Data Resource Profile: The Mental Health of Children and Young People (MHCYP) 2017 and follow-up surveys

Abstract

Introduction
Amid growing global concern about child and adolescent mental health problems and their long-term consequences, research in this area is increasingly critical. Population-representative datasets are valuable resources for addressing these challenges. The Mental Health of Children and Young People (MHCYP) 2017 survey was designed to meet this need in England.

Methods
The 2017 survey included 9117 children and young people aged 2 to 19 years. Information was collected from parents or carers (hereafter referred to as 'parents'), and for those aged 11 years or over, directly from the young people themselves, as well as from teachers. The baseline assessment used the standardised Development and Wellbeing Assessment (DAWBA), based on ICD-10 and DSM-5 diagnostic criteria. The subsequent waves in 2020, 2021, 2022 and 2023, measured mental health difficulties using the Strengths and Difficulties Questionnaire (SDQ).

Results
The MHCYP 2017 survey and its follow-up waves provide population-representative data on children and adolescents in England, encompassing a range of mental health disorders and difficulties---from eating disorders and attention and hyperactivity disorder to depression and anxiety, with longitudinal data on mental health, social situation and activities during the Covid-19 pandemic. It builds on earlier UK representative surveys conducted in 1999 and 2004.

Conclusion
Together with the 1999 and 2004 surveys, this dataset offers a unique opportunity to investigate trends in mental health disorders among young people, assess associated difficulties and comorbidities, and explore links with socio-economic factors. The MHCYP 2017 survey and follow-ups offer valuable cross-sectional data for understanding child and adolescent mental health trends in the UK, with longitudinal data from four subsequent surveys conducted between 2020 and 2023.

Key features

• The 2017 survey included 9117 children and young people aged 2 to 19, with data from parents, young people aged 11 or over, and teachers. Participants were recruited to represent England’s population across diverse socio-economic backgrounds, regions, and educational settings.
• Follow-up waves were conducted in 2020, 2021, 2022, and 2023.
• The study collected data on mental health conditions such as anxiety, depression, attention deficit hyperactivity disorder, autism, and eating difficulties/disorders. Psychiatric disorder status was determined using the clinically rated, standardised Development and Wellbeing Assessment based on ICD-10 and DSM-5 criteria.
• Data were also gathered at baseline and in the follow-up waves on family and socio-economic factors, educational outcomes, social media, and environmental influences, including the impact of COVID-19.
• The follow-up waves utilised the Strengths and Difficulties Questionnaire to estimate probable mental disorders, with additional assessments in later waves, including psychotic-like symptoms in 2022 and screening for personality disorder traits in 2023.
• Data from all surveys except the 2023 wave are available through the UK Data Service (https://beta.ukdataservice.ac.uk/datacatalogue/studies/study?id=8467) for research purposes under relatively straightforward access protocols, which take a few weeks. With final confirmation from NHS England, the 2023 data will be available within a month.

Background

There is increasing concern about the mental health of children and young people (CYP), as difficulties in this age group strongly predict long-term adverse outcomes [1, 2]. Evidence indicates a deterioration in certain mental health indicators, including rising rates of depression, anxiety, and self-harm among children and adolescents—particularly teenage girls. This trend was exacerbated by the COVID-19 pandemic [3–6]. Moreover, the negative consequences of mental health problems—such as academic underachievement and social difficulties—have intensified in more recent generations [7]. Large, population-based datasets with robust measures are invaluable resources for better understanding CYP’s mental health, particularly those that are essential for trend analyses and longitudinal studies.

The Mental Health of Children and Young People (MHCYP) Survey series were designed to estimate the prevalence of mental health disorders in this population. This series encompass three comparable cross-sectional, population-based datasets collected in the UK in 1999 (n = 10438), 2004 (n = 7797) and 2017 (n = 9117) [8]. The current data resource profile provides details on the 2017 survey, its follow-up studies as summarised in the timeline presented in Figure 1, as well as the subsequent follow-on studies which provided more in-depth investigation of policy relevant topics, as outlined in Table 3. The 2017 MHCYP survey builds on the 1999 and 2004 surveys, continuing national mental health monitoring with key updates. It reached down to age two and up to age 19, included children in local authority care, focused solely on England, and expanded questionnaire content to reflect contemporary issues. Data collection shifted from interviewer led computer completion with some self-completion sections to computer-assisted methods, improving efficiency and accuracy. The series was further extended through rapid follow-up surveys during the COVID-19 pandemic, providing timely insights into the mental health impacts of national lockdowns. These developments enhance the survey’s relevance and responsiveness to changing social and policy contexts.

