bluuebunny/crossref_metadata_2025 huggingface dataset:
Views of Swedish Elder Care Personnel on Ongoing Digital Transformation: Cross-Sectional Study
Authors: Baudin Katarina , Gustafsson Christine , Frennert Susanne
Published: May 2020

Background

Swedish municipalities are facing demographic challenges due to the growing number of older people and the resulting increased need for health care services. Welfare technologies are being launched as possible solutions for meeting some of these challenges.

Objective

The aim of this study was to explore the perception, experimentation, evaluation, and procurement of welfare technology practices among professionals working in municipal elder care in relation to their gender, age, and profession.

Methods

Data for this explorative cross-sectional study were collected from 393 responses to a web-based survey on municipal elder care in Sweden. Chi square tests were performed to determine the associations.

Results

The results revealed gender, age, and professional differences in perspectives of municipal elder care workers. Differences were particularly evident in attitudes toward technology, both the use of technology in general and in the workplace, and involvement and participation in decision making regarding the procurement of new welfare technologies. Men (37/53, 70%) expressed a more positive attitude toward and curiosity regarding new technologies than women (157/336, 46.7%) (P=.03). Regarding age, the younger respondents (18-24 years old) perceived the digital transformation in the workplace as “too slow” (4/4, 100%), whereas the majority of older respondents (65-74 years old) perceived it as happening at the “right pace” (4/7, 57%). The elder care personnel felt encouraged by management to explore and experiment with new welfare technologies, but never did so either for management or with patients. Even though the majority of the respondents were women, more men (4/7, 57%) were involved in the procurement process for welfare technology devices and solutions than women (98/336, 29.2%) (P<.001).

Conclusions

Personnel working within municipal elder care were generally very positive toward new technologies. However, both gender and age differences may influence these perspectives such as the personnel’s resistance to welfare technology and patients’ participation in welfare technology usage and deployment. Different levels of participation in the decision-making process regarding new technology deployment may negatively affect the overall digital transformation within municipal elder care.
An Exploration Into the Use of a Chatbot for Patients With Inflammatory Bowel Diseases: Retrospective Cohort Study
Authors: Zand Aria , Sharma Arjun , Stokes Zack , Reynolds Courtney , Montilla Alberto , Sauk Jenny , Hommes Daniel
Published: May 2020

Background

The emergence of chatbots in health care is fast approaching. Data on the feasibility of chatbots for chronic disease management are scarce.

Objective

This study aimed to explore the feasibility of utilizing natural language processing (NLP) for the categorization of electronic dialog data of patients with inflammatory bowel diseases (IBD) for use in the development of a chatbot.

Methods

Electronic dialog data collected between 2013 and 2018 from a care management platform (UCLA eIBD) at a tertiary referral center for IBD at the University of California, Los Angeles, were used. Part of the data was manually reviewed, and an algorithm for categorization was created. The algorithm categorized all relevant dialogs into a set number of categories using NLP. In addition, 3 independent physicians evaluated the appropriateness of the categorization.

Results

A total of 16,453 lines of dialog were collected and analyzed. We categorized 8324 messages from 424 patients into seven categories. As there was an overlap in these categories, their frequencies were measured independently as symptoms (2033/6193, 32.83%), medications (2397/6193, 38.70%), appointments (1518/6193, 24.51%), laboratory investigations (2106/6193, 34.01%), finance or insurance (447/6193, 7.22%), communications (2161/6193, 34.89%), procedures (617/6193, 9.96%), and miscellaneous (624/6193, 10.08%). Furthermore, in 95.0% (285/300) of cases, there were minor or no differences in categorization between the algorithm and the three independent physicians.

Conclusions

With increased adaptation of electronic health technologies, chatbots could have great potential in interacting with patients, collecting data, and increasing efficiency. Our categorization showcases the feasibility of using NLP in large amounts of electronic dialog for the development of a chatbot algorithm. Chatbots could allow for the monitoring of patients beyond consultations and potentially empower and educate patients and improve clinical outcomes.
Morbidity Prevalence Estimate at 6 Months Following a Stroke: Protocol for a Cohort Study
Authors: Smith Alexander , Bains Natalie , Copeland Lauren , Pennington Anna , Carter Ben , Hewitt Jonathan
Published: May 2020

Background

Knowledge of the prevalence of morbidity secondary to stroke is important for health care professionals, health care commissioners, third sector organizations, and stroke survivors to understand the likely progress of poststroke sequelae and to aid in commissioning decisions, planning care, and adjusting to life after stroke.

Objective

The primary aim of the Morbidity PRevalence Estimate In StrokE (MORe PREcISE) study is to determine the prevalence of morbidity secondary to a stroke, predictors of morbidity, and trends in quality of life and functional status using patient-reported outcomes, cognitive and functional assessments.

Methods

A total of 500 participants will be recruited across Wales and England within 14 days following an admission to a stroke unit for either an ischemic or hemorrhagic stroke as part of a multicenter cohort study. Participants are assessed at baseline ≤14 days poststroke and subsequently at 90 (± 14) days and 180 (± 14) days poststroke. At each time point, data will be collected relating to the following domains: participant demographics, routine clinical, patient reported, cognitive status, emotional well-being, and functional ability.

