Journal of Attention Disorders最新文献

{"title":"Self-Reported ADHD Diagnosis Status Among Working-Age Adults in the United States: Evidence From the 2023 National Wellbeing Survey.","authors":"Andrew S London, Shannon M Monnat, Iliya Gutin","doi":"10.1177/10870547251319861","DOIUrl":"10.1177/10870547251319861","url":null,"abstract":"<p><strong>Objective: </strong>To estimate the percentage of U.S. working-age (18- to 64-year-old) adults in 2023 who self-reported ever being diagnosed with ADHD by a health care professional.</p><p><strong>Method: </strong>We analyze data from the 2023 National Wellbeing Survey (<i>N</i> = 7,053) to estimate self-reported lifetime ADHD diagnosis status among working-age adults, overall and by sex, age, race/ethnicity, nativity, education, and rural-urban residence.</p><p><strong>Results: </strong>Among U.S. working-age adults in 2023, we estimate that 13.9% (95% confidence interval [13.0%, 15.0%]) self-reported ever being diagnosed with ADHD by a health care professional. We find statistically significant variation by each of the demographic variables analyzed, with higher rates among working-age adults who are female, younger, non-Hispanic White, U.S.-born, less well-educated, and residing in metro areas with 250,000 to 1 million people (relative to those living in metro areas with 1+ million population).</p><p><strong>Conclusion: </strong>The percentage of U.S. working-age adults who self-report in 2023 that they have ever been diagnosed with ADHD by a health care professional (13.9%) is substantially higher than estimates from 2012 (4.25%) and a 2023 estimate of 7.8% among adults of all ages (18+ years). The increase over time may reflect changes in diagnostic criteria for children and adults, greater acceptance of adult diagnosis, over- and mis-diagnosis, and methodological issues. The difference between the 2023 estimates likely reflects study-specific differences in the constructs measured, the age range of the samples, and methodological differences in the online panels used for sampling, in quality control approaches, and in post-survey weight construction. Additional data collection and empirical research is needed to validate or refine provisional estimates based on samples drawn from online panels, and to determine explanations for the observed increase over time.</p>","PeriodicalId":15237,"journal":{"name":"Journal of Attention Disorders","volume":" ","pages":"399-410"},"PeriodicalIF":2.7,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143440903","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Standardization of the Arabic Version of the Adult ADHD Self-Report Screening Scale for DSM-5 (ASRS-5) Among Adults in Saudi Arabia: Variability of ADHD Screening According to Sociodemographic Variables.","authors":"Mohammed M J Alqahtani, Nouf Mohammed Al Saud, Nawal Mohammed Alsharef, Ahmad N AlHadi, Saleh Mohammed Alsalhi, Elham H Al-Hifthy, Yasser Ad-Dab'bagh, Nader Alrahili, Fawwaz Abdulrazaq Alenazi, Barakat M Alotaibi, Sultan Mahmoud Alsaeed, Boshra A Arnout, Latifah ALQasem, Abdulkarim Alhossein, Yasser Jubran Alqahtani, Samirah A AlGhamdi, Jeremy Varnham, Saeed Abdulwahab Asiri, Maysaa W Buraik","doi":"10.1177/10870547251313879","DOIUrl":"10.1177/10870547251313879","url":null,"abstract":"<p><strong>Objective: </strong>This study investigated the psychometric properties of the Arabic version of the Adult Self-Report Scale-5 (the ASRS-5-AR) within a large sample of adults residing in Saudi Arabia.</p><p><strong>Methods: </strong>This cross-sectional study applied the ASRS-5-AR to a random sample of 4,299 Saudi and non-Saudi adults, aged 19 to 66 years (31.16 ± 9.26 years), living in the regions of Riyadh, Makkah, and the Eastern Province in Saudi Arabia. Collected data were analyzed using IBM SPSS Statistics 26, JASP 0.18.3.0 software, and MedCalc 22.030 statistical software.