Figure 1: Timeline of the Mental Health of Children and Young People (MHCYP) baseline and longitudinal follow-up surveys 1999-2023. ^aonly Strengthens and Difficulties were administered to follow-up.

Data from the 2017 survey and the follow-up studies are available via UK Data Service under special licence (https://beta.ukdataservice.ac.uk/datacatalogue/studies/ study?id=8467). The surveys represent a valuable resource for research on the mental health of CYP and the examinations of the influence of the COVID-19 pandemic. All the surveys described in this Data Resource Profile were commissioned by NHS Digital (now NHS England) and funded by the Department of Health and Social Care. The follow-up waves were augmented with a grant from UK Research and Innovation (MR/V027751/1), which also funded the follow-on studies. Follow-up studies 3 and 4, conducted in 2022 and 2023, respectively, were also funded by the Department of Education. The strength of MHCYP 2017 and its follow-up waves lies in their consistent methods, multi-informant mental health screening assessments, and longitudinal element, enabling comparisons within individuals over time [3].

Methods

Sampling and response rates for the baseline 2017 survey

The 2017 baseline survey used the NHS patient register as a sampling frame— a comprehensive database of individuals registered with the UK National Health Service— which allowed for the direct recruitment of a sample of CYP based on their age (n = 9117), including those in the care of local authorities, a subgroup previously excluded from the 1999 and 2004 surveys. Although the NHS patient register offered the most comprehensive sampling frame of CYP, it had several coverage limitations. Families may delay registering with a general practitioner (GP) when they move or migrate. University students often have two addresses simultaneously but can register with only one GP. Members of the armed forces and individuals relying on private health care are under-represented. Consequently, these issues introduce some limitations to the NHS Patient Register as a sampling frame [8].

Unlike the 1999 and 2004 surveys, which covered CYP across England, Scotland, and Wales, the 2017 wave included CYP from England only. These CYP were identified from a probability sample of 6.3% of postcode sectors stratified by Government Office Region. The sectors were selected based on the size of each region and were further sorted by socio-demographic factors associated with mental health, derived from 2011 Census data, such as tenure, employment status, and economic activity. A total of 18029 potential participants were approached, of whom 17326 were found to be eligible according to the inclusion criteria [8].

Response rate of the baseline 2017 survey

In 2017, data was collected from 52% of eligible CYP (59% of those approached), aged 2 to 19, and from 67% of parents. Both CYP and parents participated in computer-assisted face-to-face interviews administered by trained lay interviewers. The assessment also included self-reported sections for more sensitive topics. With the family’s consent, a teacher—nominated by both the parent and the CYP—received a questionnaire via mail/email, with the option to complete it on paper. Only young people aged 11 or over were eligible to participate in the interview. For participants aged 16 or under, parents were the primary point of contact. Whereas, for those aged 17 or older, the young person served as the primary contact, with the involvement of others depending on the young person’s consent [3]. Among 9117 assessed CYP, 61% had parent-only reports, 6% young person-only (ages 17–19), 33% both parent and young people (ages 11–16), and 39% included teacher reports with parental consent [9]. Children were defined as those aged 10 years or younger, and young people as those aged 11 to 24 years.

Sampling and Response Rates for follow-up surveys

All participants recruited for the follow-up waves that were conducted between 2020 and 2023 had participated in the 2017 survey and consented to be contacted for future research (or had continued to agree to be recontacted for future studies after participating in any previous follow-up surveys). Consent to be recontacted was provided either by young people if they were aged 17 or above at the time of previous survey or by a parent if the child was 16 or under at the time of previous survey. All surveys included the Strengths and Difficulties Questionnaire (SDQ), with additional measures varying to represent funding and policy interests (See Table 2 for an overview of included measures).

Table 1 summarises the number of CYP invited at baseline and at each follow-up wave, along with their age range, response rate, and the total number of eligible participants. All four follow-up surveys invited participants to complete questionnaires online with prompting to complete via telephone in 2020 [9] and telephone completion as an option, targeting participants from ethnic minorities and facing socio-economic deprivation in 2021 to 2023 [10]. Figure 2 provides an overview of participation across the baseline and follow-up surveys.

