The prevalence of mental illness and service use in people with borderline intellectual functioning compared to the general population.

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Objective for processing

The objective is to use the APMS 2014 dataset for the purposes of research (MSc research project). A secondary analysis of the data will be carried out by researchers at UCL in order to investigate how loneliness may affect people with borderline intellectual functioning. The prevalence of mental health disorders in adults with intellectual disabilities has been reported to be higher, at 35.2% (Cooper et al., 2007), compared to a prevalence of 17% for the general population in England. Loneliness has been associated with being female but there appears to be a complex relationship with age, with some studies reporting a U shaped relationship with higher levels of loneliness in younger and older people, or higher levels in older age. Other socio-demographic factors associated with loneliness include being single, living alone, low education and income, immigration status and low social support. Loneliness has been associated with life style factors such as smoking, being less physically active and lower consumption of fruit and vegetables. Loneliness is associated with increased mortality and higher rates of chronic diseases such as raised blood pressure and cholesterol and chronic heart disease. Loneliness has also been linked to depression and higher levels of psychological distress, suicide and psychosis. Background A prevalence of loneliness of 10.5% has been reported in the general population. Loneliness has been associated with being female but there appears to be a complex relationship with age, with some studies reporting a U shaped relationship with higher levels of loneliness in younger and older people, or higher levels in older age. Other socio-demographic factors associated with loneliness include being single, living alone, low education and income, immigration status and low social support. Loneliness has been associated with life style factors such as smoking, being less physically active and lower consumption of fruit and vegetables. Loneliness is associated with increased mortality and higher rates of chronic diseases such as raised blood pressure and cholesterol and chronic heart disease. Loneliness has also been linked to depression and higher levels of psychological distress, suicide and psychosis. [2 paragraphs unchanged] The APMS dataset has not previously been used to explore loneliness in this group. Because of this, analysis of the APMS data was previously carried out by researchers at UCL to investigate how loneliness may affect people with borderline intellectual functioning, as part of a MSc research project. The aims of this work were as follows: The aim of the study is to examine loneliness in people with borderline intellectual functioning and compare their physical and mental outcomes to the general population. The specific objectives are to: [4 paragraphs unchanged] The data will be analysed only within University College London. It will not be used to support a larger programme of work. The above previous aims of the research have now been investigated using the data supplied under this Agreement. UCL would like to explore new research questions. People with borderline intellectual functioning (BIF) do not meet the criterion of having an intellectual disability and are therefore often overlooked by learning disability and mental health services (Wieland and Zitman, 2016). Although the criterion for diagnosing borderline intelligence using IQ scores has been removed from the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) - a manual put together by hundreds of international experts that defines and classifies mental disorders - and BIF is not regarded as a disorder, people with BIF still constitute a group that is more vulnerable to developing mental health problems than the general population with average or above average IQ (Hassiotis et al., 2008; Emerson, 2011). In particular, BIF is associated with poor social functioning (Hassiotis et al., 2008; Gigi et al., 2014), increased rates of psychiatric diagnoses (Zammit et al., 2004) and substance misuse (Gigi et al., 2014; Didden et al., 2009). Adults with BIF tend to have poorer adaptive functioning, which in turn result in increased risk of poverty (Emerson, 2011), challenges in day-to-day functioning (Hassiotis et al., 2008), limited social support (Gigi et al., 2014; Hassiotis et al., 2008), and limited to no access to specialised services (Emerson, 2011; Hassiotis et al., 2008) – which also translates to their going unnoticed. These comprise of few of the many risk factors that could impede on the presentation and treatment of psychiatric disorders. It is therefore important to investigate the prevalence of mental health disorders in this group. As people with BIF are often deemed as not meeting full criteria to access specialist learning disabilities services, there is little knowledge of the treatments and services that this group receive for mental health problems. University College London (UCL) aim to examine trends of psychiatric diagnoses, treatments and access to services across time (1993 – 2003) in people with BIF compared to the general population. Aims 1. Compare the prevalence of common mental health disorders, psychosis, substance misuse and suicidal behaviours in people with borderline intellectual functioning and the general population. 2. Explore relationships between sociodemographic factors and psychiatric diagnoses in people with borderline intellectual functioning and the general population. 3. Examine time-trends in treatment received and services accessed by people with borderline intellectual functioning in comparison to the general population. To explore the above aims, Adult Psychiatric Morbidity Survey (APMS) data is required. The Adult Psychiatric Morbidity Survey is a sample survey of private households in England, interviewing around 7,500 adults. It provides data on the prevalence of both treated and untreated psychiatric disorder in the English adult population (aged 16 and over). The 2014 APMS dataset is held on behalf of NHS Digital by the UK Data Service (UKDS) (www.ukdataservice.ac.uk ) and UKDS are responsible for dissemination under direction by NHS Digital. UCL will get the whole dataset; there is no facility to select individual variables. The data within the APMS dataset is pseudonymised. The data will be processed according to article 6(1) e – legitimate interest under “public task”. UCL is a public authority and therefore the legitimate interest for processing data is under “public task”. Processing data for the purposes of research is considered to be one of UCL’s public tasks. The processing of the APMS dataset is considered necessary as there are no other means of examining the objectives in a less restrictive way. Individuals will not be harmed through the processing of the data. In addition, data will be processed according to article 9(2) j – processing is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes. UCL ensures that the processing meets the public interest test and appropriate safeguards are in place such as using “technical and organizational measures” to ensure minimisation e.g. pseudonymisation and not processing in a way that will cause damage or distress to individuals. University College London is the sole data controller and is also the data processor. The data will be analysed only within University College London. It will not be used to support a larger programme of work.

