Journal articles: 'ADHM data'

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Cork, Josh, and Chris Halcrow. "ADHM skyrmions." Nonlinearity 35, no. 8 (June 23, 2022): 3944–90. http://dx.doi.org/10.1088/1361-6544/ac72e6.

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Abstract We propose, via the Atiyah–Manton approximation, a framework for studying skyrmions on R 3 using Atiyah–Drinfeld–Hitchin–Manin (ADHM) data for Yang–Mills instantons on R 4 . We provide a dictionary between important concepts in the Skyrme model and analogous ideas for ADHM data, and describe an efficient process for obtaining approximate Skyrme fields directly from ADHM data. We show that the approximation successfully describes all known skyrmions with charge B ⩽ 8 , with energies reproduced within 2% of the true minimisers. We also develop factorisation methods for studying clusters of instantons and skyrmions, generalising early work by Christ–Stanton–Weinberg, and describe some relatively large families of explicit ADHM data. These tools provide a unified framework for describing coalesced highly-symmetric configurations as well as skyrmion clusters, both of which are needed to study nuclear systems in the Skyrme model.

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Ohkawa, Ryo. "Wall-crossing between stable and co-stable ADHM data." Letters in Mathematical Physics 108, no. 6 (March 16, 2018): 1485–523. http://dx.doi.org/10.1007/s11005-018-1071-2.

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Choy, Jaeyoo. "The SO(3)-instanton moduli space and tensor products of ADHM data." Journal of Algebra 528 (June 2019): 38–71. http://dx.doi.org/10.1016/j.jalgebra.2019.03.004.

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Lai, Sheng-Hong, Jen-Chi Lee, and I.-Hsun Tsai. "Extended complex Yang–Mills instanton sheaves." International Journal of Geometric Methods in Modern Physics 17, no. 04 (March 2020): 2050061. http://dx.doi.org/10.1142/s0219887820500619.

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In the search of Yang–Mills (YM) instanton sheaves with topological charge two, the rank of [Formula: see text] matrix in the monad construction can be dropped from the bundle case with rank [Formula: see text] to either rank [Formula: see text] [S. H. Lai, J. C. Lee and I. H. Tsai, Yang–Mills instanton sheaves, Ann. Phys. 377 (2017) 446] or 0 on some points of [Formula: see text] of the sheaf cases. In this paper, we first show that the sheaf case with rank [Formula: see text] does not exist for the previous construction of [Formula: see text] complex YM instantons [S. H. Lai, J. C. Lee and I. H. Tsai, Biquaternions and ADHM construction of concompact [Formula: see text] Yang–Mills instantons, Ann. Phys. 361 (2015) 14]. We then show that in the new “extended complex YM instantons” discovered in this paper, rank [Formula: see text] can be either 2 on the whole [Formula: see text] (bundle) with some given ADHM data or 1, 0 on some points of [Formula: see text] with other ADHM data (sheaves). These extended [Formula: see text] complex YM instantons have no real instanton counterparts. Finally, the potential applications to real physics systems are noted in the end of the paper.

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van Beek, Jenny H. D. A., Gonneke Willemsen, Marleen H. M. de Moor, Jouke Jan Hottenga, and Dorret I. Boomsma. "Associations Between ADH Gene Variants and Alcohol Phenotypes in Dutch Adults." Twin Research and Human Genetics 13, no. 1 (February 1, 2010): 30–42. http://dx.doi.org/10.1375/twin.13.1.30.

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AbstractRecently, Macgregor et al. (2009) demonstrated significant associations of ADH polymorphisms with reactions to alcohol and alcohol consumption measures in an Australian sample. The aim of the present study was to replicate these findings in a Dutch sample. Survey data on alcohol phenotypes came from 1,754 unrelated individuals registered with the Netherlands Twin Register. SNPs in the ADH gene cluster located on chromosome 4q (n= 491) were subdivided in seven gene sets: ADH5, ADH4, ADH6, ADH1A, ADH1B, ADH1C and ADH7. Within these sets associations of SNPs with alcohol consumption measures, age at onset variables, reactions to alcohol and problem drinking liability were examined. Of the original 38 SNPs studied by Macgregor et al. (2009), six SNPs were not available in our dataset, because one of them had a minor allele frequency < .01 (rs1229984) and five could not be imputed. The remaining SNP associations with alcohol phenotypes as identified by Macgregor et al. (2009) were not replicated in the Dutch sample, after correcting for multiple genotype and phenotype testing. Significant associations were found however, for reactions to alcohol with a SNP in ADH5 (rs6827292,p= .001) and a SNP just upstream of ADH5 (rs6819724,p= .0007) that is in strong LD with rs6827292. Furthermore, an association between age at onset of regular alcohol use and a SNP just upstream of ADH7 (rs2654849,p= .003) was observed. No significant associations were found for alcohol consumption and problem drinking liability. Although these findings do not replicate the earlier findings at the SNP level, the results confirm the role of the ADH gene cluster in alcohol phenotypes.

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Lin, Jing-Zhong, Peter L. Morrell, and Michael T. Clegg. "The Influence of Linkage and Inbreeding on Patterns of Nucleotide Sequence Diversity at Duplicate Alcohol Dehydrogenase Loci in Wild Barley (Hordeum vulgaressp. spontaneum)." Genetics 162, no. 4 (December 1, 2002): 2007–15. http://dx.doi.org/10.1093/genetics/162.4.2007.

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AbstractPatterns of nucleotide sequence diversity are analyzed for three duplicate alcohol dehydrogenase loci (adh1-adh3) within a species-wide sample of 25 accessions of wild barley (Hordeum vulgare ssp. spontaneum). The adh1 and adh2 loci are tightly linked (recombination fraction <0.01) while the adh3 locus is inherited independently. Wild barley is predominantly self-fertilizing (∼98%), and as a consequence, effective recombination is restricted by the extreme reduction in heterozygosity. Large reductions in effective recombination, in turn, widen the conditions for linkage to influence nucleotide sequence diversity through the action of selective sweeps or background selection. These considerations would appear to predict (1) homogeneity in patterns of nucleotide sequence diversity, especially between closely linked loci, and (2) extensive linkage disequilibrium relative to random-mating species. In contrast to these expectations, the wild barley data reveal heterogeneity in patterns of nucleotide sequence diversity and levels of linkage disequilibrium that are indistinguishable from those observed at adh1 in maize, an outbreeding grass species.

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Holmes, Roger S., Roland A. H. van Oorschot, and John L. Vandeberg. "Genetics of alcohol dehydrogenase and aldehyde dehydrogenase from Monodelphis domestica cornea: further evidence for identity of corneal aldehyde dehydrogenase with a major soluble protein." Genetics Research 56, no. 2-3 (October 1990): 259–65. http://dx.doi.org/10.1017/s0016672300035369.

