcare (RRR = 21.4, 95% CI 12.8, 35.8, p \u0026lt; 0.001) sources, compared with those without.\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" align=\"left\" width=\"100%\" class=\"fr-table-selection-hover\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 29px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" colspan=\"2\" valign=\"bottom\" style=\"width: 25px;\"\u003e\n \u003cp\u003eInformal only\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" colspan=\"2\" valign=\"bottom\" style=\"width: 24px;\"\u003e\n \u003cp\u003eProfessional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" colspan=\"2\" valign=\"bottom\" style=\"width: 20px;\"\u003e\n \u003cp\u003eSecondary healthcare\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 29px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePredictor\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRRR (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRRR (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRRR (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 29px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge group (ref = 11 to 16 years)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 18px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 17px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 14px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 29px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 17 to 19 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e8.49 (5.65, 12.8)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.54 (1.07, 2.21)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e0.021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.07 (1.29, 3.30)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 29px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex (ref = male)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 18px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 17px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 14px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 29px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Female\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 18px;\"\u003e\n \u003cp\u003e0.74 (0.49, 1.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e0.150\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 17px;\"\u003e\n \u003cp\u003e1.32 (0.93, 1.88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e0.118\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 14px;\"\u003e\n \u003cp\u003e1.53 (0.96, 2.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e0.077\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 29px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHousing tenure (ref = owned)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 18px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 17px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 14px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 29px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Private rented\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 18px;\"\u003e\n \u003cp\u003e1.47 (8.46, 2.54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e0.172\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 17px;\"\u003e\n \u003cp\u003e1.09 (0.69, 1.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e0.706\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 14px;\"\u003e\n \u003cp\u003e0.76 (0.39, 1.48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e0.415\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 29px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Social rented\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 18px;\"\u003e\n \u003cp\u003e1.08 (0.62, 1.88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e0.789\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 17px;\"\u003e\n \u003cp\u003e0.94 (0.62, 1.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e0.782\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 14px;\"\u003e\n \u003cp\u003e0.73 (0.41, 1.29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e0.278\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 29px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEthnicity (ref = White)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 18px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 17px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 14px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 29px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Minoritised ethnic background\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 18px;\"\u003e\n \u003cp\u003e0.63 (0.36, 1.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e0.107\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 17px;\"\u003e\n \u003cp\u003e0.64 (0.40, 1.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e0.057\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.28 (0.11, 0.68)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 29px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDSM diagnosis (ref = No concurrent diagnosis)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 18px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 17px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 14px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 29px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Any DSM5 comorbidity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.84 (1.08, 3.12)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e0.024\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e4.22 (2.91, 6.12)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e21.4 (12.8, 35.8)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003ctable cellspacing=\"0\" cellpadding=\"0\" hspace=\"0\" vspace=\"0\" align=\"left\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" align=\"left\"\u003e\n \u003cp\u003eTable V: Estimates are relative risk ratios (RRRs) from multinomial logistic regression model. See Methods for model specification. Bold values indicate p \u0026lt; 0.05. Design df = 4,012, \u0026nbsp; F(18, 3995) = 15.60, Prob \u0026gt; F \u0026lt; 0.001.\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable V: Multinomial regression analysis of help seeking\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study used a nationally representative probability sample of children and young people to examine (a) contact with sources of help among those screening positive for a possible eating problem and (b) prevalence of possible eating problems among those reporting contact with sources of help for any mental health concern. Throughout this discussion, help-seeking and service contact refer to reported contact for any mental health concern, and “possible eating problems” denotes those screening positive on DAWBA screening items rather than a clinical diagnosis.