Autism-related dietary preferences mediate autism-gut microbiome associations.

There is increasing interest in the potential contribution of the gut microbiome to autism spectrum disorder (ASD). However, previous studies have been underpowered and have not been designed to address potential confounding factors in a comprehensive way. We performed a large autism stool metagenomics study (n = 247) based on participants from the Australian Autism Biobank and the Queensland Twin Adolescent Brain project. We found negligible direct associations between ASD diagnosis and the gut microbiome. Instead, our data support a model whereby ASD-related restricted interests are associated with less-diverse diet, and in turn reduced microbial taxonomic diversity and looser stool consistency. In contrast to ASD diagnosis, our dataset was well powered to detect microbiome associations with traits such as age, dietary intake, and stool consistency. Overall, microbiome differences in ASD may reflect dietary preferences that relate to diagnostic features, and we caution against claims that the microbiome has a driving role in ASD.

ACT-i, an insomnia intervention for autistic adults: a pilot study.

BACKGROUND: Insomnia and disturbed sleep are more common in autistic adults compared with non-autistic adults, contributing to significant social, psychological and health burdens. However, sleep intervention research for autistic adults is lacking. AIMS: The aim of the study was to implement an acceptance and commitment therapy group insomnia intervention (ACT-i) tailored for autistic adults to examine its impact on insomnia and co-occurring mental health symptoms. METHOD: Eight individuals (6 male, 2 female) aged between 18 and 70 years, with a clinical diagnosis of autism spectrum disorder, and scores ranging from 9 to 26 on the Insomnia Severity Index (ISI) participated in the trial. Participants were assigned to one of two intervention groups (4 per group) within a multiple baseline over time design for group. Participants completed questionnaires pre-intervention, post-intervention, and at 2-month follow-up, actigraphy 1 week prior to intervention and 1 week post-intervention, and a daily sleep diary from baseline to 1 week post-intervention, and 1 week at follow-up. RESULTS: At a group level there were significant improvements in ISI (λ2=10.17, p=.006) and HADS-A (anxiety) (λ2=8.40, p=.015) scores across the three time points. Clinically reliable improvement occurred for ISI scores (n=5) and HADS-A scores (n=4) following intervention. Client satisfaction indicated that ACT-i was an acceptable intervention to the participants (median 4 out of 5). CONCLUSIONS: This pilot study with eight autistic adults indicates that ACT-i is both an efficacious and acceptable intervention for reducing self-reported insomnia and anxiety symptoms in autistic adults.

Stress and well-being in autistic adults: Exploring the moderating role of coping.

The wider stress literature points to negative associations between stress and well-being. Similarly, the use of engagement coping strategies and disengagement coping strategies in the face of stress are related to improved and reduced well-being respectively. However, in the autistic population stress and coping research is limited to date, and the extent to which coping may moderate the relationship between stress and well-being is not known. Using data from an Australian online study, we explored the potential moderating (i.e. buffering or exacerbating) role of coping in the relationship between stress and well-being in a sample of autistic adults (N = 86). Our findings indicated that increased stress was associated with lower well-being. Further, moderation analyses showed that while both engagement coping (e.g. problem solving, positive appraisal) and disengagement coping (e.g., self-distraction, being in denial) strategies had significant positive and negative direct effects on well-being respectively; engagement coping also moderated the relationship between stress and well-being, buffering the impact of stress on well-being. Our results illustrate the different underlying mechanisms by which coping strategies may be associated with stress and well-being. They also highlight the potential protective role of engagement coping strategies, which can be incorporated into the promotion and maintenance of well-being in autistic adults.

Brief Report: Discrete Effortful Control Skills Moderate Relations Between Childhood Behavioural Inhibition and Mental Health Difficulties in Autistic Youth.

Studies of the general population suggest that the risk for mental health difficulties conferred by dispositional behavioural inhibition (BI) may be modified by self-regulation; however, this possibility has not been explored in the context of autism. This study investigated the moderating effects of attentional-, activation-, and inhibitory control on the relationship between childhood BI and anxiety and depression among 47 autistic youths (55% male, Mage = 19.09 years, SD = 2.23). Childhood BI was associated with anxiety at low but not high levels of attentional- and activation control, and depression at low but not high levels of attentional control. However, there were no moderating effects of inhibitory control. These preliminary findings are partially consistent with those from the general population and point to avenues for future work.