Results

Recruitment commenced in October 2018 with 20 sites opened as of September 2019 and was closed on October 31, 2019.

Conclusions

The primary outcome is the prevalence of morbidity at 6 months secondary to a stroke. Further analysis will consider temporal changes in the health-related domains to describe trends among baseline, 3-, and 6-month time points.

Trial Registration

ClinicalTrials.gov NCT03605381; https://clinicaltrials.gov/ct2/show/NCT03605381

International Registered Report Identifier (IRRID)

DERR1-10.2196/15851
Effectiveness and Safety of Using Chatbots to Improve Mental Health: Systematic Review and Meta-Analysis
Authors: Abd-Alrazaq Alaa Ali , Rababeh Asma , Alajlani Mohannad , Bewick Bridgette M , Househ Mowafa
Published: May 2020

Background

The global shortage of mental health workers has prompted the utilization of technological advancements, such as chatbots, to meet the needs of people with mental health conditions. Chatbots are systems that are able to converse and interact with human users using spoken, written, and visual language. While numerous studies have assessed the effectiveness and safety of using chatbots in mental health, no reviews have pooled the results of those studies.

Objective

This study aimed to assess the effectiveness and safety of using chatbots to improve mental health through summarizing and pooling the results of previous studies.

Methods

A systematic review was carried out to achieve this objective. The search sources were 7 bibliographic databases (eg, MEDLINE, EMBASE, PsycINFO), the search engine “Google Scholar,” and backward and forward reference list checking of the included studies and relevant reviews. Two reviewers independently selected the studies, extracted data from the included studies, and assessed the risk of bias. Data extracted from studies were synthesized using narrative and statistical methods, as appropriate.

Results

Of 1048 citations retrieved, we identified 12 studies examining the effect of using chatbots on 8 outcomes. Weak evidence demonstrated that chatbots were effective in improving depression, distress, stress, and acrophobia. In contrast, according to similar evidence, there was no statistically significant effect of using chatbots on subjective psychological wellbeing. Results were conflicting regarding the effect of chatbots on the severity of anxiety and positive and negative affect. Only two studies assessed the safety of chatbots and concluded that they are safe in mental health, as no adverse events or harms were reported.

Conclusions

Chatbots have the potential to improve mental health. However, the evidence in this review was not sufficient to definitely conclude this due to lack of evidence that their effect is clinically important, a lack of studies assessing each outcome, high risk of bias in those studies, and conflicting results for some outcomes. Further studies are required to draw solid conclusions about the effectiveness and safety of chatbots.

Trial Registration

PROSPERO International Prospective Register of Systematic Reviews CRD42019141219; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42019141219
Internet-Based Health Information–Seeking Behavior of Students Aged 12 to 14 Years: Mixed Methods Study
Authors: Maitz Emanuel , Maitz Katharina , Sendlhofer Gerald , Wolfsberger Christina , Mautner Selma , Kamolz Lars-Peter , Gasteiger-Klicpera Barbara
Published: May 2020

Background

Many children and adolescents are surrounded by smartphones, tablets, and computers and know how to search the internet for almost any information. However, very few of them know how to select proper information from reliable sources. This can become a problem when health issues are concerned, where it is vital to identify incorrect or misleading information. The competence to critically evaluate digital information on health issues is of increasing importance for adolescents.

Objective

The aim of this study was to assess how children and adolescents rate their internet-based health literacy and how their actual literacy differs from their ratings. In addition, there was a question on how their search performance is related to their self-efficacy. To evaluate these questions, a criteria-based analysis of the quality of the websites they visited was performed. Finally, the possibility to increase their internet-based health literacy in a 3-day workshop was explored.

Methods

A workshop with a focus on health literacy was attended by 14 children and adolescents in an Austrian secondary school. After prior assessments (Culture Fair Intelligence Test, revised German version; Reading Speed and Reading Comprehension Test for Grades 6 to 12, German; electronic health literacy scale [eHEALS]; and General Self-Efficacy Scale, Reversed Version, German), the students were asked to perform an internet-based search on a health-related issue. Browser histories and screenshots of all internet searches were gathered, clustered, and analyzed. After the workshop, the health literacy of the students was assessed again by using the eHEALS.

Results

The 14 students opened a total of 85 homepages, but only eight of these homepages were rated as good or fair by two experts (independent rating) based on specific criteria. The analysis showed that the students judged their own internet-based health literacy much higher than the actual value, and students who had rated themselves better did not visit websites of high quality. Internet-based health literacy correlated significantly with the self-efficacy of the students (rs=0.794, P=.002).

