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基于智能手机和在线使用情况的抑郁症评估(SOLVD)应用程序试验的结果:应用程序究竟能告诉我们关于抑郁症患者的哪些信息?应用程序生成的数据与抑郁症和焦虑症标准精神科问卷之间的一致性。

Findings From a Trial of the Smartphone and OnLine Usage-based eValuation for Depression (SOLVD) Application: What Do Apps Really Tell Us About Patients with Depression? Concordance Between App-Generated Data and Standard Psychiatric Questionnaires for Depression and Anxiety.

作者信息

Moukaddam Nidal, Truong Anh, Cao Jian, Shah Asim, Sabharwal Ashutosh

出版信息

J Psychiatr Pract. 2019 Sep;25(5):365-373. doi: 10.1097/PRA.0000000000000420.

Abstract

OBJECTIVE

Depression imposes a notable societal burden, with limited treatment success despite multiple available psychotherapy and medications choices. Potential reasons may include the heterogeneity of depression diagnoses and the presence of comorbid anxiety symptoms. Despite technological advances and the introduction of many mobile phone applications (apps) claiming to relieve depression, major gaps in knowledge still exist regarding what apps truly measure and how they correlate with psychometric questionnaires. The goal of this study was to evaluate whether mobile daily mood self-ratings may be useful in monitoring and classifying depression symptoms in a clinically depressed population compared with standard psychometric instruments including the Patient Health Questionaire-9 (PHQ-9), the Hamilton Rating Scale for Depression (HAM-D), and the Hamilton Anxiety Rating Scale (HAM-A).

METHOD

For this study, 22 patients with major depressive disorder with or without comorbid anxiety disorder were recruited. The diagnosis of depression was confirmed through the Mini International Neuropsychiatric Interview (MINI). Over an 8-week period, daily moods were self-reported through the Smartphone and OnLine Usage-based eValuation for Depression (SOLVD) application, a custom-designed application that was downloaded onto patients' mobile devices. Depression and anxiety symptoms were also measured biweekly using the HAM-D, HAM-A, and PHQ-9.

RESULTS

Significant correlations were observed among self-evaluated mood, daily steps taken, SMS (text) frequency, average call duration, and biweekly psychometric scores (|r|>0.5, P<0.05). The correlation coefficients were higher in individuals with more severe depressive symptoms.

CONCLUSIONS

Although this study, given its limited sample size, was exploratory in nature, it helps fill a significant gap in our knowledge of the concordance between ratings obtained on the Ham-D, Ham-A, and the PHQ-9 psychometric instruments and data obtained via a smartphone app. These questionnaires represent gold-standard, commonly used psychiatric research/clinical instruments, and, thus, this information can serve as a foundation for digital phenotyping for depression and pave the way for interventional studies using smartphone applications.

摘要

目的

抑郁症给社会带来了显著负担,尽管有多种心理治疗方法和药物可供选择,但治疗成功率有限。潜在原因可能包括抑郁症诊断的异质性以及共病焦虑症状的存在。尽管技术不断进步,许多声称可缓解抑郁症的手机应用程序(应用)也相继推出,但对于这些应用真正测量的内容以及它们与心理测量问卷的相关性,仍存在重大知识空白。本研究的目的是评估与包括患者健康问卷-9(PHQ-9)、汉密尔顿抑郁量表(HAM-D)和汉密尔顿焦虑量表(HAM-A)在内的标准心理测量工具相比,手机每日情绪自评是否有助于监测和分类临床抑郁症患者的抑郁症状。

方法

本研究招募了22名患有或未患有共病焦虑症的重度抑郁症患者。通过迷你国际神经精神病学访谈(MINI)确诊抑郁症。在8周的时间里,患者通过智能手机和基于在线使用情况的抑郁症评估(SOLVD)应用程序自我报告每日情绪,该应用程序是一款定制设计的应用,已下载到患者的移动设备上。还每两周使用HAM-D、HAM-A和PHQ-9测量抑郁和焦虑症状。

结果

在自我评估情绪、每日步数、短信(文本)频率、平均通话时长和每两周的心理测量得分之间观察到显著相关性(|r|>0.5,P<0.05)。抑郁症状较严重的个体的相关系数更高。

结论

尽管本研究样本量有限,本质上是探索性的,但它有助于填补我们在HAM-D、HAM-A和PHQ-9心理测量工具所获评分与通过智能手机应用程序获得的数据之间一致性方面的重大知识空白。这些问卷代表了金标准、常用的精神病学研究/临床工具,因此,这些信息可为抑郁症的数字表型分析奠定基础,并为使用智能手机应用程序的干预研究铺平道路。

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