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SummaryA didelphid marsupial, the gray short-tailed opossum (Monodelphis domestica), was used as a model species to study the biochemical genetics of alcohol dehydrogenases (ADHs) and aldehyde dehydrogenase (ALDH) in corneal tissue. Isoelectric point variants of corneal ALDH (designated ALDH3) and a major soluble protein in corneal extracts were observed among eight families of animals used in studying the genetics of these proteins. Both phenotypes exhibited identical patterns following PAGE-IEF and were inherited in a normal Mendelian fashion, with two alleles at a single locus (ALDH3) showing codominant expression. The data provided evidence for genetic identity of corneal ALDH with this major soluble protein, and supported biochemical evidence, recently reported for purified bovine corneal ALDH, that this enzyme constitutes a major portion of soluble corneal protein (Abedinia et al. 1990). Isoelectric point variants for corneal ADH were also observed, with patterns for the two major forms (ADH3 and ADH4) and one minor form (ADH5) being consistent with the presence of two ADH subunits (designated γ and δ), and variant phenotypes existing for the γ subunit. The genetics of this enzyme was studied in the eight families, and the results were consistent with codominant expression of two alleles at a single locus (designated ADH3). It is relevant that a major detoxification function has been proposed for corneal ADH and ALDH, in the oxidoreduction of peroxidic aldehydes induced by available oxygen and UV-B light (Holmes & VandeBerg, 1986a). In addition, a direct role for corneal ALDH as a UV-B photoreceptor in this anterior eye tissue has also been proposed (Abedinia et al. 1990).

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Lai, Sheng-Hong, Jen-Chi Lee, and I.-Hsun Tsai. "Sheaf lines of Yang–Mills instanton sheaves." International Journal of Geometric Methods in Modern Physics 16, no. 03 (March 2019): 1950036. http://dx.doi.org/10.1142/s0219887819500361.

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We calculate a sheaf line in [Formula: see text] which is the real line supporting sheaf points on [Formula: see text] of [Formula: see text] Yang–Mills (YM) instanton (or [Formula: see text] complex YM instanton) sheaves for some given ADHM data we obtained previously. We found that this sheaf line is indeed a special jumping line over [Formula: see text] spacetime. In addition, we calculate the singularity structure of the connection [Formula: see text] and the field strength [Formula: see text] at the corresponding singular point on [Formula: see text] of this sheaf line. We found that the order of singularity at the singular point on [Formula: see text] associated with the sheaf line in [Formula: see text] is higher than those of other singular points associated with normal jumping lines. We conjecture that this is a general feature for sheaf lines among jumping lines.

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Grimmsmann, Thomas, and Wolfgang Himmel. "The 10-year trend in drug prescriptions for attention-deficit/hyperactivity disorder (ADHD) in Germany." European Journal of Clinical Pharmacology 77, no. 1 (August 17, 2020): 107–15. http://dx.doi.org/10.1007/s00228-020-02948-3.

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Abstract Purpose The aim of this study was to analyse whether the global trend in drug prescriptions for attention-deficit hyperactivity disorders (ADHD), as observed during the last years and often criticized as medicalization, have remained stable or shifted. Methods This observational study was based on a secondary analysis of data from a large German database including patients with an ADHD diagnosis between 2008 and 2018. Prescription data comprised all important ADHD drugs. Results A total of 620 practices delivered data from a total of 77,504 patients (31% of them females) with a diagnosis of AHDH. Nearly 38% (29,396/77,504) of all patients received, at least, one prescription for an ADHS medicine between 2008 and 2018. The number of patients receiving a drug steadily increased annually until 2012 and then slowly fell, but unevenly distributed across the age groups. While the number of younger patients ( ≤ 16 years) receiving a prescription fell by 24% and the defined daily doses (DDDs) remained stable, the number of patients between 17 and 24 years receiving a prescription increased by 113% and the DDDs by 150%. Respectively, the number of older adults (≥ 25 years) with a prescription increased by 355% and the DDDs by 515%. Nearly one-third of older adults received an ADHD medicine only once. Conclusion The ever-increasing prescription of ADHD medicines stopped some years ago for children. ADHS and its pharmacological management are increasingly observed among older adolescents and adults, with a different pattern of drug persistence compared with children.

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Butar-Butar, Vivi Marianti. "ATTENTION DEFICIT HYPERACTIVITY DISORDER (ADHD) IN ROBIN ROE’S NOVEL A LIST OF CAGES." Lingual: Journal of Language and Culture 8, no. 2 (February 8, 2020): 45. http://dx.doi.org/10.24843/ljlc.2019.v08.i02.p08.

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This thesis entitled "Attention Deficit Hyperactivity Disorder (ADHD) in Robin Roe's Novel A List of Cages". This thesis discussed about the symptoms Attention Deficit Hyperactivity Disorder (ADHD) in the novel A List of Cages by Robin Roe. This thesis aimed to find out how the symptoms of ADHD are described through the leading character in the novel. This thesis used to describe the core symptoms of ADHD, namely: Attention, Impulsivity, and Hyperactivity. There are symptoms of ADHD that Adam has, namely: Attention symptom is easily bored; Impulsivity symptom is agitated; and the Hyperactivity symptom is: do excessive motor activities. This thesis used Russell Barkley's theory to analyze the symptoms in a novel using Literary Psychology. In analyzing this thesis, the writer used a qualitative descriptive method that presents all data in the form of words and sentences and uses library research as a way to collect data by reading and selecting quotations from the novel A List of Cages. From this research it is found that the leading character in the novel experienced all the three core symptoms of ADHD.

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Mullins, Michael E. "ADHD Data Misleading." Emergency Medicine News 29, no. 3 (March 2007): 3–4. http://dx.doi.org/10.1097/01.eem.0000264666.53838.16.

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Gregerson, R. G., L. Cameron, M. McLean, P. Dennis, and J. Strommer. "Structure, expression, chromosomal location and product of the gene encoding Adh2 in Petunia." Genetics 133, no. 4 (April 1, 1993): 999–1007. http://dx.doi.org/10.1093/genetics/133.4.999.

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Abstract In most higher plants the genes encoding alcohol dehydrogenase comprise a small gene family, usually with two members. The Adh1 gene of Petunia has been cloned and analyzed, but a second identifiable gene was not recovered from any of three genomic libraries. We have therefore employed the polymerase chain reaction to obtain the major portion of a second Adh gene. From sequence, mapping and northern data we conclude this gene encodes ADH2, the major anaerobically inducible Adh gene of Petunia. The availability of both Adh1 and Adh2 from Petunia has permitted us to compare their structures and patterns of expression to those of the well-studied Adh genes of maize, of which one is highly expressed developmentally, while both are induced in response to hypoxia. Despite their evolutionary distance, evidenced by deduced amino acid sequence as well as taxonomic classification, the pairs of genes are regulated in strikingly similar ways in maize and Petunia. Our findings suggest a significant biological basis for the regulatory strategy employed by these distant species for differential expression of multiple Adh genes.

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JOHNSON, CLIFFORD V. "ON THE (0, 4) CONFORMAL FIELD THEORY OF THE THROAT." Modern Physics Letters A 13, no. 30 (September 28, 1998): 2463–73. http://dx.doi.org/10.1142/s021773239800262x.

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In SO(32) heterotic string theory, the space–time at the core of N coincident NS five-branes is an infinite throat, ℝ×S3. As shown by Witten, the throat signals a singularity in the usual heterotic string conformal field theory and a nonperturbative USp (2N) gauge group appears, due to the N small instantons at the five-branes' core. Nevertheless, we look for some trace of the nonperturbative physics in the description of the heterotic string infinitely far down the throat. Our guide is a D1-brane probing N D5-branes in type I, which yields a (1+1)-dimensional (0, 4) supersymmetric model with ADHM data in its couplings, as shown by Douglas. The neighborhood of the classical boundary of the hypermultiplet moduli space of the theory flows to an exact conformal field theory description of the throat theory. Ironically, the remnant of the nonperturbative symmetry is indeed found in the conformal field theory, lurking in the structure of the partition function, and encoded in a family of deformations of the theory along flat directions. The deformations have an explicit description using the flow from type I theory, and have a hyper-Kähler structure. Similar results hold true for the analogous (4, 4) supersymmetric situation in type IIB theory, as is evident in the work of Diaconescu and Seiberg.

