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.

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 The characteristics of anxiety and depression symptom severity in older adults living in public housing

2011 ◽  
Vol 24 (4) ◽  
pp. 614-623 ◽  
Author(s):  
Adam Simning ◽  
Yeates Conwell ◽  
Susan G. Fisher ◽  
Thomas M. Richardson ◽  
Edwin van Wijngaarden
Keyword(s):  
Public Housing ◽  
Older Adult ◽  
Symptom Severity ◽  
Regression Models ◽  
Late Life ◽  
Anxiety And Depression ◽  
Depression Symptoms ◽  
Depression Symptom ◽  
The Social ◽  
Public Housing Residents

ABSTRACTBackground:Anxiety and depression are common in older adult public housing residents and frequently co-occur. To understand anxiety and depression more fully in this socioeconomically disadvantaged population, this study relies on the Social Antecedent Model of Psychopathology to characterize anxiety and depression symptoms concurrently.Methods:190 public housing residents aged 60 years and older in Rochester, New York, participated in a research interview during which they reported on variables across the six stages of the Social Antecedent Model. GAD-7 and PHQ-9 assessed anxiety and depression symptoms, respectively.Results:In these older adult residents, anxiety and depression symptom severity scores were correlated (r = 0.61; p < 0.001). Correlates of anxiety and depression symptom severity were similar for both outcomes and spanned the six stages of the Social Antecedent Model. Multivariate linear regression models identified age, medical comorbidity, mobility, social support, maladaptive coping, and recent life events severity as statistically significant correlates. The regression models accounted for 43% of anxiety and 48% of depression symptom variability.Conclusions:In public housing residents, late-life anxiety and depression symptoms were moderately correlated. Anxiety symptom severity correlates were largely consistent with those found for depression symptom severity. The broad distribution of correlates across demographic, social, medical, and behavioral domains suggests that the context of late-life anxiety and depression symptomatology in public housing is complex and that multidisciplinary collaborative care approaches may be warranted in future interventions.

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 HOLOCAUST SURVIVORS IN A COMMUNITY SAMPLE: EMOTION REGULATION OF ANXIETY AND DEPRESSION SYMPTOMS

2018 ◽  
Vol 2 (suppl_1) ◽  
pp. 937-937
Author(s):  
K Morgen ◽  
D Rosenwein ◽  
A Reiner ◽  
K McMahon ◽  
G Yuhct ◽  
...  
Keyword(s):  
Emotion Regulation ◽  
Holocaust Survivors ◽  
Community Sample ◽  
Anxiety And Depression ◽  
Depression Symptoms

scholarly journals Anxiety and depression symptoms in Danish patients with an implantable cardioverter-defibrillator: prevalence and association with indication and sex up to 2 years of follow-up (data from the national DEFIB-WOMEN study)

EP Europace ◽  
2020 ◽  
Vol 22 (12) ◽  
pp. 1830-1840
Author(s):  
Vivi Skibdal Frydensberg ◽  
Jens Brock Johansen ◽  
Sören Möller ◽  
Sam Riahi ◽  
Sonja Wehberg ◽  
...  
Keyword(s):  
Implantable Cardioverter Defibrillator ◽  
Depression Scale ◽  
Anxiety And Depression ◽  
Depression Symptoms ◽  
Depression Symptom ◽  
Icd Implantation ◽  
Cardioverter Defibrillator ◽  
Time Points ◽  
Mixed Modelling

Abstract Aims To investigate (i) the prevalence of anxiety and depression and (ii) the association between indication for implantable cardioverter-defibrillator (ICD) implantation and sex in relation to anxiety and depression up to 24 months’ follow-up. Methods and results Patients with a first-time ICD, participating in the national, multi-centre, prospective DEFIB-WOMEN study (n = 1496; 18% women) completed the Hospital Anxiety and Depression Scale at baseline, 3, 6, 12, and 24 months. Data were analysed using linear mixed modelling for longitudinal data. Patients with a secondary prophylactic indication (SPI) had higher mean anxiety scores than patients with a primary prophylactic indication (PPI) at baseline, 3, and 12 months and higher mean depression scores at all-time points, except at 24 months. Women had higher mean anxiety scores as compared to men at all-time points; however, only higher mean depression scores at baseline. Overall, women with SPI had higher anxiety and depression symptom scores than men with SPI. Symptoms decreased over time in both women and men. From baseline to follow-up, the prevalence of anxiety (score ≥8) was highest in patients with SPI (13.3–20.2%) as compared to patients with PPI (range 10.0–14.7%). The prevalence of depression was stable over the follow-up period in both groups (range 8.5–11.1%). Conclusion Patients with a SPI reported higher anxiety and depression scores as compared to patients with PPI. Women reported higher anxiety scores than men, but only higher depression scores at baseline. Women with SPI reported the highest anxiety and depression scores overall.

