Creating A child-friendly social environment for fewer conduct problems and more prosocial behaviors among children: A LASSO regression approach

Chu, Meijie; Fang, Zhiwei; Mao, Li; Ma, Honghao; Lee, Chun-Yang; Chiang, Yi-Chen

doi:10.1016/j.actpsy.2024.104200

Cited by 4 publications

(1 citation statement)

References 127 publications

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“…First and foremost, LASSO and Elastic Net are arguably the most popular modern variable selection techniques within the behavioral sciences. Social psychology researchers have used such techniques to create better environments that promote prosocial environments for children [28] and health researchers have used them to model the progression of Alzheimer's disease [29] . Implementations of SVM and random forest were chosen because of their strength as classification algorithms and because they can handle more complex data types (e.g., mixed variable types or non-linearly separable).…”

Section: Variable Selection In Machine Learningmentioning

confidence: 99%

A Tutorial on Supervised Machine Learning Variable Selection Methods for the Social and Health Sciences in R

Bain,

Shi,

Ethridge

et al. 2024

Preprint

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With recent increases in the size of datasets currently available in the behavioral and health sciences, the need for efficient and effective variable selection techniques has increased. A plethora of techniques exist, yet only a few are used within the psychological sciences (e.g., stepwise regression, which is most common, the LASSO, and Elastic Net). The purpose of this tutorial is to increase awareness of the various variable selection methods available in the popular statistical software R, and guide researchers through how each method can be used to select variables in the context of classification using a recent survey-based assessment of misophonia. Specifically, readers will learn about how to implement and interpret results from the LASSO, Elastic Net, a penalized SVM classifier, an implementation of random forest, and the genetic algorithm. The associated code and data implemented in this tutorial are available on OSF to allow for a more interactive experience. This paper is written with the assumption that individuals have at least a basic understanding of R.

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Section: Variable Selection In Machine Learningmentioning

confidence: 99%

A Tutorial on Supervised Machine Learning Variable Selection Methods for the Social and Health Sciences in R

Bain,

Shi,

Ethridge

et al. 2024

Preprint

View full text Add to dashboard Cite

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Establishing a Halal Ecosystem to Eradicate Moral Degradation in Indonesian Education

Muhammad Umar Bahusin,

Sakinah Izzati Nurrizqi,

Ashifuddin Fikri

et al. 2024

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Moral degradation refers to a decline in a person's adherence to the social norms and ethical standards of society. This decline can be influenced by various factors, such as a child's environment and exposure to social media, which can lead to changes in behavior. As a result, this can disrupt the social order and contribute to feelings of social insecurity. In response to this issue, a research study was conducted to develop a "halal ecosystem" aimed at addressing moral degradation. The research employed qualitative exploratory methods, including in-depth interviews with teachers, students, child psychologists, and representatives of the Indonesian Child Protection Commission (KPAI) in Yogyakarta. The data collected was then analyzed through several stages, including data reduction, content analysis, validation, and drawing conclusions. The outcome of the research is the development of a system called Vedha Paho or Moral Science based on the Theory of Planned Behavior. This system comprises various elements designed to establish a halal ecosystem and create an optimal moral environment for child development.

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Social Skills of Elementary School Students in Bandung-West Java

Irfan Fauzi,

Ahman,

Syamsu Yusuf

et al. 2024

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The article aimed to identify the social skills aspects of elementary school students in Bandung. The research method used a survey using the social skills improvement system instrument that developed by Gresham & Elliott (2008). This research was conducted on students in grades 4, 5, and 6 in Bandung, West Java with a total of 343 students. The data collection technique used a survey, and the analysis used descriptive statistics by calculating the percentage of each aspect of social skills. Then it categorized the percentage based on criteria, namely very high, high, low and very low. The results of this research showed that the social skills achievements of elementary school students in Bandung were in the high category with an average percentage of 78.15%. The aspect of social skills that has the highest achievement was responsibility, the very high category with an average percentage of 84.06%, and the aspect of social skills that has the lowest achievement was self-control, the high category with an average percentage of 69.68%. This research contributed of education in understanding various aspects of social development, especially on the social skills of elementary school students. This research was the basis for the development of programs or interventions to improve social skills through various activities relevant to elementary school students.

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Creating A child-friendly social environment for fewer conduct problems and more prosocial behaviors among children: A LASSO regression approach

Cited by 4 publications

References 127 publications

A Tutorial on Supervised Machine Learning Variable Selection Methods for the Social and Health Sciences in R

A Tutorial on Supervised Machine Learning Variable Selection Methods for the Social and Health Sciences in R

Establishing a Halal Ecosystem to Eradicate Moral Degradation in Indonesian Education

Social Skills of Elementary School Students in Bandung-West Java

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