Brief Report: Longitudinal Role of Coping Strategies on Mental Health Outcomes in Autistic Youth and Adults.

The stress literature suggests that coping strategies are implicated in mental health outcomes. However, the longitudinal relationship between coping strategies and mental health in the autistic adult population has not yet been examined. This 2-year longitudinal study examined the predictive role of both baseline and change in coping strategy use over time (i.e., an increase or decrease) on anxiety, depression, and well-being after 2-years in 87 autistic adults aged 16 to 80 years. Controlling for baseline mental health, both baseline and increase in disengagement coping strategies (e.g., denial, self-blame) predicted higher anxiety and depression, and lower well-being, while an increase in engagement coping strategies (e.g., problem solving, acceptance) predicted higher well-being. These findings extend the current coping literature in autistic adults, offering insight into mental health support and intervention options.

The impact of sleep quality, fatigue and social well-being on depressive symptomatology in autistic older adolescents and young adults.

Depression and poor sleep quality commonly co-occur with autism, and depression has been associated with loneliness and reduced social support. In non-autistic samples, poor sleep quality and daytime fatigue also contribute to depression. However, the contribution of sleep quality and fatigue to depressive symptoms, and how they interact with social factors to influence depression in autism remain unexplored. Our aim was to examine these relationships in 114 young autistic adults aged 15-25 years (57% male) from the SASLA online, longitudinal study (baseline and 2-year follow-up). Hierarchical multiple regression models examined the association between social well-being (social integration and social contribution; T1), sleep quality (T1, T2), and fatigue (T1, T2) on depression (T1, T2). Two mediation models were conducted on T1 data predicting depression from sleep quality though fatigue and sleep quality through social well-being. Depression and fatigue scores did not change over 2 years, but sleep quality worsened. The T1 regression model was significant (R2 = 36%) with fatigue and social contribution individually predicting depression symptomatology. The longitudinal regression model was also significant (adjusted R2 = 57%) with social contribution (T1) as the only significant predictor of depression (T2). Fatigue trended towards mediating the sleep quality-depression relationship, while social well-being was a significant partial mediator of this relationship. Results highlight that sleep quality, fatigue, and social well-being contribute to depression among young autistic adults. Interestingly, fatigue and social well-being were independently associated with depression. Thus, addressing sleep quality and associated fatigue, and social well-being is important when treating depression in autistic individuals.

Development of the Impact of Diagnosis Scale-Revised (IODS-R).

No tools quantify the experience, psychological, and practical impact of receiving a diagnosis from a non-deficit perspective. Autism is increasingly late diagnosed in adulthood. The Impact of Diagnosis Scale (IODS) was initially developed for borderline personality disorder. We aimed to develop a revised version suitable for autistic adults and potentially other diagnostic groups. Following a trial of a preliminary revision, the researchers and autistic research advisors co-produced an expanded pool of 46 items, scored on 7-point Likert-type scale, within 6 hypothesized domains. Scale reduction processes were applied to data from 125 formally diagnosed autistic adults. Following iterative rounds of factor analysis using maximum likelihood estimation with Promax rotation, 22 items were retained across 4 domains to comprise the IODS-R. The IODS-R adds new understanding to the experience of receiving an autism diagnosis in adulthood. It may be useful for evaluating diagnostic services and other diagnostic groups.

Interactions between the lipidome and genetic and environmental factors in autism.

Autism omics research has historically been reductionist and diagnosis centric, with little attention paid to common co-occurring conditions (for example, sleep and feeding disorders) and the complex interplay between molecular profiles and neurodevelopment, genetics, environmental factors and health. Here we explored the plasma lipidome (783 lipid species) in 765 children (485 diagnosed with autism spectrum disorder (ASD)) within the Australian Autism Biobank. We identified lipids associated with ASD diagnosis (n = 8), sleep disturbances (n = 20) and cognitive function (n = 8) and found that long-chain polyunsaturated fatty acids may causally contribute to sleep disturbances mediated by the FADS gene cluster. We explored the interplay of environmental factors with neurodevelopment and the lipidome, finding that sleep disturbances and unhealthy diet have a convergent lipidome profile (with potential mediation by the microbiome) that is also independently associated with poorer adaptive function. In contrast, ASD lipidome differences were accounted for by dietary differences and sleep disturbances. We identified a large chr19p13.2 copy number variant genetic deletion spanning the LDLR gene and two high-confidence ASD genes (ELAVL3 and SMARCA4) in one child with an ASD diagnosis and widespread low-density lipoprotein-related lipidome derangements. Lipidomics captures the complexity of neurodevelopment, as well as the biological effects of conditions that commonly affect quality of life among autistic people.