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Guo, Ying, Jinping Wang, Shuyan Yan, and Shujie Sui. "Clinical Efficacy Evaluation of Psychological Nursing Intervention Combined with Drugs Treatment of Children with ADHD under Artificial Intelligence." Journal of Healthcare Engineering 2022 (March 29, 2022): 1–10. http://dx.doi.org/10.1155/2022/1818693.

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ADHD in children is one of the most common neurodevelopmental disorders. It is manifested as inattention, hyperactivity, impulsiveness, and other symptoms that are inconsistent with the developmental level in different occasions, accompanied by functional impairment in social, academic, and occupational aspects. At present, the treatment for children with ADHD is mainly based on psychological nursing intervention combined with drug therapy. Therefore, the actual efficacy evaluation of this treatment regimen is very important. Neural networks are widely used in smart medical care. This work combines artificial intelligence with the evaluation of clinical treatment effects of ADHD children and designs an intelligent model based on neural networks for evaluating the clinical efficacy of psychological nursing intervention combined with drug treatment of children with ADHD. The main research is that, for the evaluation of clinical treatment effect of ADHD in children, this paper proposes a 1D Parallel Multichannel Network (1DPMN), which is a convolutional neural network. The results show that network models can extract different data features through different channels and can achieve high accuracy evaluation of clinical efficacy of ADHD in children. On the basis of the model, performance is improved through the study of Adam optimizer to speed up the model convergence, adopts batch normalization algorithm to improve stability, and uses Dropout to improve the generalization ability of the network. Aiming at the problem of too many parameters, the 1DPMN is optimized through the principle of local sparseness, and the model parameters are greatly reduced.

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Simon, V. "Epidemiology of adult attention deficit hyperactivity disorder (ADHD) - first hungarian data." European Psychiatry 26, S2 (March 2011): 2142. http://dx.doi.org/10.1016/s0924-9338(11)73845-7.

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IntroductionAlthough ADHD in childhood is a well known and treated condition in Hungary, until recently there was no epidemiologic data about the prevalence of ADHD among adults.ObjectiveEstimation of the prevalence of adult ADHD in Hungary.MethodsIn this study1, 3529 subjects (18 to 60 years) were screened with the Adult Self-Report Scale2 6-item version. Out of 279 positively screened subjects, 161 participated in a detailed semi-structured clinical interview.ResultsADHD was associated with younger age and male gender [χ2=14.46; p=0.0007], however there was no significant interaction between the effect of gender and age [Estimate: –0.031, SE: 0.043, χ2=0.5124; p=0.4741]1. According to the estimates corrected for the ‘not-interviewed’ subsample and after adjusting for specificity and sensitivity data of the screener, the prevalence of ADHD was 2.3% in males, 0.91% in females; 2.02% in the ≤40 years group and 0.70% in the > 40 years group1. In our sample, 82.61% of male, and 78.94% of female ADHD subjects had at least 1 comorbid psychiatric disorder.ConclusionsThe estimated prevalence of ADHD among adults is in line with data reported in the literature.

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Marín-Méndez, Juan-Jesús, María-Cristina Borra-Ruiz, María-José Álvarez-Gómez, Kara E. McGoey, and César Soutullo. "Normative ADHD-RS-Preschool Data in a Community Sample in Spain." Journal of Attention Disorders 23, no. 6 (February 2, 2016): 615–23. http://dx.doi.org/10.1177/1087054715625300.

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Objective: The objective was to obtain normalized data from the ADHD Rating Scale–IV–Preschool Version (ADHD-RS-IV-P) in a Spanish sample. Method: We translated and adapted the ADHD-RS-IV to our culture to obtain normalized data from a random representative sample of 1,426 Spanish preschool children (3 to <7 years old; 49.7% males). To analyze differences between evaluators, we used MANOVA. Internal consistency was assessed via Cronbach’s alpha. Results: The mean age was 4.7 years old. There was a significant sex effect. The questionnaire had an internal consistency between .86 and .96 according to subscale and evaluator. Conclusion: To evaluate ADHD in preschool children, it is necessary to use scores standardized by sex. Using a validated scale in schools and primary care centers may be useful for early detection of ADHD.

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Drugas, Ioana. "The Profile of Children Diagnosed with ADHD in Bihor County. Descriptive Data." Central European Journal of Educational Research 3, no. 1 (April 30, 2021): 98–111. http://dx.doi.org/10.37441/cejer/2021/3/1/9356.

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Although the topic of the profile of children with Attention Deficit Hyperactive Disorder (ADHD) is important for those involved in therapy or teaching, we found very few studies focusing on Romanian populations, and those targeting the North-Western region (Bihor County) are even fewer. ADHD is the most common childhood disorder (Aman et al., 1998), and it is important not only to know and understand the symptoms, but also to pay attention to the cultural specificity of the ADHD diagnosis, if it is possible. We conducted a documentary analysis, aiming to identify the profile of children diagnosed with ADHD in Bihor County and in this regard, we analyzed 196 files registered at the Municipal Hospital from Oradea in 2015. We focused on the demographic data, the symptoms, the comorbid disorders, the treatments, the school environment and type. Our findings confirmed that boys diagnosed with ADHD are more numerous than girls, and we also found significant differences between children depending on their ADHD core symptoms.

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Kooij, J. J. S. "FC28-06 - ADHD in elderly. First data from a dutch epidemiological cohort (LASA study)." European Psychiatry 26, S2 (March 2011): 1976. http://dx.doi.org/10.1016/s0924-9338(11)73679-3.

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IntroductionADHD occurs in 3–5% of children and adults. Yet little is known about ADHD in elderly.ObjectivesTo review the literature and to present first Dutch epidemiological data on ADHD in elderly (VUmc/LASA and PsyQ).AimsThe study aims to estimate the prevalence of ADHD in eldery and to correlate symptoms of ADHD with comorbidity patterns, cognitive decline and somatic disorders. This knowledge may help predict the future of the current group of adults with ADHD.MethodsThe Longitudinal Aging Study Amsterdam (LASA) included a selfreport questionnaire for ADHD in 2009 in around 1500 elderly, aged 63–94 years. From those with low, intermediate and high scores, a random sample was interviewed using the DIVA, a structured Diagnostic Interview for ADHD in adults (N = 234).ResultsFirst data on prevalence of ADHD in elderly in the general Dutch population will be discussed. The long term consequences of the persistence of the disorder in adults and elderly, and the impact for the organisation of treatment of this lifespan disorder will be reviewed.ConclusionsThe continuity of ADHD symptoms and impairment from childhood into to old age, may pose psychiatric services for important questions like the usefulness of separate treatment facilities for different age groups in case of a lifespan disorder like ADHD.

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Nagendhiran, Nalini, and Lakshmanan Kuppusamy. "Adaptive Drift Detection Mechanism for Non-Stationary Data Stream." Journal of Information & Knowledge Management 20, no. 01 (March 2021): 2150008. http://dx.doi.org/10.1142/s0219649221500088.

