Thematic Analysis Using A Machine Learning Approach on User Reviews for Depression and Anxiety Chatbot Applications (Preprint)

2021 ◽  
Author(s):  
Arfan Ahmed ◽  
Sarah Aziz ◽  
Uzair Shah ◽  
Asmaa Hassan ◽  
Alaa Abd-Alrazaq ◽  
...  
Keyword(s):  
Thematic Analysis ◽  
User Interfaces ◽  
Latent Dirichlet Allocation ◽  
Low Cost ◽  
Methodological Approach ◽  
Anxiety And Depression ◽  
Depression Symptoms ◽  
Machine Learning Approach ◽  
Google Play ◽  
Privacy Issues

BACKGROUND Anxiety and depression are amongst the most commonly prevalent mental health disorders (CMDs) worldwide. Chatbot apps can play an important role in relieving anxiety and depression. Users’ reviews of chatbot apps are considered an important source of data to explore users’ opinion and satisfaction of chatbot apps. OBJECTIVE This study aims to explore users’ opinions, satisfaction, and attitudes about anxiety and depression chatbot apps through conducting a thematic analysis of users’ reviews of 11 anxiety and depression chatbot apps collected from Google play and Apple store. In addition, we propose a workflow to provide a methodological approach for future analysis of review comments. METHODS We analyzed 205,881 user review comments from chatbots dedicated for users with anxiety and depression symptoms. Using scrapper tools (Google Play Scraper and App Store Scraper python libraries), we extracted text and metadata. The reviews were divided into positive and negative meta themes, based on users rating per review. We analysed the reviews using word frequencies of bigrams (words in pair).A topic modelling technique, Latent Dirichlet Allocation (LDA) was applied to identify topics in the reviews, and analysed for detecting themes and subthemes. RESULTS A thematic analysis was conducted on 5 topics for each sentimental set. Reviews were categorized as either positive or negative. For positive reviews, the main themes were confidence and affirmation building, adequate analysis, and consultation, caring as a friend, and easy to use. Whereas for negative reviews results revealed the following themes: usability issues, update Issues, Privacy and Non-creative conversation. CONCLUSIONS Chatbots appear to have the ability to provide users suffering from anxiety and depression feel confident and give them support via a tool that is easy to use, low cost, containing adequate symptom detection whilst providing feeling of having a close friend to converse with. Users tend to dislike technical and privacy issues. Users expect engaging and creative conversations via appealing user interfaces.

scholarly journals Acceptability and Effectiveness of Artificial Intelligence Therapy for Anxiety and Depression (Youper): Longitudinal Observational Study

10.2196/26771 ◽  
2021 ◽  
Vol 23 (6) ◽  
pp. e26771
Author(s):  
Ashish Mehta ◽  
Andrea Nicole Niles ◽  
Jose Hamilton Vargas ◽  
Thiago Marafon ◽  
Diego Dotta Couto ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Emotion Regulation ◽  
Low Cost ◽  
Mobile App ◽  
Anxiety And Depression ◽  
Depression Symptoms ◽  
Symptom Reduction ◽  
Depression Symptom ◽  
Longitudinal Observational Study ◽  
Small Effect Size

Background Youper is a widely used, commercially available mobile app that uses artificial intelligence therapy for the treatment of anxiety and depression. Objective Our study examined the acceptability and effectiveness of Youper. Further, we tested the cumulative regulation hypothesis, which posits that cumulative emotion regulation successes with repeated intervention engagement will predict longer-term anxiety and depression symptom reduction. Methods We examined data from paying Youper users (N=4517) who allowed their data to be used for research. To characterize the acceptability of Youper, we asked users to rate the app on a 5-star scale and measured retention statistics for users’ first 4 weeks of subscription. To examine effectiveness, we examined longitudinal measures of anxiety and depression symptoms. To test the cumulative regulation hypothesis, we used the proportion of successful emotion regulation attempts to predict symptom reduction. Results Youper users rated the app highly (mean 4.36 stars, SD 0.84), and 42.66% (1927/4517) of users were retained by week 4. Symptoms decreased in the first 2 weeks of app use (anxiety: d=0.57; depression: d=0.46). Anxiety improvements were maintained in the subsequent 2 weeks, but depression symptoms increased slightly with a very small effect size (d=0.05). A higher proportion of successful emotion regulation attempts significantly predicted greater anxiety and depression symptom reduction. Conclusions Youper is a low-cost, completely self-guided treatment that is accessible to users who may not otherwise access mental health care. Our findings demonstrate the acceptability and effectiveness of Youper as a treatment for anxiety and depression symptoms and support continued study of Youper in a randomized clinical trial.

