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Cross-cultural adaptation and validation of the Kerlan-Jobe Orthopaedic Clinic shoulder and elbow score in Finnish-speaking overhead athletes
(2022-12) Sukanen, Maria; Pajari, Jesse; Äyrämö, Sami; Paloneva, Juha; Waller, Benjamin; Häkkinen, Arja; Multanen, Juhani
Background: The Kerlan-Jobe Orthopaedic Clinic Shoulder and Elbow score (KJOC) is developed to evaluate the shoulder and elbow function in overhead athletes. To date, the score has not been adapted into Finnish language. The aim of this study was to perform a cross-cultural adaptation of the Kerlan-Jobe Orthopaedic Clinic Shoulder and Elbow score (KJOC) into Finnish language and evaluate its validity, reliability, and responsiveness in overhead athletes. Methods: Forward–backward translation method was followed in the cross-cultural adaptation process. Subsequently, 114 overhead athletes (52 males, 62 females, mean age 18.1 ± 2.8 years) completed the Finnish version of KJOC score, Disabilities of the Arm, Shoulder and Hand (DASH), American Shoulder and Elbow Surgeons Standardized Shoulder Assessment Form (ASES) and RAND-36 to assess validity of the KJOC score. To evaluate reliability and responsiveness, the participants filled in the KJOC score 16 days and eight months after the first data collection. Validity, reliability, and responsiveness of the Finnish KJOC score were statistically tested. Results: Minor modifications were made during the cross-cultural translation and adaptation process, which were related to culture specific terminology in sports and agreed by an expert committee. Construct validity of the KJOC score was moderate to high, based on the correlations with DASH (r = − 0.757); DASH sports module (r = − 0.667); ASES (r = 0.559); and RAND-36 (r = 0.397) questionnaires. Finnish KJOC score showed excellent internal consistency (α = 0.92) and good test–retest reliability (2-way mixed-effects model ICC = 0.77) with acceptable measurement error level (SEM 5.5; MDC 15.1). Ceiling effect was detected for asymptomatic athletes in each item (23.2–61.1%), and for symptomatic athletes in item 5 (47.4%). Responsiveness of the Finnish KJOC score could not be confirmed due to conflicting follow-up results. Conclusion: The Finnish KJOC score was found to be a valid and reliable questionnaire measuring the self-reported upper arm status in Finnish-speaking overhead athletes.
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Cognitive behavioural group therapy as addition to psychoeducation and pharmacological treatment for adolescents with ADHD symptoms and related impairments : a randomised controlled trial
(2022-12) Haugan, Anne Lise Juul; Sund, Anne Mari; Young, Susan; Thomsen, Per Hove; Lydersen, Stian; Nøvik, Torunn Stene
Background: Cognitive behavioural therapy (CBT) is recommended for attention-deficit/hyperactivity-disorder (ADHD) in adolescents. However, all CBTs are not created equal, and the guidelines do not specify which CBT interventions are the most effective for this patient group. This study examines the efficacy of a group CBT without parent involvement as follow-up treatment compared to no additional CBT in adolescents with persistent and impairing ADHD symptoms after a short psychoeducational intervention and medical treatment. Methods: The authors conducted a two-arm parallel randomized controlled trial in two child and adolescent mental health outpatient clinics in Norway. One hundred patients aged 14–18 years with a diagnosis of ADHD (66%) or subthreshold ADHD (34%) were randomized to either a 12-week group CBT program (N = 50) or a non-CBT control condition (N = 50). Assessments were made at admission to the clinic, two weeks before and two weeks after treatment. The primary outcomes were parent-, teacher- and self-ratings of ADHD symptoms (ADHD Rating Scale-IV), and the secondary outcomes were ratings of ADHD symptom severity, executive function, functional impairment, and emotional problems. Evaluators blinded to group allocation rated ADHD symptom severity with the Clinical Global Impression Scale for Severity (CGI-S) at baseline and post-treatment. Results: Analyses using mixed-effects models showed no difference between the treatment arms from baseline to post treatment in primary and secondary outcomes. Conclusions: Contrary to our hypothesis, we found no incremental treatment effect on the part of a group CBT as follow-up to psychoeducation and pharmacological treatment on ADHD symptoms and accompanying impairments. Limitations with the CBT was the large number and low dosage of treatment components, causing restricted time for practice. Unlike evidence-based, individualized targeted CBTs with parent involvement, a group CBT directed solely at the adolescents with no parent involvement does not appear effective for treating ADHD. Trial registration: NCT02937142, 18/10/2016.
