Analysis on the development track and influencing factors of treatment compliance of patients with major depression
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摘要:
目的 重度抑郁症(major depressive disorder, MDD)患者治疗依从性会影响治疗效果及转归。为明确MDD患者治疗依从性发展趋势及其影响因素，本研究纳入MDD患者，运用组基轨迹模型(group-based trajectory model，GBTM)分析其发展轨迹，并探究相关影响因素，以期为提升患者治疗依从性、优化临床干预策略提供科学依据。 方法 采取便利抽样法，纳入2021年5月—2022年7月绍兴市第七人民医院收治的96例MDD患者作为研究对象。收集患者一般资料，采用Morisky服药依从性量表-8(Morisky medication adherence scale, MMAS-8)评估MDD患者不同时间段的治疗依从性，采用GBTM分析MDD患者治疗依从性的发展轨迹，采用多分类logistic回归分析其影响因素。 结果 随访6周后，统计有效问卷92份，有效回收率为95.83%(92/96)。通过GBTM拟合出最佳治疗依从性轨迹类型模型(BIC=-4 925.8)，分为持续下降组(32例)、相对稳定组(41例)和持续高水平组(19例)。3组患者文化水平、服药时间、家庭人均月收入和医患关系比较，差异均有统计学意义(P < 0.05)。以持续下降组为参照，多分类logistic回归分析显示，文化水平、服药时间、家庭人均月收入和医患关系均为MDD患者治疗依从性轨迹类别的影响因素(P < 0.05)。 结论 MDD患者治疗依从性的发展轨迹具有异质性，MDD患者治疗依从性发展轨迹与文化水平、服药时间、家庭人均月收入及医患关系相关。 Abstract:Objective Treatment adherence in patients with major depressive disorder (MDD) influences treatment outcomes and prognosis. To clarify the developmental trajectory of treatment adherence in MDD patients and its associated factors, this study enrolled MDD patients, analyzed their adherence trajectories using group-based trajectory model (GBTM), and explored influencing factors, aiming to provide a scientific basis for improving treatment adherence and optimizing clinical intervention strategies. Methods A total of 96 patients with MDD admitted to Shaoxing Seventh People' s Hospital from May 2021 to July 2022 were selected by convenient sampling method. Information such as gender, age and education level of patients were collected, and the treatment compliance of MDD patients in different time periods was evaluated by Morisky medication adherence scale-8 (MMAS-8). The development track of treatment compliance of MDD patients was analyzed by using the GBTM, and the influencing factors were analyzed by using the multinomial logistic regression coefficient. Results After 6 weeks of follow-up, 92 questionnaires were statistically valid, and the effective recovery rate was 95.83% (92/96). The optimal treatment compliance trajectory type model (BIC=-4 925.8) was fitted by GBTM, which was divided into three groups: continuous decline group (n=32), relatively stable group (n=41) and continuous high-level group (n=19). There were significant differences in the education level, medication time, family income per capita and doctor-patient relationship among the three groups (P < 0.05). Taking the declining group as a reference, the multinomial logistic regression coefficient analysis showed that education level, medication time, family per capita monthly income and doctor-patient relationship were the influencing factors of MDD patients' treatment compliance trajectory group (P < 0.05). Conclusion The developmental trajectories of treatment adherence in MDD patients exhibit heterogeneity, which is associated with educational level, medication duration, family monthly per capita income, and doctor-patient relationship. -
