Nurses' perception of knowledge, attitudes and reported practice towards patients with eating disorders: A concurrent mixed-methods study.

Eating disorders are complex disorders requiring specialised care, thus knowledge and attitudes are crucial for management. This study aims to examine nurses' knowledge, attitudes, reported practice, and perceptions towards patients with eating disorders in Singapore. A concurrent mixed-methods study was carried out in Southeast Asia's only psychiatric unit with eating disorders programme. Twenty nurses were recruited using census sampling. Quantitative data were analysed with descriptive and inferential statistics, while qualitative data were analysed with content and thematic analysis. Certain personal factors were associated with nurses' levels of perceived knowledge. Different attitudes towards managing these patients were identified during interview sessions.

Knowledge, Attitudes and Challenges of Healthcare Professionals Managing People With Eating Disorders: A Literature Review.

This review consolidates findings regarding knowledge and attitudes of healthcare professionals, together with challenges faced while caring for patients with eating disorders. A rigorous and systematic approach was taken to identify 21 articles, which include 12 quantitative, 7 qualitative, and 2 mixed-method papers. Healthcare professionals' knowledge and attitudes toward patients with eating disorders will be discussed, while identifying if factors like age, gender, work experience or profession have an impact on these two variables. Challenges faced during care provision will also be examined. Methodological limitations and knowledge gaps from these articles will be discussed, together with implications of this review.

Different perceptions of stress, coping styles, and general well-being among pregnant Chinese women: a structural equation modeling approach.

Few studies have examined different perceptions of stress or explored the positive aspects of well-being among pregnant Chinese women, so there is a need to explore these phenomena in order to fill the research gap. The aim of this study was to examine the relationships among the different perceptions of stress, coping styles, and general well-being using a structural equation modeling approach. We examined a hypothetical model among 755 pregnant Chinese women based on the integration of theoretical models. The Perceived Stress Scale (PSS), the Trait Coping Styles Questionnaire (TCSQ), and the General Well-Being Schedule (GWB) were used to measure perceived stress, coping styles, and general well-being, respectively. A structural equation model showed that positive and negative perceptions of stress significantly influenced positive and negative coping styles, respectively. Different perceptions of stress were significantly associated with general well-being, but different coping styles had no significant effects on general well-being. The model had a good fit to the data (IFI = 0.910, TLI = 0.904, CFI = 0.910, and RMSEA = 0.038). Different perception of stress was able to predict significant differences in coping styles and general well-being.

A comparison of imputation techniques for handling missing data.

Researchers are commonly faced with the problem of missing data. This article presents theoretical and empirical information for the selection and application of approaches for handling missing data on a single variable. An actual data set of 492 cases with no missing values was used to create a simulated yet realistic data set with missing at random (MAR) data. The authors compare and contrast five approaches (listwise deletion, mean substitution, simple regression, regression with an error term, and the expectation maximization [EM] algorithm) for dealing with missing data, and compare the effects of each method on descriptive statistics and correlation coefficients for the imputed data (n = 96) and the entire sample (n = 492) when imputed data are inculded. All methods had limitations, although our findings suggest that mean substitution was the least effective and that regression with an error term and the EM algorithm produced estimates closest to those of the original variables.