scholarly journals Acceptability and Effectiveness of Artificial Intelligence Therapy for Anxiety and Depression (Youper): Longitudinal Observational Study (Preprint)

2020 ◽  
Author(s):  
Ashish Mehta ◽  
Andrea Nicole Niles ◽  
Jose Hamilton Vargas ◽  
Thiago Marafon ◽  
Diego Dotta Couto ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Emotion Regulation ◽  
Low Cost ◽  
Mobile App ◽  
Anxiety And Depression ◽  
Depression Symptoms ◽  
Symptom Reduction ◽  
Depression Symptom ◽  
Longitudinal Observational Study ◽  
Small Effect Size

BACKGROUND Youper is a widely used, commercially available mobile app that uses artificial intelligence therapy for the treatment of anxiety and depression. OBJECTIVE Our study examined the acceptability and effectiveness of Youper. Further, we tested the cumulative regulation hypothesis, which posits that cumulative emotion regulation successes with repeated intervention engagement will predict longer-term anxiety and depression symptom reduction. METHODS We examined data from paying Youper users (N=4517) who allowed their data to be used for research. To characterize the acceptability of Youper, we asked users to rate the app on a 5-star scale and measured retention statistics for users’ first 4 weeks of subscription. To examine effectiveness, we examined longitudinal measures of anxiety and depression symptoms. To test the cumulative regulation hypothesis, we used the proportion of successful emotion regulation attempts to predict symptom reduction. RESULTS Youper users rated the app highly (mean 4.36 stars, SD 0.84), and 42.66% (1927/4517) of users were retained by week 4. Symptoms decreased in the first 2 weeks of app use (anxiety: <i>d</i>=0.57; depression: <i>d</i>=0.46). Anxiety improvements were maintained in the subsequent 2 weeks, but depression symptoms increased slightly with a very small effect size (<i>d</i>=0.05). A higher proportion of successful emotion regulation attempts significantly predicted greater anxiety and depression symptom reduction. CONCLUSIONS Youper is a low-cost, completely self-guided treatment that is accessible to users who may not otherwise access mental health care. Our findings demonstrate the acceptability and effectiveness of Youper as a treatment for anxiety and depression symptoms and support continued study of Youper in a randomized clinical trial.

App review of anxiety and depression chatbots and their self-care features (Preprint)

2020 ◽  
Author(s):  
Arfan Ahmed ◽  
Nashva ALi ◽  
Sarah Aziz ◽  
Alaa A Abd-Alrazaq ◽  
Asmaa Hassan ◽  
...  
Keyword(s):  
Mental Health ◽  
Meta Analysis ◽  
Self Care ◽  
Anxiety And Depression ◽  
Conversational Agents ◽  
Eligibility Criteria ◽  
On Demand ◽  
User Ratings ◽  
Google Play