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOverall, those with a possible eating problem were more likely than those without to report contact with sources of help, although almost three-quarters did not report any contact with a professional service (Table 3). Notably, around one-third of those who reported no contact with sources of help screened positive for a possible eating problem. Approximately half of young people reporting contact with a mental health specialist and almost half of those reporting contact with teachers or primary care screened positive. Among those screening positive, older adolescents (17 to 19 years) and those with a DSM-5 comorbidity were significantly more likely to report contact across all categories of support, while those from minoritised ethnic backgrounds were markedly less likely to report secondary healthcare contact. We found no association between help-seeking and sex or housing tenure (Table 6).\u003c/p\u003e\n\u003cp\u003eOlder adolescents (17 to 19 years) were more likely to report contact with all categories of mental health support compared with those aged 11 to 16 years. This contrasts with previous analysis of MHCYP 2017 data, which showed that while rates of professional service contact were similar across these age groups in the full sample (21.5% vs 22.0%), older adolescents with a DSM-5 diagnosable mental disorder were less likely than younger adolescents to report service contact[25]. Further work is needed to understand possible explanations for this finding; for example, whether disordered eating in older adolescents is associated with greater symptom salience, distress, or functional impairment that prompts help-seeking.\u003c/p\u003e\n\u003cp\u003eGreater service contact among those with a DSM-5 diagnosis likely reflects the recognised link between clinical complexity and increased help-seeking. This finding is consistent with international evidencethat psychiatric comorbidity is linked to increased service use[28,29]. Controlling for DSM-5 diagnostic status in our model ensures associations between age, ethnicity, and help-seeking are not explained by differences in diagnosable mental health conditions.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAmong young people screening positive for a possible eating problem, those from minoritised ethnic backgrounds were less likely to report secondary-healthcare contact. This finding is consistent with previous analyses of the MHCYP 2017 dataset, which found that children from Black and Asian backgrounds were less likely than White peers to report contact with professional mental health services, after adjustment for DSM-5 disorder status and sociodemographic factors[30]. A Canadian study reported similar findings among immigrant, refugee, racial and ethnic minoritised youth, after adjusting for symptom severity and perceived need[31]. Together, these findings suggest that ethnic disparities in service use are not explained by clinical need and may reflect structural or cultural barriers to accessing care.\u003c/p\u003e\n\u003cp\u003eAlthough possible eating problems were more common in females than males, sex was not significantly associated with help-seeking or service contact among those screening positive. This aligns with previous analyses of the MHCYP 2017 dataset, which also found comparable rates of professional contact in females (20.0%) and males (22.2%)[25]. These findings suggest that the greater proportion of females in eating disorder populations may primarily reflect underlying sex differences in prevalence rather than disparities in help-seeking.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe found no evidence that housing tenure was associated with help-seeking among adolescents with possible eating problems.This contrasts with previous analyses of MHCYP 2017 data, which found that 11 to 16 year-olds living in private or socially rented housing had significantly lower odds of specialist mental health contact compared with those in owner-occupied homes[30], but aligns with previous studies reporting no consistent association between socioeconomic position and help-seeking for eating disorders[32–34]. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOf note, young people with ASD were less likely to screen positive for possible eating problems. Emerging literature suggests that eating difficulties in young people with ASD may be more closely associated with sensory processing and “feeding problems”, rather than preoccupation with food, eating or body image, which the DAWBA screening module primarily assesses[35,36]. However, given the low numbers in this sample, (Table III), the dataset is underpowered to support reliable population-level inference.\u003c/p\u003e\n\u003cp\u003eOur findings add to the relatively sparse literature on help-seeking and eating problems amongst young people. Estimated rates of help-seeking from other studies vary \u0026nbsp; from around 8% to 66%[37]\u003cstrong\u003e,\u0026nbsp;\u003c/strong\u003elikely due to how help seeking is defined and measured. Our finding of a help-seeking rate of 39.3% among those with a possible eating problem sits within this range. One reason for low rates of mental health related service contact in individuals who screen positive for eating problems could be that these young people do not ‘need’ help. A recent study reports the positive predictive value of screening positive for a clinical eating disorder using the DAWBA to be very low, so the majority who screen positive are unlikely to meet full criteria for an eating disorder [24]. Furthermore, as we used survey data from one time point, difficulties may have been transitory.\u003c/p\u003e\n\u003cp\u003eHowever, some young people with eating problems may experience distress or impairment and therefore benefit from identification and support. It is concerning that over half of individuals who reported purging reported no contact with any source of support for a mental health concern in the past year. A review by the UK charity Beat found that the average length of time between someone developing an eating disorder and realizing they had an eating disorder was 69 weeks, followed by 39 weeks before seeking help from a GP[38]. Reported barriers to help seeking include stigma and fear of disclosure, low self-perceived severity of eating behaviors, minimal support from family and friends, and experiences with healthcare providers who lacked knowledge about eating disorders or dismissed parental concerns[15].