Predictors of Nursing Home Admission: A Social Work Perspective

Abstract

Institutionalisation of geriatric patients is a growing trend in ageing societies, such as Singapore. Earlier studies focused on the sociodemographic profile and attributes of nursing home residents and applications, but neglected to address the predictors of nursing home admission from a social work perspective. The present retrospective study identifies independent risk factors that predispose a patient to a nursing home discharge from a general rehabilitation ward in a community hospital in Singapore, with a multidisciplinary emphasis on clinical intervention. Factor analysis results reinforced findings that functional impairment and dementia are consistent predictors of nursing home admission. Multivariate logistic regression analysis showed that positive predictors of nursing home admission include older age, length of hospital stay, low socioeconomic status, dementia, and functional disability. Social work interventions include early referrals to the medical social worker, so that options for social and family support can be explored prior to deciding to place patients in a nursing home. Other interventions include suitable family therapy and counselling for patients and their families.     

Stress demands on school administrators in Singapore

Abstract

This study investigated the use of the Occupational Stress Indicator (OSI) on school administrators in Singapore. The sample of 223 school administrators consisted of the top management group of principals and vice-principals and the middle management group of heads of department. The school administrators reported pressure at work, and consequently, higher levels of mental and physical ill health. They had high locus of control scores, indicating low internal control over their environment. However, they also reported greater use of coping strategies and higher job satisfaction. Psychometrically, the sub-scales of sources of pressure, job satisfaction, and mental and physical ill health were found to be reliable. The items of the scales of type A, locus of control and coping skills had to be re-factor analysed for the Singaporean sample. The new factors were found to have higher reliability. When the stress and job satisfaction levels of the principals/vice-principals and heads of department were compared, the heads of department reported significantly less job satisfaction and higher levels of mental and physical ill health. They perceived less internal control in their work situation.     

Protection of Rights of Adopted Children in Relation to Duties of Adoptive Parents Under the Law in Malaysia

The relationship between parents and children can be established either through “blood,” marriage, or adoption. This relationship gives rise to certain rights and obligations. This article seeks to examine the protection of those rights of adopted children under the law in Malaysia and to evaluate the extent to which the law protects the rights of adopted children. This article will also examine whether the law in Malaysia imposes certain duties on the adoptive parents in fulfilling such rights.     

Positive-definite modification of a covariance matrix by minimizing the matrix $$\ell_{\infty}$$ ℓ ∞ norm with applications to portfolio optimization

AStA Advances in Statistical Analysis - The covariance matrix, which should be estimated from the data, plays an important role in many multivariate procedures, and its positive definiteness...     

Grocery Perishables Management

In this article, we study the joint pricing and inventory control problem for perishables when a retailer does not sell new and old inventory at the same time. At the beginning of a period, the retailer makes replenishment and pricing decisions, and at the end of a period, the retailer decides whether to dispose of ending inventory or carry it forward to the next period. The objective of the retailer is to maximize the long‐run average profit. Assuming zero lead time, we propose an efficient solution approach to the problem, which is also generalized to solve three extensions to the basic model. A feature of the present study is that we consider explicitly the influence of perishability on the demand. Among the insights gathered from the numerical analysis, we find that dynamic pricing aids extending shelf life and when disposal incurs a lower cost, or even a positive salvage value, the retailer is induced to dispose earlier since the benefit of selling new inventory offsets the loss due to disposal. We also observe that the faster the perceived rate of deterioration, the lower the threshold of the ending inventory for disposal. Perhaps a bit counter‐intuitive, maximizing profits does not mean eliminating disposals or expirations.     

Comparisons of computational methods for clustered binary data

Clustered binary data are common in medical research and can be fitted to the logistic regression model with random effects which belongs to a wider class of models called the generalized linear mixed model. The likelihood-based estimation of model parameters often has to handle intractable integration which leads to several estimation methods to overcome such difficulty. The penalized quasi-likelihood (PQL) method is the one that is very popular and computationally efficient in most cases. The expectation–maximization (EM) algorithm allows to estimate maximum-likelihood estimates, but requires to compute possibly intractable integration in the E-step. The variants of the EM algorithm to evaluate the E-step are introduced. The Monte Carlo EM (MCEM) method computes the E-step by approximating the expectation using Monte Carlo samples, while the Modified EM (MEM) method computes the E-step by approximating the expectation using the Laplace's method. All these methods involve several steps of approximation so that corresponding estimates of model parameters contain inevitable errors (large or small) induced by approximation. Understanding and quantifying discrepancy theoretically is difficult due to the complexity of approximations in each method, even though the focus is on clustered binary data. As an alternative competing computational method, we consider a non-parametric maximum-likelihood (NPML) method as well. We review and compare the PQL, MCEM, MEM and NPML methods for clustered binary data via simulation study, which will be useful for researchers when choosing an estimation method for their analysis.     

A Numerical Study of PQL Estimation Biases in Generalized Linear Mixed Models Under Heterogeneity of Random Effects

The penalized quasi-likelihood (PQL) approach is the most common estimation procedure for the generalized linear mixed model (GLMM). However, it has been noticed that the PQL tends to underestimate variance components as well as regression coefficients in the previous literature. In this article, we numerically show that the biases of variance component estimates by PQL are systematically related to the biases of regression coefficient estimates by PQL, and also show that the biases of variance component estimates by PQL increase as random effects become more heterogeneous.