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An electroencephalography connectome predictive model of major depressive disorder severity
(2022-12) Kabbara, Aya; Robert, Gabriel; Khalil, Mohamad; Verin, Marc; Benquet, Pascal; Hassan, Mahmoud
Emerging evidence showed that major depressive disorder (MDD) is associated with disruptions of brain structural and functional networks, rather than impairment of isolated brain region. Thus, connectome-based models capable of predicting the depression severity at the individual level can be clinically useful. Here, we applied a machine-learning approach to predict the severity of depression using resting-state networks derived from source-reconstructed Electroencephalography (EEG) signals. Using regression models and three independent EEG datasets (N = 328), we tested whether resting state functional connectivity could predict individual depression score. On the first dataset, results showed that individuals scores could be reasonably predicted (r = 0.6, p = 4 × 10–18) using intrinsic functional connectivity in the EEG alpha band (8–13 Hz). In particular, the brain regions which contributed the most to the predictive network belong to the default mode network. We further tested the predictive potential of the established model by conducting two external validations on (N1 = 53, N2 = 154). Results showed statistically significant correlations between the predicted and the measured depression scale scores (r1 = 0.52, r2 = 0.44, p < 0.001). These findings lay the foundation for developing a generalizable and scientifically interpretable EEG network-based markers that can ultimately support clinicians in a biologically-based characterization of MDD.
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A hybrid numerical/machine learning model development to improve the bimetal performance in the electric circuit breakers
(2022-12) Mallah, Abdul Rahman; Aljuraid, Nawaf; Alawi, Omer A.; Yaseen, Zaher Mundher; Singh, Kamaljeet; Ataki, Adel; Department of Engineering
Bimetals are widely used as a thermal tripping mechanism inside the miniature circuit breakers (MCBs) products when an overload current passes through the circuit for a certain period. Experimental, numerical, and, recently artificial intelligence methods are widely used in designing electric components. However, developing the bimetal for MCB products somewhat differs from developing other conductor items since they are strongly related to the electrical, mechanical, and thermal performance of the MCB. The conventional experimental and numerical approaches are time-consuming processes that cannot be easily utilized in optimizing the product's performance within the development lead time. In this study, a simple, fast, robust, and accurate novel methodology has been introduced to predict the temperature rise of the bimetal and other related performance characteristics. The numerical model has been built on the time-based finite difference method to frame the theoretical thermal model of the bimetal. Then, the numerical model has been consolidated by the machine learning (ML) model to take advantage of the experiments to provide an accurate, fast and reliable model finally. The novel model agrees well with the experimental tests, where the maximum error does not exceed 8%. The model has been used to redesign the bimetal of a 32 A MCB product and significantly reduce the maximum temperature by 24 °C. The novel model is promising since it considerably reduces the required design time, provides accurate predictions, and helps to optimize the performance of the circuit breaker products.
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The dynamic evolution of the Lahendong geothermal system in North-Sulawesi, Indonesia
(2022-11) Suherlina, Lily; Newson, Juliet; Kamah, Yustin; Brehme, Maren
This study uses an integrated approach to characterize the dynamic evolution of the power-producing high-enthalpy geothermal system of Lahendong, North-Sulawesi, Indonesia. Lahendong has two primary reservoirs, the southern and the northern, which have been utilised for electricity production for more than twenty years. The main focus of this study is the characterisation of heat and mass flows in the system with respect to geological structures and permeability distribution. Also, it delineates how the geothermal system has evolved and the spatial variation of the response resulting from prolonged utilization of the reservoirs. This research implemented geological structure analysis on recent surface fault mapping and pre-existing fault studies from literature. Further, the study analysed well data comprising well pressure, enthalpy, drilling program reviews and tracer tests. Hydrochemical investigation compiled new and old surface and subsurface hydrochemical evolution in both the temporal and spatial domain. The results confirm several fault trends in the study area: NE-SW and NW-SE are the major striking directions, while E-W and N-S are less dominant. The most apparent trends are NE-SW striking strike-slip faults, NW-SE thrust faults and N-S and E-W striking normal faults. The faults compartmentalize the reservoir. A comparison of the southern and the northern reservoir shows that the southern one is more controlled by faults; both reservoirs rely on fractures as permeability provider and are controlled by shallow hydrogeology, as derived from the integrated analysis of transient well data. Geochemical analysis shows that the reservoir fluids have generally a higher eelectrical conductivity and are closer to fluid-rock equilibrium, probably due to boiling, compared to spring waters. Spring waters have generally become more acidic, which is an expected result of reservoir boiling and increased steam input to near-surface waters. The spatial distribution of changes shows a permeability evolution over time and also the role of structural permeability in response to changing reservoir conditions. Observing and recording reservoir data is highly important to understand the reservoir response to production and ensure the long-term sustainability of the system. Additionally, the data is critical for making a major difference in the reservoir management strategy.

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