Coping-resilience profiles and experiences of stress in autistic adults.

Emerging studies allude to high stress in autistic adults. Considering the detrimental impact of stress on health outcomes, examining individual resources which may influence the extent to which stress is experienced (e.g., coping and resilience) is vital. Using a person-focused approach, this study aimed to identify coping-resilience profiles, and examine their relations to general perceived stress and daily hassles in a sample of autistic adults (N = 86; aged 19-74 years). Cluster analysis identified four coping-resilience profiles (i.e., high cope/ low resilience, low cope/ high resilience, engage cope/ high resilience, and disengage cope/ low resilience). The high cope/ low resilience and disengage cope/ low resilience groups had significantly higher general perceived stress than the remaining groups. No significant group differences were noted in relation to daily hassles. Jointly addressing coping and resilience may be beneficial on the perceived stress experienced in autistic adults. The use of coping-resilience profiles may also allow for the personalization of stress management and support options in the autistic adult population.

Associations between coping strategies and mental health outcomes in autistic adults.

Compared to the general population, mental health difficulties are commonly reported in autistic adults. However, the ways in which coping strategies are associated with mental health and well-being in this population remain unknown. Further, we do not know if, and if so, how these associations might differ to that of non-autistic adults. In this study, we hypothesized that in both our autistic (N = 255) and non-autistic (N = 165) adult samples, disengagement coping strategies (e.g., denial) would relate to poorer mental health and well-being, while engagement coping strategies (e.g., problem solving) would relate to better mental health and well-being. Regression analyses revealed that higher use of disengagement coping strategies was significantly associated with higher levels of anxiety and depression, and lower levels of well-being in both samples. In contrast, increased use of engagement coping strategies was associated with better well-being, but only in the autistic sample. Our results contribute to the characterization of negative and positive mental health outcomes in autistic adults from a coping perspective, with potential to offer novel information regarding coping strategies to consider when addressing support options for mental health difficulties in the autistic adult population. LAY SUMMARY: Mental health conditions (such as anxiety and depression) and poor well-being are commonly reported in autistic adults. Research suggests that how one copes with stress is associated with one's mental health and well-being. However, we have little information about how coping strategies relate to the mental health of autistic adults, and whether this might be different in non-autistic adults. In this study, we examined the relationship between coping strategies and mental health in a large group of autistic individuals aged 15-80 years. We then compared this with similar aged non-autistic individuals. We found that in both the autistic and non-autistic individuals, using more disengagement coping strategies (such as being in denial, blaming oneself) was related to poorer mental health and well-being. Additionally, using more engagement coping strategies (such as problem solving, acceptance) was related to better mental health and well-being, but only in the autistic individuals. These results can help inform support services, as they highlight the coping strategies that may need to be focused on (i.e., developing engagement coping strategies and reducing disengagement coping strategies) in order to better support the mental health of autistic individuals.

Diagnostic Accuracy of the Social Attention and Communication Surveillance-Revised With Preschool Tool for Early Autism Detection in Very Young Children.