</p><p><strong>Results: </strong>The ASRS-5-AR demonstrated strong internal consistency, with all six items showing significant positive correlation with the total score (.675-.735). Results of confirmatory factor analysis revealed a goodness-of-fit coefficient of 0.983 for the one-factor model and McDonald's omega, Cronbach's α, and Spearman-Brown coefficients of 0.786, 0.788, and 0.724, respectively. In addition, the findings revealed statistically significant differences in self-reported ADHD symptoms based on age (<i>F</i> = 18.68; <i>p</i> < .001), level of education (<i>F</i> = 2.61; <i>p</i> < .05), and marital status (<i>F</i> = 22.30; <i>p</i> < .001). However, there were no significant differences in self-reported ADHD symptoms between males and females (<i>t</i> = 0.625; <i>p</i> > .05) or Saudi and non-Saudi participants (<i>t</i> = 0.409; <i>p</i> > .05) or based on region of residence (<i>t</i> = 2.19; <i>p</i> > .05).</p><p><strong>Conclusions: </strong>This study provides valuable insights into the psychometric properties of the ASRS-5-AR within a large sample of adults in Saudi Arabia. The findings demonstrate acceptable reliability of the ASRS-5-AR within this population. While these findings suggest the ASRS-5-AR may be a useful tool for initial assessment, further research is crucial. Future studies should focus on establishing accurate cutoff scores by comparing a general population sample with a clinically diagnosed sample of adults with ADHD in Saudi Arabia. This will allow for a more accurate evaluation of the scale's utility in identifying individuals who may require further clinical assessment.</p>","PeriodicalId":15237,"journal":{"name":"Journal of Attention Disorders","volume":" ","pages":"445-457"},"PeriodicalIF":2.7,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11894827/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143028846","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Differentiating Functional Connectivity Patterns in ADHD and Autism Among the Young People: A Machine Learning Solution.","authors":"Bernis Sütçübaşı, Tuğçe Ballı, Herbert Roeyers, Jan R Wiersema, Sami Çamkerten, Ozan Cem Öztürk, Barış Metin, Edmund Sonuga-Barke","doi":"10.1177/10870547251315230","DOIUrl":"10.1177/10870547251315230","url":null,"abstract":"<p><strong>Objective: </strong>ADHD and autism are complex and frequently co-occurring neurodevelopmental conditions with shared etiological and pathophysiological elements. In this paper, we attempt to differentiate these conditions among the young people in terms of intrinsic patterns of brain connectivity revealed during resting state using machine learning approaches. We had two key objectives: (a) to determine the extent to which ADHD and autism could be effectively distinguished via machine learning from one another on this basis and (b) to identify the brain networks differentially implicated in the two conditions.</p><p><strong>Method: </strong>Data from two publicly available resting-state functional magnetic resonance imaging (fMRI) resources-Autism Brain Imaging Data Exchange (ABIDE) and the ADHD-200 Consortium-were analyzed. A total of 330 participants (65 females and 265 males; mean age = 11.6 years), comprising equal subgroups of 110 participants each for ADHD, autism, and healthy controls (HC), were selected from the data sets ensuring data quality and the exclusion of comorbidities. We identified region-to-region connectivity values, which were subsequently employed as inputs to the linear discriminant analysis algorithm.</p><p><strong>Results: </strong>Machine learning models provided strong differentiation between connectivity patterns in participants with ADHD and autism-with the highest accuracy of 85%. Predominantly frontoparietal network alterations in connectivity discriminate ADHD individuals from autism and neurotypical group. Networks contributing to discrimination of autistic individuals from neurotypical group were more heterogeneous. These included language, salience, and frontoparietal networks.</p><p><strong>Conclusion: </strong>These results contribute to our understanding of the distinct neural signatures underlying ADHD and autism in terms of intrinsic patterns of brain connectivity. The high level of discriminability between ADHD and autism, highlights the potential role of brain based metrics in supporting differential diagnostics.