Development and Validation of the Suicidal Behaviours Questionnaire - Autism Spectrum Conditions and the Autistic Depression Assessment Tool - Adult, 2018-2019

Autistic people and those with high autistic traits (but not diagnosed) are at high risk of experiencing depression and suicidality. Yet, there are no depression or suicidality assessment tools developed or validated with or for these groups. Two widely used and validated mental health assessment tools originally developed for the general population (The Patient Health Questionnaire - 9 item (PHQ-9) and the Suicidal Behaviours Questionnaire - Revised (SBQ-R)), were adapted using feedback from autistic adults, to create the Suicidal Behaviours Questionnaire - Autism Spectrum Conditions (SBQ-ASC), and the Autistic Depression Assessment Tool - Adult (ADAT-A). Data from the two anonymous online surveys developing and validating these adapted tools are included in this data collection. Delphi Survey 1 aimed to gather feedback on the original, and penultimate versions of the adapted mental health assessment tools, prior to finalising and testing the measurement properties of the original and adapted tools. Data collection through an anonymous online Qualtrics survey took place between 31st August 2018 - 31st October 2018. A community sample of autistic, possibly autistic (awaiting assessment - not yet diagnosed) and non-autistic adults were invited to rate the clarity, importance, and provide qualitative feedback for each item on the original PHQ-9 and SBQ-R, and penultimate version of the adapted versions of these tools (ADAT-A and SBQ-ASC). Validation survey 2 aimed to establish whether: a) the final adaptations addressed all the issues identified in the Delphi survey; b) test the measurement properties of the finalised adapted tools. Data collection through an anonymous online Qualtrics survey took place between 15th July 2019 - 30th August 2019. A community sample of autistic, possibly autistic (self-identified but not diagnosed), and non-autistic adults were invited to complete the original (PHQ-9 and SBQ-R) and updated versions of the adapted versions of these tools (ADAT-A and SBQ-ASC), and provide qualitative feedback on each tool (to ensure that all issues identified in the Delphi survey had been addressed). Participants also completed other measures to help test convergent and divergent validity of the adapted tools (self-report measures of autistic traits (AQ), camouflaging autistic traits (CAT-Q), depression (PHQ-9), anxiety (ASA-A), thwarted belongingness and perceived burdensomeness (INQ-15)). Please note, that validation survey 2 included the finalised SBQ-ASC which has now been published and made available. However, results from validation survey 2 showed that the ADAT-A needed further refinement to wording and response options. Therefore, the validation survey 2 data for the ADAT-A is not for the finalised version of this measure.Autism Spectrum Conditions (ASC) are a diverse group of developmental brain conditions that cause difficulties in communication, social interaction, unusually narrow interests and difficulties adapting to change. One in 100 people (700,000 in the UK) are autistic, most of whom are adults. A majority of the total economic cost of ASC to the UK is spent on supporting adults (£25 billion out of a total of £28 billion), with 36% of this cost attributable to lost employment opportunities (Knapp et al. 2009). The individual and social costs of ASC in adulthood are also high, with research showing poor outcomes in terms of educational attainment, unemployment (Howlin, 2000), and high rates of depression (32%), suicidal thoughts (66%) and suicidal behaviours (35%) (Cassidy et al. 2014). The latest reports from the ESRC Centre for Economic Performance, and the Chief Medical Officer, describe the high individual, social and economic costs of leaving mental health problems such as depression untreated. However, there are no valid measures of depression or suicidality for autistic adults, despite evidence that these are common problems (Cassidy et al. 2014; Segers and Rawana, 2014). Measures for typically developing adults are not appropriate for autistic adults, who tend to interpret questions literally (Happe et al. 1995), and have difficulty verbalising their emotional experiences (Bird et al. 2010). Depression and suicidality also manifest differently in ASC; inflexible thinking and impulsivity may increase risk (Cassidy et al. 2014). In addition to lack of appropriate measures, research progress is also hampered by the lack of a data set that includes enough autistic adults to effectively evaluate their rates of depression and suicidality on a national scale; the UK adult psychiatric morbidity survey (2007) only included 19 autistic adults. The lack of research and appropriate measures have had a profoundly negative impact on autistic adults; 1) it is not possible to conduct detailed research into the nature, risk or protective factors for depression or suicidality in autistic adults; 2) it is not possible to effectively assess their depression or suicide risk in clinical practice; 3) without the knowledge base or assessment tools, new theories and effective evidence based treatments cannot be developed or evaluated; 4) we cannot effectively evaluate the prevalence of depression or suicidality on a national scale, in order to inform effective government policy. Hence, autistic adults are not currently able to access evidence based assessment or therapies for depression or suicidality, despite being at potentially high risk. This research project will address these fundamental issues by developing the first empirically validated measures of depression and suicidality for autistic adults, for use in a national survey. This will form the first nationally representative dataset containing rates of depression and suicidality in autistic adults in the UK, made available for secondary analysis. These objectives will be achieved by creating synergy between psychiatrists and clinicians involved in ageing, autism, suicide, mental health and risk assessment research, across internationally recognized institutions (Universities of Coventry, Nottingham, Newcastle, and Cambridge). This research will build on my previously published research, which has utilized big data to explore the health and behaviour of autistic adults, including the first large-scale clinic study of depression and suicidality in adults with late diagnosis of Asperger Syndrome (a subgroup on the autism spectrum without co-occurring language delay or intellectual disability) (Cassidy et al., 2014). This project will enable me to foster a new inter-disciplinary mixed-methods approach to the study of mental health in ASC, which I will continue to lead beyond the funding period.