Importance: Early identification of children on the autism spectrum is crucial to facilitate access to early supports and services for children and families. The need for improved early autism identification tools is highlighted by the lack of sufficient diagnostic accuracy in current tools. Objectives: To examine the diagnostic accuracy of the Social Attention and Communication Surveillance-Revised (SACS-R) and SACS-Preschool (SACS-PR) tools when used with a large, community-based, convenience sample and identify the prevalence of autism in this sample. Design, Setting, and Participants: This diagnostic accuracy study was conducted in Melbourne, Australia, training maternal and child health nurses who monitored 13 511 children aged 11 to 42 months using the SACS-R and SACS-PR during their routine consultations (June 1, 2013, to July 31, 2018). Children identified as being at high likelihood for autism (12-24 months of age: n = 327; 42 months of age: n = 168) and at low likelihood for autism plus concerns (42 months of age: n = 28) were referred by their maternal and child health nurse for diagnostic assessment by the study team. Data analysis was performed from April 13, 2020, to November 29, 2021. Exposures: Children were monitored with SACS-R and SACS-PR at 12, 18, 24, and 42 months of age. Main Outcomes and Measures: Diagnostic accuracy of the SACS-R and SACS-PR was determined by comparing children's likelihood for autism with their diagnostic outcome using clinical judgment based on standard autism assessments (Autism Diagnostic Observation Schedule-Second Edition and Autism Diagnostic Interview-Revised). Results: A total of 13 511 children (female: 6494 [48.1%]; male: 7017 [51.9%]) were monitored at least once with the SACS-R at their 12-, 18-, and 24-month-old routine maternal and child health consultations (mean [SD] age, 12.3 [0.59] months at 12 months; 18.3 [0.74] months at 18 months; 24.6 [1.12] months at 24 months) and followed up at their 42-month maternal and child health consultation (mean [SD] age, 44.0 [2.74] months) with SACS-PR (8419 [62.3%]). At 12 to 24 months, SACS-R showed high diagnostic accuracy, with 83% positive predictive value (95% CI, 0.77-0.87) and 99% estimated negative predictive value (95% CI, 0.01-0.02). Specificity (99.6% [95% CI, 0.99-1.00]) was high, with modest sensitivity (62% [95% CI, 0.57-0.66]). When the SACS-PR 42-month assessment was added, estimated sensitivity increased to 96% (95% CI, 0.94-0.98). Autism prevalence was 2.0% (1 in 50) between 11 and 30 months of age and 3.3% (1 in 31) between 11 and 42 months of age. Conclusions and Relevance: The SACS-R with SACS-PR (SACS-R+PR) had high diagnostic accuracy for the identification of autism in a community-based sample of infants, toddlers, and preschoolers, indicating the utility of early autism developmental surveillance from infancy to the preschool period rather than 1-time screening. Its greater accuracy compared with psychometrics of commonly used autism screening tools when used in community-based samples suggests that the SACS-R+PR can be used universally for the early identification of autism.

Autistic Adults' Experiences of Diagnosis Disclosure.

As autism is an invisible and often stigmatised condition, disclosing the diagnosis may lead to both support and/or discrimination. This mixed-methods questionnaire study examined autistic adults' experiences of disclosure in various contexts. The sample consisted of 393 participants aged 17-83 years from two longitudinal surveys. Almost all participants disclosed their diagnosis to someone, most commonly to friends. A significant minority of participants studying and/or working at the time had not disclosed to their education provider/employer. Content analysis of open-ended responses showed participants desired to gain understanding and support from disclosure but feared prejudice. While some received support, others encountered dismissiveness and misunderstanding. Findings highlight the need to improve autism understanding and reduce stigma within and beyond educational and employment contexts.

Brief Report: What Happens After School? Exploring Post-school Outcomes for a Group of Autistic and Non-autistic Australian Youth.

Young autistic Australians are less likely to attend higher education and have lower employment rates than non-autistic Australians (in: Australian Bureau of Statistics, Survey of disability, ageing and carers Australia: Summary of Findings 2018. Australian Bureau of Statistics, Canberra, 2019a). Few studies have examined post-school outcomes among this population. Using data from the first phase of a national longitudinal study including autistic (n = 79) and non-autistic (n = 107) 17-25-year olds, we found young autistic adults were (a) less likely to be employed, (b) more likely to attend technical and further education (TAFE) than university, (c) more likely to enrol in higher education on a part-time basis and (d) less likely to be engaged in both higher education and employment, than their non-autistic peers. Findings highlight a need to understand post-school trajectories of young autistic adults.

Inter-relationships between trait resilience, coping strategies, and mental health outcomes in autistic adults.

Resilience has been depicted as a key characteristic in the promotion of mental health in the face of stress and adversity. Despite high levels of stress encountered in the autistic population, resilience studies remain scarce. Using data from an Australian longitudinal adult study, this study explored the inter-relationships between trait resilience, coping, and mental health in a sample of autistic adults (N = 78). In particular, we examined the relationship between resilience and use of coping strategies, and the potential mediating role of coping strategies in the relationship between resilience and mental health outcomes. Our findings suggested that increased use of engagement coping (e.g., problem-solving, positive appraisal) and decreased use of disengagement coping (e.g., self-blame, being in denial) strategies were associated with higher levels of resilience. Further, mediation analysis results suggest that disengagement coping mediated the associations between resilience and all three mental health outcomes (i.e., depression, anxiety, and well-being), while engagement coping strategies mediated the relationship between resilience and well-being only. Our results illustrate that coping strategies may be an important mechanism in explaining the resilience-mental health relationship in autistic adults, highlighting the importance of considering stress-related constructs together (i.e., trait resilience and coping) when addressing support and intervention options for mental health difficulties in the autistic adult population. LAY SUMMARY: This research explored how resilience and coping strategies influence the mental health and well-being of autistic adults. We found that resilient autistic adults used more engagement coping strategies, less disengagement coping strategies, and reported better mental health and well-being. Considering stress-related factors together (i.e., resilience and coping) offers a novel perspective to mental health difficulties in autistic adults and may be a vital step in the development of support options in this population.