Table 1: Participation and Response Rates in MHCYP 2017 and Follow-up Waves. CYP = Children and Young People. ^aCYP with data from parent/ CYP or both. ^bself-report sections included for sensitive topics.

Year	CYP Age Range	Invited (n)	Respondents (n) a	Response Rate	Data collection Mode
2017	2–19	18029	9117	52%	Face-to-face and computer-assistedb
2020	5–22	7855	3570	45%	Online
2021	6–23	7628	3667	48%	Online/Telephone
2022	7–24	7253	2866	40%	Online/Telephone
2023	8–25	6773	2370	35%	Online/Telephone

Figure 2: Recruitment diagram showing the sampling process for the Mental Health of Children and Young People (MHCYP) 2017 survey, including follow-up and follow-on studies (2020–2023). The diagram illustrates participant retention, new recruitment, and sample composition across study phases.

Measures

Table 2 outlines the mental health measures used in the 2017 baseline and 2020 to 2023 follow-up waves.

Table 2: Summary of mental health measures in the 2017 MHCYP baseline survey and follow-up waves. P = Parents/Carers; C = Child (10 years of age or younger); YP = Young (11 years of age or older) People; T = Teacher. ^aIn the 2017 survey, the DAWBA subscale for eating, sleeping and toilet training disorders, attachment disorder, and pervasive developmental disorders subscales were completed by parents only, and Hyperactivity disorder, Behavioural disorder and Tic disorder subscales were completed by parents, children, young people and teachers. All other DAWBA subscales were completed by parents, children and young people in 2017. This is summarised in a previous data resource profile [5]. ^bThe 2017 survey used 14-item WEMWBS; the follow-up studies used the short 7-item scale.

	Year
	2017	2020	2021	2022	2023
Strength and Difficulties Questionnaire (SDQ)	P, C, T	P, C, YP	P, C, YP	P, C, YP	P, C, YP
Development and Well-Being Assessment (DAWBA)a	P, C, YPa
Eating problems (screening questions only)			P, C, YP	P, C, YP	P, C, YP
Eating disorder (full diagnostic assessment)	P, C, YP				P, C, YP
Rosenberg Self-Esteem Scale (RSES)	C, YP
Warwick Edinburgh Mental Wellbeing Scale (WEMWBS)b	C, YP	C		C	C
General Health Questionnaire (GHQ-12)	P	P, YP	P, YP	P, YP	P, YP
McMaster Family Assessment Device (FAD)	P	P	P	P	P
Pandemic Anxiety Scale (PAS)		P, C, YP
Family Connectedness Scale (FCS)			C, YP
The Adolescent Psychotic-Like Symptom Screener (APSS)				YP
Standardised Assessment of Personality - Abbreviated Scale (SAPAS)					YP

The Development and Wellbeing Assessment (DAWBA) [11] is a multi-informant standardised diagnostic assessment that combines structured and semi-structured approaches to assessment. The DAWBA covers most common mental health conditions affecting CYP. Each module starts with a few screening items, which if endorsed lead to structured items related to the diagnostic criteria [12, 13]. Participants are then asked semi-structured probes about the nature of difficulties, their intensity, duration, frequency and impact, as well as factors that amplify or reduce them before progressing to the next module. In 2017, parents and young people aged 11 years or older were interviewed face-to-face, while if the family agreed a shorter version was mailed to a teacher. A small team of clinical raters reviewed both structured and qualitative data from all informants to assign diagnoses according to both DSM-5 [12] and ICD-10 [13]. While the full version of DAWBA was not administered in the follow-up waves, the eating disorders screening items were collected from 2021 onwards, while the full eating disorders module was collected via an online survey in 2021 and 2023.

