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題名 以BSRS5時序性追蹤資料探討居家服務老年人口自殺意念與精神病理暨個人特質之關聯分析
作者 郭熙宏
Kuo, Hsi Hong
貢獻者 江振東
郭熙宏
Kuo, Hsi Hong
關鍵詞 BSRS5
自殺意念
時序性追蹤資料
廣義估計方程式
Alternating Logistic Regressions
BSRS5
suicide ideation
longitudinal data
Generalized Estimating Equation
Alternating Logistic Regression
日期 2008
上傳時間 8-Dec-2010 14:50:39 (UTC+8)
摘要 近幾年來,國人自殺死亡率不斷提高,且自殺死亡從1997年起已連續多年列於國人十大死亡原因之一,所以自殺防治工作刻不容緩。本研究採用自殺防治中心在桃園縣六家居家服務單位(龍祥、中國、仁愛、紅十字、家輔及寬福)所做之問卷調查資料,目的在於找出何種特性者,BSRS5 (The Five-Item Brief Symptom Rating Scale)分數及自殺意念分數可能較高。本研究屬於時序性追蹤資料,自民國96年5月份起,由居服人員針對受測對象進行訪談,大約每隔兩週收集一次,總共進行四次。
針對問卷進行基本敘述性統計、單項排名分析以及交叉分析後發現,在人口特質方面,男女性比例相當,年齡層主要皆在65~84歲,教育程度以不識字及國小為主;在BSRS5五題排名方面,以第一題「睡眠困難(難以入睡或早醒)」的平均分數最高,第四題「覺得比不上別人」平均分數最低;由交叉分析的結果發現身體狀況為一個重要的變數,身體狀況差的人BSRS5總分6分以上或自殺意念2分以上明顯較多。
對資料配適廣義估計方程式及Alternating Logistic Regressions的結果,發現在反應變數為BSRS5總分時,女性、身體狀況差及曾經看過精神科者BSRS5分數達到6分以上的可能性較高。若反應變數為自殺意念時,無論是利用廣義估計方程式或Alternating Logistic Regressions,從模型配適的結果發現只有BSRS5的效應顯著。不管利用BSRS5總分或是各題分開來看,BSRS5對自殺意念是一個相當有效的檢測工具,BSRS5分數愈高則自殺意念2分以上的機會也愈高。此外利用多層結構分析方法配適廣義估計方程式,針對BSRS5與受測次數間的關聯性分析,發現與配適傳統unstructured相關性矩陣的估計結果差異不大,但是可以減少許多參數估計,並且在電腦計算時間上是較快速的。
In Taiwan, suicide has been among the top ten causes of death since 1997, and suicide prevention has thus attracted much attention since. Using the data provided by Taiwan Suicide Prevention Center (TSPC), this study is aimed to find out possible personal characteristics that might have some impacts on the BSRS5 (the Five-Item Brief Symptom Rating Scale) and suicide ideation scores The data come from a longitudinal study in which subjects from six elderly home service centers in Taoyuan County, Taiwan were visited four times between May and July, 2007, about two weeks between each visit.
The total number of subjects is 1981. The proportions of male and female are nearly the same, the age range is from 65 to 84, and most of them have only an elementary school degree. Preliminary analyses indicate that among the five items in BSRS5, insomnia (the first item) is ranked the highest, and inferiority (the fourth item) is the lowest. In addition, health status is highly correlated to the BSRS5 and suicide ideation scores, the worse the health status, the higher the BSRS5 and suicide ideation scores.
Fitting the data with Generalized Estimating Equation (GEE) and Alternating Logistic Regressions models with respect to the BSRS5 score, we further find that female, those who have bad health status, and those who have ever consulted a psychiatrist have higher probability that the BSRS5 score is greater than 6. As far as the suicide ideation score is concerned, the BSRS5 score is the only covariate that is statistically significant, an indication that BSRS5 is a useful tool for screening subjects at risk of committing suicide. While the conclusions stay the same whether the data are analyzed through GEE with commonly used unstructured correlation structure or newly developed multiblock and multilayer correlation structure, the latter approach reduces the computer time significantly.
參考文獻 Agresti A. (2002). An introduction to categorical data analysis, John Wiley & Sons, Inc., Hoboken, New Jersey.
Allison P. D. (1999). Logistic regression using the SAS system : theory and application, SAS Institute, Cary, N.C.
Carey V., Zeger S.L. and Diggle P. (1993). Modelling multivariate binary data with alternating logistic regression. Biometrika 80, 517-526.
Chao E. C. (2006). Structured correlation in models for clustered data. Statistics in Medicine 25, 2450-2468.