Is it chicken or the egg: Obesity, anxiety and depression in hospital workers

2021 ◽  
pp. 1-11
Author(s):  
Sema Akkaya Demir ◽  
Rana Nagihan Akder ◽  
Reci Meseri
Keyword(s):  
Abdominal Obesity ◽  
Depression Scale ◽  
Severe Depression ◽  
Cross Sectional Study ◽  
Anxiety And Depression ◽  
P Value ◽  
Depression Symptoms ◽  
Depression Symptom ◽  
Independent Factor ◽  
Cross Sectional

BACKGROUND: Healthcare workers are susceptible to obesity, anxiety and depression. OBJECTIVE: To determine the prevalence and association of obesity, anxiety and depression symptoms in individuals working in a hospital. METHODS: In this cross-sectional study all of the employees of a hospital were invited to participate (n = 150). Anxiety (via Beck Anxiety Scale) and depression symptoms (via Beck Depression Scale) and obesity were dependent and independent variables. Obesity was determined both with body mass index (BMI) and abdominal obesity (Waist circumference-WC). Data were collected with face-to-face interviews and anthropometric measurements were done. Data were analyzed using SPSS version 25.0 with student t-test, chi-square and correlation tests. Significance was set at a p-value <  0.05. RESULTS: Among the participants who agreed to participate (n = 131, 64.1% females), 35.1% were obese and 50.4% were abdominally obese. The 35.9% had moderate-severe anxiety symptoms, 19.1% had moderate-severe depression symptoms. Both BMI and WC had positive, moderate and significant correlation with anxiety and depression scores. After adjusting for socio-demographic variables obesity (both with BMI and WC) was an independent factor for anxiety and depression symptom presence, whereas after adjusted for these variables anxiety and depression symptom presence was an independent factor for obesity and abdominal obesity (p = 0.001 for all). CONCLUSIONS: There is a correlation between anxiety, depression and obesity. In addition to nutrition interventions in combating obesity, services that will improve mental health should be provided together as teamwork.

scholarly journals The moderating role of anxiety sensitivity in the co-occurrence of anxiety and depression symptoms among clinically anxious children

2018 ◽  
Vol 9 (3) ◽  
pp. 204380871879104
Author(s):  
Andres G. Viana ◽  
Emma C. Woodward ◽  
Abigail E. Hanna ◽  
Elizabeth M. Raines ◽  
Candice A. Alfano ◽  
...  
Keyword(s):  
Anxiety Disorders ◽  
Anxiety Sensitivity ◽  
Self Report ◽  
Anxiety And Depression ◽  
Future Research ◽  
Depression Symptoms ◽  
Depression Symptom ◽  
Targeted Interventions ◽  
Anxiety Depression

The co-occurrence between anxiety and depression symptoms among children with anxiety disorders is well-known, yet there is considerable heterogeneity in terms of explanatory factors. Although cognitive–affective processes have been hypothesized to play a prominent role, surprisingly, no research to date has examined the role of anxiety sensitivity in this co-occurrence. The present investigation examined the role of anxiety sensitivity in the co-occurrence of anxiety and depression symptoms among clinically anxious children. We expected that anxiety sensitivity would moderate the co-occurrence between anxiety and depression symptoms, such that higher anxiety would be related to higher depression among boys and girls with high (but not low) anxiety sensitivity. Participants ( N = 44, age range = 8–12 years; 52% female; 52% African American) were interviewed with the Anxiety Disorders Interview Schedule-IV: Children and Parent Versions and completed self-report measures of anxiety sensitivity, anxiety, and depression symptom severity. Controlling for child age, moderation analyses revealed that higher anxiety was related to higher depression only among girls with high anxiety sensitivity. Among girls with low anxiety sensitivity, the relation between anxiety and depression symptoms was not significant. Anxiety and depression symptoms were strongly correlated among clinically anxious boys irrespective of their levels of anxiety sensitivity. Anxiety sensitivity is an important factor related to anxiety–depression symptom co-occurrence among clinically anxious females in particular. Targeted interventions focused on anxiety sensitivity reduction may prove useful for reducing anxiety–depression symptom co-occurrence among clinically anxious girls. Future research should explore additional moderators that may explain the high correlation between anxiety and depressive symptoms observed among clinically anxious boys.

scholarly journals The Role of Emotional Regulation in Anxiety and Depression Symptom Interplay and Expression among Adolescent Females

2021 ◽  
Author(s):  
Emily McGlinchey ◽  
Karen Kirby ◽  
Eoin McElroy ◽  
Jamie Murphy
Keyword(s):  
Latent Profile Analysis ◽  
Anxiety Symptom ◽  
Adolescent Females ◽  
Anxiety And Depression ◽  
Depression Symptoms ◽  
Depression Symptom ◽  
Unique Contribution ◽  
Depression And Anxiety ◽  
Contextual Risk

