Predicting Termination Conditions in Individual Psychotherapy from Patients' Variables

從病人變項預測結束個別心理治療方式

楊大和(Ta-Ho Yang)；金樹人(Shuh-Ren Jin)

drop out ； termination style ； prior notice ； clinical variables ； 中輟 ； 結束方式 ； 提早告知 ； 臨床變項

台灣精神醫學

32卷2期（2018 / 06 / 01）

126 - 135+iii

英文

Objectives: We intended to explore the percentages and session times of psychotherapy for completers, informed dropouts, and non-informed dropouts, and to analyze the differences of clinical variables among those groups, and in an attempt to find effective predictors. Methods: The study data were based on five-year process note archives of short-term individual psychotherapy at a specialty psychiatric hospital. We did analysis of variance and multi-nominal logistic regression to analyze 16 clinical variables of 97 adult patients. Results: The percentages of completers, informed dropouts, and non-informed dropouts were 34%, 36.1%, and 29.9%, respectively, of the sample population. Those percentages are not significantly different in three groups. Their average times of attended sessions were 13.12, 6.69, and 6.31 times among those three groups, showing significant difference (F = 66.3, df = 2, 94, p ＜ 0.001). The factor of sex (χ^2 = 9.55, p ＜ 0.01), age (F = 3.99, df = 2, 92, p ＜ 0.05), and past psychotherapy experience (PPE) (χ^2 = 9.60, df = 2, p ＜ 0.01) could effectively discriminate three patients groups, with a total correct prediction rate of 55.8%. PPE was the most significant predictors among three predictors, but it could not effectively discriminate between completers and informed dropouts. Conclusion: Being young, male and without PPE were risk factors for non-informed dropout. Future studies are encouraged to set up longitudinal and detailed psychotherapy archives to further explore different features of dropout subgroups.

目的：探討完成治療者、中輟治療但提早告知者、中輟治療但未提早告知者的比例、參與治療次數、臨床變項的差異，找出有效預測三類病人的臨床變項。方法：分析臺灣某精神療養院中跨越超過五年的短期個別心理治療紀錄檔案，以ANOVA與Logistic regression分析97名成人病人在16個臨床變項上的差異。結果：完成治療者、事先告知者、未告知者的比率分別佔34%, 36.1%, 29.9%（χ^2 = 0.58, df = 2，不顯著），平均治療次數分別為13.12、6.69、6.31次(F = 66.3, df = 2, 94, p ＜ 0.001)。性別(χ^2 = 9.55, p ＜ 0.01)、年齡(F = 3.99, df = 2, 92, p ＜ 0.05)與過去治療經驗(χ^2 =9.60, df = 2, p ＜ 0.01)可以有效區別三類病人，迴歸模式對於結束治療方式的整體正確預測率為55.8%，其中過去是否有過治療經驗是最有力的預測因子，但是此因子無法區別有效區別完成治療者與提早告知者。結論：年輕、男性、過去沒有治療經驗是中輟治療且未提早告知的危險因子，未來研究應對中輟治療者進一步細分，並建立長年、詳細的心理治療紀錄。

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1. Ta-Ho Yang(2023)。A Psychodynamic Study on Premature Termination of Therapy Sessions。臺灣精神醫學，37(1)，21-28。
2. Ta-Ho Yang,Shuh-Ren Jin(2020)。How Do Patients' Attendance Profiles Influence Psychotherapy Terminations? A Preliminary Exploration。臺灣精神醫學，34(2)，84-91。