Charles S. D. (2002). Statistical methods for the analysis of repeated measurements, Springer, New York.
Khattree R. and Naik D. N. (1999). Applied multivariate statistics with SAS software, SAS Institute , Cary, N.C. ; John Wiley & Sons, Inc., New York.
Kleinbaum D.G. and Klein M. (2002). Logistic regression : a self-learning text, Springer, New York.
Liang K.Y. and Zeger S.L. (1986). Longitudinal data analysis using generalized linear models. Biometrika 73, 13-22.
Lung F. W. and Lee M. B. (2008). The five-item Brief-Symptom Rating Sacle as a suicide ideation screening instrument for psychiatric inpatients and community residents. BMC Psychiatry, 8:53.
Zeger S.L., Liang K.Y. and Albert P.S. (1988). Models for longitudinal data: a generalized estimating equation approach. Biometrics 44, 1049-1060.
描述 碩士
國立政治大學
統計研究所
96354008
97
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0096354008
資料類型 thesis
dc.contributor.advisor 江振東zh_TW
dc.contributor.author (Authors) 郭熙宏zh_TW
dc.contributor.author (Authors) Kuo, Hsi Hongen_US
dc.creator (作者) 郭熙宏zh_TW
dc.creator (作者) Kuo, Hsi Hongen_US
dc.date (日期) 2008en_US
dc.date.accessioned 8-Dec-2010 14:50:39 (UTC+8)-
dc.date.available 8-Dec-2010 14:50:39 (UTC+8)-
dc.date.issued (上傳時間) 8-Dec-2010 14:50:39 (UTC+8)-
dc.identifier (Other Identifiers) G0096354008en_US
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/49597-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 統計研究所zh_TW
dc.description (描述) 96354008zh_TW
dc.description (描述) 97zh_TW
dc.description.abstract (摘要) 近幾年來,國人自殺死亡率不斷提高,且自殺死亡從1997年起已連續多年列於國人十大死亡原因之一,所以自殺防治工作刻不容緩。本研究採用自殺防治中心在桃園縣六家居家服務單位(龍祥、中國、仁愛、紅十字、家輔及寬福)所做之問卷調查資料,目的在於找出何種特性者,BSRS5 (The Five-Item Brief Symptom Rating Scale)分數及自殺意念分數可能較高。本研究屬於時序性追蹤資料,自民國96年5月份起,由居服人員針對受測對象進行訪談,大約每隔兩週收集一次,總共進行四次。
針對問卷進行基本敘述性統計、單項排名分析以及交叉分析後發現,在人口特質方面,男女性比例相當,年齡層主要皆在65~84歲,教育程度以不識字及國小為主;在BSRS5五題排名方面,以第一題「睡眠困難(難以入睡或早醒)」的平均分數最高,第四題「覺得比不上別人」平均分數最低;由交叉分析的結果發現身體狀況為一個重要的變數,身體狀況差的人BSRS5總分6分以上或自殺意念2分以上明顯較多。
對資料配適廣義估計方程式及Alternating Logistic Regressions的結果,發現在反應變數為BSRS5總分時,女性、身體狀況差及曾經看過精神科者BSRS5分數達到6分以上的可能性較高。若反應變數為自殺意念時,無論是利用廣義估計方程式或Alternating Logistic Regressions,從模型配適的結果發現只有BSRS5的效應顯著。不管利用BSRS5總分或是各題分開來看,BSRS5對自殺意念是一個相當有效的檢測工具,BSRS5分數愈高則自殺意念2分以上的機會也愈高。此外利用多層結構分析方法配適廣義估計方程式,針對BSRS5與受測次數間的關聯性分析,發現與配適傳統unstructured相關性矩陣的估計結果差異不大,但是可以減少許多參數估計,並且在電腦計算時間上是較快速的。
zh_TW
dc.description.abstract (摘要) In Taiwan, suicide has been among the top ten causes of death since 1997, and suicide prevention has thus attracted much attention since. Using the data provided by Taiwan Suicide Prevention Center (TSPC), this study is aimed to find out possible personal characteristics that might have some impacts on the BSRS5 (the Five-Item Brief Symptom Rating Scale) and suicide ideation scores The data come from a longitudinal study in which subjects from six elderly home service centers in Taoyuan County, Taiwan were visited four times between May and July, 2007, about two weeks between each visit.
The total number of subjects is 1981. The proportions of male and female are nearly the same, the age range is from 65 to 84, and most of them have only an elementary school degree. Preliminary analyses indicate that among the five items in BSRS5, insomnia (the first item) is ranked the highest, and inferiority (the fourth item) is the lowest. In addition, health status is highly correlated to the BSRS5 and suicide ideation scores, the worse the health status, the higher the BSRS5 and suicide ideation scores.