</p>","PeriodicalId":15237,"journal":{"name":"Journal of Attention Disorders","volume":" ","pages":"486-499"},"PeriodicalIF":2.7,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143382599","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Rising Rate of Hospitalizations in Adolescents with Attention Deficit Hyperactive Disorder in Spain.","authors":"Hilario Blasco-Fontecilla, José Manuel Ramos, María Inés López-Ibor, Carlos Chiclana-Actis, Manuel Faraco, Joaquín González-Cabrera, Eduardo González-Fraile, Gemma Mestre-Bach, Héctor Pinargote-Celorio, Manuel Corpas, Lucía Gallego, Octavio Corral, Vicente Soriano","doi":"10.1177/10870547251320210","DOIUrl":"10.1177/10870547251320210","url":null,"abstract":"<p><strong>Background: </strong>Attention deficit hyperactive disorder (ADHD) is a leading mental disorder among adolescents globally and is associated with premature mortality. Knowing the trends and key determinants of ADHD in youth are critical for earlier diagnosis and interventions.</p><p><strong>Methods: </strong>We retrospectively examined all hospitalizations in patients aged 11 to 18 years with ADHD in Spain, using data from the Spanish National Registry of Hospital Discharges spanning 2000 to 2021. We compared our data with available literature.</p><p><strong>Results: </strong>Over the 22-year study period, there were 2,015,589 hospitalizations among adolescents in Spain, with 118,609 (5.9%) cases involving mental disorders. There were 10,292 admissions with ADHD, representing 8.7% of all hospitalizations among youth with mental disorders. Median age was of 14 years. Boys represented 72.6%. Admissions with ADHD experienced a 17-fold increase during the last decade (<i>p</i> < .001). The in-hospital mortality rate for adolescents with ADHD was 0.1%, lower than for other mental disorders. During the first year of the COVID-19 pandemic, admissions decreased but resumed its rising trend thereafter.</p><p><strong>Conclusion: </strong>Hospital admissions for ADHD among adolescents have significantly increased in Spain during the last two decades. This increase outpaced the mild upward trend in ADHD diagnoses over the same period, which is not due to actual increases in the incidence of ADHD, which has remained stable at 5% worldwide. Factors beyond increased awareness, improved identification, and changes in diagnostic criteria must be considered. Boys represented 72.6% of these admissions. In-hospital mortality in adolescents with ADHD was lower than for admissions with other mental disorders.</p>","PeriodicalId":15237,"journal":{"name":"Journal of Attention Disorders","volume":" ","pages":"411-422"},"PeriodicalIF":2.7,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143523647","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Investigating the Association Between Heavy Metals and Attention Deficit Hyperactivity Disorder in Children: An Exploratory Study.","authors":"Sharanpreet Kaur, Josefa Canals-Sans, Paula Morales-Hidalgo, José A Alda, Victoria Arija","doi":"10.1177/10870547251315276","DOIUrl":"10.1177/10870547251315276","url":null,"abstract":"<p><p>Exposure to heavy metals has been associated with affecting children's neurodevelopment, particularly increasing the risk of developing attention-deficit hyperactivity disorder (ADHD). The current exploratory study aims to investigate potential associations between presence of 15 different heavy metals in urine and ADHD. A total of 190 urine samples of participants from clinical and non-clinical population (non-ADHD = 66; ADHD = 124) aged between 6 and 15 years from Barcelona and Tarragona (Spain) were analysed. Logistic regressions adjusted by sex, age, SES, BMI and diet quality were performed. Highest quartiles (3rd and 4th) of Pb (lead) (aOR 5.33; CI [1.89, 14.98]), Cd (cadmium) (aOR 3.69, CI [1.38, 9.83]), Cu (copper) (aOR 16.46, CI [4.66, 58.14]) and Sb (antimony) (aOR 3.04, CI [1.12, 8.23]) were significantly associated with increased odds of ADHD DSM-5 diagnosis. Additionally, Cu and Cd were associated with higher scores of inattention symptoms. Whereas, Cu and Sb were associated with hyperactivity-impulsivity severity. This exploratory study provides preliminary valuable evidence, suggesting potential associations between environmental factors, such as metal exposure, with ADHD in school-aged children. These findings highlight the importance of further research to support these associations and, if confirmed, explore strategies to mitigate the potential impacts of these toxicants on children's health.