Which Feature is Unusable? Detecting Usability and User Experience Issues from User Reviews

2017 ◽  
Author(s):  
Elsa Bakiu ◽  
Emitza Guzman
Keyword(s):  
User Experience ◽  
User Reviews

Detecting Usability and User Experience Issues in Stroke Caregiving Apps: An Analysis of User Reviews (Preprint)

2021 ◽  
Author(s):  
Elton Lobo ◽  
Mohamed Abdelrazek ◽  
Anne Frølich ◽  
Lene Juel Rasmussen ◽  
Patricia M. Livingston ◽  
...  
Keyword(s):  
Sentiment Analysis ◽  
User Experience ◽  
Participatory Design ◽  
User Participation ◽  
User Reviews ◽  
App Store ◽  
Healthcare Needs ◽  
Recovery Trajectory ◽  
Mhealth Apps

BACKGROUND Stroke caregivers often experience negative impacts when caring for a person living with a stroke. Technologically based interventions such as mHealth apps have demonstrated potential in supporting the caregivers during the recovery trajectory. Hence, there is an increase in apps in popular app stores, with a few apps addressing the healthcare needs of stroke caregivers. Since most of these apps were published without explanation of their design and evaluation processes, it is necessary to identify the usability and user experience issues to help app developers and researchers to understand the factors that affect long-term adherence and usage in stroke caregiving technology. OBJECTIVE The purpose of this study was to determine the usability and user experience issues in commercially available mHealth apps from the user reviews published within the app store to help researchers and developers understand the factors that may affect long-term adherence and usage. METHODS User reviews were extracted from the previously identified 47 apps that support stroke caregiving needs using a python-scraper for both app stores (i.e. Google Play Store and Apple App Store). The reviews were pre-processed to (i) clean the dataset and ensure unicode normalization, (ii) remove stop words and (iii) group words together with similar meanings. The pre-processed reviews were filtered using sentiment analysis to exclude positive and non-English reviews. The final corpus was classified based on usability and user experience dimensions to highlight issues within the app. RESULTS Of 1,385,337 user reviews, only 162,095 were extracted due to the limitations in the app store. After filtration based on the sentiment analysis, 15,818 reviews were included in the study and were filtered based on the usability and user experience dimensions. Findings from the usability and user experience dimensions highlight critical errors/effectiveness, efficiency and support that contribute to decreased satisfaction, affect and emotion and frustration in using the app. CONCLUSIONS Commercially available mHealth apps consist of several usability and user experience issues due to their inability to understand the methods to address the healthcare needs of the caregivers. App developers need to consider participatory design approaches to promote user participation in design. This might ensure better understanding of the user needs and methods to support these needs; therefore, limiting any issues and ensuring continued use.

A Sentiment Analysis of User Reviews of Depression Apps Features (Preprint)

2019 ◽  
Author(s):  
Julien Meyer
Keyword(s):  
Natural Language ◽  
User Experience ◽  
Negative Emotions ◽  
Therapeutic Treatment ◽  
Medical Assessment ◽  
User Reviews ◽  
Barriers To Access ◽  
Single Feature ◽  
Starting Point ◽  
Mhealth Apps

BACKGROUND Mhealth apps are promising to overcome barriers to access mental health care. Adoption and continuous use, however, depends on users’ decisions. App reviews both reflect and influence users’ attitude and experience towards apps and influence their propensity to use mhealth apps. OBJECTIVE We investigate user app reviews on specific features in depression apps (psychoeducation, medical assessment, therapeutic treatment, supportive resources and entertainment). METHODS We extracted 3,261 user reviews of depression apps, isolated reviews associated with single feature apps. We then analyzed reviews using LIWC, a natural language analytical tool and contrasted language patterns associated with different features. RESULTS Medical Assessment features stand out for the strong negative emotions and negative ratings they generate, as users receive potentially disturbing feedback on their condition. Symptom Management and Entertainment features generate less negative emotions and anxiety. Therapeutic Treatment features also generate more positive and fewer negative emotions, even though user experience is less authentic (i.e., reflecting a personal experience). CONCLUSIONS Developers should be cautious in their choice of features when they are targeting potentially vulnerable users. Medical assessment feedback being riskier while offering information, contacts or even games may be a safer starting point to engage people with depression. App features emerged as a key dimension to consider when investigating user experience with mhealth apps. Methodologically, app reviews can be leveraged to investigate specific app features at the level of a family of apps. Specifically, Natural Language Analysis proved to be a responsive tool to investigate behaviors related to a quickly changing app environment.

scholarly journals User Experience of Cognitive Behavioral Therapy Apps for Depression: An Analysis of App Functionality and User Reviews

10.2196/10120 ◽  
2018 ◽  
Vol 20 (6) ◽  
pp. e10120 ◽  
Author(s):  
Katarzyna Stawarz ◽  
Chris Preist ◽  
Debbie Tallon ◽  
Nicola Wiles ◽  
David Coyle
Keyword(s):  
Cognitive Behavioral Therapy ◽  
User Experience ◽  
Behavioral Therapy ◽  
Cognitive Behavioral ◽  
User Reviews

scholarly journals User Experience of Cognitive Behavioral Therapy Apps for Depression: An Analysis of App Functionality and User Reviews (Preprint)

