Family Theory Framework and Case Analysis using AI Tools

In this assignment, students will utilize AI tools, like ChatGPT, to analyze a case study in social work practice and generate recommendations for intervention strategies and treatment plans based on a selected family theory and framework. Students will critically evaluate the responses provided by ChatGPT, considering its strengths and limitations in addressing the client\u27s needs. This assignment aims to comprehend the knowledge of family theory and framework, and enhance students\u27 critical thinking skills, ethical decision-making, and understanding of the role of AI in social work practic

Psychosocial Determinants of Insomnia in Adolescents: Roles of Mental Health, Behavioral Health, and Social Environment

The theoretical explanation of human problems is derived from the complex interplay of psychological, social, economic, political, and physical factors. Aims: This study examined the roles of behavioral health (i.e., alcohol abuse and suicidality) and social environment (i.e., family support, school connectedness, and favorable neighborhood) and mental health [i.e., depression, anxiety, and attention deficit hyperactivity disorder (ADHD)] in predicting insomnia in adolescents in an ecological perspective. Methods: Approximately 6445 high school students in Taiwan were administered an anonymous self-report survey. Hierarchical multiple regression was performed to examine how multidimensional social environment, behavioral health, and mental health factors were associated with insomnia in adolescents. Results: The prevalence rate of insomnia in the sample was 30%. The results indicated that alcohol abuse (β = 0.04), suicidality (β = 0.06), depression (β = 0.29), anxiety (β = 0.14), and ADHD (β = 0.11) were positively associated with insomnia (p \u3c 0.001), whereas family support (β = −0.06), school connectedness (β = −0.05), and favorable neighborhood (β = −0.10) were negatively associated with insomnia (p \u3c 0.001). Sex did not predict insomnia, but age was positively associated with insomnia (β = 0.09, p \u3c 0.001). Among all predictors of insomnia in the study, mental health factors, especially depression, play a major role on insomnia among adolescents, and is as much important as social environment factors. Conclusion: This study demonstrated how both psychosocial variables (social environment and behavioral health) and psychological symptoms were associated with insomnia in adolescents when the demographic variables (sex and age) were controlled and provided valuable information and evidence for clinicians, social workers, and health professionals who provide support to adolescents with insomnia. Applying an ecological approach in practice can aid in understanding at individual, family, school, and community levels and in identifying the strengths and weaknesses of their interactions with each other. Implications: This perspective enables practitioners in effectively treating problems and addressing the needs of the various levels, including the individual, family, school, and the broader community. Thus, prevention and intervention of insomnia in adolescents should focus on multidimensional risk and protective factors, including mental health, behavioral health, and social environment, in the context of an ecological system

Decay Constants of Pseudoscalar DD-mesons in Lattice QCD with Domain-Wall Fermion

We present the first study of the masses and decay constants of the pseudoscalar $D$ mesons in two flavors lattice QCD with domain-wall fermion. The gauge ensembles are generated on the $24^3 \times 48$ lattice with the extent $N_s = 16$ in the fifth dimension, and the plaquette gauge action at $\beta = 6.10$, for three sea-quark masses with corresponding pion masses in the range $260-475$ MeV. We compute the point-to-point quark propagators, and measure the time-correlation functions of the pseudoscalar and vector mesons. The inverse lattice spacing is determined by the Wilson flow, while the strange and the charm quark masses by the masses of the vector mesons $\phi(1020)$ and $J/\psi(3097)$ respectively. Using heavy meson chiral perturbation theory (HMChPT) to extrapolate to the physical pion mass, we obtain $f_D = 202.3(2.2)(2.6)$ MeV and $f_{D_s} = 258.7(1.1)(2.9)$ MeV.Comment: 15 pages, 3 figures. v2: the statistics of ensemble (A) with m_sea = 0.005 has been increased, more details on the systematic error, to appear in Phys. Lett.

