Psychology and Methods, School of Business, Social & Decision Sciences, Constructor University Bremen gGmbH, Bremen, Germany.
Klinikum Bremerhaven Reinkenheide gGmbH, Bremerhaven, Germany.
JMIR Hum Factors. 2024 Apr 26;11:e48218. doi: 10.2196/48218.
In the medical field of obstetrics, communication plays a crucial role, and pregnant women, in particular, can benefit from interventions improving their self-reported communication behavior. Effective communication behavior can be understood as the correct transmission of information without misunderstanding, confusion, or losses. Although effective communication can be trained by patient education, there is limited research testing this systematically with an app-based digital intervention. Thus, little is known about the success of such a digital intervention in the form of a web-app, potential behavioral barriers for engagement, as well as the processes by which such a web-app might improve self-reported communication behavior.
This study fills this research gap by applying a web-app aiming at improving pregnant women's communication behavior in clinical care. The goals of this study were to (1) uncover the potential risk factors for early dropout from the web-app and (2) investigate the social-cognitive factors that predict self-reported communication behavior after having used the web-app.
In this study, 1187 pregnant women were recruited. They all started to use a theory-based web-app focusing on intention, planning, self-efficacy, and outcome expectancy to improve communication behavior. Mechanisms of behavior change as a result of exposure to the web-app were explored using stepwise regression and path analysis. Moreover, determinants of dropout were tested using logistic regression.
We found that dropout was associated with younger age (P=.014). Mechanisms of behavior change were consistent with the predictions of the health action process approach. The stepwise regression analysis revealed that action planning was the best predictor for successful behavioral change over the course of the app-based digital intervention (β=.331; P<.001). The path analyses proved that self-efficacy beliefs affected the intention to communicate effectively, which in turn, elicited action planning and thereby improved communication behavior (β=.017; comparative fit index=0.994; Tucker-Lewis index=0.971; root mean square error of approximation=0.055).
Our findings can guide the development and improvement of apps addressing communication behavior in the following ways in obstetric care. First, such tools would enable action planning to improve communication behavior, as action planning is the key predictor of behavior change. Second, younger women need more attention to keep them from dropping out. However, future research should build upon the gained insights by conducting similar internet interventions in related fields of clinical care. The focus should be on processes of behavior change and strategies to minimize dropout rates, as well as replicating the findings with patient safety measures.
ClinicalTrials.gov identifier: NCT03855735; https://classic.clinicaltrials.gov/ct2/show/NCT03855735.
在妇产科医学领域，沟通起着至关重要的作用，尤其是孕妇，她们可以从改善自我报告沟通行为的干预措施中受益。有效的沟通行为可以理解为正确传递信息，而不会产生误解、混淆或信息丢失。虽然可以通过患者教育来培养有效的沟通能力，但系统地利用基于应用程序的数字干预措施进行测试的研究有限。因此，对于以网络应用程序形式出现的这种数字干预措施的成功程度、潜在的参与行为障碍以及该网络应用程序可能改善自我报告沟通行为的过程知之甚少。
本研究通过应用旨在改善临床护理中孕妇沟通行为的网络应用程序来填补这一研究空白。本研究的目的是：（1）揭示早期退出网络应用程序的潜在风险因素；（2）研究使用网络应用程序后预测自我报告沟通行为的社会认知因素。
本研究招募了 1187 名孕妇。她们都开始使用一个基于理论的网络应用程序，该应用程序专注于意图、计划、自我效能和结果预期，以改善沟通行为。使用逐步回归和路径分析探索由于暴露于网络应用程序而产生的行为变化机制。此外，使用逻辑回归测试辍学的决定因素。
我们发现，年龄较小（P=.014）与辍学有关。行为变化的机制与健康行动过程方法的预测一致。逐步回归分析显示，行动规划是基于应用程序的数字干预过程中成功行为改变的最佳预测因素（β=.331；P<.001）。路径分析证明，自我效能信念影响有效沟通的意愿，进而激发行动计划，并由此改善沟通行为（β=.017；比较拟合指数=0.994；Tucker-Lewis 指数=0.971；均方根误差近似值=0.055）。
我们的发现可以指导在以下方面开发和改进针对妇产科护理中沟通行为的应用程序：首先，此类工具可以通过行动计划来改善沟通行为，因为行动计划是行为改变的关键预测因素。其次，需要更加关注年轻女性，以防止她们辍学。然而，未来的研究应该在相关临床护理领域开展类似的互联网干预研究的基础上，进一步深入了解。重点应放在行为改变过程和降低辍学率的策略上，以及用患者安全措施复制这些发现。
ClinicalTrials.gov 标识符：NCT03855735；https://classic.clinicaltrials.gov/ct2/show/NCT03855735。
