scholarly journals Evaluation of a Web-Based Stress Management Application—a Feasibility Study

2018 ◽  
Vol 3 (3) ◽  
pp. 150-160 ◽  
Author(s):  
Caroline Eklund ◽  
Magnus L. Elfström ◽  
Yvonne Eriksson ◽  
Anne Söderlund
10.2196/11493 ◽  
2019 ◽  
Vol 8 (1) ◽  
pp. e11493 ◽  
Author(s):  
Dilfa Juniar ◽  
Wouter van Ballegooijen ◽  
Eirini Karyotaki ◽  
Anneke van Schaik ◽  
Jan Passchier ◽  
...  

2018 ◽  
Author(s):  
Dilfa Juniar ◽  
Wouter van Ballegooijen ◽  
Eirini Karyotaki ◽  
Anneke van Schaik ◽  
Jan Passchier ◽  
...  

BACKGROUND The number of university students experiencing stress is increasing, which often leads to adverse effects such as poor grades, academic probation, and emotional problems. Unfortunately, most of these problems remain untreated because of limited professional resources and fear of stigma. Several Web-based stress management interventions are now available for student populations, but these treatments are not yet available in Indonesia. To make treatment for stress more acceptable in Indonesia, a cultural adaptation process is needed, and part of the process is assessing the feasibility of the adapted intervention. OBJECTIVE This paper describes the first two stages of a cultural adaptation process and the protocol of a feasibility study that will assess the acceptability of a culturally adapted stress management intervention for university students in Indonesia. METHODS Focus group discussions with Indonesian university students were held, and input from Indonesian psychologists was gathered for developing the adapted intervention. A single-group feasibility study with a pre-post design will be conducted. We will recruit at minimum 50 university students who have an elevated level of stress (Depression, Anxiety, and Stress Scales–42 stress subscale score ≥15), identify themselves as being of Indonesian culture (eg, able to speak Bahasa Indonesia fluently), and are studying at a university in Indonesia. The primary endpoints of this study will be rates of participant satisfaction, system usability, dropout rates, and level of adherence. We will also use qualitative data to assess the adapted intervention more thoroughly. Secondary study endpoints will be quality of life, stress, anxiety, and depression levels. Feasibility parameters (eg, participant satisfaction, system usability, and level of adherence) will be summarized with descriptive statistics. Two-tailed paired within-group t tests will be used to analyze stress, anxiety, depression, and quality of life. RESULTS The enrollment of pilot study is currently ongoing. First results are expected to be ready for analysis in the second half of 2019. The project was funded as part of a PhD trajectory in 2015 by the Indonesian Endowment Fund for Education. CONCLUSIONS This is one of the first studies to assess the feasibility of a culturally adapted Web-based stress management intervention for university students in Indonesia. Strengths and limitations of the study are discussed. INTERNATIONAL REGISTERED REPOR DERR1-10.2196/11493


2018 ◽  
Vol 57 (7) ◽  
pp. 924-934 ◽  
Author(s):  
Heleen C. Melissant ◽  
Irma M. Verdonck-de Leeuw ◽  
Birgit I. Lissenberg-Witte ◽  
Inge R. Konings ◽  
Pim Cuijpers ◽  
...  

2020 ◽  
Author(s):  
Matthew Louis Mauriello ◽  
Nantanick Tantivasadakarn ◽  
Marco Antonio Mora-Mendoza ◽  
Emmanuel Thierry Lincoln ◽  
Grace Hon ◽  
...  

BACKGROUND Approximately 60%-80% of the primary care visits have a psychological stress component, but only 3% of patients receive stress management advice during these visits. Given recent advances in natural language processing, there is renewed interest in mental health chatbots. Conversational agents that can understand a user’s problems and deliver advice that mitigates the effects of daily stress could be an effective public health tool. However, such systems are complex to build and costly to develop. OBJECTIVE To address these challenges, our aim is to develop and evaluate a fully automated mobile suite of shallow chatbots—we call them Popbots—that may serve as a new species of chatbots and further complement human assistance in an ecosystem of stress management support. METHODS After conducting an exploratory Wizard of Oz study (N=14) to evaluate the feasibility of a suite of multiple chatbots, we conducted a web-based study (N=47) to evaluate the implementation of our prototype. Each participant was randomly assigned to a different chatbot designed on the basis of a proven cognitive or behavioral intervention method. To measure the effectiveness of the chatbots, the participants’ stress levels were determined using self-reported psychometric evaluations (eg, web-based daily surveys and Patient Health Questionnaire-4). The participants in these studies were recruited through email and enrolled on the web, and some of them participated in follow-up interviews that were conducted in person or on the web (as necessary). RESULTS Of the 47 participants, 31 (66%) completed the main study. The findings suggest that the users viewed the conversations with our chatbots as helpful or at least neutral and came away with increasingly positive sentiment toward the use of chatbots for proactive stress management. Moreover, those users who used the system more often (ie, they had more than or equal to the median number of conversations) noted a decrease in depression symptoms compared with those who used the system less often based on a Wilcoxon signed-rank test (W=91.50; Z=−2.54; <i>P</i>=.01; <i>r</i>=0.47). The follow-up interviews with a subset of the participants indicated that half of the common daily stressors could be discussed with chatbots, potentially reducing the burden on human coping resources. CONCLUSIONS Our work suggests that suites of shallow chatbots may offer benefits for both users and designers. As a result, this study’s contributions include the design and evaluation of a novel suite of shallow chatbots for daily stress management, a summary of benefits and challenges associated with random delivery of multiple conversational interventions, and design guidelines and directions for future research into similar systems, including authoring chatbot systems and artificial intelligence–enabled recommendation algorithms.


2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Thomas van der Velden ◽  
Bianca W. M. Schalk ◽  
Mirjam Harmsen ◽  
Guido Adriaansens ◽  
Tjard R. Schermer ◽  
...  

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