Key words:
- Major depressive disorder /
- Compliance /
- Development track /
- Cultural level /
- Adverse reactions
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图 1 不同组别治疗依从性的轨迹特征
Figure 1. Trajectory characteristics of treatment compliance in different groups
表 1 拟合模型不同轨迹特征组的参数分析
Table 1. Parameter analysis of the fitted model across different trajectory feature groups
项目 类别1 类别2 类别3 截距 -0.840 -0.389 -0.296 AvePP 0.965 0.957 0.950 估计总体比例(%) 32.466 41.210 26.324 实际总体比例(%) 34.783 44.565 20.652 注：AvePP为平均后验概率。 
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表 2 3组MDD患者治疗依从性轨迹类别的一般资料比较
Table 2. Comparison of baseline characteristics among the three treatment adherence trajectory groups in patients with MDD
项目 持续下降组(n=32) 相对稳定组(n=41) 持续高水平组(n=19) 统计量 P值 性别[例(%)] 1.022a 0.600 男性 17(53.13) 26(63.41) 10(52.63) 女性 15(46.87) 15(36.59) 9(47.37) 年龄[M(P25, P75)，岁] 35(19, 62) 36(21, 65) 36(20, 64) 0.391b 0.678 文化水平[例(%)] 11.117a 0.004 小学及以下 10(31.25) 4(9.76) 1(5.26) 初中及高中 13(40.63) 16(39.02) 5(26.32) 专科及以上 9(28.12) 21(51.22) 13(68.42) 服药时间[例(%)] 12.726a 0.002 ≤6个月 11(34.38) 28(68.29) 14(73.68) ＞6个月 21(65.62) 13(31.71) 5(26.32) 婚姻状况[例(%)] 0.654a 0.721 已婚 17(53.13) 25(60.98) 12(63.16) 未婚/离异/丧偶 15(46.87) 16(39.02) 7(36.84) 付费方式[例(%)] 0.286a 0.867 自费 5(15.63) 8(19.51) 4(21.05) 医保 27(84.37) 33(80.49) 15(78.95) 居住地[例(%)] 0.334a 0.846 农村 6(18.75) 9(21.95) 3(15.79) 城镇 26(81.25) 32(78.05) 16(84.21) 家庭人均月收入(元) 8.473a 0.014 ≤3 000 15(46.87) 10(24.39) 2(10.53) ＞3 000 17(53.13) 31(75.61) 17(89.57) 基础疾病[例(%)] 糖尿病 5(15.63) 4(9.76) 2(10.53) 0.635a 0.728 高血压 4(12.50) 2(4.88) 1(5.26) 1.673a 0.433 冠心病 1(3.13) 2(4.88) 0 0.982a 0.612 医患关系[例(%)] 13.086a 0.001 良好 13(40.63) 32(78.05) 15(78.95) 较差 19(59.37) 9(21.95) 4(21.05) 注：a为χ2值，b为H值。
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表 3 变量赋值情况
Table 3. Variable assignment
变量 赋值方法 轨迹归属类别 相对稳定组=(1，0)，持续高水平组=(0，1)，持续下降组=(0，0) 文化水平 小学及以下=0，初中及高中=1，专科及以上=2 服药时间 ＞6个月=0，≤6个月=1 家庭人均月收入 ≤3 000元=0，＞3 000元=1 医患关系 较差=0，良好=1
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表 4 MDD患者不同治疗依从性轨迹类别影响因素的多分类logistic回归分析
Table 4. Univariable logistic regression analysis of factors associated with different treatment adherence trajectory categories in patients with MDD
变量 相对稳定组 持续高水平组 B SE Waldχ2 P值 OR(95% CI) B SE Waldχ2 P值 OR(95% CI) 文化水平 6.146 0.046 7.527 0.023 初中及高中 -1.764 0.713 6.114 0.013 0.171(0.042~0.694) -2.670 1.135 5.536 0.019 0.069(0.007~0.640) 专科及以上 -0.640 0.546 1.372 0.241 0.241(0.181~1.538) -1.323 0.682 3.766 0.052 0.266(0.070~1.013) 服药时间 1.414 0.501 7.959 0.005 4.112(1.540~10.981) 1.676 0.640 6.854 0.009 5.345(1.524~18.750) 家庭人均月收入 1.006 0.508 3.928 0.047 2.735(1.011~7.399) 2.015 0.827 5.933 0.015 7.500(1.482~37.949) 医患关系 1.648 0.521 9.988 0.002 5.197(1.870~14.440) 1.701 0.668 6.486 0.011 5.481(1.480~20.297)
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