Conclusions

Our study showed that it is possible to draw the attention of students to critical aspects of internet search and to slightly improve their search competence in a workshop. Targeted improvement of health literacy is urgently required, and students need special instruction for this purpose. Further investigations in this area with larger sets of data, which could be feasible with the help of a computer program, are urgently needed.
Digital Biomarkers of Social Anxiety Severity: Digital Phenotyping Using Passive Smartphone Sensors
Authors: Jacobson Nicholas C , Summers Berta , Wilhelm Sabine
Published: May 2020

Background

Social anxiety disorder is a highly prevalent and burdensome condition. Persons with social anxiety frequently avoid seeking physician support and rarely receive treatment. Social anxiety symptoms are frequently underreported and underrecognized, creating a barrier to the accurate assessment of these symptoms. Consequently, more research is needed to identify passive biomarkers of social anxiety symptom severity. Digital phenotyping, the use of passive sensor data to inform health care decisions, offers a possible method of addressing this assessment barrier.

Objective

This study aims to determine whether passive sensor data acquired from smartphone data can accurately predict social anxiety symptom severity using a publicly available dataset.

Methods

In this study, participants (n=59) completed self-report assessments of their social anxiety symptom severity, depressive symptom severity, positive affect, and negative affect. Next, participants installed an app, which passively collected data about their movement (accelerometers) and social contact (incoming and outgoing calls and texts) over 2 weeks. Afterward, these passive sensor data were used to form digital biomarkers, which were paired with machine learning models to predict participants’ social anxiety symptom severity.

Results

The results suggested that these passive sensor data could be utilized to accurately predict participants’ social anxiety symptom severity (r=0.702 between predicted and observed symptom severity) and demonstrated discriminant validity between depression, negative affect, and positive affect.

Conclusions

These results suggest that smartphone sensor data may be utilized to accurately detect social anxiety symptom severity and discriminate social anxiety symptom severity from depressive symptoms, negative affect, and positive affect.
Design, Recruitment, and Baseline Characteristics of a Virtual 1-Year Mental Health Study on Behavioral Data and Health Outcomes: Observational Study
Authors: Kumar Shefali , Tran Jennifer L A , Ramirez Ernesto , Lee Wei-Nchih , Foschini Luca , Juusola Jessie L
Published: May 2020

Background

Depression and anxiety greatly impact daily behaviors, such as sleep and activity levels. With the increasing use of activity tracking wearables among the general population, there has been a growing interest in how data collected from these devices can be used to further understand the severity and progression of mental health conditions.

Objective

This virtual 1-year observational study was designed with the objective of creating a longitudinal data set combining self-reported health outcomes, health care utilization, and quality of life data with activity tracker and app-based behavioral data for individuals with depression and anxiety. We provide an overview of the study design, report on baseline health and behavioral characteristics of the study population, and provide initial insights into how behavioral characteristics differ between groups of individuals with varying levels of disease severity.

Methods

Individuals who were existing members of an online health community (Achievement, Evidation Health Inc) and were 18 years or older who had self-reported a diagnosis of depression or anxiety were eligible to enroll in this virtual 1-year study. Participants agreed to connect wearable activity trackers that captured data related to physical activity and sleep behavior. Mental health outcomes such as the Patient Health Questionnaire (PHQ-9), the Generalized Anxiety Disorder Questionnaire (GAD-7), mental health hospitalizations, and medication use were captured with surveys completed at baseline and months 3, 6, 9, and 12. In this analysis, we report on baseline characteristics of the sample, including mental health disease severity and health care utilization. Additionally, we explore the relationship between passively collected behavioral data and baseline mental health status and health care utilization.

Results

Of the 1304 participants enrolled in the study, 1277 individuals completed the baseline survey and 1068 individuals had sufficient activity tracker data. Mean age was 33 (SD 9) years, and the majority of the study population was female (77.2%, 994/1288) and identified as Caucasian (88.3%, 1137/1288). At baseline, 94.8% (1211/1277) of study participants reported experiencing depression or anxiety symptoms in the last year. This baseline analysis found that some passively tracked behavioral traits are associated with more severe forms of anxiety or depression. Individuals with depressive symptoms were less active than those with minimal depressive symptoms. Severe forms of depression were also significantly associated with inconsistent sleep patterns and more disordered sleep.

Conclusions

These initial findings suggest that longitudinal behavioral and health outcomes data may be useful for developing digital measures of health for mental health symptom severity and progression.
A Web-Based, Positive Emotion Skills Intervention for Enhancing Posttreatment Psychological Well-Being in Young Adult Cancer Survivors (EMPOWER): Protocol for a Single-Arm Feasibility Trial
Authors: Salsman John M , McLouth Laurie E , Cohn Michael , Tooze Janet A , Sorkin Mia , Moskowitz Judith T
Published: May 2020

Background

Adolescent and young adult cancer survivors (AYAs) experience clinically significant distress and have limited access to supportive care services. Interventions to enhance psychological well-being have improved positive affect and reduced depression in clinical and healthy populations but have not been routinely tested in AYAs.

Objective

The aim of this protocol is to (1) test the feasibility and acceptability of a Web-based positive emotion skills intervention for posttreatment AYAs called Enhancing Management of Psychological Outcomes With Emotion Regulation (EMPOWER) and (2) examine proof of concept for reducing psychological distress and enhancing psychological well-being.

