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社会人口统计学变量是否会调节针对轻至中度抑郁症状的互联网干预效果?一项纳入1013名参与者的随机对照试验(EVIDENT)的探索性分析。

Do sociodemographic variables moderate effects of an internet intervention for mild to moderate depressive symptoms? An exploratory analysis of a randomised controlled trial (EVIDENT) including 1013 participants.

作者信息

Nolte Sandra, Busija Ljoudmila, Berger Thomas, Meyer Björn, Moritz Steffen, Rose Matthias, Schröder Johanna, Späth-Nellissen Christina, Klein Jan Philipp

机构信息

Medical Department, Division of Psychosomatic Medicine, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany

Research Methodology Division, Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.

出版信息

BMJ Open. 2021 Jan 26;11(1):e041389. doi: 10.1136/bmjopen-2020-041389.

Abstract

OBJECTIVE

To explore the moderating effects of sociodemographic variables on treatment benefits received from participating in an internet intervention for depression.

DESIGN

Randomised, assessor-blind, controlled trial.

SETTING

Online intervention, with participant recruitment using multiple settings, including inpatient and outpatient medical and psychological clinics, depression online forums, health insurance companies and the media (eg, newspaper, radio).

PARTICIPANTS

The EVIDENT trial included 1013 participants with mild to moderate depressive symptoms.

INTERVENTIONS

The intervention group subjects (n=509) received an online intervention (Deprexis) in addition to care as usual (CAU), while 504 participants received CAU alone.

METHODS

To explore subgroup differences, moderating effects were investigated using linear regression models based on intention-to-treat analyses. Moderating effects included sex, age, educational attainment, employment status, relationship status and lifetime frequency of episodes.

PRIMARY AND SECONDARY OUTCOME MEASURES

The primary endpoint was change in self-rated depression severity measured by the Patient Health Questionnaire-9 (PHQ-9), comparing baseline versus 12-week post-test assessment. Secondary outcome measures were the Hamilton Rating Scale for Depression and the Quick Inventory of Depressive Symptoms each at 12 weeks and at 6 and 12 months, and PHQ-9 at 6 and 12 months, respectively. In this article, we focus on the primary outcome measure only.

RESULTS

Between-group differences were observed in post-test scores, indicating the effectiveness of Deprexis. While the effects of the intervention could be demonstrated across all subgroups, some showed larger between-group differences than others. However, after exploring the moderating effects based on linear regression models, none of the selected variables was found to be moderating treatment outcomes.

CONCLUSIONS

Our findings suggest that Deprexis is equally beneficial to a wide range of people; that is, participant characteristics were not associated with treatment benefits. Therefore, participant recruitment into web-based psychotherapeutic interventions should be broad, while special attention may be paid to those currently under-represented in these interventions.

TRIAL REGISTRATION NUMBER

NCT01636752.

摘要

目的

探讨社会人口统计学变量对参与抑郁症互联网干预所获治疗益处的调节作用。

设计

随机、评估者盲法、对照试验。

设置

在线干预,通过多种途径招募参与者,包括住院和门诊医疗及心理诊所、抑郁症在线论坛、健康保险公司和媒体(如报纸、广播)。

参与者

EVIDENT试验纳入了1013名有轻度至中度抑郁症状的参与者。

干预措施

干预组受试者(n = 509)除接受常规护理(CAU)外,还接受在线干预(Deprexis),而504名参与者仅接受常规护理。

方法

为探讨亚组差异,基于意向性分析使用线性回归模型研究调节作用。调节作用的变量包括性别、年龄、教育程度、就业状况、恋爱状况和发作的终生频率。

主要和次要结局指标

主要终点是通过患者健康问卷-9(PHQ-9)测量的自评抑郁严重程度的变化,比较基线与12周后测评估。次要结局指标分别是12周、6个月和12个月时的汉密尔顿抑郁评定量表和抑郁症状快速量表,以及6个月和12个月时的PHQ-9。在本文中,我们仅关注主要结局指标。

结果

在后测分数中观察到组间差异,表明Deprexis有效。虽然干预效果在所有亚组中均可得到证明,但有些亚组的组间差异比其他亚组更大。然而,在基于线性回归模型探讨调节作用后,未发现所选变量中的任何一个对治疗结局有调节作用。

结论

我们的研究结果表明,Deprexis对广泛人群同样有益;也就是说,参与者特征与治疗益处无关。因此,基于网络的心理治疗干预的参与者招募范围应广泛,同时可能需要特别关注目前在这些干预中代表性不足的人群。

试验注册号

NCT01636752。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b5ee/7839881/efb68ab65daf/bmjopen-2020-041389f01.jpg

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