State-Federal Vocational Rehabilitation Services, Demographic Characteristics and Employment Outcomes for Native Americans with Mental Illnesses

There were 9.7 million Native Americans (American Indian, Alaska Native-AI/AN- these acronyms will be used interchangeably with Native Americans throughout the paper) in 2019 comprising 2.9% of the U.S. population. Native American populations have disproportionately higher rates of mental illnesses compared to other racial groups in the U.S. Mental health is a significant public health concern for this population, impacting different areas of their lives including employment. Additionally, Native Americans continue to experience significant disparities in access to Vocational Rehabilitation (VR) services and have poor employment outcomes. However, little is known about the relationships among demographic factors, vocational rehabilitation services, and employment outcomes of Native Americans with mental illness. Consequently, the current study examined how demographic factors and VR services are related to successful employment outcomes for Native American VR clients with mental illnesses using data from the Rehabilitation Services Administration (RSA) program year (2019) Case Service Report (9-11). Both descriptive analysis and data mining approaches were used to answer the research questions. Chi-square Automatic Interaction Detector (CHAID) analysis was used to determine which of the VR services could best predict the successful employment outcome of Native Americans with mental illness. The findings of the data mining approach revealed that among all the vocational rehabilitation services, job placement assistance was the strongest predictor of successful employment among Native American clients with mental illnesses. The second most important service predicting successful employment for those who received job placement assistance was shown to be maintenance. Implications for rehabilitation counselors and future research are discussed.

Social network analysis: Understanding nurses' advice-seeking interactions

AIM

This study aimed to determine advice-seeking interactions of nurses in a private hospital by using social network analysis.

DESIGN

This study was designed as a cross-sectional descriptive study.

METHODS

The study was conducted in a private hospital with 70 nurses. The data were collected with a social network analysis questionnaire. The social network analysis (SNA) focused on certain values such as network density, component, degree centrality, and betweenness centrality. The SNA was carried out using UCINET, and statistical analyses were performed with SPSS version 23.0.

RESULTS

The network density was reported to be 0.062, and it was composed of three components. It was further noted that nurse Y1 was found to have the highest scores of degree and betweenness centrality. Chi-Square Automatic Interaction Detector (CHAID) analysis indicated that the most common variables that affected degree centrality score were education, department, and position.

CONCLUSION

It was concluded that social network analysis was a useful instrument to delineate strengths and weaknesses of seeking advice relationships among nurses.

IMPLICATIONS FOR NURSING AND HEALTH POLICY

Top- and middle-level nursing managers occupy a significant position in advice-seeking networks. Nursing managers with higher education degrees will absolutely improve advice-seeking networks.

Preschool teachers display a flexible pattern of pedagogical actions in promoting healthy habits in children

The school represents the optimal setting for promoting the physical, emotional, and social health of children, especially during the first years of life. Understanding the pedagogical actions of teachers to address health education is an important first step in promoting healthy behaviors in children. We inhere analyzed the pedagogical action patterns in the preschool teaching of healthy habits from a holistic health perspective. We used photography as a strategy for data collection and applied a Chi-square automatic interaction detection (CHAID) classification tree, a data mining procedure, to generate a pattern model. We found that the school space and the learning playfulness strategies for the development of executive functions, classified according to the exercise, symbolic, assembly, rules (ESAR) model, were the main factors that influence the pedagogical actions fostering healthy habits. By contrast, the school and the pedagogical resources of the classroom are factors with a much smaller impact on working with healthy habits. This pedagogical action pattern is flexible, since teachers conduct a multiplicity of pedagogical actions through different strategies, in different school spaces, at any time. In conclusion, our results unmask the interdependent relationships between the different factors that determine the teacher's actions at the preschool. It also contributes to the understanding of the teacher's practices in fostering healthy habits in a healthy learning environment.

Factors relating to childbirth self efficacy among pregnant women: a CHAID analysis

Childbirth self-efficacy is a useful measure for determining a woman's confidence in managing childbirth and for determining any preconceptions that require reinforcement. Childbirth self-efficacy is also particularly helpful in advising not only how to cope with birth, but also maternal well-being and fostering the improvement of a wide variety of perinatal outcomes. The present study aims to determine the factors affecting childbirth self-efficacy in pregnant women. The sample size consisted of 380 pregnant women between the ages of 18 and 45. Data were collected via face to face interviews using the Childbirth Self Efficacy Scale Short Form (CBSEI-32) in the Akdeniz University Hospital between November 2019 and February 2020 and used Chi-squared Automatic Interaction Detector analyses, resulting in a mean CBSEI-32 score of 244.279 ± 45.121. As a result of the analysis, it was seen that income status affects self-efficacy, and personal experiences such as foetal loss affect a woman's childbirth self-efficacy. In addition, it was also found that the level of prenatal education affected childbirth self-efficacy. Health professionals should assess pregnant women during the antenatal period in terms of their childbirth self efficacy and prepare personalised training programs and plan initiatives to increase perceptions of self-efficacy.IMPACT STATEMENTWhat is already known on this subject? Childbirth self-efficacy is one of the important psychological parameters to determine a woman's belief in her confidence in managing childbirth and to measure women's perceptions of her need for reinforcement.What do the results of this study add? Sociodemographic and obstetric characteristics of women affect their childbirth self-efficacy perception positively and negatively. Women's birth self-efficacy can be improved positively with prenatal education. In addition, it is one of the interesting findings of the study that the self-efficacy level of women who had a previous low experience was high.What are the implications of these findings for clinical practice and/or further research? Women's childbirth self efficacy can be improved with trainings and appropriate nursing interventions. For this reason, it is important to determine the factors affecting the self-efficacy perception of women. In future studies, the childbirth self-efficacy perceptions of women in different samples (risky pregnancy, disabled pregnant, etc.) should be measured.

