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      Needing more, needing less: unravelling why a prompt dependency cycle forms in neurodiverse relationships

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          Abstract

          Social interaction is a fundamental component of relationships; however, the key features of Autism Spectrum Disorder (ASD) include marked and lifelong impairments in social interaction that adversely affects abilities to fulfil this essential relationship requirement. Despite the momentum of worldwide research on ASD, there is insufficient empirical study on adults with ASD and their relationships. This research examined the reported social interaction needs of adults when involved in neurodiverse relationships (relationships that include adults with ASD and neurotypical (NT) adults). The use of an advocacy/participatory approach allowed for a detailed investigation of the characteristics of participants’ interpersonal communication. It was identified that a pairing of incompatible social interaction needs caused a sequence of distinctive, competing, and intertwined interactions that formed into interwoven communication cycles. These cycles included compensatory and competing behaviours, which were specific to each group of participants. Prompting, prompt dependency and/or prompt avoidance occurred within a dynamic system.

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          Most cited references70

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          The Satisfaction With Life Scale.

          This article reports the development and validation of a scale to measure global life satisfaction, the Satisfaction With Life Scale (SWLS). Among the various components of subjective well-being, the SWLS is narrowly focused to assess global life satisfaction and does not tap related constructs such as positive affect or loneliness. The SWLS is shown to have favorable psychometric properties, including high internal consistency and high temporal reliability. Scores on the SWLS correlate moderately to highly with other measures of subjective well-being, and correlate predictably with specific personality characteristics. It is noted that the SWLS is Suited for use with different age groups, and other potential uses of the scale are discussed.
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            Prevalence and Characteristics of Autism Spectrum Disorder Among Children Aged 8 Years — Autism and Developmental Disabilities Monitoring Network, 11 Sites, United States, 2018

            Problem/Condition Autism spectrum disorder (ASD). Period Covered 2018. Description of System The Autism and Developmental Disabilities Monitoring (ADDM) Network conducts active surveillance of ASD. This report focuses on the prevalence and characteristics of ASD among children aged 8 years in 2018 whose parents or guardians lived in 11 ADDM Network sites in the United States (Arizona, Arkansas, California, Georgia, Maryland, Minnesota, Missouri, New Jersey, Tennessee, Utah, and Wisconsin). To ascertain ASD among children aged 8 years, ADDM Network staff review and abstract developmental evaluations and records from community medical and educational service providers. In 2018, children met the case definition if their records documented 1) an ASD diagnostic statement in an evaluation (diagnosis), 2) a special education classification of ASD (eligibility), or 3) an ASD International Classification of Diseases (ICD) code. Results For 2018, across all 11 ADDM sites, ASD prevalence per 1,000 children aged 8 years ranged from 16.5 in Missouri to 38.9 in California. The overall ASD prevalence was 23.0 per 1,000 (one in 44) children aged 8 years, and ASD was 4.2 times as prevalent among boys as among girls. Overall ASD prevalence was similar across racial and ethnic groups, except American Indian/Alaska Native children had higher ASD prevalence than non-Hispanic White (White) children (29.0 versus 21.2 per 1,000 children aged 8 years). At multiple sites, Hispanic children had lower ASD prevalence than White children (Arizona, Arkansas, Georgia, and Utah), and non-Hispanic Black (Black) children (Georgia and Minnesota). The associations between ASD prevalence and neighborhood-level median household income varied by site. Among the 5,058 children who met the ASD case definition, 75.8% had a diagnostic statement of ASD in an evaluation, 18.8% had an ASD special education classification or eligibility and no ASD diagnostic statement, and 5.4% had an ASD ICD code only. ASD prevalence per 1,000 children aged 8 years that was based exclusively on documented ASD diagnostic statements was 17.4 overall (range: 11.2 in Maryland to 29.9 in California). The median age of earliest known ASD diagnosis ranged from 36 months in California to 63 months in Minnesota. Among the 3,007 children with ASD and data on cognitive ability, 35.2% were classified as having an intelligence quotient (IQ) score ≤70. The percentages of children with ASD with IQ scores ≤70 were 49.8%, 33.1%, and 29.7% among Black, Hispanic, and White children, respectively. Overall, children with ASD and IQ scores ≤70 had earlier median ages of ASD diagnosis than children with ASD and IQ scores >70 (44 versus 53 months). Interpretation In 2018, one in 44 children aged 8 years was estimated to have ASD, and prevalence and median age of identification varied widely across sites. Whereas overall ASD prevalence was similar by race and ethnicity, at certain sites Hispanic children were less likely to be identified as having ASD than White or Black children. The higher proportion of Black children compared with White and Hispanic children classified as having intellectual disability was consistent with previous findings. Public Health Action The variability in ASD prevalence and community ASD identification practices among children with different racial, ethnic, and geographical characteristics highlights the importance of research into the causes of that variability and strategies to provide equitable access to developmental evaluations and services. These findings also underscore the need for enhanced infrastructure for diagnostic, treatment, and support services to meet the needs of all children.
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              Identifying the lost generation of adults with autism spectrum conditions.

              Autism spectrum conditions comprise a set of early-onset neurodevelopmental syndromes with a prevalence of 1% across all ages. First diagnosis in adulthood has finally become recognised as an important clinical issue due to the increasing awareness of autism, broadening of diagnostic criteria, and the introduction of the spectrum concept. Thus, the idea of a lost generation of people who were previously excluded from a diagnosis of classic autism has arisen. Making a first diagnosis of autism spectrum conditions in adults can be challenging for practical reasons (eg, no person to provide a developmental history), developmental reasons (eg, the acquisition of learnt or camouflaging strategies), and clinical reasons (eg, high frequency of co-occurring disorders). The diagnostic process includes referral, screening, interviews with informants and patients, and functional assessments. In delineating differential diagnoses, true comorbidities, and overlapping behaviour with other psychiatric diagnoses, particular attention should be paid to anxiety, depression, obsessive-compulsive disorder, psychosis, personality disorders, and other neurodevelopmental disorders. Possible misdiagnosis, especially in women, should be explored. The creation of supportive, accepting, and autism-friendly social and physical environments is important and requires a coordinated effort across agencies and needs support from government policies.
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                Author and article information

                Contributors
                (View ORCID Profile)
                Journal
                Journal of Social and Personal Relationships
                Journal of Social and Personal Relationships
                SAGE Publications
                0265-4075
                1460-3608
                September 2023
                March 21 2023
                September 2023
                : 40
                : 9
                : 2892-2917
                Affiliations
                [1 ]Edith Cowan University, Joondalup, WA, Australia
                Article
                10.1177/02654075231161308
                7270c6fe-36db-49e8-88c6-38d0ca2cb0ce
                © 2023

                https://creativecommons.org/licenses/by-nc/4.0/

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