Processing activities

NHS Digital reminds all organisations party to this agreement of the need [17 words unchanged] that use) by “Personnel” (as defined within the Data Sharing Framework Contract ie: i.e.: employees, agents and contractors of the Data Recipient who may have access to that data). The 2014 APMS dataset is held on behalf of NHS Digital by the UK Data Service (UKDS) (www.ukdataservice.ac.uk ) and UKDS are responsible for dissemination under direction by NHS Digital. UCL will get the whole dataset; there is no facility to select individual variables. They will be able to download the dataset from UKDS for the [49 words unchanged] of individuals being able to identify anyone taking part in the survey. [1 paragraph unchanged] The data obtained will be fully anonymous. It will be stored directly and processed only using UCL Data Safe Haven, [32 words unchanged] numbers suppressed. No data will be linked to record level patient data. Justification for processing the data: The data will be processed according to article 6(1) e – legitimate interest under “public task”. UCL is a public authority and therefore the legitimate interest for processing data is under “public task”. Processing data for the purposes of research is considered to be one of UCL’s public tasks. The processing of the APMS dataset is considered necessary as there are no other means of examining the objectives in a less restrictive way. Individuals will not be harmed through the processing of the data. In addition, data will be processed according to article 9(2) j – processing is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes. UCL ensures that the processing meets the public interest test and appropriate safeguards are in place such as using “technical and organizational measures” to ensure minimisation e.g. pseudonymisation and not processing in a way that will cause damage or distress to individuals. [1 paragraph unchanged] A secondary analysis of data will be conducted using The Adult Psychiatric Morbidity Survey, 2014. This is the fourth and most recent survey of adult mental health in the general population. It comprised two phases, an initial interview with the whole sample and a second phase interview that was conducted with a sub-sample of phase one participants by clinically trained interviewers coordinated by the University of Leicester. Sample: The survey employed a multi-stage stratified probability sampling design. The sampling frame was based on the small user Postcode address File (PAF), which permitted private households to be indentified. The primary sampling units (PSU) were individual or groups of postcode sectors. The PSUs were stratified by a number of different strata and a random sample was obtained from this list. Addresses that did not contain private households were excluded. One person over the age of 16 was randomly selected to take part in the survey per household. The study will include two population samples: people with BIF and the general population. Participants are identified as having BIF based on having an IQ between 70 to 85 (i.e. between 1 and 2 standard deviations below the mean on the normal curve of the distribution of intelligence). 13313 individuals were contacted but 7546 participants completed the survey (57 % response rate). Data Collection: Measures The Adult Psychiatric Morbidity Survey has been conducted in 1993, 2000, 2007 and 2014 and is a survey of adult mental health in the general population in the UK. Data was collected through structured interviews. The proposed study will conduct a secondary analysis on the APMS exploring trends of common mental health disorders in people with borderline intellectual functioning across time (1993 – 2014). 1. Measuring intellectual functioning Measures: 1. Intellectual functioning will be assessed using the functioning: The National Adult Reading Test (NART), which is a standardized test designed (NART) will be used to estimate measure the level of premorbid intelligence level of in adults. The NART It consists of 50 English words that are presented in ascending order of difficulty (Nelson & Willison, 1991). The NART error (Nelson, 1982). A verbal IQ score is calculated from by measuring the total number of reading errors made by the candidate and this is used to estimate made. Participants who obtain a verbal IQ score. An IQ score between 70-85 will be used to identify the sample of participants with BIF and those with an IQ greater than 86 have no educational qualifications will be identified as being in having BIF, and those who have scores over 86 will be classified as belonging to the general population (variable name: iqbest2g) . The sample will be further defined by excluding participants who have educational qualifications of A-levels or higher. group. 2. Measuring loneliness and social support 2. Common mental health disorders: The Clinical Interview Schedule Revised (CIS-R) will be used to identify any common mental health disorders, which includes depression, phobia, panic attacks, post-traumatic stress disorder, post-natal depression, nervous breakdown, obsessive compulsive disorder and season affective disorder. Participants diagnosed with or being treated for any of the 8 common mental disorders in the past 12 months at the time of assessment will be examined. Loneliness will be measured using one item “I feel lonely and isolated from other people”. A four point likert scale was used (very much, sometimes, not often and not at all). 