947 resultados para Niemi, Juhani: Arvid Järnefelt
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The article introduces the E-learning Circle, a tool developed to assure the quality of the software design process of e-learning systems, considering pedagogical principles as well as technology. The E-learning Circle consists of a number of concentric circles which are divided into three sectors. The content of the inner circles is based on pedagogical principles, while the outer circle specifies how the pedagogical principles may be implemented with technology. The circle’s centre is dedicated to the subject taught, ensuring focus on the specific subject’s properties. The three sectors represent the student, the teacher and the learning objectives. The strengths of the E-learning Circle are the compact presentation combined with the overview it provides, as well as the usefulness of a design tool dealing with complexity, providing a common language and embedding best practice. The E-learning Circle is not a prescriptive method, but is useful in several design models and processes. The article presents two projects where the E-learning Circle was used as a design tool.
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Non-verbal communication (NVC) is considered to represent more than 90 percent of everyday communication. In virtual world, this important aspect of interaction between virtual humans (VH) is strongly neglected. This paper presents a user-test study to demonstrate the impact of automatically generated graphics-based NVC expression on the dialog quality: first, we wanted to compare impassive and emotion facial expression simulation for impact on the chatting. Second, we wanted to see whether people like chatting within a 3D graphical environment. Our model only proposes facial expressions and head movements induced from spontaneous chatting between VHs. Only subtle facial expressions are being used as nonverbal cues - i.e. related to the emotional model. Motion capture animations related to hand gestures, such as cleaning glasses, were randomly used to make the virtual human lively. After briefly introducing the technical architecture of the 3D-chatting system, we focus on two aspects of chatting through VHs. First, what is the influence of facial expressions that are induced from text dialog? For this purpose, we exploited an emotion engine extracting an emotional content from a text and depicting it into a virtual character developed previously [GAS11]. Second, as our goal was not addressing automatic generation of text, we compared the impact of nonverbal cues in conversation with a chatbot or with a human operator with a wizard of oz approach. Among main results, the within group study -involving 40 subjects- suggests that subtle facial expressions impact significantly not only on the quality of experience but also on dialog understanding.
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Background: Available studies vary in their estimated prevalence of attention deficit/hyperactivity disor-der (ADHD) in substance use disorder (SUD) patients, ranging from 2 to 83%. A better understanding ofthe possible reasons for this variability and the effect of the change from DSM-IV to DSM-5 is needed.Methods: A two stage international multi-center, cross-sectional study in 10 countries, among patientsform inpatient and outpatient addiction treatment centers for alcohol and/or drug use disorder patients. Atotal of 3558 treatment seeking SUD patients were screened for adult ADHD. A subsample of 1276 subjects,both screen positive and screen negative patients, participated in a structured diagnostic interview. 5AdultsResults: Prevalence of DSM-IV and DSM-5 adult ADHD varied for DSM-IV from 5.4% (CI 95%: 2.4–8.3) forHungary to 31.3% (CI 95%:25.2–37.5) for Norway and for DSM-5 from 7.6% (CI 95%: 4.1–11.1) for Hungary to32.6% (CI 95%: 26.4–38.8) for Norway. Using the same assessment procedures in all countries and centersresulted in substantial reduction of the variability in the prevalence of adult ADHD reported in previousstudies among SUD patients (2–83% → 5.4–31.3%). The remaining variability was partly explained byprimary substance of abuse and by country (Nordic versus non-Nordic countries). Prevalence estimatesfor DSM-5 were slightly higher than for DSM-IV.Conclusions: Given the generally high prevalence of adult ADHD, all treatment seeking SUD patientsshould be screened and, after a confirmed diagnosis, treated for ADHD since the literature indicates poorprognoses of SUD in treatment seeking SUD patients with ADHD.