Methods

The intervention development and testing are taking place in 3 phases. In phase 1, we adapted the content of an existing, Web-based positive emotion intervention so that it would be suitable for AYAs. EMPOWER targets 8 skills (noticing positive events, capitalizing, gratitude, mindfulness, positive reappraisal, goal setting, personal strengths, and acts of kindness) and is delivered remotely as a 5-week, Web-based intervention. Phase 2 consisted of a pilot test of EMPOWER in a single-arm trial to evaluate feasibility, acceptability, retention, and adherence and to collect data on psychosocial outcomes for proof of concept. In phase 3, we are refining study procedures and conducting a second pilot test.

Results

The project was part of a career development award. Pilot work began in June 2015, and data collection was completed in March 2019. The analysis is ongoing, and results will be submitted for publication by May 2020.

Conclusions

If this intervention proves feasible and acceptable, EMPOWER will be primed for a subsequent large, multisite randomized controlled trial. As a scalable intervention, it will be ideally suited for AYA survivors who would otherwise not have access to supportive care interventions to help manage posttreatment distress and enhance well-being.

Trial Registration

ClinicalTrials.gov NCT02832154, https://clinicaltrials.gov/ct2/show/NCT02832154.

International Registered Report Identifier (IRRID)

DERR1-10.2196/17078
User Experiences and Preferences Regarding an App for the Treatment of Urinary Incontinence in Adult Women: Qualitative Study
Authors: Wessels Nienke J , Hulshof Lisa , Loohuis Anne M M , van Gemert-Pijnen Lisette , Jellema Petra , van der Worp Henk , Blanker Marco H
Published: May 2020

Background

Although several apps are available to support the treatment of urinary incontinence (UI), little has been reported about the experiences and preferences of their users.

Objective

The objective of this study was to explore the experiences and preferences of women using a mobile app for the treatment of UI and to identify potential improvements to the app. We developed this app for three types of UI: stress UI, urgency UI, and mixed UI.

Methods

The participants in this qualitative study were women with self-reported stress UI, urgency UI, or mixed UI who used an app-based treatment to manage their condition for at least six weeks. Following the intervention, semistructured interviews were conducted to explore the participants’ experiences and preferences regarding the app. All interviews were audio-recorded, transcribed verbatim, and analyzed separately by two researchers.

Results

Data saturation was reached after interviewing 9 women (aged 32-68 years) with stress UI (n=1, 11%), urgency UI (n=3, 33%), or mixed UI (n=5, 56%). Accessibility, awareness, usability, and adherence emerged as the main themes. On the one hand, participants appreciated that the app increased their accessibility to care, preserved their privacy, increased their awareness of therapeutic options, was easy to use and useful, and supported treatment adherence. On the other hand, some participants reported that they wanted more contact with a care provider, and others reported that using the app increased their awareness of symptoms.

Conclusions

This qualitative study indicates that women appreciate app-based treatment for UI because it can lower barriers to treatment and increase both awareness and adherence to treatment. However, the app does not offer the ability of face-to-face contact and can lead to a greater focus on symptoms.
Distinguishing Obstructive Versus Central Apneas in Infrared Video of Sleep Using Deep Learning: Validation Study
Authors: Akbarian Sina , Montazeri Ghahjaverestan Nasim , Yadollahi Azadeh , Taati Babak
Published: May 2020

Background

Sleep apnea is a respiratory disorder characterized by an intermittent reduction (hypopnea) or cessation (apnea) of breathing during sleep. Depending on the presence of a breathing effort, sleep apnea is divided into obstructive sleep apnea (OSA) and central sleep apnea (CSA) based on the different pathologies involved. If the majority of apneas in a person are obstructive, they will be diagnosed as OSA or otherwise as CSA. In addition, as it is challenging and highly controversial to divide hypopneas into central or obstructive, the decision about sleep apnea type (OSA vs CSA) is made based on apneas only. Choosing the appropriate treatment relies on distinguishing between obstructive apnea (OA) and central apnea (CA).

Objective

The objective of this study was to develop a noncontact method to distinguish between OAs and CAs.

Methods

Five different computer vision-based algorithms were used to process infrared (IR) video data to track and analyze body movements to differentiate different types of apnea (OA vs CA). In the first two methods, supervised classifiers were trained to process optical flow information. In the remaining three methods, a convolutional neural network (CNN) was designed to extract distinctive features from optical flow and to distinguish OA from CA.

Results

Overnight sleeping data of 42 participants (mean age 53, SD 15 years; mean BMI 30, SD 7 kg/m2; 27 men and 15 women; mean number of OA 16, SD 30; mean number of CA 3, SD 7; mean apnea-hypopnea index 27, SD 31 events/hour; mean sleep duration 5 hours, SD 1 hour) were collected for this study. The test and train data were recorded in two separate laboratory rooms. The best-performing model (3D-CNN) obtained 95% accuracy and an F1 score of 89% in differentiating OA vs CA.