Factors associated with age at autism diagnosis in a community sample of Australian adults.

Autism diagnosis in adulthood has become increasingly common due to a range of factors including changes in awareness, diagnostic criteria, and professional practices. Past research identified a range of demographic and autism-related factors associated with autism diagnosis age in children. However, it is unclear whether these apply to autistic adults. This study aimed to examine predictors of autism diagnosis age in adults while controlling for current age and autistic traits. We used a cross-sectional sample of 657 adults aged 15-80 from three self and carer-report studies: the Australian Longitudinal Study of Autism in Adulthood (ALSAA), Study of Australian School-Leavers with Autism (SASLA) and Pathways, Predictors and Impact of Receiving an Autism Spectrum Diagnosis in Adulthood (Pathways). Using hierarchical multiplicative heteroscedastic regression, we found that older current age and higher self-reported autistic traits predicted older diagnosis age, and that female gender, lack of intellectual disability, language other than English, family history of autism, lifetime depression, and no obsessive-compulsive disorder predicted older diagnosis age beyond current age and autistic traits. The paradoxical relationship between high autistic traits and older diagnosis age requires further investigation. Based on these findings, we recommended strategies to improve autism recognition in women and people from non-English-speaking backgrounds. Future studies could extend the findings by examining the effects of childhood and adulthood socioeconomic status on adult diagnosis age. LAY SUMMARY: We studied the relationship between age at autism diagnosis and other characteristics in adults. We found that both older current age and higher autistic traits, female gender, language other than English, family history of autism, and history of depression were related to older age at diagnosis, while intellectual disability and history of obsessive-compulsive disorder were related to younger age at diagnosis. Our findings suggest more work is needed to help recognize autism in women and people from non-English-speaking backgrounds.

Brief Report: Psychometric Properties of the Patient Health Questionaire-9 (PHQ-9) in Autistic Adults.

Despite the high prevalence of depression and other mental illnesses in autistic adults, screening instruments such as the Patient Health Questionnaire (PHQ-9) have not been specifically validated in an autistic sample. Using data from two Autism CRC longitudinal studies (n = 581), confirmatory factor analysis supported the two-factor model (somatic and cognitive/affective) in the autistic sample and one-factor model in the community comparison sample. Confirmatory bifactor analysis also supported use of the PHQ-9 total score in autism. Good convergent validity was found with two measures of psychological well-being for PHQ-9 total and subdomain scores. The PHQ-9 is a useful tool for autism research allowing comparison across autistic and non-autistic participants.

"The Single Most Important Thing That Has Happened to Me in My Life": Development of the Impact of Diagnosis Scale-Preliminary Revision.

