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Do Psychosocial Factors Predict Readmission among Diabetic Elderly Patients?

BACKGROUND: Despite advances in diabetes treatment, the rate of readmission is still relatively high among these patients, especially in older population. Various factors may predict readmission in these patients; hence, the aim of this study was to assess the role of psychosocial factors in predict...

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Autores principales: Alavi, Mousa, Baharlooei, Omeleila, AdelMehraban, Marzieh
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Medknow Publications & Media Pvt Ltd 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5684794/
https://www.ncbi.nlm.nih.gov/pubmed/29184585
http://dx.doi.org/10.4103/ijnmr.IJNMR_138_16
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author Alavi, Mousa
Baharlooei, Omeleila
AdelMehraban, Marzieh
author_facet Alavi, Mousa
Baharlooei, Omeleila
AdelMehraban, Marzieh
author_sort Alavi, Mousa
collection PubMed
description BACKGROUND: Despite advances in diabetes treatment, the rate of readmission is still relatively high among these patients, especially in older population. Various factors may predict readmission in these patients; hence, the aim of this study was to assess the role of psychosocial factors in predicting readmission among diabetic elderly hospitalized in selected hospitals of Isfahan. MATERIALS AND METHODS: In this cross-sectional study conducted from January to September 2016, 150 diabetic elderly hospitalized in selected hospitals affiliated with Isfahan University of medical sciences were chosen using a convenient sampling method. The initial information was collected by a three-part questionnaire consisting of (a) demographic characteristics, (b) 21-item depression, anxiety, and stress scale (DASS-21), and (c) multidimensional scale of perceived social support (MSPSS). Further information about readmission was gathered 3 months after completing the questionnaires through a phone call follow-up. Descriptive and inferential statistics (discriminant function analysis test) were used to analyze the data. RESULTS: During 3 months after discharge, 44% of hospitalized diabetic elderly were readmitted. Analytical model predicted the readmission status of 109 individuals (of total 150 persons) in the studied units (success rate of 72.2%). Among predicting factors, depression and social support had the most and the least important roles in predicting readmission rate, respectively. CONCLUSIONS: Interventions to improve mental status (i.e., decreasing levels of depression, anxiety, and stress) and develop social support are suggested to reduce the risk of readmission among diabetic elderly patients. Nevertheless, future studies are needed to verify the value of such interventions.
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spelling pubmed-56847942017-11-28 Do Psychosocial Factors Predict Readmission among Diabetic Elderly Patients? Alavi, Mousa Baharlooei, Omeleila AdelMehraban, Marzieh Iran J Nurs Midwifery Res Original Article BACKGROUND: Despite advances in diabetes treatment, the rate of readmission is still relatively high among these patients, especially in older population. Various factors may predict readmission in these patients; hence, the aim of this study was to assess the role of psychosocial factors in predicting readmission among diabetic elderly hospitalized in selected hospitals of Isfahan. MATERIALS AND METHODS: In this cross-sectional study conducted from January to September 2016, 150 diabetic elderly hospitalized in selected hospitals affiliated with Isfahan University of medical sciences were chosen using a convenient sampling method. The initial information was collected by a three-part questionnaire consisting of (a) demographic characteristics, (b) 21-item depression, anxiety, and stress scale (DASS-21), and (c) multidimensional scale of perceived social support (MSPSS). Further information about readmission was gathered 3 months after completing the questionnaires through a phone call follow-up. Descriptive and inferential statistics (discriminant function analysis test) were used to analyze the data. RESULTS: During 3 months after discharge, 44% of hospitalized diabetic elderly were readmitted. Analytical model predicted the readmission status of 109 individuals (of total 150 persons) in the studied units (success rate of 72.2%). Among predicting factors, depression and social support had the most and the least important roles in predicting readmission rate, respectively. CONCLUSIONS: Interventions to improve mental status (i.e., decreasing levels of depression, anxiety, and stress) and develop social support are suggested to reduce the risk of readmission among diabetic elderly patients. Nevertheless, future studies are needed to verify the value of such interventions. Medknow Publications & Media Pvt Ltd 2017 /pmc/articles/PMC5684794/ /pubmed/29184585 http://dx.doi.org/10.4103/ijnmr.IJNMR_138_16 Text en Copyright: © 2017 Iranian Journal of Nursing and Midwifery Research http://creativecommons.org/licenses/by-nc-sa/3.0 This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as the author is credited and the new creations are licensed under the identical terms.
spellingShingle Original Article
Alavi, Mousa
Baharlooei, Omeleila
AdelMehraban, Marzieh
Do Psychosocial Factors Predict Readmission among Diabetic Elderly Patients?
title Do Psychosocial Factors Predict Readmission among Diabetic Elderly Patients?
title_full Do Psychosocial Factors Predict Readmission among Diabetic Elderly Patients?
title_fullStr Do Psychosocial Factors Predict Readmission among Diabetic Elderly Patients?
title_full_unstemmed Do Psychosocial Factors Predict Readmission among Diabetic Elderly Patients?
title_short Do Psychosocial Factors Predict Readmission among Diabetic Elderly Patients?
title_sort do psychosocial factors predict readmission among diabetic elderly patients?
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5684794/
https://www.ncbi.nlm.nih.gov/pubmed/29184585
http://dx.doi.org/10.4103/ijnmr.IJNMR_138_16
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