bluuebunny/crossref_metadata_2025 huggingface dataset:
Continuous 7-Month Internet of Things–Based Monitoring of Health Parameters of Pregnant and Postpartum Women: Prospective Observational Feasibility Study
Authors: Saarikko Johanna , Niela-Vilen Hannakaisa , Ekholm Eeva , Hamari Lotta , Azimi Iman , Liljeberg Pasi , Rahmani Amir M , Löyttyniemi Eliisa , Axelin Anna
Published: May 2020

Background

Monitoring during pregnancy is vital to ensure the mother’s and infant’s health. Remote continuous monitoring provides health care professionals with significant opportunities to observe health-related parameters in their patients and to detect any pathological signs at an early stage of pregnancy, and may thus partially replace traditional appointments.

Objective

This study aimed to evaluate the feasibility of continuously monitoring the health parameters (physical activity, sleep, and heart rate) of nulliparous women throughout pregnancy and until 1 month postpartum, with a smart wristband and an Internet of Things (IoT)–based monitoring system.

Methods

This prospective observational feasibility study used a convenience sample of 20 nulliparous women from the Hospital District of Southwest Finland. Continuous monitoring of physical activity/step counts, sleep, and heart rate was performed with a smart wristband for 24 hours a day, 7 days a week over 7 months (6 months during pregnancy and 1 month postpartum). The smart wristband was connected to a cloud server. The total number of possible monitoring days during pregnancy weeks 13 to 42 was 203 days and 28 days in the postpartum period.

Results

Valid physical activity data were available for a median of 144 (range 13-188) days (75% of possible monitoring days), and valid sleep data were available for a median of 137 (range 0-184) days (72% of possible monitoring days) per participant during pregnancy. During the postpartum period, a median of 15 (range 0-25) days (54% of possible monitoring days) of valid physical activity data and 16 (range 0-27) days (57% of possible monitoring days) of valid sleep data were available. Physical activity decreased from the second trimester to the third trimester by a mean of 1793 (95% CI 1039-2548) steps per day (P<.001). The decrease continued by a mean of 1339 (95% CI 474-2205) steps to the postpartum period (P=.004). Sleep during pregnancy also decreased from the second trimester to the third trimester by a mean of 20 minutes (95% CI –0.7 to 42 minutes; P=.06) and sleep time shortened an additional 1 hour (95% CI 39 minutes to 1.5 hours) after delivery (P<.001). The mean resting heart rate increased toward the third trimester and returned to the early pregnancy level during the postpartum period.

Conclusions

The smart wristband with IoT technology was a feasible system for collecting representative data on continuous variables of health parameters during pregnancy. Continuous monitoring provides real-time information between scheduled appointments and thus may help target and tailor pregnancy follow-up.
Robust Feature Engineering for Parkinson Disease Diagnosis: New Machine Learning Techniques
Authors: Wang Max , Ge Wenbo , Apthorp Deborah , Suominen Hanna
Published: May 2020

Background

Parkinson disease (PD) is a common neurodegenerative disorder that affects between 7 and 10 million people worldwide. No objective test for PD currently exists, and studies suggest misdiagnosis rates of up to 34%. Machine learning (ML) presents an opportunity to improve diagnosis; however, the size and nature of data sets make it difficult to generalize the performance of ML models to real-world applications.

Objective

This study aims to consolidate prior work and introduce new techniques in feature engineering and ML for diagnosis based on vowel phonation. Additional features and ML techniques were introduced, showing major performance improvements on the large mPower vocal phonation data set.

Methods

We used 1600 randomly selected /aa/ phonation samples from the entire data set to derive rules for filtering out faulty samples from the data set. The application of these rules, along with a joint age-gender balancing filter, results in a data set of 511 PD patients and 511 controls. We calculated features on a 1.5-second window of audio, beginning at the 1-second mark, for a support vector machine. This was evaluated with 10-fold cross-validation (CV), with stratification for balancing the number of patients and controls for each CV fold.

Results

We showed that the features used in prior literature do not perform well when extrapolated to the much larger mPower data set. Owing to the natural variation in speech, the separation of patients and controls is not as simple as previously believed. We presented significant performance improvements using additional novel features (with 88.6% certainty, derived from a Bayesian correlated t test) in separating patients and controls, with accuracy exceeding 58%.

