数据集大小与同质性:一项机器学习研究,将干预数据汇集到电子心理健康中断预测中
Kirsten Zantvoort1, Nils Hentati Isacsson2, Burkhardt Funk1
1Institute of Information Systems, Leuphana University, Lueneburg, Germany.
Digital health
|May 17, 2024
概括
从基于互联网的认知行为疗法干预中汇集数据可以增加机器学习的数据集大小. 这种方法改善了对患有抑郁症,社会焦虑症和恐慌症患者干预中断的预测.
科学领域:
- 数字心理健康数字心理健康
- 机器学习在医疗保健中的应用
- 心理干预 心理干预
背景情况:
- 基于互联网的认知行为疗法 (iCBT) 干预经常面临有限的数据集大小的挑战.
- 小数据集可能会阻碍机器学习模型的开发和准确性,以预测患者的结果.
- 了解不同ICBT干预措施的用户行为和症状数据相似性对于数据聚合至关重要.
研究的目的:
- 调查从不同的iCBT干预中汇集数据的可行性和好处.
- 为了检查用户行为和症状数据的相似性,iCBT干预抑郁症,社会焦虑症和恐慌症的干预措施.
- 确定聚合的数据是否能提高预测干预中断的准确性.
主要方法:
- 从斯德哥尔摩的互联网精神病学中分析常规护理患者数据 (n=6418).
- 集群技术的应用,以根据活动水平识别患者组.
- 开发和比较使用个人与聚合干预数据集的脱学预测模型,在不同大小的数据集上进行测试.
主要成果:
- 聚类发现了三个不同的患者群体,其特点是活动水平,独立于特定干预措施.
- 汇集干预数据显著提高了在九种测试的场景中的八种中断预测的准确性.
- 在较小的数据集上训练的模型表现出高估预测结果的倾向.
结论:
- 患有抑郁症,社会焦虑症和恐慌症的患者在iCBT干预中表现出类似的在线活动和学模式.
- 从不同的iCBT干预中汇集数据是克服心理学研究中小数据集局限性的可行策略.
- 这种方法可以提高机器学习模型在数字心理健康中的稳定性和通用性.
更多相关视频
相关概念视频
01:52Regression Toward the Mean
6.3K
Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when...
6.3K
02:20Longitudinal Research
12.0K
Sometimes we want to see how people change over time, as in studies of human development and lifespan. When we test the same group of individuals repeatedly over an extended period of time, we are conducting longitudinal research. Longitudinal research is a research design in which data-gathering is administered repeatedly over an extended period of time. For example, we may survey a group of individuals about their dietary habits at age 20, retest them a decade later at age 30, and then again...
12.0K
01:26Longitudinal Studies
157
Longitudinal studies are also widely used in other medical and social science fields. For instance, in cardiovascular research, they can monitor patients' health over decades to identify risk factors for heart disease, such as high cholesterol or smoking, and evaluate the long-term effectiveness of preventive measures. Similarly, in mental health studies, researchers might follow individuals from adolescence into adulthood to understand the development and progression of conditions like...
157
01:15One-Way ANOVA: Equal Sample Sizes
3.3K
One-Way ANOVA can be performed on three or more samples with equal or unequal sample sizes. When one-way ANOVA is performed on two datasets with samples of equal sizes, it can be easily observed that the computed F statistic is highly sensitive to the sample mean.
Different sample means can result in different values for the variance estimate: variance between samples. This is because the variance between samples is calculated as the product of the sample size and the variance between the...
Different sample means can result in different values for the variance estimate: variance between samples. This is because the variance between samples is calculated as the product of the sample size and the variance between the...
3.3K
01:23Mechanistic Models: Compartment Models in Individual and Population Analysis
38
Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
38