Development and Validation of the Parents\u27 Perceived Self-Efficacy to Manage Children\u27s Internet Use Scale for Parents of Adolescents with Attention-Deficit/Hyperactivity Disorder

Background and aims: This study developed and validated the Parents’ Perceived Self-Efficacy to Manage Children’s Internet Use Scale (PSMIS) in the parents of children with attention-deficit/hyperactivity disorder (ADHD). Methods: In total, 231 parents of children with ADHD were invited to complete the PSMIS, followed by the Chen Internet Addiction Scale and the short version of Swanson, Nolan, and Pelham, Version IV Scale – Chinese version for analyzing Internet addiction severity and ADHD symptoms, respectively. Results: The results of exploratory and confirmatory factor analyses confirmed the four-factor structure of the 18-item PSMIS. The significant difference in the levels of parents’ perceived self-efficacy between the parents of children with and without Internet addiction supported the criterion-related validity of the PSMIS. The internal consistency and 1-month test–retest reliability were acceptable. Conclusion: The results indicate that the PSMIS has acceptable validity and reliability and can be used for measuring parents’ perceived self-efficacy to manage children’s Internet use among parents of children with ADHD

Psychological Pathway from Obesity-Related Stigma to Anxiety via Internalized Stigma and Self-Esteem among Adolescents in Taiwan

The objective of this research was to examine the pathway from public stigma, to perceived stigma, to depression in adolescents via internalized stigma. Adolescents in grade 7 through 9 from a junior high school in Changhua County in Taiwan completed self-administered surveys from March to July in 2018. Adolescents were asked questions regarding depressive symptoms, obesity-related perceived stigma, and internalized stigma. Structural equation modeling was used to fit the pathway model. The pathway was first analyzed with the full sample and then stratified by actual and perceived weight status. Our final analytic sample consisted of 464 adolescents. The pathway model suggested an acceptable model fit. Perceived weight stigma (PWS) was significantly associated with internalized stigma regardless of actual or self-perceived weight status. Internalized stigma was significantly associated with anxiety for both actual (β = 0.186) and self-perceived nonoverweight (non-OW) participants (β = 0.170) but not for overweight (OW) participants (neither actual nor self-perceived). For OW adolescents, perceived weight stigma was associated with anxiety. However, the internalization process did not exist. It may be that the influence of perceived weight stigma is larger than internalized stigma on anxiety. It may also be that the level of internalization was not yet high enough to result in anxiet

Metal-free sp(3) C-H functionalization: a novel approach for the syntheses of selenide ethers and thioesters from methyl arenes

A DTBP-promoted metal-free and solvent-free formation of C-Se and C-S bonds through sp(3) C-H functionalization of methyl arenes with diselenides and disulfides is described

GenEpi: gene-based epistasis discovery using machine learning.

BackgroundGenome-wide association studies (GWAS) provide a powerful means to identify associations between genetic variants and phenotypes. However, GWAS techniques for detecting epistasis, the interactions between genetic variants associated with phenotypes, are still limited. We believe that developing an efficient and effective GWAS method to detect epistasis will be a key for discovering sophisticated pathogenesis, which is especially important for complex diseases such as Alzheimer's disease (AD).ResultsIn this regard, this study presents GenEpi, a computational package to uncover epistasis associated with phenotypes by the proposed machine learning approach. GenEpi identifies both within-gene and cross-gene epistasis through a two-stage modeling workflow. In both stages, GenEpi adopts two-element combinatorial encoding when producing features and constructs the prediction models by L1-regularized regression with stability selection. The simulated data showed that GenEpi outperforms other widely-used methods on detecting the ground-truth epistasis. As real data is concerned, this study uses AD as an example to reveal the capability of GenEpi in finding disease-related variants and variant interactions that show both biological meanings and predictive power.ConclusionsThe results on simulation data and AD demonstrated that GenEpi has the ability to detect the epistasis associated with phenotypes effectively and efficiently. The released package can be generalized to largely facilitate the studies of many complex diseases in the near future

A Flexible-Frame-Rate Vision-Aided Inertial Object Tracking System for Mobile Devices

Real-time object pose estimation and tracking is challenging but essential for emerging augmented reality (AR) applications. In general, state-of-the-art methods address this problem using deep neural networks which indeed yield satisfactory results. Nevertheless, the high computational cost of these methods makes them unsuitable for mobile devices where real-world applications usually take place. In addition, head-mounted displays such as AR glasses require at least 90~FPS to avoid motion sickness, which further complicates the problem. We propose a flexible-frame-rate object pose estimation and tracking system for mobile devices. It is a monocular visual-inertial-based system with a client-server architecture. Inertial measurement unit (IMU) pose propagation is performed on the client side for high speed tracking, and RGB image-based 3D pose estimation is performed on the server side to obtain accurate poses, after which the pose is sent to the client side for visual-inertial fusion, where we propose a bias self-correction mechanism to reduce drift. We also propose a pose inspection algorithm to detect tracking failures and incorrect pose estimation. Connected by high-speed networking, our system supports flexible frame rates up to 120 FPS and guarantees high precision and real-time tracking on low-end devices. Both simulations and real world experiments show that our method achieves accurate and robust object tracking