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Use of physical restraint: Nurses' knowledge, attitude, intention and practice and influencing factors

Eskandari F, Abdullah KL, Zainal NZ, Wong LP

J Clin Nurs, 2017 Dec;26(23-24):4479-4488.
PMID: 28233363 DOI: 10.1111/jocn.13778

AIMS AND OBJECTIVES: To investigate the knowledge, attitude, intention and practice of nurses towards physical restraint and factors influencing these variables.
BACKGROUND: A literature review showed a lack of studies focused on the intention of nurses regarding physical restraint throughout the world. Considering that very little research on physical restraint use has been carried out in Malaysia, assessment of nurses' knowledge, attitude, intention and practice is necessary before developing a minimising programme in hospitals.
DESIGN: A cross-sectional study was used.
METHODS: A questionnaire to assess the knowledge, attitude, intention and practice was completed by all nurses (n = 309) in twelve wards of a teaching hospital in Kuala Lumpur.
RESULTS: Moderate knowledge and attitude with strong intention to use physical restraint were found among the nurses. Less than half of nurses considered alternatives to physical restraint and most of them did not understand the reasons for the physical restraint. Nurses' academic qualification, read any information source during past year and nurses' work unit showed a significant association with nurses' knowledge. Multiple linear regression analysis found knowledge, attitude and intention were significantly associated with nurses' practice to use physical restraint.
CONCLUSION: This study showed some important misunderstandings of nurses about using physical restraint and strong intention regarding using physical restraint. Findings of this study serve as a supporting reason for importance of educating nurses about the use of physical restraint.
RELEVANCE TO CLINICAL PRACTICE: Exploring the knowledge, attitude, intention and current practice of nurses towards physical restraint is important so that an effective strategy can be formulated to minimise the use of physical restraints in hospitals.
The effect of educational intervention on nurses' knowledge, attitude, intention, practice and incidence rate of physical restraint use

Eskandari F, Abdullah KL, Zainal NZ, Wong LP

Nurse Educ Pract, 2018 Sep;32:52-57.
PMID: 30029085 DOI: 10.1016/j.nepr.2018.07.007

The use of physical restraint exposes patients and staff to negative effects, including death. Therefore, teaching nursing staff to develop the improve knowledge, skills, and attitudes regarding physical restraint has become necessary. A quasi-experimental pre-post design was used to evaluate the effect of educational intervention on nurses' knowledge, attitude, intention, practice and incidence rate of physical restraint in 12 wards of a hospital using a self-reported questionnaire and a restraint order form in Malaysia. The educational intervention, which included a one-day session on minimising physical restraint use in hospital, was presented to 245 nurses. The results showed a significant increase in the mean knowledge, attitude sand practice score and a significant decrease in the mean intention score of nurses to use physical restraint after intervention. There was a statistically significant decrease in the incidence rate of physical restraint use in the wards of the hospital except geriatric-rehabilitation wards after intervention.
Incidence Rate and Patterns of Physical Restraint Use Among Adult Patients in Malaysia

Eskandari F, Abdullah KL, Zainal NZ, Wong LP

Clin Nurs Res, 2018 03;27(3):278-295.
PMID: 27856788 DOI: 10.1177/1054773816677807

Incidence rate and patterns of physical restraint use were examined based on a cross-sectional study in 22 wards of a large teaching hospital in Malaysia. Results indicated that the highest rate of physical restraint (19.7%) was reported from neurology-neurosurgery wards. "Un-cooperative for electroconvulsive therapy" and "trying to pull out catheters" were the most commonly reported reasons to use restraint in psychiatric and non-psychiatric wards, respectively. There were some relationships between patterns of physical restraint in this study. Exploring the incidence rate and patterns of physical restraint is important so that effective strategies can be formulated to minimize using restraint in hospitals.
Fulltext Short-term Gini coefficient estimation using nonlinear autoregressive multilayer perceptron model

Amin Megat Ali MS, Zabidi A, Md Tahir N, Mohd Yassin I, Eskandari F, Saadon A, et al.

Heliyon, 2024 Feb 29;10(4):e26438.
PMID: 38420485 DOI: 10.1016/j.heliyon.2024.e26438

Poverty, an intricate global challenge influenced by economic, political, and social elements, is characterized by a deficiency in crucial resources, necessitating collective efforts towards its mitigation as embodied in the United Nations' Sustainable Development Goals. The Gini coefficient is a statistical instrument used by nations to measure income inequality, economic status, and social disparity, as escalated income inequality often parallels high poverty rates. Despite its standard annual computation, impeded by logistical hurdles and the gradual transformation of income inequality, we suggest that short-term forecasting of the Gini coefficient could offer instantaneous comprehension of shifts in income inequality during swift transitions, such as variances due to seasonal employment patterns in the expanding gig economy. System Identification (SI), a methodology utilized in domains like engineering and mathematical modeling to construct or refine dynamic system models from captured data, relies significantly on the Nonlinear Auto-Regressive (NAR) model due to its reliability and capability of integrating nonlinear functions, complemented by contemporary machine learning strategies and computational algorithms to approximate complex system dynamics to address these limitations. In this study, we introduce a NAR Multi-Layer Perceptron (MLP) approach for brief term estimation of the Gini coefficient. Several parameters were tested to discover the optimal model for Malaysia's Gini coefficient within 1987-2015, namely the output lag space, hidden units, and initial random seeds. The One-Step-Ahead (OSA), residual correlation, and residual histograms were used to test the validity of the model. The results demonstrate the model's efficacy over a 28-year period with superior model fit (MSE: 1.14 × 10-7) and uncorrelated residuals, thereby substantiating the model's validity and usefulness for predicting short-term variations in much smaller time steps compared to traditional manual approaches.