\u003c/p\u003e\n\u003cp\u003eRelatively high proportions of young people who reported contact with professional services screened positive for possible eating problems. It is therefore important for professionals to have awareness of eating difficulties and disorders, the difference between the two, and the potential for “atypical” presentations.Recent findings from England’s national child mental health surveys \u0026nbsp;indicate the prevalence of ‘other’ eating disorders have risen over time[6]. Despite this, education and assessment on eating disorders remain limited in UK medical education, prompting initiatives like Beat’s training for medical students and foundation doctors[39,40]. It is important that professionals are aware that they are likely to be in contact with adolescents with possible eating problems and are equipped to appropriately identify and refer individuals needing further assessment.\u003c/p\u003e\n\u003cp\u003eThis study has several strengths, notably it uses a national probability sample of 11 to 19 year-olds, thus allowing the study of both those who are, and are not, in contact with services. It also includes self-reported and parent-reported symptoms through use of the DAWBA. The DAWBA screening module was designed to rule \u003cem\u003eout\u003c/em\u003e eating disorders, and as such it has a high sensitivity[24]. However it has low specificity and a low positive predictive value (2.4% for children aged 11 to 16 and 2.5% for those aged 17 to 19 years)[24]. As such, the DAWBA is well suited for our aim to examine service contact and possible eating problems in a population sample of young people. However, due to the focus on symptoms characteristic of anorexia nervosa and bulimia nervosa[24], the DAWBA screening questions may not be as good at identifying other eating disorders or conditions such as binge eating or purging disorder. Additionally, the self-reported and retrospective nature of service contact data may introduce bias. For those aged 11 to 16, we used parent-reported service contact, which may be limited by the parent’s knowledge of their child’s help-seeking. Importantly, we do not know whether participants sought help regarding eating concerns, or a different mental health concern, or what happened subsequently.\u003c/p\u003e\n\u003cp\u003eDespite the large population sample, we used a dichotomised measure of ethnicity to improve the stability of our regression model. Whilst this allows a less nuanced assessment of the relationship between ethnicity and service contact, it allowed us to include ethnicity in our model and is consistent with how data on ethnicity from MHCYP has previously been used [25].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe use of longitudinal linked data could help address these limitations in future research. Linking primary and secondary care data would allow symptoms, service contact and referral pathways to be tracked over time, including pre-and post-pandemic. Qualitative studies may further understanding of what enables and hinders help-seeking among adolescents with eating problems. Longitudinal population studies should also investigate long-term trajectories and outcomes of adolescents with eating difficulties, including progression to eating disorders or other conditions, and broader health outcomes.\u0026nbsp;\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eA high proportion of adolescents in this nationally representative English survey screen positive for a possible eating problem. Most of those screening positive did not report any contact with sources of mental health support. Around half of those in contact with specialist mental health services and almost half of those in contact with teachers or primary care for mental health concerns reported eating difficulties; clinicians and teachers should be alert to these problems as they may not be disclosed. Within the subgroup of young people with possible eating problems, older adolescents, and those with a comorbid DSM-5 disorder were more likely to report contact with informal, formal, and secondary-care sources, while those from minoritised ethnic backgrounds were less likely to report contact with secondary care. Future work should examine the clinical course and treatment journeys of adolescents with possible eating problems.\u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by BG and TND. The first draft of the manuscript was written by BG and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe MHCYP 2017 dataset is archived with the UK Data Service. Approval for access to the MHYCP data can be obtained through the UK Data Service Data Access Request Service.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRights retention\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFor the purpose of open access, the author has applied a Creative Commons Attribution (CC BY) license to any Author Accepted Manuscript version arising from this submission.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBG, HB, TF and TND have no relevant financial or non-financial interests to disclose. This report is independent research. HB was supported by an NIHR Advanced Fellowship (302271). BG was supported by an NIHR Academic Clinical Fellowship\u0026nbsp;(ACF-2024-23-010)\u003cstrong\u003e.\u0026nbsp;\u003c/strong\u003eTF’s research group receives funding from Place2Be, a third sector organisation that provides mental health training and interventions in UK schools. All research at the Department of Psychiatry in the University of Cambridge is supported by the NIHR Cambridge Biomedical Research Centre (NIHR203312) and the NIHR Applied Research Collaboration East of England. The views expressed in this publication are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBG would like to acknowledge the support of the Royal College of Psychiatrists Faculty of Eating Disorders Psychiatry for awarding him a research bursary to support presenting this work and related projects.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthic approval\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe MHCYP-2017 survey received approvals from the West London \u0026amp; GTAC Research Ethics Committee (reference: 16/LO/0155) and the Health Research Authority Confidentiality Advisory Group (reference: 16/CAG/0016) [18]. TND obtained ethical approval for secondary analysis of the MHCYP-2017 data via the University of Exeter College of Medicine and Health Research Ethics Committee (reference: Nov20/D/270). The study was performed in accordance with the ethical standards as laid down in the 1964 Declaration of Helsinki and its later amendments.