AbstractDepression and anxiety are highly comorbid constructs. However little is known about the mechanisms that underpin this comorbidity/connectivity or the divergence between constructs that seems to occur in adolescence. The current study targeted emotion regulation (ER) as a potential plausible mechanism for explaining how anxiety and depression symptoms in adolescence might begin to connect, perpetuate, and ultimately diverge from one another. Using data from a cross-sectional school-based study, of adolescent females (age 11–18 years; N = 615; majority were white (97.7%)), we modelled variation in ER using latent profile analysis. Then, using network analysis (NA), we generated separate depression-anxiety symptom networks for adolescents at varying levels of ER. Three latent classes of ER were identified (low ER 15%, intermediate ER 34%, high ER 51%). The results of the network comparison test found no significant differences in global strength between the ‘low ER’ and the ‘intermediate ER’ ability network. This study is among the first to attempt to model change in depression-anxiety symptom connectivity in adolescence in relation to a common contextual/risk factor. The current study therefore offers a unique contribution to the examination of the role of transdiagnostic factors in the study of adolescent depression and anxiety from a network perspective, and provides a promising framework for the study of ER among anxiety and depression symptomatology in adolescence.

scholarly journals An Artificial Intelligence-Assisted Portable Low-Cost Device for the Rapid Detection of SARS-CoV-2

Electronics ◽  
2021 ◽  
Vol 10 (17) ◽  
pp. 2065
Author(s):  
Mukunthan Tharmakulasingam ◽  
Nouman S. Chaudhry ◽  
Manoharanehru Branavan ◽  
Wamadeva Balachandran ◽  
Aurore C. Poirier ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Rapid Detection ◽  
Template Matching ◽  
Low Cost ◽  
Lamp Assay ◽  
High Sensitivity ◽  
High Specificity ◽  
Cost Effective ◽  
Mobile App ◽  
Run Time

An artificial intelligence-assisted low-cost portable device for the rapid detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is presented here. This standalone temperature-controlled device houses tubes designed for conducting reverse transcription loop-mediated isothermal amplification (RT-LAMP) assays. Moreover, the device utilises tubes illuminated by LEDs, an in-built camera, and a small onboard computer with automated image acquisition and processing algorithms. This intelligent device significantly reduces the normal assay run time and removes the subjectivity associated with operator interpretation of colourimetric RT-LAMP results. To further improve this device’s usability, a mobile app has been integrated into the system to control the LAMP assay environment and to visually display the assay results by connecting the device to a smartphone via Bluetooth. This study was undertaken using ~5000 images produced from the ~200 LAMP amplification assays using the prototype device. Synthetic RNA and a small panel of positive and negative SARS-CoV-2 patient samples were assayed for this study. State-of-the-art image processing and artificial intelligence algorithms were applied to these images to analyse them and to select the most efficient algorithm. The template matching algorithm for image extraction and MobileNet CNN architecture for classification results provided 98.0% accuracy with an average run time of 20 min to confirm the endpoint result. Two working points were chosen based on the best compromise between sensitivity and specificity. The high sensitivity point has a sensitivity value of 99.12% and specificity value of 70.8%, while at the high specificity point, the sensitivity is 96.05% and specificity 93.59%. Furthermore, this device provides an efficient and cost-effective platform for non-health professionals to detect not only SARS-CoV-2 but also other pathogens in resource-limited laboratories, factories, airports, schools, universities, and homes.

Predictors of Anxiety and Depression Symptom Improvement in CBT Adapted for Traumatic Brain Injury: Pre/Post-Injury and Therapy Process Factors

2020 ◽  
Vol 26 (1) ◽  
pp. 97-107 ◽  
Author(s):  
Leah M. Zelencich ◽  
Dana Wong ◽  
Nikolaos Kazantzis ◽  
Dean P. McKenzie ◽  
Marina Downing ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Recovery Period ◽  
Anxiety And Depression ◽  
Symptom Improvement ◽  
Depression Symptoms ◽  
Depression Symptom ◽  
Post Injury ◽  
Independent Observer ◽  
Process Factors

AbstractObjectives:The current study examined the association of demographic/preinjury, injury-related, and cognitive behavior therapy (CBT) process variables, with anxiety and depression symptom change in traumatic brain injury (TBI)-adapted CBT (CBT-ABI).Methods:The audio recordings of 177 CBT-ABI sessions representing 31 therapist–client dyads were assessed from the independent observer perspective on measures of working alliance, homework engagement, and therapist competency in using homework.Results:Linear regressions showed that older client age, longer post-TBI recovery period, better executive functioning, higher levels of client homework engagement, as well as higher levels of therapist competence in reviewing homework were associated with greater improvement in anxiety and/or depression symptoms.Conclusions:CBT-ABI is a promising treatment for post-TBI depression and anxiety. The current study highlights how therapists can enhance CBT-ABI effectiveness, specifically: comprehensive facilitation of client homework engagement with emphasis on homework review, and accommodation of executive deficits. The current study also suggests that the role of client age and the length of post-TBI recovery period require further investigation.

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