Prevalence of obesity and hypertension in children and determination of associated factors by CHAID analysis

BACKGROUND

The prevalence of obesity and hypertension in children is associated with an increased risk of cardiovascular disease and increases the prevalence of heart failure and associated morbidity and mortality. This study aimed to determine the prevalence of obesity and hypertension, as well as the associated risk factors, in school-age children.

METHODS

This cross-sectional study was conducted in 21 schools in Antalya, Turkey. A total of 5160 students between the ages of 5 and 15 years participated in the study. The data were collected using a questionnaire, and students' height, weight, and blood pressure were measured. The data were evaluated using numbers, percentages, mean, and chi-squared automatic interaction detector (CHAID) analysis.

RESULTS

In all, 11.4% of children were overweight, 11.8% were obese, 6.8% had prehypertension, and 5.7% had hypertension. School level, school location, and father's educational status were determined as factors associated with overweight and obesity; BMI, school level, school location, and mother's working status were determined as factors related to hypertension in the children.

CONCLUSION

The prevalence of hypertension, overweight, and obesity was found to be significantly high in the children, especially those living in rural areas. Therefore, it is recommended that these health issues be monitored in children and that necessary measures be taken by considering regional differences.

[CHANGING THE FUNCTIONALITY: HOW DO MEDICAL PROFESSIONALS PERCEIVE INNOVATIONS?]

The article is devoted to the study of the issue of changing the functionality of nurses, analyzing the opinions of nurses and doctors themselves on the implementation of such an innovation, assessing the benefits and consequences associated with expanding the functions and increasing the role of nurses in the medical community. The research is based on CHAID-analysis of data from a questionnaire survey conducted in 2020, which revealed the respondents' attitude to the idea of improving the status of nurses and expanding their functions, expectations of the possible reaction of the medical community and patients to this innovation, and the development of so-called «trees» of classifications for various variables. The collected and systematized data on changes in the functionality of nurses can serve as a starting point for the possible expansion of the functions and powers of nurses in the metropolitan health care, as well as increasing the role and status of nurses in the professional environment. The results of the Moscow study presented in the article confirm the conclusions of other scientists and practitioners from the Russian regions, in which a pilot project has already been implemented to change the functionality of nurses.

A hierarchy of correlates impacting adults' sensor-based physical activity and sedentary time

Investigation into correlates across all levels of the socio-ecological model predictive of objectively measured physical activity has rarely been assessed in adults. While considering a diversity of correlates, we determined which correlates best predict sensor-based moderate-to-vigorous physical activity (MVPA) and sedentary-time (ST) in adults. A Chi-squared Automatic Interaction Detection algorithm was used to hierarchize the correlates associated with high ST (≥66.6^thpercentile) and sufficient MVPA (≥150 min/week) in 865 adults. The main correlate predictive of being active was currently partaking in sport/exercise. The following relevant correlates were being male for the exercisers and having trees in the neighbourhood for the non-exercisers. The final correlate to boost male exercisers' MVPA was having lots of shops in the neighbourhood and not having television in the bedroom for women. The primary correlate for high ST was job activity level, with individuals having highly active jobs being less likely to exhibit high levels of ST; being single, male, and a former athlete also increased the chances of being highly sedentary. To increase adults' MVPA, promotion of sport participation, neighbourhood landscape planning, shop availability, as well as limiting television in the bedroom must be prioritized. For counteracting ST, increasing workplace activity level is warranted.

Employment predictors and outcomes of U.S. state-federal vocational rehabilitation consumers with affective disorders: A CHAID analysis

BACKGROUND

This study examined the demographic and rehabilitation service variables affecting employment outcomes of people with affective disorders receiving services from U.S. state-federal vocational rehabilitation (VR) agencies.

METHODS

An ex post facto design, using data mining as a statistical analysis strategy, was used to analyze the Rehabilitation Services Administration Case Service Report (RSA-911) for the fiscal year 2011. The sample included 44,960 customers with affective disorders who were closed either as successfully employed (Status 26) or not employed (Status 28) by their VR agency. The dependent variable is employment outcome. The predictor variables include a set of personal characteristic variables and rehabilitation service variables.

RESULTS

The chi-squared automatic interaction detector (CHAID) data mining analysis results indicated that job placement services, on-the-job supports, and job search assistance services were significant predictors of successful employment outcomes for individuals with affective disorders.

LIMITATIONS

The study used data from the RSA-911 database. Causality cannot be inferred due to the use of archival data.

CONCLUSIONS

Employment should be viewed as a viable treatment outcome for individuals with affective disorders. Rehabilitation professionals should advocate for their clients to receive VR services, including job placement services, on-the-job supports, and job search assistance services in order to maximize their employment and mental health outcomes.

The Development and Validation of an Actuarial Risk Assessment Tool for the Prediction of First-Time Offending

For prevention purposes, it is important that police officers can estimate the risk for delinquency among juveniles who were involved in a criminal offense, but not in the role of a suspect. In the present study, the Youth Actuarial Risk Assessment Tool for First-Time Offending (Y-ARAT-FO) was developed based solely on police records with the aim to enable Dutch police officers to predict the risk for first-time offending. For the construction of this initial screening instrument, an Exhaustive Chi-squared Automatic Interaction Detector (Exhaustive CHAID) analysis was performed on a data set that was retrieved from the Dutch police system. The Y-ARAT-FO was developed on a sample of 1,368 juveniles and validated on a different sample of 886 juveniles showing moderate predictive accuracy in the validation sample (area under the receiver operating characteristic curve [AUC] = .728). The predictive accuracy of the Y-ARAT-FO was considered sufficient to justify its use as an initial screening instrument by the Dutch police.