Conclusions

The results are promising, showing the potential for ML in detecting symptoms imperceptible to a neurologist.
Efficiency of Text Message Contact on Medical Safety in Outpatient Surgery: Retrospective Study
Authors: Peuchot Jeremy , Allard Etienne , Dureuil Bertrand , Veber Benoit , Compère Vincent
Published: May 2020

Background

Establishing pre- and postoperative contact with patients is part of successful medical management in outpatient surgery. In France, this is mostly done via telephone. Automated information with short message service (SMS) reminders might be an interesting alternative to increase the rate of compliance with preoperative instructions, but no study has shown the safety of this approach.

Objective

The objective of this study was to evaluate the impact of pre- and postoperative automated information with SMS reminders on medical safety in outpatient surgery.

Methods

We conducted a retrospective, single-center, nonrandomized, controlled study with a before-after design. All adult patients who had outpatient surgery between September 2016 and December 2017 in our university hospital center were included. Before April 2017, patients were contacted by telephone by an outpatient surgery nurse. After April 2017, patients were contacted by SMS reminder. All patients were contacted the day before and the day after surgery. Patients contacted by SMS reminder were also contacted on day 7 after surgery. The primary end point was the conversion rate to full-time hospitalization. Secondary end points were hospitalization causes (anesthetic, surgical, organizational) and hospitalization costs.

Results

A total of 4388 patients were included, 2160 before and 2228 after the introduction of SMS reminders. The conversion rate to full-time hospitalization was 34/4388 (0.77%) with a difference between SMS group (8/2228, 0.36%) and telephone group (26/2160, 1.20%). The cost of SMS reminders was estimated as half that of telephone calls.

Conclusions

In this work, we report a decrease in the rate of conversion to full-time hospitalization with the use of pre- and postoperative SMS reminders. This new approach could represent a safe and cost-effective method in an outpatient surgery setting.
Monitoring Occupational Sitting, Standing, and Stepping in Office Employees With the W@W-App and the MetaWearC Sensor: Validation Study
Authors: Bort-Roig Judit , Chirveches-Pérez Emilia , Garcia-Cuyàs Francesc , Dowd Kieran P , Puig-Ribera Anna
Published: May 2020

Background

Replacing occupational sitting time with active tasks has several proposed health benefits for office employees. Mobile phones and motion sensors can provide objective information in real time on occupational sitting behavior. However, the validity and feasibility of using mobile health (mHealth) devices to quantify and modify occupational sedentary time is unclear.

Objective

The aim of this study is to validate the new Walk@Work-Application (W@W-App)—including an external motion sensor (MetaWearC) attached to the thigh—for measuring occupational sitting, standing, and stepping in free-living conditions against the activPAL3M, the current gold-standard, device-based measure for postural behaviors.

Methods

In total, 20 office workers (16 [80%] females; mean age 39.5, SD 8.1 years) downloaded the W@W-App to their mobile phones, wore a MetaWearC sensor attached to their thigh using a tailored band, and wore the activPAL3M for 3-8 consecutive working hours. Differences between both measures were examined using paired-samples t tests and Wilcoxon signed-rank tests. Agreement between measures was examined using concordance correlation coefficients (CCCs), 95% CIs, Bland-Altman plots (mean bias, 95% limits of agreement [LoA]), and equivalence testing techniques.

Results

The median recording time for the W@W-App+MetaWearC and the activPAL3M was 237.5 (SD 132.8) minutes and 240.0 (SD 127.5) minutes, respectively (P<.001). No significant differences between sitting (P=.53), standing (P=.12), and stepping times (P=.61) were identified. The CCC identified substantial agreement between both measures for sitting (CCC=0.98, 95% CI 0.96-0.99), moderate agreement for standing (CCC=0.93, 95% CI 0.81-0.97), and poor agreement for stepping (CCC=0.74, 95% CI 0.47-0.88). Bland-Altman plots indicated that sitting time (mean bias –1.66 minutes, 95% LoA –30.37 to 20.05) and standing time (mean bias –4.85 minutes, 95% LoA –31.31 to 21.62) were underreported. For stepping time, a positive mean bias of 1.15 minutes (95% LoA –15.11 to 17.41) was identified. Equivalence testing demonstrated that the estimates obtained from the W@W-App+MetaWearC and the activPAL3M were considered equivalent for all variables excluding stepping time.

Conclusions

The W@W-App+MetaWearC is a low-cost tool with acceptable levels of accuracy that can objectively quantify occupational sitting, standing, stationary, and upright times in real time. Due to the availability of real-time feedback for users, this tool can positively influence occupational sitting behaviors in future interventions.