Conclusions

In this study, the first vision-based method was developed that differentiates apnea types (OA vs CA). The developed algorithm tracks and analyses chest and abdominal movements captured via an IR video camera. Unlike previously developed approaches, this method does not require any attachment to a user that could potentially alter the sleeping condition.
Health Care Professionals’ Views on Using Remote Measurement Technology in Managing Central Nervous System Disorders: Qualitative Interview Study
Authors: Andrews Jacob A , Craven Michael P , Jamnadas-Khoda Jennifer , Lang Alexandra R , Morriss Richard , Hollis Chris ,   The RADAR-CNS Consortium
Published: May 2020

Background

Remote measurement technologies (RMT) can be used to collect data on a variety of bio-behavioral variables, which may improve the care of patients with central nervous system disorders. Although various studies have explored their potential, prior work has highlighted a knowledge gap in health care professionals’ (HCPs) perceptions of the value of RMT in clinical practice.

Objective

This study aims to understand HCPs’ perspectives on using RMT in health care practice for the care of patients with depression, epilepsy, or multiple sclerosis (MS).

Methods

Semistructured interviews were conducted with 26 multidisciplinary primary and secondary care HCPs who care for patients with epilepsy, depression, or MS. Interviews were transcribed verbatim and analyzed using thematic analysis.

Results

A total of 8 main themes emerged from the analysis: (1) potential clinical value of RMT data; (2) when to use RMT in care pathways; (3) roles of health care staff who may use RMT data; (4) presentation and accessibility of data; (5) obstacles to successful use of RMT; (6) limits to the role of RMT; (7) empowering patients; and (8) considerations around alert-based systems.

Conclusions

RMT could add value to the system of care for patients with central nervous system disorders by providing clinicians with graphic summaries of data in the patient record. Barriers of both technical and human nature should be considered when using these technologies, as should the limits to the benefits they can offer.
Medical Device Apps: An Introduction to Regulatory Affairs for Developers
Authors: Keutzer Lina , Simonsson Ulrika SH
Published: May 2020

The Poly Implant Prothèse (PIP) scandal in France prompted a revision of the regulations regarding the marketing of medical devices. The new Medical Device Regulation (MDR [EU]) 2017/745 was developed and entered into force on May 25, 2017. After a transition period of 3 years, the regulations must be implemented in all EU and European Economic Area member states. The implementation of this regulation bears many changes for medical device development and marketing, including medical device software and mobile apps. Medical device development and marketing is a complex process by which manufacturers must keep many regulatory requirements and obligations in mind. The objective of this paper is to provide an introduction and overview of regulatory affairs for manufacturers that are new to the field of medical device software and apps with a specific focus on the new MDR, accompanying harmonized standards, and guidance documents from the European Commission. This work provides a concise overview of the qualification and classification of medical device software and apps, conformity assessment routes, technical documentation, clinical evaluation, the involvement of notified bodies, and the unique device identifier. Compared to the previous Medical Device Directive (MDD) 93/42/EEC, the MDR provides greater detail about the requirements for software qualification and classification. In particular, rule 11 sets specific rules for the classification of medical device software and will be described in this paper. In comparison to the previous MDD, the MDR is more stringent, especially regarding the classification of health apps and software. The implementation of the MDR in May 2020 and its interpretation by the authorities will demonstrate how app and software manufacturers as well as patients will be affected by the regulation.
Multi-Level Representation Learning for Chinese Medical Entity Recognition: Model Development and Validation
Authors: Zhang Zhichang , Zhu Lin , Yu Peilin
Published: May 2020

Background

Medical entity recognition is a key technology that supports the development of smart medicine. Existing methods on English medical entity recognition have undergone great development, but their progress in the Chinese language has been slow. Because of limitations due to the complexity of the Chinese language and annotated corpora, these methods are based on simple neural networks, which cannot effectively extract the deep semantic representations of electronic medical records (EMRs) and be used on the scarce medical corpora. We thus developed a new Chinese EMR (CEMR) dataset with six types of entities and proposed a multi-level representation learning model based on Bidirectional Encoder Representation from Transformers (BERT) for Chinese medical entity recognition.

Objective

This study aimed to improve the performance of the language model by having it learn multi-level representation and recognize Chinese medical entities.

Methods

In this paper, the pretraining language representation model was investigated; utilizing information not only from the final layer but from intermediate layers was found to affect the performance of the Chinese medical entity recognition task. Therefore, we proposed a multi-level representation learning model for entity recognition in Chinese EMRs. Specifically, we first used the BERT language model to extract semantic representations. Then, the multi-head attention mechanism was leveraged to automatically extract deeper semantic information from each layer. Finally, semantic representations from multi-level representation extraction were utilized as the final semantic context embedding for each token and we used softmax to predict the entity tags.

Results

The best F1 score reached by the experiment was 82.11% when using the CEMR dataset, and the F1 score when using the CCKS (China Conference on Knowledge Graph and Semantic Computing) 2018 benchmark dataset further increased to 83.18%. Various comparative experiments showed that our proposed method outperforms methods from previous work and performs as a new state-of-the-art method.