The Strengths and Difficulties Questionnaire (SDQ) [14] assesses social, emotional and behavioural issues through 25 items grouped into five subscales: conduct problems, hyperactivity-inattention, emotional symptoms, peer relationship problems, and prosocial behaviours. Although the SDQ was developed for use in children aged 4 to 16, with some validations extending to age 18 [15] evidence is accruing of similarly strong psychometric properties in individuals up to age 25 [15, 16]. There are parallel versions for parents, teachers and young people aged 11 years or more. While the prosocial scale measures social skills—where higher scores indicate stronger abilities—the other four subscales contribute to a total difficulties score. Responses are rated as "not true", "somewhat true", or "certainly true", corresponding to scores of 0, 1, or 2 respectively. Positively phrased items are reverse scored, ensuring higher scores on the first four subscales signify greater challenges. The total difficulties score was reliable in UK populations, with a Cronbach’s alpha of 0.73, demonstrating strong internal consistency [14]. The SDQ also includes an impact supplement, which examines the functional impairment in friendships, classroom learning, home life, and leisure activities, caused by difficulties. The burden of these difficulties is rated on a scale ranging from "not at all" to "a great deal". The parent and CYP reports on the SDQ were combined through a pseudo-diagnostic algorithm (www.sdqinfo.org) to estimate the likelihood of a child having a mental health disorder in the four follow-up waves. The algorithm combined parental and self-report, if both were available to classify CYP as "unlikely," "possible," or "probable" for having any mental health condition. While this method does not provide a clinical diagnosis, it serves as a pseudo-diagnostic tool, offering valuable insights into mental health trends and helping to assess service needs on a broader scale [17].

The Warwick-Edinburgh Mental Wellbeing Scale (WEMWBS) [18] measures wellbeing through 14 positively worded items that capture functional and psychological aspects like feeling useful, relaxed, and close to others. Responses are rated on a five-point Likert scale from “none” to “all of the time”. While it is originally designed for the adult population, a validation study in students aged 13 to 16 in England and Scotland demonstrated strong internal consistency (Cronbach’s alpha = 0.87). In follow-up waves conducted from 2020 to 2023, the seven-item short form of this scale (SWEMWBS) [19] was used.

The General Health Questionnaire (GHQ-12) [20] consists of 12 items that measure psychological distress, including aspects of emotional well-being, social functioning, and cognitive difficulties. Items are rated on a four-point scale, ranging from “not at all” to “much more than usual”. The GHQ-12 is commonly used as unidimensional measure of general psychological distress. The measure demonstrates strong psychometric properties, with good reliability and validity [20]. It was administered to parents in the 2017 baseline and to both parents and young people aged 17 plus in subsequent follow-up waves.

The McMaster Family Assessment Device (FAD) [21] measures family functioning across seven dimensions: problem solving, communication, roles, affective responsiveness, emotional involvement, behavioural control, and general functioning. It consists of 60 items, rated on a four-point Likert scale, ranging from "strongly agree" (scored as 1) to "strongly disagree" (scored as 4), with total scores ranging from 60 to 240. Higher scores indicate poorer family functioning. The McMaster FAD has demonstrated strong reliability (Cronbach’s alpha >0.80) and validity [21]. It is widely used in research and clinical settings to assess family dynamics. While the 2017 baseline included all 12 items of the General Functioning subscale, the 2020 follow-up and following waves assessed family functioning using only four items from this subscale. These items were administered to parents of children aged 16 or under to evaluate challenges in family functioning. The MHCYP 2017 and its follow-ups include variables on household composition and living arrangements, which can be used to contextualise responses to the McMaster Family Assessment Device (FAD). As participants age, their concept of ‘family’ may shift. While the FAD measure itself remains unchanged, analyses should, where possible, be stratified by age and living situation—acknowledging that responses may refer to different family units across waves. The same consideration applies to the Family Connectedness Scale.

The Pandemic Anxiety Scale (PAS) [22] captures the aspects of pandemic which generates worry, including the worries about the COVID virus, and those resulted by the lockdown This measure comprises nine self-reporting items with answers being rated on a five-point Likert scale from "strongly disagree" to "strongly agree", with scores ranging from 0 to 4 respectively. Higher scores on the PAS indicate greater levels of pandemic-related anxiety. This measure has been shown to be both valid and reliable [22]. It was administered to CYP and parents during the 2020 wave only.

The Rosenberg Self-Esteem Scale (RSES) [23] assesses global self-esteem. The scale consists of 10 items. Each item is rated on a four-point Likert scale, from "strongly agree" to "strongly disagree", with higher scores reflecting higher self-esteem. The RSES has been confirmed to have appropriate psychometric properties, including high internal consistency (Cronbach’s alpha around 0.87) and robust construct validity [23]. This measure was administered during the 2017 baseline survey in CYP.