</p>","PeriodicalId":15237,"journal":{"name":"Journal of Attention Disorders","volume":" ","pages":"423-436"},"PeriodicalIF":2.7,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143065975","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring Risk Factors for ADHD Among Children at a Mongolian Public School: A Cross-Sectional Analysis.","authors":"Mallika Iyer, Adrian R Martineau, Polyna Khudyakov, Chuluun-Erdene Achtai, Tungalag Altan, Narankhuu Yansanjav, Ariunzaya Saranjav, Uyanga Buyanjargal, Davaasambuu Ganmaa","doi":"10.1177/10870547251318485","DOIUrl":"10.1177/10870547251318485","url":null,"abstract":"<p><strong>Introduction: </strong>Attention Deficit Hyperactivity Disorder (ADHD) is a complex neurodevelopmental disorder with numerous hypothesized risk factors that have not yet been thoroughly investigated in many non-Western populations, including Mongolian schoolchildren. Exploring these risk factors could yield insight on which children are more likely to be impacted and on how risk differs across locations and cultures.</p><p><strong>Objective: </strong>The aim of the study was to assess whether elevated scores reported by parents and teachers on the Conners-3 Assessment, a detailed survey tool used to assess ADHD symptoms, correspond with indicators of lower socioeconomic status.</p><p><strong>Methods: </strong>We conducted a cross-sectional analysis involving 201 schoolchildren aged 8 to 13 attending a public school in Ulaanbaatar, Mongolia. We investigated associations between factors including student age, parental education level, family income, exposure to cigarette smoke, calcium intake and vitamin D status with Conners-3 scores for inattention, hyperactivity, and defiance/aggression. Cohen's <i>d</i> effect sizes and adjusted mean differences (aMD) for Conners-3 scores between groups were calculated using multivariable analysis.</p><p><strong>Results: </strong>Our findings revealed large effect sizes between different types of accommodation, a key indicator of socioeconomic status in modern Mongolia, and moderate effect sizes between different levels of parental education. Other findings included that engaging in over 2 hr of outdoor activity was independently associated with an increased inattention score (aMD 0.53, 95% CI [0.03, 1.03]) and increased hyperactivity score (aMD 0.63, 95% CI [0.10, 1.16]). A lower household income was independently associated with an increased inattention score (aMD 0.0005, 95% CI [0.000011, 0.001042]) and increased defiance/aggression score (aMD 0.0009, 95% CI [0.0004, 0.0015]). Factors such as calcium intake, Vitamin D level, exposure to cigarette smoke, and parental employment status did not yield significant associations.</p><p><strong>Conclusion: </strong>We found that Conners-3 scores indicating higher symptoms of ADHD among Mongolian schoolchildren were associated with lower household income and high outdoor activity, and should be further investigated in relation to type of accommodation.</p>","PeriodicalId":15237,"journal":{"name":"Journal of Attention Disorders","volume":" ","pages":"458-473"},"PeriodicalIF":2.7,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143542074","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Telomere Length and Symptoms of Attention Deficit and Hyperactivity Disorder in Children at 6-12 Years.","authors":"Irene Campos-Sánchez, Eva María Navarrete-Muñoz, Dries S Martens, Isolina Riaño-Galán, Aitana Lertxundi, Sabrina Llop, Mónica Guxens, Cristina Rodríguez-Dehli, Nerea Lertxundi, Raquel Soler-Blasco, Martine Vrijheid, Tim S Nawrot, John Wright, Tiffany C Yang, Rosie McEachan, Kristine Bjerve Gützkow, Vaia Lida Chatzi, Marina Vafeiadi, Mariza Kampouri, Regina Grazuleviciene, Sandra Andrusaityte, Johanna Lepeule, Desirée Valera-Gran","doi":"10.1177/10870547251314923","DOIUrl":"10.1177/10870547251314923","url":null,"abstract":"<p><strong>Objective: </strong>To explore the association between telomere length (TL) and attention deficit hyperactivity disorder (ADHD) symptoms in children at 6-12 years.