BACKGROUND Anxiety and depression rates are at an all-time high along with other mental health disorders. Smartphone-based mental health chatbots or conversational agents can aid psychiatrists and replace some of the costly human based interaction and represent a unique opportunity to expand the availability and quality of mental health services and treatment. Regular up-to-date reviews will allow medics and individuals to recommend or use anxiety and depression related smartphone based chatbots with greater confidence. OBJECTIVE Assess the quality and characteristics of chatbots for anxiety and depression available on Android and iOS systems. METHODS A search was performed in the App Store and Google Play Store following the Preferred Reporting Items for Systematic reviews and Meta-Analysis (PRISMA) protocol to identify existing chatbots for anxiety and depression. Eligibility of the chatbots was assessed by two individuals based on predefined eligibility criteria. Meta-data of the included chatbots and their characteristics were extracted from their description and upon installation by 2 reviewers. Finally, chatbots quality information was assessed by following the mHONcode principles. RESULTS Although around 1000 anxiety and depression related chatbots exist, only a few (n=11) contained actual chatbots that could provide the user a real substitute for a human-human based interaction, even with today's Artificial Intelligence advancements, only one of these chatbots had voice as an input/output modality. Of the selected apps that contained chatbots all were clearly built with a therapeutic human substitute goal in mind. The majority had high user ratings and downloads highlighting the popularity of such chatbots and their promising future within the realm of anxiety and depression. CONCLUSIONS Anxiety and depression chatbot apps have the potential to increase the capacity of mental health self-care providing much needed assistance to professionals. In the current covid-19 pandemic, chatbots can also serve as a conversational companion with the potential of combating loneliness, especially in lockdowns where there is a lack of social interaction. Due to the ubiquitous nature of chatbots users can access them on-demand at the touch of a screen on ones’ smartphone. Self-care interventions are known to be effective and exist in various forms and some can be made available as chatbot features, such as assessment, mood tracking, medicine tracking, or simply providing conversation in times of loneliness.

Childhood Material Hardship and Adolescent Mental Health

2021 ◽  
pp. 0044118X2110018
Author(s):  
Chrisse Edmunds ◽  
Melissa Alcaraz
Keyword(s):  
Mental Health ◽  
Adolescent Depression ◽  
Adolescent Mental Health ◽  
Anxiety And Depression ◽  
Fragile Families ◽  
Depression Symptoms ◽  
Depression And Anxiety ◽  
Material Hardship ◽  
Critical Age ◽  
The Relationship

Adolescent mental health has implications for current and future wellbeing. While a link exists between poverty and mental health, little is known about how experiencing material hardship, such as insecurity of food, housing, utilities, and medical care, throughout early childhood affects adolescent mental health. We examine the relationship between material hardship in childhood and adolescent mental health. We use Poisson regression to examine the effect of material hardship experienced at different stages of childhood on adolescent depression and anxiety outcomes at age 15. We use longitudinal data from the Fragile Families and Child Wellbeing Study ( N = 3,222). We find that recently experiencing material hardship during childhood is positively and significantly associated with anxiety and depression symptoms at age 15, even when controlling for material hardship at age 15. Additionally, we find that insecurity during mid-childhood and the stress of lacking basic needs during a critical age may influence mental health in adolescence.

scholarly journals Prevalence of anxiety and depression symptoms in pregnant women with type 2 diabetes and the impact on glycaemic control

2020 ◽  
Author(s):  
Björg Ásbjörnsdóttir ◽  
Marianne Vestgaard ◽  
Nicoline C. Do ◽  
Lene Ringholm ◽  
Lise L.T. Andersen ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Glycaemic Control ◽  
Pregnant Women ◽  
Anxiety And Depression ◽  
Depression Symptoms ◽  
The Impact

scholarly journals Exploring the Frequency of Anxiety and Depression Symptoms in a Brazilian Sample during the COVID-19 Outbreak

2021 ◽  
Vol 18 (9) ◽  
pp. 4847
Author(s):  
Fabiana Silva Ribeiro ◽  
Flávia H. Santos ◽  
Luis Anunciação ◽  
Lucas Barrozo ◽  
Jesus Landeira-Fernandez ◽  
...  
Keyword(s):  
Mental Health Professionals ◽  
Online Survey ◽  
Age Groups ◽  
Health Sector ◽  
Severe Depression ◽  
Well Being ◽  
Sociodemographic Factors ◽  
Anxiety And Depression ◽  
Depression Symptoms ◽  
Brazilian Sample

The COVID-19 pandemic is a public health emergency of international concern, and the main measures to contain the spread of the coronavirus causing COVID-19 were social distancing, quarantine, and self-isolation. Although these policies are effective in containing the spread of the virus, they might represent a challenge to psychological well-being, increasing levels of depressive and anxiety-related symptoms. Aims: We explored the frequency of anxiety and depression symptoms during COVID-19 restrictions and associations with sociodemographic factors in a Brazilian sample. Method: Data of a total of 936 Brazilian adults (68.2% women) aged 18 to 77 years old (M = 38.95, SD = 13.91) were collected through an online survey. Results: In general, we observed a frequency of 17.36% for severe anxiety and 66.13% for severe depression symptoms, in which younger participants (18–39 years old) and women showed higher scores in anxiety and depression scales compared to older age groups. Logistic regressions showed that women were more likely to present severe symptoms of anxiety (20.4%) compared to men (10.9%), as well as respondents in the educational sector (24.3%) compared to those in the health sector (10%). Conclusions: We highlight the importance of mental health professionals in developing strategies to help younger adults to mitigate the effects of social restriction.