Conclusions

The multi-level representation learning model is proposed as a method to perform the Chinese EMRs entity recognition task. Experiments on two clinical datasets demonstrate the usefulness of using the multi-head attention mechanism to extract multi-level representation as part of the language model.
Android and iPhone Mobile Apps for Psychosocial Wellness and Stress Management: Systematic Search in App Stores and Literature Review
Authors: Lau Nancy , O'Daffer Alison , Colt Susannah , Yi-Frazier Joyce P , Palermo Tonya M , McCauley Elizabeth , Rosenberg Abby R
Published: May 2020

Background

In an oversaturated market of publicly available mobile apps for psychosocial self-care and stress management, health care providers, patients, and consumers interested in mental health–related apps may wonder which, if any, are efficacious. Readily available metrics for consumers include user popularity and media buzz rather than scientific evidence.

Objective

This systematic review aimed to (1) examine the breadth of therapeutic contents and features of psychosocial wellness and stress management apps available to self-help seekers for public download and (2) determine which of these apps have original research support.

Methods

First, we conducted a systematic review of publicly available apps on the iPhone App Store (Apple Inc) and Android Google Play (Google LLC) platforms using conventional self-help-seeking search terms related to wellness and stress. The results were limited to English-language apps available for free download. In total, 2 reviewers independently evaluated all apps and discussed the findings to reach 100% consensus regarding inclusion. Second, a literature review was conducted on the included apps to identify supporting studies with original data collection.

Results

We screened 3287 apps and found 1009 psychosocial wellness and stress management apps. Content varied widely. The most common evidence-based strategy was mindfulness-meditation, followed by positive psychology and goal setting. Most apps were intended to be used as self-help interventions, with only 1.09% (11/1009) involving an electronic therapist and 1.88% (19/1009) designed as a supplement to in-person psychotherapy. Only 4.66% (47/1009) of apps targeted individuals with psychological disorders, and less than 1% of apps (6/1009, 0.59%) targeted individuals with other chronic illnesses. Approximately 2% (21/1009, 2.08%) were supported by original research publications, with a total of 25 efficacy studies and 10 feasibility studies. The Headspace mindfulness app had the most evidence, including 8 efficacy studies. Most other scientifically backed apps were supported by a single feasibility or efficacy study.

Conclusions

Only 2.08% (21/1009) of publicly available psychosocial wellness and stress management mobile apps discoverable to self-help seekers have published, peer-reviewed evidence of feasibility and/or efficacy. Clinicians and investigators may use these findings to help patients and families navigate the volume of emerging digital health interventions for stress management and wellness.
Physiological State and Learning Ability of Students in Normal and Virtual Reality Conditions: Complexity-Based Analysis
Authors: Babini Mohammad H , Kulish Vladimir V , Namazi Hamidreza
Published: May 2020

Background

Education and learning are the most important goals of all universities. For this purpose, lecturers use various tools to grab the attention of students and improve their learning ability. Virtual reality refers to the subjective sensory experience of being immersed in a computer-mediated world, and has recently been implemented in learning environments.

Objective

The aim of this study was to analyze the effect of a virtual reality condition on students’ learning ability and physiological state.

Methods

Students were shown 6 sets of videos (3 videos in a two-dimensional condition and 3 videos in a three-dimensional condition), and their learning ability was analyzed based on a subsequent questionnaire. In addition, we analyzed the reaction of the brain and facial muscles of the students during both the two-dimensional and three-dimensional viewing conditions and used fractal theory to investigate their attention to the videos.

Results

The learning ability of students was increased in the three-dimensional condition compared to that in the two-dimensional condition. In addition, analysis of physiological signals showed that students paid more attention to the three-dimensional videos.

Conclusions

A virtual reality condition has a greater effect on enhancing the learning ability of students. The analytical approach of this study can be further extended to evaluate other physiological signals of subjects in a virtual reality condition.
Association of Social Media Use and High-Risk Behaviors in Adolescents: Cross-Sectional Study
Authors: Vente Teresa , Daley Mary , Killmeyer Elizabeth , Grubb Laura K
Published: May 2020

Background

Previous studies have demonstrated the prevalence of social media use and identified the presence of high-risk behaviors among adolescents, including self-harm and sharing of sexually explicit messages.

Objective

This study aimed to identify patterns in the amount of time spent on social media by adolescents who engage in high-risk behavior and the extent to which they use social media as a platform for sharing such behaviors.

Methods

This was a descriptive cross-sectional study of 179 adolescents seen in a pediatric clinic at an urban medical center. We used an anonymous self-report survey to obtain demographic characteristics, rates of self-harm thoughts and behaviors, sharing of sexually explicit messages, and social media use as determined by total hours spent on social media per day and the number of applications used.

Results

Most adolescents reported spending 3 to 5 hours on social media each day and using 3 or more social media applications. Almost 1 in 8 (22/179, 12.3%) adolescents self-reported having ever engaged in self-injury with a mean age of onset of 11.8 years. Over a quarter (49/179, 27.4%) of adolescents reported sharing sexually explicit messages. Relative risk of engaging in self-injury and or sharing sexually explicit messages increased with the use of 4 or more social media applications (1.66; CI 1.11-2.48).