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Mining is a challenging and important task in a non-stationary data stream. It is used in financial sectors, web log analysis, sensor networks, network traffic management, etc. In this environment, data distribution may change overtime and is called concept drift. So, it is necessary to identify the changes and address them to keep the model relevant to the incoming data. Many researchers have used Drift Detection Method (DDM). However, DDM is very sensitive to detect gradual drift where the detection delay is high. In this paper, we propose Adaptive Drift Detection Method (ADDM) which improves the performance of the drift detection mechanism. The ADDM uses a new parameter to detect the gradual drift in order to reduce the detection delay. The proposed method, ADDM, experiments with six synthetic datasets and four real-world datasets. Experimental results confirm that ADDM reduces the drift detection delay and false-positive rate (FPR) while preserving high classification accuracy.

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Gregório Hertz, P., D. Turner, and W. Retz. "Sexuality in ADHD: empirical data concerning hypersexual and paraphilic fantasies and behaviors in adults with ADHD." European Psychiatry 65, S1 (June 2022): S283. http://dx.doi.org/10.1192/j.eurpsy.2022.725.

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Introduction ADHD is a neurodevelopmental disorder displaying inattention, hyperactivity, and impulsivity as core symptoms. It can affect several areas of life including sexual health. Clinicians have often made assumptions concerning the bound of specific ADHD symptoms affecting sexual desire by increasing its frequency and intensity. Yet, there is still a lack of knowledge about the comorbidity between ADHD, hypersexuality, and paraphilias. A recent literature review could show that some individuals who suffer from ADHD report about hypersexual and paraphilic fantasies and behaviors, but as far as we know, no clear empirical data has emerged supporting the idea that hypersexuality and paraphilias are more frequent in individuals with ADHD. Objectives The present investigation aimed to compare several sexuality related aspects between individuals with and without ADHD. Methods Therefore, we designed an extensive online survey based on established questionnaires, such as the Hypersexual Behavior Inventory (HBI). The survey was implemented in a outpatient sample, ADHD specific fora as well as other general online channels. Results In total, N = 238 individuals participated in the survey (n = 160 with ADHD). Thereby, individuals with ADHD reported significantly more often about a wide range of hypersexual fantasies and behaviors in comparison to individuals without ADHD. Furthermore, individuals with ADHD reported significantly more often about paraphilic fantasies and behaviors including fetishistic and sadistic sexual fantasies. No differences were found concerning other paraphilias. Further results regarding other facets of sexuality, such as sexual orientation, are to be presented and discussed. Conclusions The present study contributes to closing the knowledge gap regarding sexuality in individuals with an ADHD. Disclosure No significant relationships.

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Kramer, Whitney. "Review of 3D Data Creation to Curation: Community Standards for 3D Data Preservation." Journal of New Librarianship 8, no. 1 (February 18, 2023): 60–63. http://dx.doi.org/10.33011/newlibs/13/6.

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Review of Moore, Jennifer, Adam Rountrey, and Hannah Scates Kettler, eds., 3D Data Creation to Curation: Community Standards for 3D Data Preservation. Chicago, Illinois: Association of College and Research Libraries, 2022.

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SPLETE, HEIDI. "Psychiatrist Skeptical of New ADHD Data." Clinical Psychiatry News 34, no. 9 (September 2006): 2. http://dx.doi.org/10.1016/s0270-6644(06)71709-x.

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Shao, Lizhen, Donghui Zhang, Haipeng Du, and Dongmei Fu. "Deep Forest in ADHD Data Classification." IEEE Access 7 (2019): 137913–19. http://dx.doi.org/10.1109/access.2019.2941515.

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Libutzki, Berit, Saskia Ludwig, Melanie May, Rasmus Højbjerg Jacobsen, Andreas Reif, and Catharina A. Hartman. "Direct medical costs of ADHD and its comorbid conditions on basis of a claims data analysis." European Psychiatry 58 (February 23, 2019): 38–44. http://dx.doi.org/10.1016/j.eurpsy.2019.01.019.

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AbstractBackground:ADHD is a highly prevalent disease in childhood which often persists into adulthood, then co-occurring with common adult conditions. Especially for adult ADHD, little is known about the costs of ADHD and the additional costs of comorbid conditions.Aims:To determine medical costs of ADHD and costs of comorbidities (mood, anxiety and substance use disorders, obesity), including their co-occurrence rates, stratified by age and gender.Method:Claims data from a German Statutory Health Insurance database with approximately four million member-records per year were analysed. A total of 25,300 prevalent ADHD patients were identified by means of an ICD-10 GM diagnosis of ADHD. A 1:1 age and gender adjusted reference group without ADHD diagnosis was randomly selected. Total health claims and health care costs related to ADHD were analysed, in addition to more targeted analyses of the occurrence and costs of pre-defined common comorbidities of, in particular, adult ADHD (SUD, mood and anxiety disorders, obesity). Outcomes were mean costs per patient and occurrence rates of comorbid conditions. Surplus costs of a comorbid condition in persons with ADHD relative to costs of this condition in persons without ADHD were calculated. Subgroup analyses were conducted based on age (0–12 years, 13–17 years, 18–30years, 30+ years) and gender.Results:Patients with ADHD were €1500 more expensive annually than individuals without ADHD (p < 0.001). Main cost drivers were inpatient care, psychiatrists and psychotherapists. Mood, anxiety, substance use disorders and obesity were significantly more frequent in ADHD patients and additional costs resulting from the comorbid conditions amounted up to €2800. Costs were slightly higher in women than men and increased with age for both genders. In young adults (18–30 years) health care costs dropped notably, especially costs for the medical treatment of ADHD with stimulants and costs for psychiatrists, before rising again in the group of patients over 30 years who had higher comorbidity rates.Conclusions:Medical costs for ADHD are substantial, in part through frequently occurring comorbid conditions, and particularly in adulthood, and are likely to further accelerate in the coming years. A gap of care was found, starting with the transition age group of patients over 17 years, as indicated by reduced costs per person during young adulthood, as well as an overall strong drop in administrative prevalence. In the future, approaches to improve the situation of care and reduce costs at the same time, i.e. through managed care programmes, should be implemented and benefit from detailed knowledge on age and gender-specific cost-drivers.

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Zhou, Dingfu, Zhihang Liao, and Rong Chen. "Deep Learning Enabled Diagnosis of Children’s ADHD Based on the Big Data of Video Screen Long-Range EEG." Journal of Healthcare Engineering 2022 (April 4, 2022): 1–9. http://dx.doi.org/10.1155/2022/5222136.

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Attention-deficit hyperactivity disorder (ADHD) is a common neurodevelopmental disorder in children. At the same time, ADHD is prone to coexist with other mental disorders, so the diagnosis of ADHD in children is very important. Electroencephalogram (EEG) is the sum of the electrical activity of local neurons recorded from the extracranial scalp or intracranial. At present, there are two main methods of long-range EEG monitoring commonly used in clinical practice: one is ambulatory EEG monitoring, and the other is long-range video EEG monitoring. The purpose of this study is to summarize the brain electrical activity and clinical characteristics of children with ADHD through the video long-range computer graphics data of children with ADHD and to explore the clinical significance of video long-range EEG in the diagnosis of children with ADHD. For a more effective analysis, this study further processed the video data of long-range computer graphics of children with ADHD and constructed several neural network algorithm models based on deep learning, mainly including fully connected neural network models and two-dimensional convolutional neural networks. Model and long- and short-term memory neural network model. By comparing the recognition effects of these several algorithms, find the appropriate recognition algorithm to improve the accuracy and then establish a recognition method for the diagnosis of children’s ADHD based on deep learning long-range EEG big data. Finally, it is concluded that long-term video EEG can analyze the EEG relationship of children with ADHD and provide a diagnostic basis for the diagnosis of ADHD.