The Family Connectedness Scale [24] measures the perceived emotional support and connection within families. It consists of 12 items, with responses given on a five-point Likert scale, ranging from "Strongly disagree" to "Strongly agree" scored on a range of 1 to 5. The scale includes two subscales: Family Communication and Family Support. Higher scores indicate stronger family connectedness. The scale has demonstrated strong psychometric properties, with good reliability (Cronbach’s alpha >0.80) and validity in assessing the role of family support in adolescent and young adult well-being [24].

The Adolescent Psychotic-Like Symptom Screener (APSS) [25] is a self-reported scale designed to identify psychotic-like symptoms in adolescents, including hallucinations, delusions, disorganised thinking, and mood disturbances. This 7-item screener is responded to on a Likert scale with three options comprising ’yes, definitely’, ’maybe’ and ’no, never’, scored as 1, 0.5, and 0 respectively, to assesses the frequency and intensity of symptoms. The total score is calculated by summing individual item scores, with higher scores indicating more severe or frequent symptoms. Additionally, the APSS shows good sensitivity and specificity, which helps identifying adolescents at risk of psychotic disorders. The APSS was originally developed for adolescents aged 11 to 13 [25] and has limited validation in older age groups [26]. While it was used in MHCYP for participants aged 11 to 16, its continued use beyond age 13 should be interpreted with caution. The psychometric properties of the APSS within the MHCYP context are currently under review to inform future data collections.

The Standardised Assessment of Personality – Abbreviated Scale (SAPAS) [27] is based on the Standardised Assessment of Personality Disorders (SAP), which is a diagnostic tool for assessing personality disorder. However, SAPAS does not provide a formal diagnosis. It consists of eight items, each indicating the presence of specific personality traits. Each item is scored as 0 or 1, and the responses are summed to produce a total score. SAPAS has established psychometric properties [27]. It was used in 2023 follow-up to assess the likelihood of general personality disorder traits.

Follow-on studies

Table 3 summarises five follow-on studies [28–31] that aimed to examine particular policy issues in depth and involved sub-samples from the follow-up waves. The 2021 eating disorders follow-on study went into the field in 2022 and invited all CYP who endorsed at least one screening item, or whose parents endorsed two screening items. In 2023, data were collected as part of the follow-up survey, and we also invited a randomly pre-selected sample of 500 screen negatives.

Table 3: Summary of follow-on studies. CYP = children and young people; DAWBA = Development and Well-Being Assessment; MYCHP = Mental Health of Children and Young People in England; SEN = special educational needs and disabilities.

Year	Follow-on study	Details
Wave 1 (2020)	Experience of lockdown/service use qualitative interviews	Cross et al., (2024)–semi-structured interviews with 10 young people aged 14 to 23 and 10 parents of children aged 5 to 18 to explore their experiences and beliefs about the impact of COVID-19 restrictions. Mathews et al., (2023) –semi-structured interviews with 6 young people aged 17 to 22 and 11 parents of children aged 5 to 16 to explore their experiences with mental health services during the pandemic, focusing on effectiveness, accessibility and concerns.
Wave 2 (2021)	MyJournE RESHAPE study	The study collected data on the mental health, wellbeing, and daily experiences of 230 children and 213 young people aged 11-23 using a survey and a two-week app-based mood and diary monitoring system, involving standardised measures and optional self-reports; 234 participants submitted mood entries and 123 recorded diary entries during the study period.
	Eating Disorders feasibility study	The study assessed the feasibility of online completion of the DAWBA eating disorder module with clinical raters among 1029 participants who screened positive in 2021 and estimated the persistence of eating difficulties in 2022.
	Special Educational Needs and Disabilities (SEND) interviews	The study explored the experiences of children and young people with SEND during the COVID-19 pandemic, focusing on how they adapted to home confinement, remote learning, and accessed education and mental health support. A total of 14 semi-structured interviews were conducted with 12 CYPs and 9 parents/caregivers.
Wave 4 (2023)	Eating Disorders follow-on	Children aged 11 to 16 years and their parents, and young people aged 17 to 25 years who screened positive on the DAWBA eating disorder screening questions were invited to complete the full DAWBA eating disorder module as part of the MYCHP questionnaire. This study was continuous with the Wave 4 survey for all those screening positive on the DAWBA eating disorder module and a pre-selected random sample of screen negatives and is reported in the main survey report. https://digital.nhs.uk/data-and-information/publications/statistical/mental-health-of-children-and-young-people-in-england.

