Adult ADHD Self-Report Scale Symptom Checklist

Kessler, Ronald C.; Adler, Lenard A.; Ames, Minnie; Demler, Olga; Faraone, Stephen V.; Hiripi, Èva; Howes, Mary J.; Jin, Robert; Secnik, Kristina; Spencer, Thomas; Üstün, T. Bedirhan; Walters, Ellen E.

doi:10.1037/t03454-000

Cited by 5 publications

(6 citation statements)

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“…Norwegian version of the Adult ADHD Self-report scale (ASRS; Kessler et al 2005). The ASRS consists of 18 statements about hyperactivity-inattention (e.g., "I never remember," "I concentrate easily"), that the participants respond to using options "Never," "Rarely," SUBJECTIVE ECONOMIC STATUS AND MENTAL HEALTH 11 "Sometimes," "Often," or "Always."…”

Section: Hyperactivity-inattention Hyperactivity-inattention Was Meamentioning

confidence: 99%

Subjective Economic Status in Adolescence: Determinants and Associations with Mental Health in the Norwegian Youth@Hordaland Study

et al. 2017

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His current research is on social inequality in mental health among children and adolescents, and on psychometric methods. He received his PhD from the University of Bergen in Norway. Eric Dearing is a psychologist, professor in the Lynch School of Education at Boston College in Boston, Massachusetts (US), and a senior researcher at the Norwegian Center for Child Behavioral Development, Oslo, Norway. His research is focused on the roles of family, school, and community in the lives of children growing up poor.

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Section: Hyperactivity-inattention Hyperactivity-inattention Was Meamentioning

confidence: 99%

Subjective Economic Status in Adolescence: Determinants and Associations with Mental Health in the Norwegian Youth@Hordaland Study

et al. 2017

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“…In contrast, in the current study, depressive symptoms were considered to be conceptually related to the group membership variable given the well-established relationship between depression and OCD (e.g., Pallanti, Grassi, Sarrecchia, Cantisani, & Pellegrini, 2011). Indeed, the high rates of comorbidity between lifetime OCD and depression suggest that this comorbidity is not a coincidence (e.g., Kessler et al, 2005), and may indicate the presence of shared etiological factors between disorders. For example, one suggestion has been that negative affectivity may be an etiological factor shared between disorders (e.g., Watson, Clark, & Greg, 1988;Stanton & Watson, 2014).…”

Section: Statistical Analysesmentioning

confidence: 86%

“…OCD affects approximately 2-3% of the population (Kessler et al, 2005, Weissman et al, 1994. It is defined by the presence of obsessions (repetitive thoughts/images/impulses that are unwanted, intrusive and distressing), and/or compulsions (repetitive behaviours or mental acts) that are time consuming and result in significant distress or impairment.…”

Section: Introduction To the Ocrdsmentioning

confidence: 99%

Neurocognitive and Dysfunctional Belief Candidate Endophenotypes of Obsessive-Compulsive and Related Disorders

Taillefer¹

2023

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Background: The current dissertation examined neurocognitive and dysfunctional belief candidate endophenotypes (CEs) across the obsessive compulsive spectrum to elucidate general versus specific factors. This study included CEs from two etiological perspectives well established in the literature. Secondary analyses examined several CEs multidimensionally and examined the relationship between CEs and of QOL. Methods: A total of 77 participants took part in this study, divided into four groups; OCD (n = 21), Hoarding Disorder (HD; n = 16), Grooming Disorders which included both Trichotillomania and Excoriation Disorder (GD; n = 18), and control participants (n = 22). Participants completed a clinical interview and battery of neurocognitive tasks and questionnaires. Results: Those with HD performed worse than controls on measures of response inhibition and set-shifting. OCD continued to predict significant variance in number sequencing. Examination of dysfunctional belief CEs revealed specificity of Responsibility/Threat beliefs and Importance/Control of Thoughts beliefs to OCD. Perfectionism/Intolerance of Uncertainty appear to be broad CEs; however, differing specificity emerged depending on the measure utilized to measure the construct. Self-report indecision revealed specificity to OCD and HD. Differing patterns of QOL impairments emerged across the spectrum. A better understanding of CEs specificity has implications for diagnostic classification, etiology, course, and treatment.

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“…We used the validated arabic version Adult ADHD Self-Report Scale (ASRS-v1.1), a 6-item screening tool for attention-deficit/hyperactivity disorder (ADHD) to assess Adult ADHD, it was proven to be a reliable tool, with a sensitivity of (68.7%), and specificity of (99.5%), two-thirds of clinical cases of ADHD scored 4-6 (Kessler et al, 2005) Results:…”

Section: Methodsmentioning

confidence: 99%

Smartphone Addiction and Associated Factors among Postgraduate Students in an Arabic Sample: A Cross-Sectional Study.

Alageel

Alyahya

Bahatheq

et al. 2020

Preprint

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Background With the wide variety of convenient functionalities, smartphones have become an integral part of society, and in such a small period. It is imperative to examine the adverse effect and consequences of such highly impactful technologies on our individual lives and society as a whole. Like smartphone addiction, behavioral addictions have been established to accompany social, physical, and mental health issues. In this article, we will be investigating the prevalence of smartphone addiction among postgraduate students as well as assessing its relationship to social demographics, depression, ADHD, and nicotine dependence. Objectives · The prevalence of smartphone addiction among middle eastern postgraduate students. · Ascertain the associated factors of smartphone addiction. · Measure the incidence of MDD, ADHD, insomnia, and nicotine addiction among postgraduate students with smartphone addiction. Methods A Cross-sectional online survey, a self-questionnaire is divided into six sections; 1st section is Socio-demographic (age, gender, academic year). 2nd section is the Arabic-validated versions of the Smartphone Addiction Scale (SAS) 3rd section is Patient Health Questionnaire for Depression (PHQ9). 4 th is Athens Insomnia Scale (AIS) to assess the quality of sleep. 5th concerns nicotine dependence and uses the Fagerstrom Test for Cigarette Dependence Questionnaire (FTCd). The 6th section is the Adult ADHD Self-Report Scale (ASRS-v1.1) Results The total number of participants in this study is 506, 158 (31.23%) males, and 348 (68.77%) females. According to the Smartphone Addiction Scale, 51.0% of the participants appear to be high smartphone users, while 49.0% are low smartphone users. The PHQ-9 questionnaire for depression showed a significant association between high smartphone use and MDD (p=0.001). 41.5% of smokers are addicted to smartphones (p=0.039). Smartphone addicts have about two times the risk of developing insomnia (OR= 2.113) (P= 0.013). Those who were addicted to smartphone use had a significant risk of developing ADHD symptoms (OR =2.712) (P <0.001). Conclusion Confirming several studies, we found a positive association between Insomnia, Depression, Adult ADHD, and Smartphone addiction. Therefore, we encourage the scientific community to study the impacts of smartphone addiction and the mental health of post-graduate students.

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Adult ADHD Self-Report Scale Symptom Checklist

Cited by 5 publications

References 0 publications

Subjective Economic Status in Adolescence: Determinants and Associations with Mental Health in the Norwegian Youth@Hordaland Study

Subjective Economic Status in Adolescence: Determinants and Associations with Mental Health in the Norwegian Youth@Hordaland Study

Neurocognitive and Dysfunctional Belief Candidate Endophenotypes of Obsessive-Compulsive and Related Disorders

Smartphone Addiction and Associated Factors among Postgraduate Students in an Arabic Sample: A Cross-Sectional Study.

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