A PHP Error was encountered

Severity: Warning

Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests

Filename: helpers/my_audit_helper.php

Line Number: 176

Backtrace:

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3122
Function: getPubMedXML

File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global

File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword

File: /var/www/html/index.php
Line: 316
Function: require_once

Factors influencing why nursing care is missed. | LitMetric

Aims And Objectives: This study explores the reasons nurses identify missed care and what factors account for this variance in nursing practice. Second, the study seeks to understand if the identified reasons behind missed care interact with one another and form a multidimensional construct.

Background: This study draws on the results of previous research conducted by Kalisch in developing the MISSCARE research survey tool and now applies it to an Australian context.

Design: This study engages a nonexperimental exploratory approach where 16 latent variables are identified and estimated using structural equation modelling to determine the capacity each of these factors has in predicting the reasons for reported missed nursing care.

Methods: Data were obtained from an electronic survey sent to nursing members of the Australian Nursing and Midwifery Federation of South Australia. A self-report, Likert-type instrument was used to capture the strength and direction of consensus derived from a sample of 289 nurses and midwives.

Results/findings: Eight variables were identified as having direct predictor effects as to why nursing care was being missed, and included shift type, nursing resource allocation, health professional communication, workload intensity, workload predictability, the nurses' satisfaction with their current job and their intention to remain working. Additional indirect effects of other variables explained 34% of the variance of the total scores for why nursing care was reported as being missed.

Conclusion: Historically, the MISSCARE survey has identified and quantified what types of nursing care is missed. This paper takes this concept further by producing an interactional model identifying the effects different variables have on why nursing care is missed.

Relevance To Clinical Practice: These Australian findings not only contribute to other international studies that identify why nursing care is omitted, it provides a framework for why reported episodes of missed care can be predicted and subsequently addressed.

Download full-text PDF

Source
http://dx.doi.org/10.1111/jocn.12688DOI Listing

Publication Analysis

Top Keywords

nursing care
24
care missed
12
missed care
12
nursing
11
care
9
misscare survey
8
variables identified
8
effects variables
8
missed
7
factors influencing
4

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!