Results

Data resource use

The findings of previous studies that used these data have enhanced awareness of CYP’s health and informed policies, particularly in government public health monitoring and decision making related to schools. For instance, during COVID-19, a time of significant social and environmental change and uncertainty, the 2020 follow-up wave revealed a marked increase in emotional difficulties among CYP due to social isolation, disruptions to education, and family stressors during the pandemic [17].

Strengths and weaknesses

These data, representative of England, enables the study of CYP’s mental health in association with contextual factors and demographics. The MHCYP 2017 survey achieved a 52% response rate, which is typical for large-scale mental health surveys but may introduce non-response bias. To address this, data were weighted to align with the population of 2 to 19-year-olds in England, adjusting for non-response and ensuring representativeness. These weights were updated in subsequent waves to account for additional attrition and are provided to analysts accessing the data (see Survey Design and Methods Report for 2017 and following waves on NHS England). Additionally, MHCYP 2017 and its follow-up waves provide longitudinal data, enabling the study of developmental trajectories over time. The use of validated measures and multiple informants for mental health and other assessments is also a strength.

There are inevitably limitations. First, the transition from the DAWBA, administered face-to-face in 2017, to the remotely administered SDQ in follow-up waves introduces methodological differences that may affect comparability over time. The DAWBA is a diagnostic tool involving multiple informants and clinical rating, whereas the SDQ is a brief screening questionnaire. As a result, the instruments differ in sensitivity and specificity and may classify mental health difficulties differently. However, the SDQ was also collected in 2017, so it is possible for studies to compare consistent measures of psychopathology across time. Notably, the prevalence of mental health conditions using the SDQ algorithm in 2017 (1 in 9) was lower than that estimated by the DAWBA (1 in 8) [17]. This suggests that the use of the SDQ will not have inflated the estimated prevalence of mental health condition in the follow-up waves. Additional diagnostic data was collected in relation to eating disorders using the DAWBA in 2021/2 and 2023. Changes in data collection mode—from interviewer-led, in-person assessments to online or telephone self-report—may also impact responses. Face-to-face methods allow for clarification and more contextual information, and may improve data quality, while remote completion may increase item non-response or misunderstandings, particularly in younger participants or those with lower digital literacy or certain disabilities. However, a comparison of interview versus paper and pencil completion among 66 parents of children aged 3 to 15 revealed a strong correlation between the two types of administration of the SDQ [32]. Other studies have found equally appropriate psychometric properties for either type of administration [33].

Remote methods may differentially affect participation across demographic groups, introducing potential bias. Although weighting and non-response adjustments are applied, residual differences may influence observed trends. Therefore, we recommend that longitudinal comparisons focus on consistent measures (e.g. SDQ scores across waves) and interpret changes with caution, recognising the potential influence of these methodological shifts. Second, as the 2017 baseline was not designed as a longitudinal study, attrition was significant. The 2020 response rate was 45%, with higher non-response among those at greater risk of mental health conditions, introducing potential bias. Third, the 2017 MHCYP survey was conducted as a cross-sectional study, designed to provide a snapshot of children’s mental health at that point in time. While the survey design allowed for the possibility of follow-up waves, the design is one of repeated cross-sectional surveys of the same sample, rather than a cohort study. Importantly, the “keeping in touch” strategies that would form an essential part of a cohort study were only funded between Waves 3 and 4 or follow up. As a result, attrition was significant and only a small number of children/families took part in every wave. Fourth, the 2020 and later waves did not use the DAWBA, except for eating disorders in 2023. While the SDQ has reasonable sensitivity and specificity, it is not a diagnostic tool like the DAWBA. However, in 2017, the SDQ any probable disorder estimate was lower (1 in 9) compared to the DAWBA prevalence estimate of any mental health condition (1 in 8) [17]. This is important because it suggests that the SDQ diagnostic algorithm did not substantially overestimate prevalence rates, which is a concern given the increased and high prevalences reported in the follow up waves. Importantly, prevalence of 11.1% via the SDQ and 12.5% from the DAWBA in 2017 are not substantially different. Fifth, MHCYP 2017 and its follow-up waves included only a small, if representative sample of ethnically diverse CYP and their families, limiting statistical power for ethnicity analysis. Finally, the MHCYP 2017 and follow-up waves do not systematically measure direct experiences of domestic abuse, coercive control, or detailed accounts of physical and emotional abuse within the home, due to safeguarding and ethical constraints [34].