Background: Awareness and diagnosis of autism in adulthood is on the rise. Studies have considered the impact of receiving an autism diagnosis for parents of children on the spectrum, although only few primarily qualitative studies have considered the self-reported impact of autism diagnosis. The Impact of Diagnosis Scale (IODS) was initially developed with a focus on borderline personality disorder. Our aim was to develop a version suitable for autistic individuals. Methods: The research team and a group of autistic advisors revised the IODS items for suitability and accessibility to autistic participants. We gathered participant data for 92 autistic adolescents and adults from the Cooperative Research Centre for Living with Autism (Autism CRC) Study of Australian School Leavers with Autism (SASLA) and the Australian Longitudinal Study of Autism in Adulthood (ALSAA). We used iterated principal factors analysis to explore potential factors, and thematic analysis to explore responses to two open-ended items. Results: Factor analysis suggested three factors of "Service Access (SA)," "Being Understood (BU)," and "Self-Acceptance and Understanding (SU)" for the 12 items of the IODS-Preliminary Revision (IODS-PR). Cronbach's alpha was good overall and acceptable for subdomains. Item mean scores suggest that although impact of autism diagnosis was generally perceived as positive for SU, scores were neutral in other domains. Qualitative analysis identified themes of Self-Understanding, Identity, and Acceptance, Supports and Services, Valence of Response, Relationships, and Camouflaging. Conclusions: The IODS-PR is the first scale to measure the self-reported experience of receiving an autism diagnosis. It showed good psychometrics and provides new insight into the experience of autism diagnosis. Qualitative analysis identified domains that remain unexplored and the potential for an expanded item set. A further revision of the tool will soon be available. It will provide critical information for clinicians and has potential applications for research and service evaluation. Lay summary: Why was this study done?: There are increasing numbers of adults who are only diagnosed with autism in their teen and adult years. Research on this topic is limited, with most using surveys or interviews.What was the purpose of this study?: The purpose was to develop a revision of the Impact of Diagnosis Scale (IODS) to make it suitable to autistic teenagers and adults.What did the researchers do?: We worked with autistic research advisors to create the IODS-Preliminary Revision (IODS-PR), which has 12 items scored on a 7-point agree/disagree scale and two open-ended questions. We then gathered data using the IODS-PR from the Study of Australian School Leavers with Autism (SASLA) and the Australian Longitudinal Study of Autism in Adulthood (ALSAA). We ran a factor analysis on the scores and conducted a thematic analysis of the open-ended responses. One of the autistic advisors reviewed how we interpreted our results.What were the results of the study?: There were 92 autistic participants (46 males, 38 females, 8 nonbinary; mean age of 36 years old). On average, participants were diagnosed with autism at age 30. The factor analysis suggested three domains in the IOD-PR: Self-Acceptance and Understanding, Being Understood, and Service Access. On average, participants' scores suggested receiving an autism diagnosis was helpful for understanding and accepting themselves, but neutral for being understood by others or getting support from services.The thematic analysis identified several themes, the strongest theme was Self-Understanding, Identity, and Acceptance, where participants mostly commented on the positive new self-identity that came from their autism diagnosis. There was a Supports and Services theme that was divided into Enabled Support, Support not needed, and No or poor services. Most concerning was that many participants commented that the autism diagnosis did not enable any access to supports or that there were no appropriate supports available. There was a Valence of Response theme that was divided into Relief, Positive impact, Wish diagnosed earlier, and Negative impact. There was a Relationships theme divided into Connected with autistic community, Improves relationships, and Others lack understanding. Finally, there was a Camouflaging theme.Based on these results, the researchers are working on further revisions to the IODS-PR to make it more useful and accessible.What do these findings add to what was already known?: The adapted IODS shows promise and findings will guide further development of the tool. These early-stage findings agree with what previous research said about the impact of receiving a diagnosis of autism in adulthood.What are potential weaknesses in the study?: There are strengths and weaknesses to using a questionnaire tool to research this topic. Interview research can get a more in-depth understanding of an individual's response to the diagnosis.How will these findings help autistic adults now or in the future?: When the revised IODS is available, it could be used to evaluate support services and help clinicians understand how to help create a more positive response to diagnosis. Our findings confirm more needs to be performed about postdiagnosis supports.

Sleep Quality in Autism from Adolescence to Old Age.