scholarly journals Caregiver burden versus intensity of anxiety and depression symptoms in parents of children with cerebral palsy as well as factors potentially differentiating the level of burden: a cross-sectional study (Poland)

BMJ Open ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. e036494
Author(s):  
Barbara Gugała
Keyword(s):  
Cerebral Palsy ◽  
Health Status ◽  
Caregiver Burden ◽  
Depression Scale ◽  
Secondary Outcome ◽  
Anxiety And Depression ◽  
Depression Symptoms ◽  
Emotional Involvement ◽  
Children With Cerebral Palsy ◽  
General Strain

ObjectivesTo assess the relationship between caregiver burden and severity of symptoms of anxiety/depression in parents of children with cerebral palsy (CP), and to identify factors differentiating the level of caregiver burden.SettingRegional rehabilitation centres in South-Eastern Poland.ParticipantsThe study involved 190 parents of children with CP, that is, 138 women and 52 men.Primary and secondary outcome measuresCaregiver burden was assessed using Caregiver Burden Scale (CBS), while the intensity of anxiety and depression symptoms was measured using Hospital Anxiety and Depression Scale (HADS). Potential predictors were examined using Gross Motor Function Classification System for Cerebral Palsy (GMFCS), Barthel Index (BI) as well as a questionnaire focusing on the characteristics of the child, the parent and the family. The analyses applied Pearson’s linear correlation coefficient as well as multiple regression analysis.ResultsAll the CBS measures are significantly correlated to HADS-A (anxiety) and HADS-D (depression). Intensity of anxiety is most visibly linked to CBS measures of disappointment and environment (p<0.0001), while severity of depression is related to emotional involvement and general strain (p<0.0001). The factors differentiating caregiver burden measure in the subscales of general strain (p<0.0001) and social isolation (p<0.0001) include the child’s age and BI, and the parent’s health status; in the subscale of disappointment (p<0.0001)—the child’s age, BI, GMFCS, as well as the parent’s age and health status; in the subscale of emotional involvement (p=0.0007)—BI, and the parent’s health status; in the subscale of environment (p=0.0002)—the child’s age and BI.ConclusionsThere is a positive linear relationship between the caregiver burden measures and severity of anxiety and depression. Effort should be made to relieve caregiver burden in parents of children with CP.

scholarly journals Implementation of a Six-Layer Smart Factory Architecture with Special Focus on Transdisciplinary Engineering Education

Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 2944
Author(s):  
Benjamin James Ralph ◽  
Marcel Sorger ◽  
Benjamin Schödinger ◽  
Hans-Jörg Schmölzer ◽  
Karin Hartl ◽  
...  
Keyword(s):  
Open Source ◽  
User Interfaces ◽  
Industrial Revolution ◽  
Low Cost ◽  
Material Behavior ◽  
Sensor Data ◽  
Management Tool ◽  
Special Focus ◽  
Programming Environments ◽  
Metal Processing

Smart factories are an integral element of the manufacturing infrastructure in the context of the fourth industrial revolution. Nevertheless, there is frequently a deficiency of adequate training facilities for future engineering experts in the academic environment. For this reason, this paper describes the development and implementation of two different layer architectures for the metal processing environment. The first architecture is based on low-cost but resilient devices, allowing interested parties to work with mostly open-source interfaces and standard back-end programming environments. Additionally, one proprietary and two open-source graphical user interfaces (GUIs) were developed. Those interfaces can be adapted front-end as well as back-end, ensuring a holistic comprehension of their capabilities and limits. As a result, a six-layer architecture, from digitization to an interactive project management tool, was designed and implemented in the practical workflow at the academic institution. To take the complexity of thermo-mechanical processing in the metal processing field into account, an alternative layer, connected with the thermo-mechanical treatment simulator Gleeble 3800, was designed. This framework is capable of transferring sensor data with high frequency, enabling data collection for the numerical simulation of complex material behavior under high temperature processing. Finally, the possibility of connecting both systems by using open-source software packages is demonstrated.