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De Silva, Senuri, Sanuwani Dayarathna, Gangani Ariyarathne, Dulani Meedeniya, and Sampath Jayarathna. "A Survey of Attention Deficit Hyperactivity Disorder Identification Using Psychophysiological Data." International Journal of Online and Biomedical Engineering (iJOE) 15, no. 13 (September 30, 2019): 61. http://dx.doi.org/10.3991/ijoe.v15i13.10744.

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Attention Deficit Hyperactivity Disorder (ADHD) is one of the most common neurological disorders among children, that affects different areas in the brain that allows executing certain functionalities. This may lead to a variety of impairments such as difficulties in paying attention or focusing, controlling impulsive behaviors and overreacting. The continuous symptoms may have a severe impact in the long-term. This paper discusses the existing literature on the identification of ADHD using eye movement data and fMRI together including different deep learning techniques, existing models and a thorough analysis of the existing literature. We have identified the current challenges and possible future directions to provide computational support for early identification of ADHD patients that enable early treatments.

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Wehmeier, P., A. Schacht, R. W. Dittmann, and T. Banaschewski. "Reasons for Choice of Medication - Baseline Data of the Outpatient ADHD Treatment Study “Comply”." European Psychiatry 24, S1 (January 2009): 1. http://dx.doi.org/10.1016/s0924-9338(09)71158-7.

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Aims:Patient-related factors and physicians’ attitudes leading to the decision which particular treatment is prescribed for attention-deficit/hyperactivity disorder (ADHD) have not been investigated in detail. We assessed the reasons for choice of medication and the socioeconomic status of treatment-naïve ADHD patients when initiated on ADHD medication.Method:Multicenter, prospective, 6-month observational study in children and adolescents with ADHD (ICD-10 or DSM-IV). Demographic, disease, and socioeconomic characteristics, and ADHD-related symptoms (ADHD-RS, CGI-S, GIPD) were captured at baseline, and compared between two medication groups (non-stimulant vs. stimulant). Physicians’ reasons for choice of medication were recorded. Correlations between those reasons were explored by Pearson"s correlation coefficient, Cohen"s Kappa, and cluster analyses.Results:Overall, 504 patients, mean age 9.6 years (range 6-17), 27.4% female, were included. Non-stimulant medication was prescribed in 50.0% and stimulant in 49.0% of patients (1% received both). In the non-stimulant group, patients were significantly older (0.6 years), had significantly more problems with regard to their psychosocial situation, and had more concomitant psychiatric disorders. There were no significant differences in questionnaire scores. Physicians’ reasons for prescribing medication differed for non-stimulant vs. stimulant treatment: duration of action (73.4%/28.7%), beneficial for compliance (60.3%/40.1%), and patient/parent decision (33.7%/26.3%) were reasons in favor of non-stimulant treatment; good efficacy (93.1%/73.0%), good tolerability (66.4%/44.1%), and well-priced (38.1%/2.8%) in favor of stimulant treatment.Conclusion:Patients initiating stimulant or non-stimulant ADHD treatment differed significantly on some points according to their baseline characteristics. Physicians’ reasons for choice of medication clearly differed between the two medication groups.

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Basishvili, T., M. Eliozishvili, T. Oniani, T. Tchintcharauli, I. Sakhelashvili, N. Oniani, I. G. Campbell, I. Feinberg, and N. Darchia. "0327 NREM Sleep EEG in Typically Developing and Drug-Naïve ADHD Adolescents: Data from a Longitudinal Study." Sleep 43, Supplement_1 (April 2020): A124. http://dx.doi.org/10.1093/sleep/zsaa056.324.

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Abstract Introduction Structural MRI studies suggest delayed brain maturation in children with attention deficit hyperactivity disorder (ADHD). The steep adolescent decline in sleep slow wave EEG activity provides an opportunity to investigate brain electrophysiological evidence for this maturational delay. Most ADHD sleep EEG studies have been cross-sectional. Here we present data from an ongoing longitudinal study of the maturational trajectories of sleep EEG in drug-naïve ADHD and typically developing adolescents. Methods Nine children diagnosed with ADHD (combined subtype, DSM-V criteria, mean age 12.39±0.61 years), and nine typically developing controls (12.07±0.35 years) were recruited. Subjects underwent an adaptation night and all night polysomnography twice yearly at the Laboratory. Sleep EEG was analyzed using fast Fourier transform. NREM delta and theta EEG activity were compared across first two recordings. Results Group effects (ADHD vs. control) on all night delta and theta energy, and delta power were not significant (p>0.2 for all). All night theta power was lower (p=0.035) for the ADHD group, and all night NREM sleep duration trended (p=0.060) toward being lower for the ADHD group. Controlling for sleep duration differences by examining only the first 5 h of NREM sleep showed no group effect on delta power (p=0.77) and a trend toward lower theta power (p=0.057) for the ADHD group. Conclusion At age 12 to 13 years, NREM sleep delta EEG did not differ between ADHD and control subjects. Theta power, which declines at a younger age than delta, was lower in control subjects. The two recordings thus far differ only by 6 months. The entire study will provide 5 semiannual recordings and allow us to determine if the higher theta power in the ADHD group will hold and if delta power will be greater as well, and thus provide electrophysiological support for the delayed brain maturation suggested by MRI findings. Support Shota Rustaveli National Science Foundation Grant FR17_94; Subjects Recruitment Support - Mental Health Service in Tbilisi “Kamara”.

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Porter, S. C., C.-Y. Guo, J. Molino, S. L. Toomey, and E. Chan. "The influence of task environment and health literacy on the quality of parent-reported ADHD data." Applied Clinical Informatics 03, no. 01 (2012): 24–37. http://dx.doi.org/10.4338/aci-2011-10-ra-0062.

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Summary Objectives: To determine 1) the extent to which paper-based and computer-based environments influence the sufficiency of parents’ report of child behaviors and the accuracy of data on current medications, and 2) the impact of parents’ health literacy on the quality of information produced. Methods: We completed a randomized controlled trial of data entry tasks with parents of children with Attention Deficit Hyperactivity Disorder (ADHD). Parents completed the NICHQ Vanderbilt ADHD screen and a report of current ADHD medications on paper or using a computer application designed to facilitate data entry. Literacy was assessed by the Test of Functional Health Literacy in Adults (TOFHLA). Primary outcomes included sufficient data to screen for ADHD subtypes and accurate report of total daily dose of prescribed ADHD medications. Results: Of 271 parents screened, 194/271 were eligible and 182 were randomized. Data from 180 parents were analyzed. 5.6% parents had inadequate/marginal TOFHLA scores. Using the computer, parents provided more sufficient and accurate data compared to paper (sufficiency for ADHD screening, paper vs. computer: 87.8% vs. 93.3%, P = 0.20; accuracy of medication report: 14.3% vs. 69.4%; p<0.0001). Parents with adequate literacy had increased odds of reporting sufficient and accurate data (sufficiency for ADHD screening: OR 8.0, 95% CI 2.0–32.1; accuracy of medication report: OR 4.4, 95% CI 0.5–37.4). In adjusted models, the computer task environment remained a significant predictor of accurate medication report (OR 18.7, 95% CI 7.5–46.9). Conclusions: Structured, computer-based data entry by parents may improve the quality of specific types of information needed for ADHD care. Health literacy affects parents’ ability to share valid information.