Trial Registration

ClinicalTrials.gov NCT04092738; https://clinicaltrials.gov/ct2/show/NCT04092738
Effectiveness of Wearable Trackers on Physical Activity in Healthy Adults: Systematic Review and Meta-Analysis of Randomized Controlled Trials
Authors: Tang Matilda Swee Sun , Moore Katherine , McGavigan Andrew , Clark Robyn A , Ganesan Anand N
Published: May 2020

Background

Wearable trackers are an increasingly popular tool among healthy adults and are used to facilitate self-monitoring of physical activity.

Objective

We aimed to systematically review the effectiveness of wearable trackers for improving physical activity and weight reduction among healthy adults.

Methods

This review used the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methodology and reporting criteria. English-language randomized controlled trials with more than 20 participants from MEDLINE, CINAHL, Cochrane Library, Web of Science, PubMed, and Scopus (2000-2017) were identified. Studies were eligible for inclusion if they reported an intervention group using wearable trackers, reporting steps per day, total moderate-to-vigorous physical activity, activity, physical activity, energy expenditure, and weight reduction.

Results

Twelve eligible studies with a total of 1693 participants met the inclusion criteria. The weighted average age was 40.7 years (95% CI 31.1-50.3), with 64.4% women. The mean intervention duration was 21.4 weeks (95% CI 6.1-36.7). The usage of wearable trackers was associated with increased physical activity (standardized mean difference 0.449, 95% CI 0.10-0.80; P=.01). In the subgroup analyses, however, wearable trackers demonstrated no clear benefit for physical activity or weight reduction.

Conclusions

These data suggest that the use of wearable trackers in healthy adults may be associated with modest short-term increases in physical activity. Further data are required to determine if a sustained benefit is associated with wearable tracker usage.
Combination of 3-Dimensional Virtual Reality and Hands-On Aromatherapy in Improving Institutionalized Older Adults’ Psychological Health: Quasi-Experimental Study
Authors: Cheng Vivian Ya-Wen , Huang Chiu-Mieh , Liao Jung-Yu , Hsu Hsiao-Pei , Wang Shih-Wen , Huang Su-Fei , Guo Jong-Long
Published: May 2020

Background

In Taiwan, which has one of the most rapidly aging populations in the world, it is becoming increasingly critical to promote successful aging strategies that are effective, easily usable, and acceptable to institutionalized older adults. Although many practitioners and professionals have explored aromatherapy and identified its psychological benefits, the effectiveness of combining 3-dimensional (3D) virtual reality and hands-on aromatherapy remains unknown.

Objective

A quasi-experimental trial was designed to evaluate the effectiveness of this combination in lowering perceived stress and promoting happiness, sleep quality, meditation experience, and life satisfaction among institutionalized older adults in Taiwan.

Methods

A total of 60 institutionalized elderly participants either received the combined intervention or were in a control group. Weekly 2-hour sessions were implemented over 9 weeks. The outcome variables were happiness, perceived stress, sleep quality, meditation experience, and life satisfaction, which were assessed at baseline and after the intervention.

Results

Generalized estimating equation (GEE) analyses indicated that the experimental group showed significant post-intervention improvements in terms of scores for happiness, perceived stress, sleep quality, meditation experience, and life satisfaction (n=48; all P<.001). Another GEE analysis showed that the significant improvements in the 5 outcome variables persisted in participants aged 80 years and older (n=35; all P<.001).

Conclusions

This is the first trial to explore the effectiveness of a combination of 3D virtual reality and hands-on aromatherapy in improving older adults’ psychological health. The results are promising for the promotion of psychological health in institutionalized older adults.

Trial Registration

ClinicalTrials.gov NCT04324216; https://clinicaltrials.gov/ct2/show/NCT04324216.
Ecological Momentary Assessment Within a Digital Health Intervention for Reminiscence in Persons With Dementia and Caregivers: User Engagement Study
Authors: Potts Courtney , Bond Raymond , Ryan Assumpta , Mulvenna Maurice , McCauley Claire , Laird Elizabeth , Goode Deborah
Published: May 2020

Background

User-interaction event logs provide rich and large data sets that can provide valuable insights into how people engage with technology. Approaches such as ecological momentary assessment (EMA) can be used to gather accurate real-time data in an individual’s natural environment by asking questions at any given instant.

Objective

The purpose of this study was to evaluate user engagement and responses to EMA questions using InspireD, an app used for reminiscence by persons with dementia and their caregivers. Research findings can be used to inform EMA use within digital health interventions.