scholarly journals P50 Exploring the Merits and Availability of Smartphone Applications Related to Melanoma

BJS Open ◽  
2021 ◽  
Vol 5 (Supplement_1) ◽  
Author(s):  
Jade Kabbani ◽  
Jamil Kabbani ◽  
Jade Kabbani
Keyword(s):  
Clinical Management ◽  
Literature Search ◽  
Patient Access ◽  
Smartphone Applications ◽  
App Store ◽  
Widespread Availability ◽  
Smartphone Use ◽  
Clinical Tools ◽  
Google Play ◽  
Privacy Issues

Abstract Background The increased use of smartphone applications across healthcare specialties has been particularly relevant in dermatology, with dermatology related applications widely available on mainstream application stores. We reviewed published literature regarding melanoma-related applications, and the number and types of such applications available for download. Methods A literature search of “dermatology”, “smartphone” and “melanoma” was conducted to identify publications assessing applications of interest. “Melanoma” was searched in Apple’s (iOS) “App Store” and Google’s “Google Play”, and application purposes and ratings were analysed. Results 54 of the 63 literature search results explored smartphone use in relation to melanoma, describing benefits including quicker patient access to care, reduced referrals and hence unnecessary consultations, and improved accessibility to information. However, concerns include insufficient image quality, privacy issues related to encryption, and diagnostic inaccuracy. Searches on the Google Play and iOS stores identified 249 and 51 apps respectively. 25% of Google Play results were categorised as clinical tools, 17% as educational, and 58% as recreational. The corresponding results for the App store were 92%, 6% and 2%. 81% of the educational apps and 92% of the clinical management apps related to dermatology and melanoma on Google Play, whereas all of the clinical management apps and 67% of the education apps on the App store were of relevance. Conclusion The results illustrate the widespread availability of applications related to melanoma, particularly for educational and clinical purposes. Standardising photographing techniques, improving diagnostic accuracy, and privacy issues are important aspects to consider and warrant further investigation.

scholarly journals Evaluation of the relationship between perceived social support, coping strategies, anxiety, and depression symptoms among hospitalized COVID-19 patients

2020 ◽  
pp. 009121742098208
Author(s):  
Ali Kandeğer ◽  
Memduha Aydın ◽  
Kürşat Altınbaş ◽  
Alparslan Cansız ◽  
Özge Tan ◽  
...  
Keyword(s):  
Social Support ◽  
Coping Strategies ◽  
Perceived Social Support ◽  
Depression Scale ◽  
Negative Association ◽  
Anxiety And Depression ◽  
Control Group ◽  
Depression Symptoms ◽  
Adaptive Coping ◽  
The Relationship

Objective We aimed to evaluate the relationship between perceived social support, coping strategies, anxiety, and depression symptoms among hospitalized COVID-19 patients by comparing them with a matched control group in terms of age, gender, and education level. Method The patient group (n = 84) and the healthy controls (HCs, n = 92) filled in the questionnaire including the socio-demographic form, Hospital Anxiety Depression Scale, Multidimensional Perceived Social Support Scale, and Brief Coping Orientation to Problems Experienced through the online survey link. Results The COVID-19 patients had higher perceived social support and coping strategies scores than the HCs. However, anxiety and depression scores did not differ significantly between the two groups. In logistic regression analysis performed in COVID-19 patients, the presence of chest CT finding (OR = 4.31; 95% CI = 1.04–17.95) was a risk factor for anxiety and the use of adaptive coping strategies (OR = 0.86; 95% CI = 0.73–0.99) had a negative association with anxiety. In addition, the use of adaptive coping strategies (OR = 0.89; 95% CI = 0.79–0.98) and high perceived social support (OR = 0.97; 95% CI = 0.93– 0,99) had a negative association with depression symptoms. Conclusions Longitudinal studies involving the return to normality phase of the COVID-19 pandemic are needed to investigate the effects of factors such as coping strategies and perceived social support that could increase the psychological adjustment and resilience of individuals on anxiety and depression.

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