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Lee, Wonjun, Deokwon Lee, Sanghyub Lee, Kooksung Jun, and Mun Sang Kim. "Deep-Learning-Based ADHD Classification Using Children’s Skeleton Data Acquired through the ADHD Screening Game." Sensors 23, no. 1 (December 26, 2022): 246. http://dx.doi.org/10.3390/s23010246.

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The identification of attention deficit hyperactivity disorder (ADHD) in children, which is increasing every year worldwide, is very important for early diagnosis and treatment. However, since ADHD is not a simple disease that can be diagnosed with a simple test, doctors require a large period of time and substantial effort for accurate diagnosis and treatment. Currently, ADHD classification studies using various datasets and machine learning or deep learning algorithms are actively being conducted for the screening diagnosis of ADHD. However, there has been no study of ADHD classification using only skeleton data. It was hypothesized that the main symptoms of ADHD, such as distraction, hyperactivity, and impulsivity, could be differentiated through skeleton data. Thus, we devised a game system for the screening and diagnosis of children’s ADHD and acquired children’s skeleton data using five Azure Kinect units equipped with depth sensors, while the game was being played. The game for screening diagnosis involves a robot first travelling on a specific path, after which the child must remember the path the robot took and then follow it. The skeleton data used in this study were divided into two categories: standby data, obtained when a child waits while the robot demonstrates the path; and game data, obtained when a child plays the game. The acquired data were classified using the RNN series of GRU, RNN, and LSTM algorithms; a bidirectional layer; and a weighted cross-entropy loss function. Among these, an LSTM algorithm using a bidirectional layer and a weighted cross-entropy loss function obtained a classification accuracy of 97.82%.

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López-Martín, S., J. Albert, A. Fernández-Jaén, and L. Carretié. "Emotional response inhibition in children with attention-deficit/hyperactivity disorder: neural and behavioural data." Psychological Medicine 45, no. 10 (February 24, 2015): 2057–71. http://dx.doi.org/10.1017/s0033291714003195.

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BackgroundAlthough both emotion and response inhibition are thought to be important in attention-deficit/hyperactivity disorder (ADHD), little is known about the neural mechanisms that underlie the interaction between these two processes in patients with this disorder. This study aimed at examining how emotional contexts affect inhibitory control in children with ADHD.MethodA total of 24 ADHD children and 24 healthy comparison subjects performed a modified go/no-go task during three different emotionally laden contexts: negative, neutral and positive. To explore the timing and the underlying neural substrates of emotion-modulated response inhibition, event-related potentials were measured and further analysed both at the scalp and at the voxel level.ResultsPatients with ADHD showed greater activation of inhibition-related neural mechanisms (i.e. no-go P3 amplitudes and orbitofrontal cortex activity) to maintain a similar level of performance as healthy comparison subjects, especially during the emotionally arousing contexts (negative and positive).ConclusionsThis study provides plausible neural mechanisms for the difficulty that ADHD children have in controlling their behaviour in highly emotional situations. Such emotional contexts might increase the need for top-down inhibitory control and put ADHD children at greater risk for impulsive behaviours and emotional dysregulation.

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SPLETE, HEIDI. "Data on ADHD Stimulants Deemed Not ‘Threatening’." Clinical Psychiatry News 37, no. 8 (August 2009): 16. http://dx.doi.org/10.1016/s0270-6644(09)70281-4.

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SPLETE, HEIDI. "Data on ADHD Stimulants Deemed Not Threatening." Pediatric News 43, no. 7 (July 2009): 2. http://dx.doi.org/10.1016/s0031-398x(09)70190-0.

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SPLETE, HEIDI. "Data on ADHD Stimulants Deemed Not ‘Threatening’." Family Practice News 39, no. 13 (July 2009): 20. http://dx.doi.org/10.1016/s0300-7073(09)70535-3.

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Woodbridge, M., C. D. Tomlinson, and S. A. Butcher. "ADAM: automated data management for research datasets." Bioinformatics 29, no. 1 (October 29, 2012): 146–47. http://dx.doi.org/10.1093/bioinformatics/bts644.

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Kim, Beomjun, Yongtae Kim, Prashant Nair, and Seokin Hong. "Exploiting Data Compression for Adaptive Block Placement in Hybrid Caches." Electronics 11, no. 2 (January 12, 2022): 240. http://dx.doi.org/10.3390/electronics11020240.

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STT-RAM (Spin-Transfer Torque Random Access Memory) appears to be a viable alternative to SRAM-based on-chip caches. Due to its high density and low leakage power, STT-RAM can be used to build massive capacity last-level caches (LLC). Unfortunately, STT-RAM has a much longer write latency and a much greater write energy than SRAM. Researchers developed hybrid caches made up of SRAM and STT-RAM regions to cope with these challenges. In order to store as many write-intensive blocks in the SRAM region as possible in hybrid caches, an intelligent block placement policy is essential. This paper proposes an adaptive block placement framework for hybrid caches that incorporates metadata embedding (ADAM). When a cache block is evicted from the LLC, ADAM embeds metadata (i.e., write intensity) into the block. Metadata embedded in the cache block are then extracted and used to determine the block’s write intensity when it is fetched from main memory. Our research demonstrates that ADAM can enhance performance by 26% (on average) when compared to a baseline block placement scheme.

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Zakershoshtari, Maryam, and Zahra Dasht Bozorgi. "The Effectiveness of Play Therapy on Reduction of the Symptoms of Attention Deficit Hyperactivity Disorder (ADHD) in Children." Asian Social Science 12, no. 6 (May 20, 2016): 188. http://dx.doi.org/10.5539/ass.v12n6p188.

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<p class="a"><span lang="EN">This study aimed to investigate the effectiveness of play therapy on reduction of the symptoms of attention defect hyperactivity disorder (ADHD) in children of Ahvaz, Iran. To this end, 20 children with ADHA were selected using the available sampling method using the quasi-experimental design with pretest and posttest and were randomly divided into two groups. Both groups were evaluated using the Conners' scale as the pretest and posttest and the treatment group received play therapy for eight sessions. For data analysis, factorial ANCOVA was used. The results showed that there is a significant difference between the mean scores of pre-test and post-test in the two groups. Follow-up study also showed the lasting effect of the independent variable.</span></p>

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Widayanti, Ratna Siwi. "Manajemen Program Afirmasi Pendidikan Menengah (ADEM) Papua-Papua Barat dan Repatriasi Pada Sekolah Mitra di Daerah Istimewa Yogyakarta." Media Manajemen Pendidikan 4, no. 2 (January 7, 2022): 290–310. http://dx.doi.org/10.30738/mmp.v4i2.10039.