Methods

A feasibility trial was conducted in which participants (n=56) used the InspireD app over a 12-week period. Participants were a mean age of 73 (SD 13) and were either persons with dementia (n=28) or their caregivers (n=28). Questions, which they could either answer or choose to dismiss, were presented to participants at various instants after reminiscence with personal or generic photos, videos, and music. Presentation and dismissal rates for questions were compared by hour of the day and by trial week to investigate user engagement.

Results

Overall engagement was high, with 69.1% of questions answered when presented. Questions that were presented in the evening had the lowest dismissal rate; the dismissal rate for questions presented at 9 PM was significantly lower than the dismissal rate for questions presented at 11 AM (9 PM: 10%; 11 AM: 50%; χ21=21.4, P<.001). Questions asked following reminiscence with personal media, especially those asked after personal photos, were less likely to be answered compared to those asked after other media. In contrast, questions asked after the user had listened to generic media, in particular those asked after generic music, were much more likely to be answered.

Conclusions

The main limitation of our study was the lack of generalizability of results to a larger population given the quasi-experimental design and older demographic where half of participants were persons with dementia; however, this study shows that older people are willing to participate and engage in EMA. Based on this study, we propose a series of recommendations for app design to increase user engagement with EMA. These include presenting questions no more than once per day, after 8 PM in the evening, and only if the user is not trying to complete a task within the app.
Managing Illicit Online Pharmacies: Web Analytics and Predictive Models Study
Authors: Zhao Hui , Muthupandi Sowmyasri , Kumara Soundar
Published: May 2020

Background

Online pharmacies have grown significantly in recent years, from US $29.35 billion in 2014 to an expected US $128 billion in 2023 worldwide. Although legitimate online pharmacies (LOPs) provide a channel of convenience and potentially lower costs for patients, illicit online pharmacies (IOPs) open the doors to unfettered access to prescription drugs, controlled substances (eg, opioids), and potentially counterfeits, posing a dramatic risk to the drug supply chain and the health of the patient. Unfortunately, we know little about IOPs, and even identifying and monitoring IOPs is challenging because of the large number of online pharmacies (at least 30,000-35,000) and the dynamic nature of the online channel (online pharmacies open and shut down easily).

Objective

This study aims to increase our understanding of IOPs through web data traffic analysis and propose a novel framework using referral links to predict and identify IOPs, the first step in fighting IOPs.

Methods

We first collected web traffic and engagement data to study and compare how consumers access and engage with LOPs and IOPs. We then proposed a simple but novel framework for predicting the status of online pharmacies (legitimate or illicit) through the referral links between websites. Under this framework, we developed 2 prediction models, the reference rating prediction method (RRPM) and the reference-based K-nearest neighbor.

Results

We found that direct (typing URL), search, and referral are the 3 major traffic sources, representing more than 95% traffic to both LOPs and IOPs. It is alarming to see that direct represents the second-highest traffic source (34.32%) to IOPs. When tested on a data set with 763 online pharmacies, both RRPM and R2NN performed well, achieving an accuracy above 95% in their predictions of the status for the online pharmacies. R2NN outperformed RRPM in full performance metrics (accuracy, kappa, specificity, and sensitivity). On implementing the 2 models on Google search results for popular drugs (Xanax [alprazolam], OxyContin, and opioids), they produced an error rate of only 7.96% (R2NN) and 6.20% (RRPM).

Conclusions

Our prediction models use what we know (referral links) to tackle the many unknown aspects of IOPs. They have many potential applications for patients, search engines, social media, payment companies, policy makers or government agencies, and drug manufacturers to help fight IOPs. With scarce work in this area, we hope to help address the current opioid crisis from this perspective and inspire future research in the critical area of drug safety.
Wikipedia in Vascular Surgery Medical Education: Comparative Study
Authors: Yacob Michael , Lotfi Shamim , Tang Shannon , Jetty Prasad
Published: May 2020

Background

Medical students commonly refer to Wikipedia as their preferred online resource for medical information. The quality and readability of articles about common vascular disorders on Wikipedia has not been evaluated or compared against a standard textbook of surgery.

Objective

The aims of this study were to (1) compare the quality of Wikipedia articles to that of equivalent chapters in a standard undergraduate medical textbook of surgery, (2) identify any errors of omission in either resource, and (3) compare the readability of both resources using validated ease-of-reading and grade-level tools.