Fitting the data with Generalized Estimating Equation (GEE) and Alternating Logistic Regressions models with respect to the BSRS5 score, we further find that female, those who have bad health status, and those who have ever consulted a psychiatrist have higher probability that the BSRS5 score is greater than 6. As far as the suicide ideation score is concerned, the BSRS5 score is the only covariate that is statistically significant, an indication that BSRS5 is a useful tool for screening subjects at risk of committing suicide. While the conclusions stay the same whether the data are analyzed through GEE with commonly used unstructured correlation structure or newly developed multiblock and multilayer correlation structure, the latter approach reduces the computer time significantly.
en_US
dc.description.tableofcontents 摘要 I
英文摘要 III
表目錄 VII
圖目錄 XI

第一章 緒論 1
第一節 研究背景與動機 1
第二節 研究目的 3
第三節 本文編排 3
第二章 文獻回顧 4
第一節 廣義估計方程式 4
第二節 Alternating Logistic Regressions 8
第三節 多層結構分析 9
第三章 研究方法 13
第一節 研究設計 13
第二節 資料來源 13
第三節 研究對象 13
第四節 變項分類與處理 14
第五節 方法架構 17
第四章 樣本資料分析 19
第一節 人口特質 19
第二節 BSRS5單項排名分析 21
第三節 交叉分析 23
第五章 實證分析 25
第一節 廣義估計方程式分析 25
第二節 Alternating Logistic Regressions 31
第三節 多層結構分析 37
第六章 結論、研究限制與建議 42
第一節 結論 42
第二節 研究限制與建議 43

參考文獻 44
附錄 45
附錄一 心情溫度紀錄表 45
附錄二 附表 47
附錄三 SAS與S-plus程式指令 75
zh_TW
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dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0096354008en_US
dc.subject (關鍵詞) BSRS5zh_TW
dc.subject (關鍵詞) 自殺意念zh_TW
dc.subject (關鍵詞) 時序性追蹤資料zh_TW
dc.subject (關鍵詞) 廣義估計方程式zh_TW
dc.subject (關鍵詞) Alternating Logistic Regressionszh_TW
dc.subject (關鍵詞) BSRS5en_US
dc.subject (關鍵詞) suicide ideationen_US
dc.subject (關鍵詞) longitudinal dataen_US
dc.subject (關鍵詞) Generalized Estimating Equationen_US
dc.subject (關鍵詞) Alternating Logistic Regressionen_US
dc.title (題名) 以BSRS5時序性追蹤資料探討居家服務老年人口自殺意念與精神病理暨個人特質之關聯分析zh_TW
dc.type (資料類型) thesisen
dc.relation.reference (參考文獻) Agresti A. (2002). An introduction to categorical data analysis, John Wiley & Sons, Inc., Hoboken, New Jersey.zh_TW
dc.relation.reference (參考文獻) Allison P. D. (1999). Logistic regression using the SAS system : theory and application, SAS Institute, Cary, N.C.zh_TW
dc.relation.reference (參考文獻) Carey V., Zeger S.L. and Diggle P. (1993). Modelling multivariate binary data with alternating logistic regression. Biometrika 80, 517-526.zh_TW
dc.relation.reference (參考文獻) Chao E. C. (2006). Structured correlation in models for clustered data. Statistics in Medicine 25, 2450-2468.zh_TW
dc.relation.reference (參考文獻) Charles S. D. (2002). Statistical methods for the analysis of repeated measurements, Springer, New York.zh_TW
dc.relation.reference (參考文獻) Khattree R. and Naik D. N. (1999). Applied multivariate statistics with SAS software, SAS Institute , Cary, N.C. ; John Wiley & Sons, Inc., New York.zh_TW
dc.relation.reference (參考文獻) Kleinbaum D.G. and Klein M. (2002). Logistic regression : a self-learning text, Springer, New York.zh_TW
dc.relation.reference (參考文獻) Liang K.Y. and Zeger S.L. (1986). Longitudinal data analysis using generalized linear models. Biometrika 73, 13-22.zh_TW
dc.relation.reference (參考文獻) Lung F. W. and Lee M. B. (2008). The five-item Brief-Symptom Rating Sacle as a suicide ideation screening instrument for psychiatric inpatients and community residents. BMC Psychiatry, 8:53.zh_TW
dc.relation.reference (參考文獻) Zeger S.L., Liang K.Y. and Albert P.S. (1988). Models for longitudinal data: a generalized estimating equation approach. Biometrics 44, 1049-1060.zh_TW