3. Psychosis: will be measured using the Psychosis Screening Questionnaire (PSQ) (Bebbington and Nayani, 1995). Social support will be measured using the total score from 7 items measuring social support, which includes items such as “there are people I know amongst my family and friends who make me happy”, “there are people I know amongst my family and friends who can be relied on no matter what” and “there are people amongst my family and friends who give me support and encouragement”. These questions were rated on a three point scale (not true, partly true, certainly true). 4. Substance Misuse: will be measured using a series of questions on drug dependence based on Diagnostic One Interview Schedule (Malgady et al., 1992) and alcohol use disorders using AUDIT (Saunders et al., 1993), and SADQ (Stockwell et al., 1994). In addition, we will use one item using a variable that has been derived from the Social support scale that examines the number of family and friends the respondent feels close to (variable name: Primgrp) 5. Suicidal Behaviour: Self-reported measures of suicidal behaviour and attempted suicide will be used. 3. Wellbeing Proposed Analysis Well being will be measured using the total score on the Warwick- Edinburgh mental wellbeing scale (WEMWBS). This is a 14-item scale with five response categories, providing a total score ranging from 14–70. The items are all cover both feeling and functioning aspects of mental wellbeing. A higher score The data will be analysed using Stata. Both sample groups will be described using descriptive statistics. Point prevalence of selected psychiatric disorders will be calculated for both sample groups (people with BIF and the general population). Regression analysis will be used to explore and compare relationships between sociodemographic factors and psychiatric diagnoses in both groups. Further regression analysis will be conducted to examine time-trends in treatment received and services accessed by both groups. indicates a higher level of mental wellbeing. 4. Common mental health disorders The Clinical Interview Schedule Revised (CIS-R) was used to identify the presence of common mental disorders. The following will be examined: Participants who were diagnosed with depression in the past 12 months, participants who were diagnosed with phobia in the past 12 months, participants who were diagnosed with panic attacks in the last 12 months and participants who were diagnosed with Post Traumatic Stress Disorder in the past 12 months . The overall CISR score (variable name CISR Two) and participants who were diagnosed and treated with any common mental health problem in the last 12 months will also be examined. Suicidal thoughts in the last 12 months will be analysed. 5. Physical health disorders One item about general heath will be used: “How is your health in general?”. This item is rated on a 5 point Scale (excellent, very good, good, fair or poor). Participants were presented with a list of 22 physical conditions and were asked whether they had ever had any of these conditions; whether they had the condition in the past year; whether the condition had been diagnosed by a health professional and if they received any medication or other treatment for it. The presence of any chronic disease (e.g. asthma, diabetes, epilepsy, high blood pressure, cancer) in the last 12 month will be examined as well as individual disorders. 6. Socio-demographic variables The following socio-demographic variables will be analysed: age, sex, marital status, ethnicity, income, any educational qualifications, employment (paid work in the last 7 days (wrking), ever had a job, accommodation. Whether people feel safe in their neighbour hood will also be examined using 1 item: “ I feel safe around here in the day time”. This item was measured on a five point scale (strongly agree to strongly disagree). Analysis Stata will be used to analyse the data and sampling weights will be applied to all the analyses. Descriptive statistics will be used to describe the sample (proportion of people with borderline intellectual functioning, the number of males and females, mean age and ethnicity in both groups (general population and borderline intellectual functioning). The proportion of people reporting loneliness will be compared in people with borderline intellectual functioning and the general population. Data will be presented as weighted percentages and Chi Square tests/ T tests will be reported, where appropriate. Subgroup analysis will be carried with both groups to identify the relationship between loneliness (dependent variable) and socio-demographic variables, mental health and chronic physical disorders. The moderating effects of loneliness on the relationship between intellectual functioning and chronic mental health and physical disorders will be analysed.