Conclusions

Results show a relationship between the number of social media applications used and increased rates of high-risk behaviors. We identified relevant risk factors that clinicians can use to screen for high-risk behavior and parents can monitor to encourage education about healthy online practices.
User-Dependent Usability and Feasibility of a Swallowing Training mHealth App for Older Adults: Mixed Methods Pilot Study (Preprint)
Authors: Kim HyangHee , Lee Sang-Ho , Cho Nam-Bin , You Heecheon , Choi Teukgyu , Kim Jinwon
Published: May 2020

BACKGROUND

Swallowing difficulties (ie, dysphagia) are common among older adults, with a 13% to 54% prevalence. Adequate interventions to improve the swallowing function of older adults would reduce morbidity and enhance health-related quality of life outcomes. Mobile health (mHealth) apps may help alleviate dysphagia symptoms by providing programs that maximize the intensity and frequency of training without requiring high costs or regular clinic visits.

OBJECTIVE

The aim of this pilot study was to assess the usability of swallowing training apps by quantitatively and qualitatively evaluating older adults’ self-reported data, taking into consideration their educational levels and exposure to mobile technology. We conducted surveys and brief interviews while the participants used a swallowing intervention app we developed. We subsequently identified and resolved individual-specific usability issues to improve future implementation of the app protocol for older persons with swallowing difficulties.

METHODS

A total of 11 participants (10 women, 91%; mean age 75.7 years, SD 3.93) from two district-run senior welfare centers took part in this study. The participants were divided into a high-potential group and a low-potential group based on their total number of years of education and smart device usage. To investigate the usability of the app twice (ie, in the second week of the intervention and the postintervention stage), we used mixed methods consisting of both quantitative approaches, namely the System Usability Scale (SUS) and modified Computer Self-Efficacy Scale (mCSES) surveys, and qualitative approaches (ie, interviews).

RESULTS

The quantitative results of the SUS and mCSES surveys revealed that the high-potential group was more inclined to adopt and learn new technology than the low-potential group. Specifically, within the high-potential group, a Wilcoxon signed-rank test indicated that the postintervention mCSES scores (median 65.50) were significantly higher than those in the second week of intervention (median 54.00; z=–2.023, P=.04). Additionally, the usability scores in the low-potential group were within the “marginal acceptability” range even after completion of an 8-week intervention program. Qualitative analyses via semi-structured interviews yielded promising outcomes regarding app acceptability, training program utilization, emotional responses, and learning experience.

CONCLUSIONS

To the best of the authors’ knowledge, this usability and feasibility study is the first report of a swallowing training app designed to improve the swallowing function of older adults. Future research should consider several issues, such as user characteristics, pretraining education, and the intensity and innate characteristics of the intervention program.
Physiotherapists’ Use of Web-Based Information Resources to Fulfill Their Information Needs During a Theoretical Examination: Randomized Crossover Trial (Preprint)
Authors: Doherty Cailbhe , Joorabchi Arash , Megyesi Peter , Flynn Aileen , Caulfield Brian
Published: May 2020

BACKGROUND

The widespread availability of internet-connected smart devices in the health care setting has the potential to improve the delivery of research evidence to the care pathway and fulfill health care professionals’ information needs.

OBJECTIVE

This study aims to evaluate the frequency with which physiotherapists experience information needs, the capacity of digital information resources to fulfill these needs, and the specific types of resources they use to do so.

METHODS

A total of 38 participants (all practicing physiotherapists; 19 females, 19 males) were randomly assigned to complete three 20-question multiple-choice questionnaire (MCQ) examinations under 3 conditions in a randomized crossover study design: assisted by a web browser, assisted by a federated search portal system, and unassisted. MCQ scores, times, and frequencies of information needs were recorded for overall examination-level and individual question-level analyses. Generalized estimating equations were used to assess differences between conditions for the primary outcomes. A log file analysis was conducted to evaluate participants’ web search and retrieval behaviors.

RESULTS

Participants experienced an information need in 55.59% (845/1520) MCQs (assisted conditions only) and exhibited a mean improvement of 10% and 16% in overall examination scores for the federated search and web browser conditions, respectively, compared with the unassisted condition (P<.001). In the web browser condition, Google was the most popular resource and the only search engine used, accounting for 1273 (64%) of hits, followed by PubMed (195 hits; 10% of total). In the federated search condition, Wikipedia and PubMed were the most popular resources with 1518 (46% of total) and 1273 (39% of total) hits, respectively.

