Background

Smartphone-based monitoring constitutes a cost-effective instrument to assess and predict affective symptom trajectories. Large-scale transdiagnostic studies utilizing this methodology are yet lacking in psychiatric research. Thus, we introduce the Remote Monitoring Application in Psychiatry (ReMAP) and evaluate its feasibility and adherence in a large transdiagnostic sample.

Methods

The ReMAP app was distributed among n = 997 healthy control participants and psychiatric patients, including affective, anxiety, and psychotic disorders. Passive sensor data (acceleration, geolocation, walking distance, steps), optional standardized self-reports on mood and sleep, and voice samples were assessed. Feasibility and adherence were evaluated based on frequency of transferred data, and participation duration. Preliminary results are presented while data collection is ongoing.

Results

Retention rates of 90.25% for the minimum study duration of two weeks and 33.09% for one year were achieved (median participation 135 days, IQR=111). Participants transferred an average of 51.83 passive events per day. An average of 34.59 self-report events were transferred per user, with a considerable range across participants (0–552 events). Clinical and non-clinical subgroups did not differ in participation duration or rate of data transfer. The mean rate of days with passive data was higher and less heterogeneous in iOS (91.85%, SD=21.25) as compared to Android users (63.04%, SD=35.09).

Limitations

Subjective user experience was not assessed limiting conclusions about app acceptance.

Conclusions

ReMAP is a technically feasible tool to assess affective symptoms with high temporal resolution in large-scale transdiagnostic samples with good adherence. Future studies should account for differences between operating systems.

中文翻译：

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精神病学远程监测应用程序 (ReMAP) 用于评估情感症状的技术可行性和依从性

背景

基于智能手机的监测构成了一种评估和预测情感症状轨迹的经济有效的工具。精神病学研究尚缺乏使用这种方法的大规模跨诊断研究。因此，我们介绍了精神病学中的远程监控应用程序 (ReMAP)，并在大型跨诊断样本中评估其可行性和依从性。

方法

ReMAP 应用程序分布在n  = 997 名健康对照参与者和精神病患者中，包括情感障碍、焦虑障碍和精神病患者。评估了被动传感器数据（加速度、地理位置、步行距离、步数）、可选的关于情绪和睡眠的标准化自我报告以及语音样本。根据传输数据的频率和参与持续时间评估可行性和依从性。在进行数据收集的同时提供初步结果。

结果

最短研究持续时间为 90.25%，一年为 33.09%（中位参与天数为 135 天，IQR=111）。参与者平均每天转移 51.83 个被动事件。每个用户平均传输 34.59 个自我报告事件，参与者之间的范围相当大（0-552 个事件）。临床和非临床亚组在参与持续时间或数据传输率方面没有差异。与 Android 用户（63.04%，SD=35.09）相比，iOS 中被动数据的平均天数（91.85%，SD=21.25）更高，异构更少。

限制

没有评估主观用户体验，限制了有关应用程序接受度的结论。

结论

ReMAP 是一种技术上可行的工具，可以在具有良好依从性的大规模跨诊断样本中以高时间分辨率评估情感症状。未来的研究应该考虑操作系统之间的差异。