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Penelitian ini bertujuan untuk mendeskripsikan: 1) manajemen program Afirmasi Pendidikan Menengah, 2) faktor pendukung dan penghambat program, 3) hasil yang dicapai dari program Afirmasi Pendidikan Menengah (ADEM). Penelitian ini merupakan penelitian deskriptif kualitatif. Subjek penelitin ini adalah kepala sekolah dan koordinator/pendamping Program Afirmasi Pendidikan Menengah (ADEM) pada sekolah Mitra di Daerah Istimewa Yogyakarta (DIY). Teknik pengumpulan data menggunakan observasi, wawancara, dan dokumentasi. Analisis data menggunakan langkah pengumpulan data, reduksi data, penyajian data, dan penarikan kesimpulan. Hasil penelitian menunjukkan bahwa: 1) manajemen program Afirmasi Pendidikan Menengah Papua-Papua Barat dan Repatriasi terdiri dari: perencanaan program, pengorganisasian program, pelaksanaan program, dan pengawasan/pengendalian program. 2) Faktor pendukung berasal dari guru dan karyawan, pendampingan dari dinas dan koordinator ADEM DIY, dana yang cukup dari direktorat, dan faktor penghambat yaitu kemampuan peserta didik penerima beasiswa ADEM masih rendah, motivasi dan ketekunan peserta didik kurang, sifat dan karakter peserta didik yang berbeda dengan peserta didik dari Jawa dan 3) Hasil yang dicapai program ADEM, peserta didik melanjutkan pendidikan melalui jalur Afirmasi Pendidikan Tinggi (ADIK), prestasi akademik maupun non akademik. ADEM juga menghasilkan pemerataan pendidikan bagi seluruh warga Negara Indonesai, tidak ada kesenjangan pendidikan serta suksesnya program Direktorat Pendidikan Masyarakat dan Pendidikan Khusus.

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dos Santos Siqueira, Anderson, Claudinei Eduardo Biazoli Junior, William Edgar Comfort, Luis Augusto Rohde, and João Ricardo Sato. "Abnormal Functional Resting-State Networks in ADHD: Graph Theory and Pattern Recognition Analysis of fMRI Data." BioMed Research International 2014 (2014): 1–10. http://dx.doi.org/10.1155/2014/380531.

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The framework of graph theory provides useful tools for investigating the neural substrates of neuropsychiatric disorders. Graph description measures may be useful as predictor variables in classification procedures. Here, we consider several centrality measures as predictor features in a classification algorithm to identify nodes of resting-state networks containing predictive information that can discriminate between typical developing children and patients with attention-deficit/hyperactivity disorder (ADHD). The prediction was based on a support vector machines classifier. The analyses were performed in a multisite and publicly available resting-state fMRI dataset of healthy children and ADHD patients: the ADHD-200 database. Network centrality measures contained little predictive information for the discrimination between ADHD patients and healthy subjects. However, the classification between inattentive and combined ADHD subtypes was more promising, achieving accuracies higher than 65% (balance between sensitivity and specificity) in some sites. Finally, brain regions were ranked according to the amount of discriminant information and the most relevant were mapped. As hypothesized, we found that brain regions in motor, frontoparietal, and default mode networks contained the most predictive information. We concluded that the functional connectivity estimations are strongly dependent on the sample characteristics. Thus different acquisition protocols and clinical heterogeneity decrease the predictive values of the graph descriptors.

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Kaur, Amandeep, and Karanjeet Singh Kahlon. "Accurate Identification of ADHD among Adults Using Real-Time Activity Data." Brain Sciences 12, no. 7 (June 26, 2022): 831. http://dx.doi.org/10.3390/brainsci12070831.

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Attention Deficit Hyperactivity Disorder (ADHD) is a neurodevelopment disorder that affects millions of children and typically persists into adulthood. It must be diagnosed efficiently and consistently to receive adequate treatment, otherwise, it can have a detrimental impact on the patient’s professional performance, mental health, and relationships. In this work, motor activity data of adults suffering from ADHD and clinical controls has been preprocessed to obtain 788 activity-related statistical features. Afterwards, principal component analysis has been carried out to obtain significant features for accurate classification. These features are then fed into six different machine learning algorithms for classification, which include C4.5, kNN, Random Forest, LogitBoost, SVM, and Naive Bayes. The detailed evaluation of the results through 10-fold cross-validation reveals that SVM outperforms other classifiers with an accuracy of 98.43%, F-measure of 98.42%, sensitivity of 98.33%, specificity of 98.56% and AUC of 0.983. Thus, a PCA-based SVM approach appears to be an effective choice for accurate identification of ADHD patients among other clinical controls using real-time analysis of activity data.

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Šverko, Zoran, Ivan Markovinović, Miroslav Vrankić, and Saša Vlahinić. "EEG data processing in ADHD diagnosis and neurofeedback." Engineering review 40, no. 3 (May 21, 2020): 116–23. http://dx.doi.org/10.30765/er.40.3.12.

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In this paper, EEG data processing was conducted in order to define the parameters for neurofeedback. A new survey was conducted based on a brief review of previous research. Two groups of participants were chosen: ADHD (3) and nonADHD (14). The main part of this study includes EEG signal data pre-processing and processing. We have outlined statistical features of observed EEG signals such as mean value, grand-mean value and their ratios. It can be concluded that an increase in grand-mean values of power theta-low beta ratio on Cz electrode gives confirmation of previous research. The value of alpha-delta power ratio higher than 1 on C3, Cz, P3, Pz, P4 in ADHD group is proposed as a new approach to classification. Based on these conclusions we will design a neurofeedback protocol as a continuation of this work.

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Yoshida, Makiko, Taku Obara, Saya Kikuchi, Michihiro Satoh, Yoshihiko Morikawa, Nobuhiro Ooba, Hiroaki Yamaguchi, and Nariyasu Mano. "Drug Prescriptions for Children With ADHD in Japan: A Study Based on Health Insurance Claims Data Between 2005 and 2015." Journal of Attention Disorders 24, no. 2 (May 5, 2019): 175–91. http://dx.doi.org/10.1177/1087054719843179.

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Objective: The aim of this study is to investigate the trend of prescription drugs for children with ADHD in Japan. Method: Using health insurance claims data of 3,672,951 people between January 2005 and December 2015, we investigated the trend of prescription drugs for 7,856 children with ADHD. Results: After approval in 2007, the proportion of prescriptions for methylphenidate-osmotic-controlled release oral delivery system tablets was 31.4% in 2009 (adjusted odds ratio [AOR] = 2.72; 95% confidence interval [CI] = [2.12, 3.51]) and reached a plateau approximately after 2009 (AOR = 0.96; 95% CI = [0.94, 0.98]). The proportion of prescriptions for atomoxetine increased from 6.1% in 2008 to 21.8% in 2014 (AOR = 1.12; 95% CI = [1.13, 1.18]). The proportion of prescriptions for aripiprazole and ramelteon increased (all trend p < .001). Conclusion: Prescriptions of drugs for children with ADHD have changed. We need to monitor the safety of ADHD medications among children with ADHD.

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Christiansen, H., B. Kis, O. Hirsch, A. Philipsen, M. Henneck, A. Panczuk, R. Pietrowsky, J. Hebebrand, and B. G. Schimmelmann. "German Validation of the Conners Adult ADHD Rating Scales–self-report (CAARS-S) I: Factor Structure and Normative Data." European Psychiatry 26, no. 2 (July 8, 2010): 100–107. http://dx.doi.org/10.1016/j.eurpsy.2009.12.024.

