預測精神分裂症病患藥物遵從性的影響因素分析

Predictors of medication adherence in patients with schizophrenia

林美吟(Mei-Ying Lin)

指導教授 ： 林双金

高雄醫學大學/藥學院/藥學研究所碩士在職專班/碩士(2008年)

https://doi.org/10.6832/KMU.2008.00020

摘要

研究背景：抗精神病藥物治療是精神分裂症成功治療的一個重要因素，然而，在藥物持續治療過程中大約有40%到60%的精神分裂症患者，因不遵從藥物治療，而成為主要的問題，所以，不遵從藥物治療對於精神分裂症的成功治療是一個很重要的障礙，而且導致臨床及醫療支出成本上沉重的負擔，因此本研究之目的在探討及預測精神分裂症病患藥物遵從性的影響因素及特徵。
方法：研究設計為相關性研究，採立意取樣，以台灣南部一所醫學中心及一所區域教學醫院之精神分裂症病患為對象，資料收集於2007年7月至2008年2月，分析共90位依據DSM-IV診斷為精神分裂症患者，利用結構式問卷量表，進行橫斷性訪談，測量結果包括藥物治療態度、藥物遵從性、藥物副作用、病識感及社會支持度等，將所得資料經由SPSS Windows 12.0中文版之統計軟體，運用描述性統計、t-test、單因子變異數分析、Kruskal-Wallis 檢定、皮爾森積差相關和逐步迴歸分析等方法進行統計分析。
結果：研究結果顯示年齡、教育程度和抗精神病藥物種類對藥物遵從性有顯著性差異 (p<0.05)，年輕者、教育程度較低者及使用第二代抗精神病藥物者其藥物遵從性較差。在變項與藥物遵從性之相關性分析中，結果顯示對於藥物的正向(r=0.39, p<0.001)及負向態度(r=－0.32, p=0.002)、整體藥物副作用(r=－0.42, p<0.001)及病識感(r=0.28, p=0.009)具有顯著相關性，但是社會支持度顯示與藥物遵從性之間並無相關性。在逐步迴歸的分析中，顯示抗膽鹼激素藥物副作用(p=0.002)、藥物正向態度(p=0.011)與病識感中接受治療的情況(p=0.013)，三者為影響精神分裂症病患藥物遵從性的重要預測因子。
結論：探討精神分裂症病患藥物遵從性預測因子，可以提供最佳的遵從性介入治療之參考，研究資料可以提供臨床人員未來在改善精神分裂症病患藥物遵從性介入治療的方向，並且在這個領域中進一步設計出提高患者藥物遵從性的治療策略。

關鍵字

精神分裂症 ； 抗精神病藥物 ； 藥物遵從性

並列摘要

Background: Antipsychotic medication is a critical component of successful treatment for schizophrenia. However, nonadherence to these medications continues to be a major problem for 40% to 60% of patients with schizophrenia. Antipsychotic nonadherence is an important barrier to the successful treatment of schizophrenia and can lead to clinical and economic burdens for health services. The aim of this study was to identify the features of schizophrenia that predict antipsychotic medication adherence.
Method: A correlation research design and purposive sampling were used in the study. Schizophrenia patients in a medical center and a regional teaching hospital in the south part of Taiwan were chose. The data was collected from July 2007 to February 2008. Analyses included 90 patients with DSM-IV diagnoses of schizophrenia, using structural questionnaire and cross section interview. Outcome measures included attitudes toward treatment, self-reported medication adherence, drug adverse effects, insight and social support. Statistical analyses were performed with descriptive statistics, t-test, one-way ANOVA, Kruskal-Wallis test, Pearson’s correlation coefficient and stepwise regression by SPSS for Windows 12.0.
Results: The results indicated significant difference in the proportion of patients with age, education level and prescribed antipsychotic medication (p＜0.01). Younger patients, lower education level and second-generation antipsychotic had showed poor medication adherence. Correlation analysis was carried out to examine associations of variables with adherence to medication. Positive attitudes toward medication (r=0.39, p<0.001) and negative attitudes toward medication (r=－0.32, p=0.002) were correlated significantly with medication adherence. In addition, there were significant correlation between adherence and antipyschotic side effects (r=－0.42, p<0.001) and total insight (r=0.28, p=0.009). However, Social support showed no significant correlation with adherence. In a stepwise regression analysis, adverse effects of anticholinergic (p=0.002), positive attitude toward medication (p=0.011) and insight of need for treatment (p=0.013) were major predictors of medication adherence in patient of schizophrenia.
Conclusion：It may be possible to identify patients most likely to benefit from adherence intervention. The data presented here will help to inform future research of clinical interventions to improve medication adherence in schizophrenia and help to design further work and treatment strategies for medication adherence enhancement in this area.

並列關鍵字

schizophrenia ； antipsychotic medication ； medication adherence

參考文獻

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