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Aims To determine comorbidity patterns in treatment-seeking substance use disorder (SUD) patients with and without adult attention deficit hyperactivity disorder (ADHD), with an emphasis on subgroups defined by ADHD subtype, taking into account differences related to gender and primary substance of abuse. Design Data were obtained from the cross-sectional International ADHD in Substance use disorder Prevalence (IASP) study. Setting Forty-seven centres of SUD treatment in 10 countries. Participants A total of 1205 treatment-seeking SUD patients. Measurements Structured diagnostic assessments were used for all disorders: presence of ADHD was assessed with the Conners' Adult ADHD Diagnostic Interview for DSM-IV (CAADID), the presence of antisocial personality disorder (ASPD), major depression (MD) and (hypo)manic episode (HME) was assessed with the Mini International Neuropsychiatric Interview-Plus (MINI Plus), and the presence of borderline personality disorder (BPD) was assessed with the Structured Clinical Interview for DSM-IV Axis II (SCID II). Findings The prevalence of DSM-IV adult ADHD in this SUD sample was 13.9%. ASPD [odds ratio (OR) = 2.8, 95% confidence interval (CI) = 1.8–4.2], BPD (OR = 7.0, 95% CI = 3.1–15.6 for alcohol; OR = 3.4, 95% CI = 1.8–6.4 for drugs), MD in patients with alcohol as primary substance of abuse (OR = 4.1, 95% CI = 2.1–7.8) and HME (OR = 4.3, 95% CI = 2.1–8.7) were all more prevalent in ADHD+ compared with ADHD− patients (P < 0.001). These results also indicate increased levels of BPD and MD for alcohol compared with drugs as primary substance of abuse. Comorbidity patterns differed between ADHD subtypes with increased MD in the inattentive and combined subtype (P < 0.01), increased HME and ASPD in the hyperactive/impulsive (P < 0.01) and combined subtypes (P < 0.001) and increased BPD in all subtypes (P < 0.001) compared with SUD patients without ADHD. Seventy-five per cent of ADHD patients had at least one additional comorbid disorder compared with 37% of SUD patients without ADHD. Conclusions Treatment-seeking substance use disorder patients with attention deficit hyperactivity disorder are at a very high risk for additional externalizing disorders.
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We prove analogs of classical almost sure dimension theorems for Euclidean projection mappings in the first Heisenberg group, equipped with a sub-Riemannian metric.
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Background: To detect attention deficit hyperactivity disorder (ADHD) in treatment seeking substance use disorders (SUD) patients, a valid screening instrument is needed. Objectives: To test the performance of the Adult ADHD Self-Report Scale V 1.1(ASRS) for adult ADHD in an international sample of treatment seeking SUD patients for DSM-IV-TR; for the proposed DSM-5 criteria; in different subpopulations, at intake and 1–2 weeks after intake; using different scoring algorithms; and different externalizing disorders as external criterion (including adult ADHD, bipolar disorder, antisocial and borderline personality disorder). Methods: In 1138 treatment seeking SUD subjects, ASRS performance was determined using diagnoses based on Conner's Adult ADHD Diagnostic Interview for DSM-IV (CAADID) as gold standard. Results: The prevalence of adult ADHD was 13.0% (95% CI: 11.0–15.0%). The overall positive predictive value (PPV) of the ASRS was 0.26 (95% CI: 0.22–0.30), the negative predictive value (NPV) was 0.97 (95% CI: 0.96–0.98). The sensitivity (0.84, 95% CI: 0.76–0.88) and specificity (0.66, 95% CI: 0.63–0.69) measured at admission were similar to the sensitivity (0.88, 95% CI: 0.83–0.93) and specificity (0.67, 95% CI: 0.64–0.70) measured 2 weeks after admission. Sensitivity was similar, but specificity was significantly better in patients with alcohol compared to (illicit) drugs as the primary substance of abuse (0.76 vs. 0.56). ASRS was not a good screener for externalizing disorders other than ADHD. Conclusions: The ASRS is a sensitive screener for identifying possible ADHD cases with very few missed cases among those screening negative in this population.
Resumo:
Attention deficit/hyperactivity disorder (ADHD) is an increasingly recognized comorbid condition in subjects with substance use disorders (SUDs). This paper describes the methods and study population of the International ADHD in Substance Use Disorders Prevalence (IASP) study. Objectives of the IASP are to determine the prevalence of ADHD in adult treatment seeking patients with SUD in different countries and SUD populations, determine the reliability and validity of the Adult ADHD Self-report Scale V 1.1 (ASRS) as ADHD screening instrument in SUD populations, investigate the comorbidity profile of SUD patients with and without ADHD, compare risk factors and protective factors in SUD patients with and without a comorbid diagnosis of ADHD, and increase our knowledge about the relationship between ADHD and the onset and course of SUD. In this cross-sectional, multi-centre two stage study, subjects were screened for ADHD with the ASRS, diagnosed with the Conner's Adult ADHD Diagnostic Interview for DSM-IV (CAADID), and evaluated for SUD, major depression, bipolar disorder, anti social personality disorder and borderline personality disorder. Three thousand five hundred and fifty-eight subjects from 10 countries were included. Of these 40.9% screened positive for ADHD. This is the largest international study on this population evaluating ADHD and comorbid disorders.