Expected output

The results of the study will be of interest to mental health practitioners and mental health services that encounter people with borderline intellectual impairment. The study will raise awareness of the issues experienced by people with borderline intellectual functioning and how their needs should be better met. The findings of the study will be published in a peer reviewed scientific journal such as the Journal of Intellectual Disability Research and presented at conferences (e.g. the International Association for the Scientific Study of Intellectual and Developmental Disabilities). Personal identifiable data will not be published. Outputs will only contain aggregate level data. UCL have published a paper in the Journal of Affective Disorders using the APMS dataset, which relates to the previous aims of the research (Papagavriel K, Jones R, Sheehan R, Hassiotis A, Ali A. The association between loneliness and common mental disorders in adults with borderline intellectual impairment. Journal of Affective Disorders. 2020; 277: 954-961). The findings were also presented at the Royal College of Psychiatrists International Conference in July 2019. The target data for publication within a scientific journal is 02/01/2019. The results of the above study and ongoing work will be of interest to mental health practitioners and mental health services that encounter people with borderline intellectual impairment. The study will raise awareness of the issues experienced by people with borderline intellectual functioning and how their needs should be better met. The findings from the new research aims will be published in a peer reviewed scientific journal such as the Journal of Intellectual Disability Research and presented at conferences (e.g., the International Association for the Scientific Study of Intellectual and Developmental Disabilities). Personal identifiable data will not be published. Outputs will only contain aggregate level data. In order to protect patient confidentiality in publications resulting from analysis of APMS data users must: The target date for publication within a scientific journal for the new research aims is 02/01/2023. In order to protect patient confidentiality in publications resulting from analysis of APMS data, users must: [2 paragraphs unchanged]

Expected measurable benefits

The research study will further the understanding of the mental and physical health impacts of loneliness in people with borderline intellectual functioning. The research study will further the understanding of the mental and physical health impacts of loneliness in people with borderline intellectual functioning. The study will also further the understanding of the prevalence of mental health disorders in people with borderline intellectual functioning and how this has changed over time. It may help to improve the planning mental health services for this group of individuals whose needs are often neglected or unmet, and highlight the need for additional training for front line staff involved in the assessment of mental health problems in this group (e.g., communication skills). The results will be disseminated to commissioners and mental health charities (e.g. MIND), including befriending organisations that support people who are lonely or those who have limited or no social support (target date 01/06/2019). Tackling and reducing loneliness may lead to improvements in physical and mental health outcomes and therefore the research findings could help to promote the role of befriending and volunteering organisations and provide evidence for the need to lead to develop interventions to reduce loneliness in this group (and other disadvantaged groups). The findings of the study will be disseminated to clinicians and commissioners in order to improve awareness of mental health disorders in people with borderline intellectual functioning.

Benefits reported

Yielded Benefits is not a requirement for new applications. Research is ongoing, and the paper that has already been published on loneliness in people with BIF was published only recently (2020). The benefits to the Health and Social Care system that are expected to be yielded from this work have not yet been established, but it is hoped that the benefits described above will arise once the work is complete.