PDF(Pubmed)
Abstract：
High dropout rates are a common problem reported in web-based studies. Understanding which risk factors interrelate with dropping out from the studies provides the option to prevent dropout by tailoring effective strategies.
This study aims to contribute an understanding of the predictors of web-based study dropout among psychosomatic rehabilitation patients. We investigated whether sociodemographics, voluntary interventions, physical and mental health, digital use for health and rehabilitation, and COVID-19 pandemic-related variables determine study dropout.
Patients (N=2155) recruited from 4 psychosomatic rehabilitation clinics in Germany filled in a web-based questionnaire at T1, which was before their rehabilitation stay. Approximately half of the patients (1082/2155, 50.21%) dropped out at T2, which was after the rehabilitation stay, before and during which 3 voluntary digital trainings were provided to them. According to the number of trainings that the patients participated in, they were categorized into a comparison group or 1 of 3 intervention groups. Chi-square tests were performed to examine the differences between dropout patients and retained patients in terms of sociodemographic variables and to compare the dropout rate differences between the comparison and intervention groups. Logistic regression analyses were used to assess what factors were related to study dropout.
The comparison group had the highest dropout rate of 68.4% (173/253) compared with the intervention groups\' dropout rates of 47.98% (749/1561), 50% (96/192), and 42.9% (64/149). Patients with a diagnosis of combined anxiety and depressive disorder had the highest dropout rate of 64% (47/74). Younger patients (those aged <50 y) and patients who were less educated were more likely to drop out of the study. Patients who used health-related apps and the internet less were more likely to drop out of the study. Patients who remained in their jobs and patients who were infected by COVID-19 were more likely to drop out of the study.
This study investigated the predictors of dropout in web-based studies. Different factors such as patient sociodemographics, physical and mental health, digital use, COVID-19 pandemic correlates, and study design can correlate with the dropout rate. For web-based studies with a focus on mental health, it is suggested to consider these possible dropout predictors and take appropriate steps to help patients with a high risk of dropping out overcome difficulties in completing the study.
This study aims to contribute an understanding of the predictors of web-based study dropout among psychosomatic rehabilitation patients. We investigated whether sociodemographics, voluntary interventions, physical and mental health, digital use for health and rehabilitation, and COVID-19 pandemic-related variables determine study dropout.
Patients (N=2155) recruited from 4 psychosomatic rehabilitation clinics in Germany filled in a web-based questionnaire at T1, which was before their rehabilitation stay. Approximately half of the patients (1082/2155, 50.21%) dropped out at T2, which was after the rehabilitation stay, before and during which 3 voluntary digital trainings were provided to them. According to the number of trainings that the patients participated in, they were categorized into a comparison group or 1 of 3 intervention groups. Chi-square tests were performed to examine the differences between dropout patients and retained patients in terms of sociodemographic variables and to compare the dropout rate differences between the comparison and intervention groups. Logistic regression analyses were used to assess what factors were related to study dropout.
The comparison group had the highest dropout rate of 68.4% (173/253) compared with the intervention groups\' dropout rates of 47.98% (749/1561), 50% (96/192), and 42.9% (64/149). Patients with a diagnosis of combined anxiety and depressive disorder had the highest dropout rate of 64% (47/74). Younger patients (those aged <50 y) and patients who were less educated were more likely to drop out of the study. Patients who used health-related apps and the internet less were more likely to drop out of the study. Patients who remained in their jobs and patients who were infected by COVID-19 were more likely to drop out of the study.
This study investigated the predictors of dropout in web-based studies. Different factors such as patient sociodemographics, physical and mental health, digital use, COVID-19 pandemic correlates, and study design can correlate with the dropout rate. For web-based studies with a focus on mental health, it is suggested to consider these possible dropout predictors and take appropriate steps to help patients with a high risk of dropping out overcome difficulties in completing the study.
摘要：
背景：高辍学率是在线研究中报道的常见问题。了解哪些风险因素与退出研究相关，可以通过制定有效的策略来防止退出研究。
目的：本研究旨在加深对心身康复患者在线研究退出预测因素的理解。我们调查了社会人口统计学，自愿干预，身心健康,数字用于健康和康复，与COVID大流行相关的变量决定了研究退出。
方法：患者（N=2155）从德国的四个心身康复诊所招募，并在T1时填写在线问卷，这是在他们的康复住院之前。其中大约一半（1082/2155，50.2％）在康复住院后的T2退出，在此期间，向患者提供了三项自愿数字培训。根据患者参加的培训数量，他们被定义为对照组或干预组.进行卡方检验，以检查退出患者和保留患者在社会人口统计学变量方面的差异；并比较比较组和干预组之间的退出率差异。使用Logistic回归分析来评估与调查中保留的因素有关。
结果：对照组的辍学率最高，为68.4％（173/253），与48.0%的干预组(749/1561)相比，50.0%（96/192），和43.0%(64/149)的辍学率。诊断为焦虑和抑郁综合障碍的患者的辍学率最高，高达63.5％（47/74）。年轻患者（<50岁）和受教育程度较低的患者更有可能退出研究。与健康相关的应用程序和/或互联网使用行为较少的患者更有可能退出研究。留在工作中的病人，感染冠状病毒的患者更有可能退出研究。
结论：这项研究调查了在线研究中辍学的预测因素。患者社会人口统计学的不同因素，身心健康,数字使用,COVID大流行相关因素，研究设计可以与辍学率相关。对于以心理健康为重点的在线研究，建议考虑这些可能的辍学预测因素，并采取适当的策略来帮助辍学风险高的患者克服困难完成研究。
背景：ClinicalTrials.gov标识符：NCT04453475；https://clinicaltrials.gov/ct2/show/NCT04453475。
目的：本研究旨在加深对心身康复患者在线研究退出预测因素的理解。我们调查了社会人口统计学，自愿干预，身心健康,数字用于健康和康复，与COVID大流行相关的变量决定了研究退出。
方法：患者（N=2155）从德国的四个心身康复诊所招募，并在T1时填写在线问卷，这是在他们的康复住院之前。其中大约一半（1082/2155，50.2％）在康复住院后的T2退出，在此期间，向患者提供了三项自愿数字培训。根据患者参加的培训数量，他们被定义为对照组或干预组.进行卡方检验，以检查退出患者和保留患者在社会人口统计学变量方面的差异；并比较比较组和干预组之间的退出率差异。使用Logistic回归分析来评估与调查中保留的因素有关。
结果：对照组的辍学率最高，为68.4％（173/253），与48.0%的干预组(749/1561)相比，50.0%（96/192），和43.0%(64/149)的辍学率。诊断为焦虑和抑郁综合障碍的患者的辍学率最高，高达63.5％（47/74）。年轻患者（<50岁）和受教育程度较低的患者更有可能退出研究。与健康相关的应用程序和/或互联网使用行为较少的患者更有可能退出研究。留在工作中的病人，感染冠状病毒的患者更有可能退出研究。
结论：这项研究调查了在线研究中辍学的预测因素。患者社会人口统计学的不同因素，身心健康,数字使用,COVID大流行相关因素，研究设计可以与辍学率相关。对于以心理健康为重点的在线研究，建议考虑这些可能的辍学预测因素，并采取适当的策略来帮助辍学风险高的患者克服困难完成研究。
背景：ClinicalTrials.gov标识符：NCT04453475；https://clinicaltrials.gov/ct2/show/NCT04453475。