Background: Sleep problems are common in autism from early childhood. Although research suggests that poor sleep continues at least into early middle age, the pattern of sleep problems has rarely been characterized beyond childhood. The aim of this study was to examine sleep quality from adolescence to old age in autistic individuals as compared with age-matched non-autistic comparison groups from the general population. Methods: Participants ranged from 15 to 80 years; there were 297 participants in the autistic group (mean [M]age = 34.36 years, standard deviation [SD] = 15.24), and the comparison group had 233 participants (Mage = 33.01 years, SD = 15.53). Sleep quality, sleep onset latency (SoL), total night sleep, and sleep efficiency as measured by Pittsburgh Sleep Quality Index were compared between groups and across age groups (15-19, 20-39, 40-59, 60+ years). Five predictors of sleep quality (autistic traits, mental health condition, medication, employment, and sex) were also examined. Results: Overall, problematic sleep was more common for the autistic participants (63.7%) than the comparison group (46.4%), and autistic participants had poorer sleep quality and longer SoL (all p < 0.001). In early adulthood and middle age, autistic adults had significantly poorer sleep quality and longer SoL than similar age comparison group adults; autistic and comparison group adolescents and the elderly did not differ. In the autistic group, predictors accounted for 21% of sleep quality variance. Sex (p < 0.001) was the strongest predictor, with all predictors except employment contributing unique variance. In the comparison group, predictors accounted for 25% of the variance in sleep quality. The strongest predictor was mental health condition (p < 0.001), with all predictors except sex contributing unique variance. Conclusions: Autistic adolescents and adults, particularly females, remain vulnerable to sleep problems, with early and middle adulthood being at times of particular risk. Targeted sleep interventions are required. Lay summary: Why was this study done?: Difficulty sleeping is a common occurrence among autistic individuals, but we know very little about sleep in autistic adults.What was the purpose of the study?: To compare self-reported sleep quality in autistic and non-autistic people aged 15 to 80 years.What did the researchers do?: Online surveys were completed by 297 autistic individuals (average age 34.36 years) and 233 non-autistic individuals (average age 33.01 years). Participants were asked questions about their sleep quality, the time it takes them to fall asleep (sleep latency), and the number of hours of sleep they usually get each night (total sleep). Using information about how long they slept and their responses to questions about their bedtime and wake time we calculated the percentage of time they spent in bed asleep (sleep efficiency [SE]). We compared these sleep measures between the autistic and non-autistic participants. We also split the participants into four age groups (15-19, 20-39, 40-59, and 60+ years) to look at any differences at specific age points. Finally, we looked to see whether autistic symptoms, having a mental health problem, being on medication, being unemployed, and/or sex (male/female) predicted sleep quality.What were the results of the study?: Poor sleep quality was more common for the autistic participants (63.7%) than non-autistic participants (46.4%). On average, autistic participants also had poorer sleep quality scores and it took them longer to fall asleep than non-autistic participants. Autistic participants in early adulthood (20-39) and middle age (40-59) had poorer sleep quality and took longer to fall asleep than non-autistic adults of the same age. There were no differences between autistic and non-autistic adolescents (15-19) or older adults (60+). For autistic participants, the best predictor of poor sleep quality was being female; other predictors of poor sleep quality were having a mental health problem, more autistic symptoms, and being on medication. Among non-autistic participants, the best predictor of poor sleep quality was having a mental health problem; other predictors were more autistic symptoms, being on medication, and being unemployed.What do these findings add to what is already known?: Similar to the findings in autistic children, autistic adults are more likely to have poor sleep quality compared with non-autistic adults. Autistic females are particularly at risk for poor sleep, and autistic adults aged 20 to 59 years are more at risk for poor sleep quality.What are potential weaknesses in the study?: Sleep was measured by using a self-report questionnaire, which is not as reliable as using a sleep diary or other objective measures of sleep (e.g., actigraphy). In addition, this study only looked at data collected at one point in time, and as such it is not possible to examine changes over time in sleep quality among autistic adults.How will these findings help autistic adults now or in the future?: The findings in this study identified that sleep difficulties persist across the lifespan for autistic adults. Therefore, there is a critical need for future research to focus on understanding the cause of poor sleep quality in autism and develop sleep interventions for autistic adults.

Cross-sectional and longitudinal predictors of quality of life in autistic individuals from adolescence to adulthood: The role of mental health and sleep quality.

LAY ABSTRACT: Research shows that autistic adults are at risk of a range of physical (e.g. sleep difficulties) and mental health (e.g. anxiety) conditions, as well as lower employment and post-secondary education participation; these all can affect one's quality of life. However, we have little information about what affects quality of life for autistic individuals across the lifespan and whether this differs from non-autistic people. We determined what factors (e.g. mental or physical health challenges) affected quality of life in a large group of autistic individuals aged 15-80 years compared with similar age non-autistic individuals. We also examined what factors affected quality of life of the autistic group 2 years later. We found a similar pattern of results for the autistic and non-autistic groups; depression symptoms, psychological well-being, sleep quality and autonomic symptoms (e.g. sweating) were all significant predictors of quality of life. In addition, among the autistic group, baseline quality of life had the most influence on quality of life 2 years later. These results have implications for support services, as they highlight the relationship between mental health (especially depression) and quality of life. Given that sleep challenges (e.g. insomnia) are related to mental health, an intervention addressing both insomnia and mental health may be most useful in helping autistic individuals improve their quality of life.