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AbstractBackgroundAttention-deficit/hyperactivity disorder (ADHD) often persists into adulthood. Instruments for diagnosing ADHD in childhood are well validated and reliable, but diagnosis of ADHD in adults remains problematic. Attempts have been made to develop criteria specific for adult ADHD, resulting in the development of self-report and observer-rated questionnaires. To date, the Conners Adult ADHD Rating Scales (CAARS) are the international standard for questionnaire assessment of ADHD. The current study evaluates a German version of the CAARS self-report (CAARS-S).MethodsEight hundred and fifty healthy German control subjects were recruited to fill out the CAARS-S and to answer questions on sociodemographic variables. Explorative and confirmative factor analyses were conducted to obtain the factor structure for the German model and to replicate the factor structure of the original American model. Analyses on gender, age, and education level were calculated for normative data.ResultsThe explorative factor analysis of the German sample results in a six-factor solution that explained 52% of the variance. A confirmative analysis that was based on the 42 items of the original American model showed a high model-fit. Analyses of normative data showed significant influences of age, gender, and education level on the emerging subscales.ConclusionEven though the explorative factor analysis yields a solution different from the American original, the confirmative factor analysis results in such a high model-fit that use of the American version is justified with respect to international multicenter studies, for which this instrument will be highly valuable.

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Grazioli, S., M. Mauri, E. Rosi, F. Villa, F. Tizzoni, A. Tarabelloni, S. Trabattoni, et al. "Use of machine learning on clinical questionnaires data to support the diagnostic classification of Attention DeficitHyperactivity Disorder: a personalized medicine approach." European Psychiatry 65, S1 (June 2022): S165—S166. http://dx.doi.org/10.1192/j.eurpsy.2022.441.

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Introduction Attention Deficit / Hyperactivity Disorder (ADHD) is a highly prevalent neurodevelopmental condition characterized by inattention, motor hyperactivity and impulsivity. ADHD cognitive and behavioral presentation is characterized by a high heterogeneity (APA, 2013). Indeed, a complex diagnostic process, that considers several validated tools, is, to date, necessary. Objectives The main aim is to develop supervised machine learning (ML) algorithms that could be used to support the diagnostic process for ADHD, by identifying the most relevant features in discriminating between the presence or absence of the ADHD diagnosis in children. Methods We analyzed data from 342 children (Mean age: 8y 8m ± 1y; 61 F) referred for possible ADHD symptomatology. Assessments were performed by an expert clinician and through questionnaires: Social Responsiveness Scale (SRS), Child Behavior Checklist (CBCL), Conners Rating Scale for Parents (CPRS) and for Teachers (CTRS). Data were analyzed using a decision tree classifier and random forest algorithms. Results The decision tree model performed an accuracy of 0.71. The random forest model that was identified as the best tested, performed an accuracy of 0.77 (Figure 1) and it identified as most informative parent- and teacher-rated DSM-oriented ADHD symptoms (Figure 2). Figure 1: Random forest confusion matrix and statistics. Figure 2: Ranking of variables importance. Conclusions A random forest classifier could represent an effective algorithm to support the identification of ADHD children and to simplify the diagnostic process as an initial step. The use of supervised machine learning algorithms could be useful in helping the diagnostic process, highlighting the importance of a personalized medicine approach. Disclosure No significant relationships.

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Gosling, Corentin J., Charlotte Pinabiaux, Serge Caparos, Richard Delorme, and Samuele Cortese. "Influence of the month of birth on persistence of ADHD in prospective studies: protocol for an individual patient data meta-analysis." BMJ Open 10, no. 11 (November 2020): e040952. http://dx.doi.org/10.1136/bmjopen-2020-040952.

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IntroductionAttention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder with symptoms, especially the hyperactive ones, that tend to decrease in severity with age. Interestingly, children born just before the school-entry cut-off date (ie, the youngest pupils of a classroom) are at higher risk of being diagnosed with ADHD compared with children born just after the cut-off date. Noteworthy, this month-of-birth effect tends to disappear with increasing absolute age. Therefore, it is possible that young children erroneously diagnosed with ADHD due to their month of birth present a lower chance to have their diagnosis confirmed at a later age, artificially reinforcing the low persistence of ADHD across the lifespan. This protocol outlines an individual patient data (IPD) meta-analysis of prospective observational studies to explore the role of the month of birth in the low persistence of ADHD across the lifespan.Methods and analysisFive databases will be systematically searched in order to find prospective observational studies where the presence of ADHD is assessed both at baseline and at a follow-up of at least 4 years. We will use a two-stage IPD meta-analytic approach to estimate the role of the month of birth in the persistence of ADHD. Various sensitivity analyses will be performed to assess the robustness of the results.Ethics and disseminationNo additional data will be collected and no de-identified raw data will be used. Ethics approval is thus not required for the present study. Results of this IPD meta-analysis will be submitted for publication in a peer-reviewed journal.PROSPERO registration numberCRD42020212650

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Lalithambigai, M., and A. Hema. "A Survey on ADHD using Data Mining Techniques." International Journal of Computer Sciences and Engineering 06, no. 08 (October 31, 2018): 30–33. http://dx.doi.org/10.26438/ijcse/v6si8.3033.

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Robinson, Daniel P., and Rachael Tappenden. "A Flexible ADMM Algorithm for Big Data Applications." Journal of Scientific Computing 71, no. 1 (October 26, 2016): 435–67. http://dx.doi.org/10.1007/s10915-016-0306-6.

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Rosack, Jim. "Data Refute Claims of ADHD Overmedication, Congress Told." Psychiatric News 37, no. 21 (November 2002): 20–21. http://dx.doi.org/10.1176/pn.37.21.0020.

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Yu, Liqun, and Nan Lin. "ADMM for Penalized Quantile Regression in Big Data." International Statistical Review 85, no. 3 (August 17, 2017): 494–518. http://dx.doi.org/10.1111/insr.12221.

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Ter-Minassian, Lucile, Natalia Viani, Alice Wickersham, Lauren Cross, Robert Stewart, Sumithra Velupillai, and Johnny Downs. "Assessing machine learning for fair prediction of ADHD in school pupils using a retrospective cohort study of linked education and healthcare data." BMJ Open 12, no. 12 (December 2022): e058058. http://dx.doi.org/10.1136/bmjopen-2021-058058.

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ObjectivesAttention deficit hyperactivity disorder (ADHD) is a prevalent childhood disorder, but often goes unrecognised and untreated. To improve access to services, accurate predictions of populations at high risk of ADHD are needed for effective resource allocation. Using a unique linked health and education data resource, we examined how machine learning (ML) approaches can predict risk of ADHD.DesignRetrospective population cohort study.SettingSouth London (2007–2013).Participantsn=56 258 pupils with linked education and health data.Primary outcome measuresUsing area under the curve (AUC), we compared the predictive accuracy of four ML models and one neural network for ADHD diagnosis. Ethnic group and language biases were weighted using a fair pre-processing algorithm.ResultsRandom forest and logistic regression prediction models provided the highest predictive accuracy for ADHD in population samples (AUC 0.86 and 0.86, respectively) and clinical samples (AUC 0.72 and 0.70). Precision-recall curve analyses were less favourable. Sociodemographic biases were effectively reduced by a fair pre-processing algorithm without loss of accuracy.ConclusionsML approaches using linked routinely collected education and health data offer accurate, low-cost and scalable prediction models of ADHD. These approaches could help identify areas of need and inform resource allocation. Introducing ‘fairness weighting’ attenuates some sociodemographic biases which would otherwise underestimate ADHD risk within minority groups.

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Journal articles on the topic 'ADHM data'

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