</p><p><strong>Method: </strong>Data from 1,759 children belonging to the HELIX project cohorts and the Asturias, Gipuzkoa and Valencia cohorts of INMA project were included. TL was determined by blood sample using a PCR protocol. ADHD symptoms were described by parents using the Conners' Parent Rating Scale-Revised: Short Form. Multiple negative binomial regression models adjusted for potential confounders were used to estimate associations.</p><p><strong>Results: </strong>Overall estimates showed no associations between TL and ADHD symptoms. However, we observed that a longer TL was significantly associated with a lower risk of presenting hyperactivity symptoms in children belonging to the HELIX project (IRR = 0.93, 95% CI [0.87, 0.99]; <i>p</i> = .022).</p><p><strong>Conclusion: </strong>While our study did not find a consistent association between TL and ADHD symptoms across all cohorts, the significant association found within the HELIX cohort suggests that longer TL may be linked to a lower risk of hyperactivity symptoms. Further research is needed to explore this association in more detail.</p>","PeriodicalId":15237,"journal":{"name":"Journal of Attention Disorders","volume":" ","pages":"474-485"},"PeriodicalIF":2.7,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143059267","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing the Construct Validity of the Adult ADHD Self-report Scale for DSM-5 and Prevalence of ADHD in a Danish Population Sample.","authors":"Kaj Sparle Christensen, Ole Jakob Storebø, Bo Bach","doi":"10.1177/10870547241312575","DOIUrl":"10.1177/10870547241312575","url":null,"abstract":"<p><strong>Objective: </strong>This study examines the validity of the ASRS-5 as a new screening tool for ADHD and evaluates its proposed screening cut-off in a general population context.</p><p><strong>Method: </strong>A nationally representative sample of 2,002 individuals aged 18 to 80 years was surveyed using the ASRS-5, with complete data obtained from 714 participants. Psychometric analysis evaluated fit to the Rasch model, response categories, dimensionality, differential item functioning, local dependency, and reliability. A cut-off score of 14, based on a simple additive scale, was applied.</p><p><strong>Results: </strong>The ASRS-5 generally conformed to the expectations of the Rasch model. However, disordered response categories were observed for item 6, and gender-related differential item functioning was noted in items 3, 4, and 6. The ASRS-5 demonstrated a unidimensional construct, and a cut-off score of 14 identified 6.0% of the sample as potential ADHD cases.</p><p><strong>Conclusion: </strong>Although the ASRS-5 aligns well with the Rasch model, certain measurement challenges exist. The recommended cut-off score effectively identifies an ADHD prevalence consistent with the 6.5% reported in the original ASRS-5 study.</p>","PeriodicalId":15237,"journal":{"name":"Journal of Attention Disorders","volume":" ","pages":"437-444"},"PeriodicalIF":2.7,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143022961","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Symptoms of ADHD and Other Common Mental Disorders Influence Academic Success in South African Undergraduates.","authors":"Nawal Mohamad, Kim-Louise Rousseau, Fatimah Dowlut, Milton Gering, Kevin G F Thomas","doi":"10.1177/10870547241310659","DOIUrl":"10.1177/10870547241310659","url":null,"abstract":"<p><strong>Objective: </strong>ADHD symptoms are highly prevalent among university students. These symptoms, particularly the inattentive cluster, predispose students to poorer academic performance and worse academic adjustment. Moreover, ADHD symptoms are often comorbid with other common mental disorders; this comorbidity also leads to poor outcomes. South African students often have fewer resources to successfully transition to university. Hence, our longitudinal study used data from a sample of South African first-year undergraduate students to investigate (a) associations between ADHD symptoms and academic performance/adjustment, (b) separate influences of the inattentive and hyperactivity-impulsivity clusters on academic performance/adjustment, and (c) the influence of the combination of ADHD and psychiatric comorbidities on academic performance/adjustment.