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eArcelus J, Mitchell AJ, Wales J et al (2011) Mortality rates in patients with anorexia nervosa and other eating disorders. A meta-analysis of 36 studies. 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An Updated Systematic Review and Meta-Analysis. Int J Eat Disord 58:46\u0026ndash;65. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/eat.24306\u003c/span\u003e\u003cspan address=\"10.1002/eat.24306\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBeat (2017) Delaying for years, denied for months\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAyton A, Ibrahim A (2018) Does UK medical education provide doctors with sufficient skills and knowledge to manage patients with eating disorders safely? Postgrad Med J 94:374\u0026ndash;380. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1136/postgradmedj-2018-135658\u003c/span\u003e\u003cspan address=\"10.1136/postgradmedj-2018-135658\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBeat Training for Medical Students and Foundation Doctors \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.beateatingdisorders.org.uk/get-information-and-support/training-for-professionals/training-for-healthcare-clinical-professionals/eating-disorders-training-for-medical-students-and-foundation-doctors/\u003c/span\u003e\u003cspan address=\"https://www.beateatingdisorders.org.uk/get-information-and-support/training-for-professionals/training-for-healthcare-clinical-professionals/eating-disorders-training-for-medical-students-and-foundation-doctors/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Accessed 13 October 2021\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"european-child-and-adolescent-psychiatry","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ecap","sideBox":"Learn more about [European Child \u0026 Adolescent Psychiatry](http://link.springer.com/journal/787)","snPcode":"787","submissionUrl":"https://submission.nature.com/new-submission/787/3","title":"European Child \u0026 Adolescent Psychiatry","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"disordered eating, eating problems, service contact, help seeking","lastPublishedDoi":"10.21203/rs.3.rs-8886674/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8886674/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective:\u003c/h2\u003e \u003cp\u003eTo describe patterns of service contact among adolescents screening positive for possible eating problems.\u003c/p\u003e\u003ch2\u003eMethods:\u003c/h2\u003e \u003cp\u003eSecondary analysis of the Mental Health of Children and Young People in England 2017 survey, a national stratified probability sample. Possible eating problems were identified using Development and Wellbeing Assessment (DAWBA) eating disorder screening items in adolescents aged 11\u0026ndash;19. Individuals answered questions regarding contact with sources of help for any mental health concern.\u003c/p\u003e\u003ch2\u003eResults:\u003c/h2\u003e \u003cp\u003eOverall, 36.4% of adolescents screened positive for a possible eating problem, of whom 60.7% reported no contact with sources of mental health support. Among those reporting contact with formal and specialist services, a substantial proportion screened positive for possible eating problems, including half of those reporting contact with mental health specialists. In weighted multinomial logistic regression restricted to screen-positive adolescents, older age (17\u0026ndash;19 years) and presence of a DSM-5 diagnosis on the DAWBA were associated with higher likelihood of contact across informal, formal, and secondary healthcare sources. Adolescents from minoritised ethnic backgrounds were less likely to report secondary healthcare contact than White peers.\u003c/p\u003e\u003ch2\u003eConclusion:\u003c/h2\u003e \u003cp\u003eDespite high numbers of adolescents screening positive for possible eating problems, rates of help seeking in this group were low. Within this subgroup, service contact varies by age, ethnicity, and clinical comorbidity. Differences in service contact in this subgroup should be further explored.\u003c/p\u003e","manuscriptTitle":"Mental health-related service contact amongst young people with a possible eating problem in the English national child mental health surveys","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-03 02:15:50","doi":"10.21203/rs.3.rs-8886674/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-05-14T11:16:11+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-08T08:02:41+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-14T11:12:25+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"283472453505695362335092825514241593513","date":"2026-04-09T07:56:40+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"77161297831661378554447070942165126618","date":"2026-03-30T06:10:57+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"107827458091591409651658764992884239047","date":"2026-03-29T07:10:34+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-03-28T21:20:01+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-17T14:43:30+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-02-17T14:42:04+00:00","index":"","fulltext":""},{"type":"submitted","content":"European Child \u0026 Adolescent Psychiatry","date":"2026-02-15T14:23:45+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"european-child-and-adolescent-psychiatry","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ecap","sideBox":"Learn more about [European Child \u0026 Adolescent Psychiatry](http://link.springer.com/journal/787)","snPcode":"787","submissionUrl":"https://submission.nature.com/new-submission/787/3","title":"European Child \u0026 Adolescent Psychiatry","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"8d49b167-a7ca-46c2-8db2-800fa5f5b5be","owner":[],"postedDate":"April 3rd, 2026","published":true,"recentEditorialEvents":[{"type":"editorInvitedReview","content":"","date":"2026-05-14T11:16:11+00:00","index":19,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-08T08:02:41+00:00","index":18,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-03T02:15:50+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-03 02:15:50","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8886674","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8886674","identity":"rs-8886674","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}