CONCLUSIONS

In agreement with the findings of previous research studies among medical physicians, the results of this study demonstrate that physiotherapists frequently experience information needs. This study provides new insights into the preferred digital information resources used by physiotherapists to fulfill these needs. Future research should clarify the implications of physiotherapists’ apparent high reliance on Google, whether these results reflect the authentic clinical environment, and whether fulfilling clinical information needs alters practice behaviors or improves patient outcomes.
E-cigarettes Perceptions and Use among Jordanian Medical Students
Authors: K Al Oweidat , M Saleh , S Mubarak , A Alomoush , S Alrahmeh , R Alhyari , G Alnajdawi , M Yousef , M Juweid
Published: May 2020

Purpose: Medical students are the cornerstone for future public health awareness; this study aimed to assess e-cigarettes perceptions and use among medical students.Methods: This is a cross-sectional, questionnaire-based national study. The study included all five medical schools in the country and addressed students in their clinical years. Data were collected through a self-administered and structured paper-based questionnaire between Dec 1, 2018, and Mar 30, 2019. Data obtained were analyzed using IBM SPSS Statistics for Windows and univariate inferential tests were employed to examine differences between groups.Results: A total sample of 1819 (97.4%) students returned their questionnaires; with a declaration of their smoking habits from the five medical schools, 47% are males, and 53% are females. Only 13 students 0.7% of all students or 2.1% of all smokers used e-cigarettes solely, but 177 students 9.5% of all students or 29% of all smokers used e-cigarettes combined with other types of smoking. Most medical students (86%) were aware of e-cigarettes. The main motive behind using e-cigarettes was the rare and different flavors provided by these cigarettes. The general perception among smokers and non-smokers is that e-cigarettes are less harmful and helpful in quitting smoking.Conclusion: Most medical students are aware of e-cigarettes. While their use as the only form of smoking is rare, e-cigarettes are frequently used in combination with other types of smoking.
Los límites procesales de la protección de derechos fundamentales y el filtro de admisibilidad en la Corte de Apelaciones
Authors: Larroucau Torres Jorge
Published: May 2020

The procedural protection of the fundamental rights by art. 20 of the 1980 Constitution have substantive and procedural limits. This article analyzes the procedural reasons supporting the fact of not giving rise to the protection for any general reason –distribution of powers– or two specific criteria: the inability of providing precautionary measure and the deference with the specialized instances. For reasons of justice and efficiency, the Courts of appeals should apply these criteria when deciding on the admissibility of the protection, unless there is information to invoke the thesis of the “evident violation”, which it is usually based on the guarantee of property or the guarantee of due process.
La lucidez fragmentaria: Jean de la Bruyère y la cuarta edición de Los caracteres
Authors: Echeverría Zuno Adolfo
Published: May 2020

Cuando Jean de La Bruyère empezó a escribir los primeros textos de Los caracteres, la máxima había ya alcanzado un lugar preponderante como género privilegiado de la crítica ética y moral del Clasicismo francés. No bastante, la cuarta edición de su obra (publicada en 1689) introdujo ciertas innovaciones ideológicas y escriturales que trascendieron las convenciones de la máxima clásica. Al objetar tajantemente la exposición discursiva propia de la discusión filosófica y la argumentación teológica, La Bruyère favoreció, en contra de las abstracciones sistémicas, el análisis fragmentario y la conjetura demostrativa. Este acontecimiento representó un hecho literario históricamente notable, pues le permitió a la máxima alcanzar una modernidad sin precedentes, al convertir el lenguaje, a la vez, en instrumento y materia de investigación y examen de sí mismo.
La hermenéutica como lectura y traducción en George Steiner
Authors: López Hernández Fernando Aurelio
Published: May 2020

El artículo explora algunas tesis centrales de George Steiner —el acto de lectura, la traducción como interpretación y la razón de ser del arte— en el contexto de lo que él denomina el mundo de la “post-palabra”. En efecto, en la sociedad contemporánea se ha erosionado la “cultura logocéntrica”, aquella que tiene al logos como referencia sustantiva de la educación y de la formación intelectual. Para Steiner, el lector es un intérprete y éste debe ser, ante todo, un filólogo; el libro es una fuente inagotable de sentido y el quehacer hermenéutico un arduo trabajo intelectual. La instrumentalización de la lectura ha provocado que cada vez sea más arduo para el lector contemporáneo el encuentro con textos cuya dificultad supone aislamiento, silencio, meditación, y que demandan una respuesta, un compromiso responsable frente a lo leído.
lectura sociocrítica de la novela francesa contemporánea No y yo, de Delphine de Vigan
Authors: Landais Choimet Monique
Published: May 2020

Elegir es eliminar, pero también es privilegiar y, para este artículo, mi elección recayó en No y yo (2007) de Delphine de Vigan, una novela que se encuentra en la encrucijada de dos tendencias literarias muy estudiadas por Dominique Viart y Alexandre Gefen.  El primero de estos dos teóricos franceses ha estado analizando la literatura de campo desde los años 80; el segundo explora la función terapéutica de una práctica escritural que busca reparar al mundo. Esta encrucijada de ópticas en el límite de la producción literaria y de las ciencias humanas y sociales ilustra la facultad de la literatura para organizar encuentros individuales que nos ayudan a comprender mejor el mundo social, sus problemas estéticos y éticos, sus caminos tortuosos e improbables que nos revelan a nosotros mismos y a los demás. A través de la perspectiva sociocrítica de Claude Duchet y Pierre Popovic, este artículo planea dilucidar qué dice la novela sobre el mundo y de qué manera lo dice. Así definida, la lectura sociocrítica toma forma y sentido a medida que se entrelazan el análisis textual y el estudio sociológico de la novela. Este enfoque híbrido captura el espíritu de nuestro tiempo y fomenta una reflexividad crítica.