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.

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.

scholarly journals Creating Gameful Design in mHealth: A Participatory Co-Design Approach (Preprint)

2018 ◽  
Author(s):  
Stian Jessen ◽  
Jelena Mirkovic ◽  
Cornelia M Ruland
Keyword(s):  
Chronic Conditions ◽  
Participatory Design ◽  
Design Approach ◽  
Self Management ◽  
Chronic Patients ◽  
Starting Point ◽  
Wide Range ◽  
Design Activities ◽  
The Look ◽  
Mhealth Apps

BACKGROUND Gameful designs (gamification), using design pieces and concepts typically found in the world of games, is a promising approach to increase users’ engagement with, and adherence to, electronic health and mobile health (mHealth) tools. Even though both identifying and addressing users’ requirements and needs are important steps of designing information technology tools, little is known about the users’ requirements and preferences for gameful designs in the context of self-management of chronic conditions. OBJECTIVE This study aimed to present findings as well as the applied methods and design activities from a series of participatory design workshops with patients with chronic conditions, organized to generate and explore user needs, preferences, and ideas to the implementation of gameful designs in an mHealth self-management app. METHODS We conducted three sets of two consecutive co-design workshops with a total of 22 participants with chronic conditions. In the workshops, we applied participatory design methods to engage users in different activities such as design games, scenario making, prototyping, and sticky notes exercises. The workshops were filmed, and the participants’ interactions, written products, ideas, and suggestions were analyzed thematically. RESULTS During the workshops, the participants identified a wide range of requirements, concerns, and ideas for using the gameful elements in the design of an mHealth self-management app. Overall inputs on the design of the app concerned aspects such as providing a positive user experience by promoting collaboration and not visibly losing to someone or by designing all feedback in the app to be uplifting and positive. The participants provided both general inputs (regarding the degree of competitiveness, use of rewards, or possibilities for customization) and specific inputs (such as being able to customize the look of their avatars or by having rewards that can be exchanged for real-world goods in a gift shop). However, inputs also highlighted the importance of making tools that provide features that are meaningful and motivating on their own and do not only have to rely on gameful design features to make people use them. CONCLUSIONS The main contribution in this study was users’ contextualized and richly described needs and requirements for gamefully designed mHealth tools for supporting chronic patients in self-management as well as the methods and techniques used to facilitate and support both the participant’s creativity and communication of ideas and inputs. The range, variety, and depth of the inputs from our participants also showed the appropriateness of our design approach and activities. These findings may be combined with literature and relevant theories to further inform in the selection and application of gameful designs in mHealth apps, or they can be used as a starting point for conducting more participatory workshops focused on co-designing gameful health apps.

Improving Learner Experience Within Educational Nooks in Digital Libraries

2018 ◽  
pp. 174-193 ◽  
Author(s):  
Desislava Paneva-Marinova ◽  
Radoslav Pavlov
Keyword(s):  
User Experience ◽  
Digital Library ◽  
Digital Libraries ◽  
Educational Games ◽  
Learning Experience ◽  
Learning Tools ◽  
Experience Design ◽  
Smart Learning ◽  
Starting Point ◽  
Art And Culture

This chapter presents solutions for personalized observation and enhanced learning experience in digital libraries (DLs) by special smart educational nooks. Main factors related to the DLs user experience and content usability issues are considered. During the user experience design, the users' needs, goals, preferences, and interests have been carefully studied and have become the starting point for the new DLs functionality development. This chapter demonstrates several educational nooks or their components, such as learning tools in a digital library for fashion objects, a smart learning corner in an iconographical art digital library, an ontology of learning analysis method, and some educational games for art and culture in which authors are co-developers.

scholarly journals Dreaming during Covid-19 pandemic: Computational assessment of dreams reveals mental suffering and fear of contagion

2020 ◽  
Author(s):  
Natalia B Mota ◽  
Janaina Weissheimer ◽  
Marina Ribeiro ◽  
Mizziara De Paiva ◽  
Juliana D'Avila ◽  
...  
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Social Isolation ◽  
Language Processing ◽  
Negative Emotions ◽  
Global Threat

Neuroscience and psychology agree that dreaming helps to cope with negative emotions and learn from experience. The current global threat related to the COVID-19 pandemic led to widespread social isolation. Does dreaming change and/or reflect mental suffering? To address these questions, we applied natural language processing tools to study 239 dream reports from 67 individuals either before the Covid-19 outbreak or during March-April, 2020, when quarantine was imposed in Brazil following the pandemic announcement by the WHO. Pandemic dreams showed a higher proportion of anger and sadness words and higher average semantic similarities to the terms contamination and cleanness. These features were associated with mental suffering related to social isolation, as they explained 39% of the variance in PANSS negative subscale (p=0.0092). These results corroborate the hypothesis that pandemic dreams reflect mental suffering, fear of contagion, and important changes in daily habits.

Database Tuning using Natural Language Processing

2021 ◽  
Vol 50 (3) ◽  
pp. 27-28
Author(s):  
Immanuel Trummer
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Training Data ◽  
Language Models ◽  
Learning Approaches ◽  
Training Samples ◽  
Starting Point ◽  
Training Cost ◽  
Transformer Model

Introduction. We have seen significant advances in the state of the art in natural language processing (NLP) over the past few years [20]. These advances have been driven by new neural network architectures, in particular the Transformer model [19], as well as the successful application of transfer learning approaches to NLP [13]. Typically, training for specific NLP tasks starts from large language models that have been pre-trained on generic tasks (e.g., predicting obfuscated words in text [5]) for which large amounts of training data are available. Using such models as a starting point reduces task-specific training cost as well as the number of required training samples by orders of magnitude [7]. These advances motivate new use cases for NLP methods in the context of databases.

Scientific and Design Understandings of Aesthetics

2021 ◽  
Vol 65 (1) ◽  
pp. 380-384
Author(s):  
Dahlia Alharoon ◽  
Douglas J. Gillan ◽  
Carina Lei
Keyword(s):  
Individual Differences ◽  
User Experience ◽  
Scientific Research ◽  
Present Review ◽  
Research Opportunities ◽  
Aesthetic Responses ◽  
Starting Point ◽  
Aesthetic Preferences

User Experience (UX) extends the construct of usability by an additional focus on emotion, motivation and aesthetics. An emphasis on aesthetics has been undertaken to a greater extent by design disciplines than by science. The present review examines both design and scientific approaches to aesthetics in order to integrate the two approaches and identify research opportunities that could result in science based design principals. The review of design approaches to aesthetics indicates the primary importance of balance as an element of design. Accordingly, research on the role of balance in producing aesthetic responses from users is a reasonable starting point for a program of research. Additionally, the analysis of aesthetic metrics and individual differences in aesthetic preferences in scientific research are discussed as possible collaboration areas for designers.

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