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运用计划行为理论评估基层医疗医生开具病假条意愿的预测因素。

Assessing predictors of intention to prescribe sick leave among primary care physicians using the theory of planned behaviour.

作者信息

Swarna Nantha Yogarabindranath, Wee Lei Hum, Chan Caryn Mei-Hsien

机构信息

Non-Communicable Disease Clinic, Seremban Primary Care Clinic, Jalan Rasah, 70300, Seremban, Negeri Sembilan, Malaysia.

Faculty of Health Sciences, Universiti Kebangsaan Malaysia, 50586, Kuala Lumpur, Malaysia.

出版信息

BMC Fam Pract. 2018 Jan 16;19(1):18. doi: 10.1186/s12875-017-0690-5.

DOI:10.1186/s12875-017-0690-5
PMID:29338699
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5771020/
Abstract

BACKGROUND

Providing sickness certification is a decision that primary care physicians make on a daily basis. The majority of sickness certification studies in the literature involve a general assessment of physician or patient behaviour without the use of a robust psychological framework to guide research accuracy. To address this deficiency, this study utilized the Theory of Planned Behaviour (TPB) to specifically gauge the intention and other salient predictors related to sickness certification prescribing behaviour amongst primary care physicians.

METHODS

A cross-sectional study was conducted among N = 271 primary care physicians from 86 primary care practices throughout two states in Malaysia. Questionnaires used were specifically developed based on the TPB, consisting of both direct and indirect measures related to the provision of sickness leave. Questionnaire validity was established through factor analysis and the determination of internal consistency between theoretically related constructs. The temporal stability of the indirect measures was determined via the test-retest correlation analysis. Structural equation modelling was conducted to determine the strength of predictors related to intentions.

RESULTS

The mean scores for intention to provide patients with sickness was low. The Cronbach α value for the direct measures was good: overall physician intent to provide sick leave (0.77), physician attitude towards prescribing sick leave for patients (0.77) and physician attitude in trusting the intention of patients seeking sick leave (0.83). The temporal stability of the indirect measures of the questionnaire was satisfactory with significant correlation between constructs separated by an interval of two weeks (p < 0.05). Attitudes and subjective norms were identified as important predictors in physician intention to provide sick leave to patients.

CONCLUSION

An integrated behavioural model utilizing the TPB could help fully explain the complex act of providing sickness leave to patients. Findings from this study could assist relevant agencies to facilitate the creation of policies that may help regulate the provision of sickness leave and alleviate the work burden of sickness leave tasks faced by physicians in Malaysia.

摘要

背景

开具病假证明是基层医疗医生日常工作中要做出的一项决定。文献中大多数关于病假证明的研究都只是对医生或患者行为进行一般性评估,而没有使用强大的心理学框架来指导研究的准确性。为了弥补这一不足,本研究运用计划行为理论(TPB)来具体衡量基层医疗医生开具病假证明行为的意图及其他显著预测因素。

方法

对马来西亚两个州86家基层医疗诊所的271名基层医疗医生进行了横断面研究。所使用的问卷是专门基于TPB编制的,包括与提供病假相关的直接和间接测量方法。通过因子分析和理论相关结构之间内部一致性的测定来确定问卷的有效性。通过重测相关分析来确定间接测量方法的时间稳定性。进行结构方程建模以确定与意图相关的预测因素的强度。

结果

为患者开具病假的意图平均得分较低。直接测量方法的Cronbach α值良好:医生总体开具病假的意图(0.77)、医生对为患者开具病假的态度(0.77)以及医生对患者寻求病假意图的信任态度(0.83)。问卷间接测量方法的时间稳定性令人满意,间隔两周的结构之间存在显著相关性(p < 0.05)。态度和主观规范被确定为医生为患者开具病假意图的重要预测因素。

结论

运用TPB的综合行为模型有助于充分解释为患者提供病假这一复杂行为。本研究结果可协助相关机构制定政策,以规范病假的提供并减轻马来西亚医生面临的病假工作负担。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e0e8/5771020/dbedc8230d56/12875_2017_690_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e0e8/5771020/489d31824ba5/12875_2017_690_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e0e8/5771020/4c838d068b97/12875_2017_690_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e0e8/5771020/dbedc8230d56/12875_2017_690_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e0e8/5771020/489d31824ba5/12875_2017_690_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e0e8/5771020/4c838d068b97/12875_2017_690_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e0e8/5771020/dbedc8230d56/12875_2017_690_Fig3_HTML.jpg

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