Data resource availability and access

Comprehensive reports of descriptive statistics from these surveys are available from NHS England, which also provides access to the survey documents. Data access requires prior approval through the UK Data Service, and applications must comply with the General Data Protection Regulation (GDPR) 2018. The surveys can be accessed via the UK Data Service website, with the following study numbers: the 2017 baseline survey (UKDA-SN-9090-1), the 2020 follow-up wave (UKDA-SN-9128-2), the 2021 follow-up wave (UKDA-SN-9322-1), and the 2022 follow-up wave (UKDA-SN-9372-1).

Conclusion

This data resource profile has described The Mental Health of Children and Young People (MHCYP) 2017, a nationally representative study of England, along with its follow-up and follow-on studies. The multiformat data—featuring diagnostic assessments at the 2017 baseline and measures of mental health difficulties across follow-up waves—enable researchers to examine trends in child and adolescent mental health. Notably, the dataset allows for comparisons with the 1999 and 2004 MHCYP surveys. While the longitudinal component is more limited, it still offers valuable insights into mental health trajectories over time. Access to this data is available through the UK Data Service. Researchers must follow a specific application procedure, which includes completing Safe Researcher Training.

Ethics approval

The NHS Research Ethics Committee (REC), specifically the West London REC, approved the 2017 MHCYP survey (reference 16/LO/0155) and its follow-up waves. The 2017 baseline survey adhered to established protocols to ensure participant confidentiality and welfare. Ethics approval was renewed for each follow-up wave to align with updated methodologies. Follow-on studies received ethical approval from the University of Cambridge Psychology Ethics Committee (PRE.2020.145).

Author contributions

MK: Writing (Original draft preparation), Writing (editing and improving)

HB: Writing (Original draft preparation), Visualisation

TF: Conceptualisation, Supervision, Funding acquisition, Writing (editing and improving)

LC: Contribution to data resource development, Writing (editing and improving).

TND: Contribution to data resource development, Writing (editing and improving).

JD: Contribution to data resource development, Funding acquisition, Writing (editing and improving)

SM: Contribution to data resource development, Writing (editing and improving).

FM: Contribution to data resource development, Writing (editing and improving).

JP: Contribution to data resource development, Writing (editing and improving).

AB: Contribution to data resource development, Writing (editing and improving).

FMa (Franziska): Contribution to data resource development, Writing (editing and improving)

CF: Contribution to data resource development, Writing (editing and improving).

Funding

England’s Department of Health and Social Care funded the 2017 survey and follow-up waves, and it was commissioned by NHS Digital (now NHS England). The research was conducted by a consortium comprising the National Centre for Social Research (NatCen), the Office for National Statistics (ONS), the University of Cambridge, the University of Exeter Medical School, and Youthinmind. UK Research and Innovation (MR/V027751/1) funded the follow-on studies.

Acknowledgements

We would like to thank the children, young people and parents who participated in MHCYP, as well as Tracy Williams from the Office for National Statistics who worked on all the follow-up surveys. 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. TND was supported by a National Institute for Health Research (NIHR) Advanced Fellowship during work on this data resource (NIHR300056). SM receives salary support from MR/V049879/1. The views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care.

Conflict of interest

Tamsin Ford’s group receives funding for research methodology consultation from Place2Be, a third sector organisation that provides mental health training and interventions to schools across the UK.

Abbreviations

APSS:	Adolescent Psychotic-Like Symptom Screener
CYP:	Children and Young People
DAWBA:	Development and Well-being Assessment
DSM:	Diagnostic and Statistical Manual of Mental Disorders
FAD:	McMaster Family Assessment Device
GDPR:	General Data Protection Regulation
GHQ:	General Health Questionnaire
GP:	General Practitioner
ICD:	International Classification of Diseases
MHCYP:	Mental Health of Children and Young People
NHS:	National Health Service
NIHR:	National Institute for Health Research
ONS:	Office for National Statistics
PAS:	Pandemic Anxiety Scale
REC:	Research Ethics Committee
RSES:	Rosenberg Self-Esteem Scale
SAP:	Standardised Assessment of Personality Disorders
SAPAS:	Standardised Assessment of Personality – Abbreviated Scale
SDQ:	Strengths and Difficulties Questionnaire
SWEMWBS:	Short-form Warwick-Edinburgh Mental Wellbeing Scale
WEMWBS:	Warwick-Edinburgh Mental Wellbeing Scale
WHO:	World Health Organization

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