2018 ◽  
Author(s):  
Katarzyna Stawarz ◽  
Chris Preist ◽  
Debbie Tallon ◽  
Nicola Wiles ◽  
David Coyle
Keyword(s):  
Mental Health ◽  
Cognitive Behavioral Therapy ◽  
User Experience ◽  
Behavioral Therapy ◽  
Well Being ◽  
Cognitive Behavioral ◽  
Evidence Based ◽  
User Reviews ◽  
Mental Well Being ◽  
Health And Well Being

BACKGROUND Hundreds of mental health apps are available to the general public. With increasing pressures on health care systems, they offer a potential way for people to support their mental health and well-being. However, although many are highly rated by users, few are evidence-based. Equally, our understanding of what makes apps engaging and valuable to users is limited. OBJECTIVE The aim of this paper was to analyze functionality and user opinions of mobile apps purporting to support cognitive behavioral therapy for depression and to explore key factors that have an impact on user experience and support engagement. METHODS We systematically identified apps described as being based on cognitive behavioral therapy for depression. We then conducted 2 studies. In the first, we analyzed the therapeutic functionality of apps. This corroborated existing work on apps’ fidelity to cognitive behavioral therapy theory, but we also extended prior work by examining features designed to support user engagement. Engagement features found in cognitive behavioral therapy apps for depression were compared with those found in a larger group of apps that support mental well-being in a more general sense. Our second study involved a more detailed examination of user experience, through a thematic analysis of publicly available user reviews of cognitive behavioral therapy apps for depression. RESULTS We identified 31 apps that purport to be based on cognitive behavioral therapy for depression. Functionality analysis (study 1) showed that they offered an eclectic mix of features, including many not based on cognitive behavioral therapy practice. Cognitive behavioral therapy apps used less varied engagement features compared with 253 other mental well-being apps. The analysis of 1287 user reviews of cognitive behavioral therapy apps for depression (study 2) showed that apps are used in a wide range of contexts, both replacing and augmenting therapy, and allowing users to play an active role in supporting their mental health and well-being. Users, including health professionals, valued and used apps that incorporated both core cognitive behavioral therapy and non-cognitive behavioral therapy elements, but concerns were also expressed regarding the unsupervised use of apps. Positivity was seen as important to engagement, for example, in the context of automatic thoughts, users expressed a preference to capture not just negative but also positive ones. Privacy, security, and trust were crucial to the user experience. CONCLUSIONS Cognitive behavioral therapy apps for depression need to improve with respect to incorporating evidence-based cognitive behavioral therapy elements. Equally, a positive user experience is dependent on other design factors, including consideration of varying contexts of use. App designers should be able to clearly identify the therapeutic basis of their apps, but they should also draw on evidence-based strategies to support a positive and engaging user experience. The most effective apps are likely to strike a balance between evidence-based cognitive behavioral therapy strategies and evidence-based design strategies, including the possibility of eclectic therapeutic techniques.

scholarly journals Insights from user reviews to improve mental health apps

2020 ◽  
Vol 26 (3) ◽  
pp. 2042-2066 ◽  
Author(s):  
Felwah Alqahtani ◽  
Rita Orji
Keyword(s):  
Mental Health ◽  
User Experience ◽  
Mobile App ◽  
Security And Privacy ◽  
Great Promise ◽  
Health Issues ◽  
User Reviews ◽  
Health Apps ◽  
Mental Health Issues ◽  
Health Applications

Mental health applications hold great promise as interventions for addressing common mental issues. Although many people with mental health issues use mobile app interventions, their adherence level remains low. Low engagement affects the effectiveness of mobile interventions. However, there is still a dearth of research to explain the reasons for low engagement. User experience and usability are two factors that determine the adoption and usage of apps. Analyzing user reviews of mobile apps for mental health issues reveals user experience and what features users liked and disliked in the apps and hence informs future app design and refinements. This research aims to analyze user reviews of publicly available mental health applications to uncover their strengths, weaknesses, and gaps, hence revealing why users are likely to cease using these applications. We mined reviews of 106 mental health apps retrieved from Apple’s App Store and Google Play and employed thematic analysis on 13,549 reviews. The review analysis shows that users placed more emphasis on the user interface and the user-friendliness of the app. Users also appreciated apps that present them with a variety of options, functionalities, and content that they can choose. Again, apps that offer adaptive functionalities that allow users to adapt some app features also received high ratings. In contrast, poor usability emerged as the most common reason for abandoning mental health apps. Other pitfalls include lack of a content variety, lack of personalization, lack of customer service and trust, and security and privacy issues.

Assessing User Experience with Crutch Use

2011 ◽  
Author(s):  
Christina Harrington ◽  
Sharon Joines
Keyword(s):  
User Experience
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