</p><p><strong>Method: </strong>We collected data three times through the first semester of 2023. Predictors within our regression models included sociodemographic variables, psychological variables (self-reported symptoms of ADHD, depression, anxiety, and risky alcohol use), and high school academic performance. Outcomes were first-semester GPA and self-reported academic adjustment (magnitude of change across the semester and overall adjustment at the end of the semester).</p><p><strong>Results: </strong>Analyses showed that, unlike academic performance (<i>N</i> = 506), magnitude of change in academic adjustment (<i>N</i> = 180) was significantly predicted by ADHD symptoms and the combination of ADHD (<i>p</i> = .02), depression (<i>p</i> < .001), and anxiety symptoms (<i>p</i> = .01). Inattentive ADHD symptoms predicted both academic performance and magnitude of change in academic adjustment.</p><p><strong>Conclusions: </strong>Our findings suggest that the presence of ADHD symptoms (both with and without other common mental disorders) is associated with a smaller magnitude of academic adjustment, and that the presence of inattentive symptoms of ADHD is associated with both poorer academic performance and smaller magnitude of academic adjustment. These findings are significant in informing future interventions targeting the academic outcomes of first-year university students.</p>","PeriodicalId":15237,"journal":{"name":"Journal of Attention Disorders","volume":" ","pages":"363-386"},"PeriodicalIF":2.7,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11800717/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143005471","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Operationalizing In-session Treatment Engagement Strategies and Behaviors for Adolescents With ADHD and Their Parents.","authors":"Margaret H Sibley, Lourdes M Rodriguez, Melissa Lopez, Erika M Brochu, Fabiana V Bracho, Mercedes Ortiz, Jasmine Hashimoto","doi":"10.1177/10870547241308632","DOIUrl":"10.1177/10870547241308632","url":null,"abstract":"<p><strong>Objective: </strong>Many treatment engagement challenges are documented for adolescents with ADHD. Across contexts, helping professionals (i.e., therapists, prescribers, educators, coaches) might benefit from an engagement strategy toolbox to facilitate work with adolescents with ADHD and their families.</p><p><strong>Method: </strong>The current study describes the development and psychometric testing of the ADHD Engagement Process Code (AEPC), a measure that operationalizes engagement strategies in the context of a blended behavioral/motivational interviewing treatment for adolescent ADHD (Supporting Teens' Autonomy Daily; STAND). The AEPC also operationalizes in-session parent and adolescent engagement-related behaviors. Behavior counts and global codes were coded for 840 audio-recorded STAND sessions delivered by 21 therapists to 121 adolescents. Subsets of tapes were double coded using the AEPC's parent, adolescent, and therapist coding systems to assess kappa for line-by-line verbalizations and intraclass correlations for session-level behavior counts and global scores. Construct validity was assessed. We explored low frequency and low variability codes and examined correlations between codes.</p><p><strong>Results: </strong>AEPC codes possessed good to excellent inter-rater reliability and strong discriminant validity. Three low frequency codes and one low variability global were identified indicating opportunities for AEPC refinement.</p><p><strong>Conclusions: </strong>The AEPC is publicly available (https://osf.io/kshfy/) and offers a library of adolescent-specific codes for those interested in measuring provider, parent, or adolescent engagement behaviors in relevant populations or contexts.</p>","PeriodicalId":15237,"journal":{"name":"Journal of Attention Disorders","volume":" ","pages":"336-350"},"PeriodicalIF":2.7,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142931889","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}