Methods

Using the Medical Council of Canada Objectives for the Qualifying Examination, 8 fundamental topics of vascular surgery were chosen. The articles were found on Wikipedia using Wikipedia’s native search engine. The equivalent chapters were identified in Schwartz Principles of Surgery (ninth edition). Medical learners (n=2) assessed each of the texts on their original platforms to independently evaluate readability, quality, and errors of omission. Readability was evaluated with Flesch Reading Ease scores and 5 grade-level scores (Flesch-Kincaid Grade Level, Gunning Fog Index, Coleman-Liau Index, Simple Measure of Gobbledygook Index, and Automated Readability Index), quality was evaluated using the DISCERN instrument, and errors of omission were evaluated using a standardized scoring system that was designed by the authors.

Results

Flesch Reading Ease scores suggested that Wikipedia (mean 30.5; SD 8.4) was significantly easier to read (P=.03) than Schwartz (mean 20.2; SD 9.0). The mean grade level (calculated using all grade-level indices) of the Wikipedia articles (mean 14.2; SD 1.3) was significantly different (P=.02) than the mean grade level of Schwartz (mean 15.9; SD 1.4). The quality of the text was also assessed using the DISCERN instrument and suggested that Schwartz (mean 71.4; SD 3.1) had a significantly higher quality (P=.002) compared to that of Wikipedia (mean 52.9; SD 11.4). Finally, the Wikipedia error of omission rate (mean 12.5; SD 6.8) was higher than that of Schwartz (mean 21.3; SD 1.9) indicating that there were significantly fewer errors of omission in the surgical textbook (P=.008).

Conclusions

Online resources are increasingly easier to access but can vary in quality. Based on this comparison, the authors of this study recommend the use of vascular surgery textbooks as a primary source of learning material because the information within is more consistent in quality and has fewer errors of omission. Wikipedia can be a useful resource for quick reference, particularly because of its ease of reading, but its vascular surgery articles require further development.
Using Online Support Communities for Tourette Syndrome and Tic Disorders: Online Survey of Users’ Experiences
Authors: Perkins Victoria , Coulson Neil S , Davies E Bethan
Published: May 2020

Background

People living with a tic disorder (TD)—such as Tourette syndrome (TS)—experience many negative psychological and social challenges arising from chronic tics, such as stigmatization from peers and poorer quality of life, and these can impact upon their families too. It can be difficult for this population to access face-to-face support for tics, and so online support communities offer one avenue for support from peers facing similar experiences. However, little is known about how online support communities may be used by people with TS and other TDs, and by others (eg, parents, caregivers) supporting a person with TS/TD.

Objective

This study aimed to explore users’ experiences of participation in online support communities for TS and TDs.

Methods

In total, 90 respondents (aged 13-62 years; 62% [56/90] female) from 13 countries completed an online survey exploring their experiences of using online support communities for TS and TDs. Respondents were people living with TS/TD themselves (n=68) or supportive others of someone with TS/TD (eg, parent, sibling, spouse; n=14), or both (n=8). The online survey contained open-ended questions eliciting their self-reported motivations for using online communities, their benefits and drawbacks of participation, and whether online support communities affected offline management of tics. Responses were analyzed using thematic analysis.

Results

Seven overarching themes captured experiences of using online support communities for TS/TDs. The overwhelming reason for their use was to find accessible support due to a lack of offline face-to-face support. Online support communities were valued sources of informational and emotional support, and also had a positive impact upon helping users’ psychological well-being. Online communities helped provide a space where people with TS/TDs could feel accepted and reduce the social isolation they felt offline. The suggestible nature of tics and being reminded of the challenging nature of TDs were main disadvantages arising from using online support communities, alongside conflict arising within online communities.

Conclusions

The findings suggest that online support communities appear to offer valuable informational and emotional support to those living with TS/TD and their families too, especially given the lack of locally available support. This facilitates a sense of community online, which can help users in overcoming long-standing social isolation and aid self-reported improvements in psychosocial well-being. Users reported some drawbacks in engaging with online support communities, such as conflict between different types of users and triggering content, which negatively affected experiences of community participation.
Artificial Intelligence in Health Care: Bibliometric Analysis
Authors: Guo Yuqi , Hao Zhichao , Zhao Shichong , Gong Jiaqi , Yang Fan
Published: May 2020

Background

As a critical driving power to promote health care, the health care–related artificial intelligence (AI) literature is growing rapidly.

Objective

The purpose of this analysis is to provide a dynamic and longitudinal bibliometric analysis of health care–related AI publications.

Methods

The Web of Science (Clarivate PLC) was searched to retrieve all existing and highly cited AI-related health care research papers published in English up to December 2019. Based on bibliometric indicators, a search strategy was developed to screen the title for eligibility, using the abstract and full text where needed. The growth rate of publications, characteristics of research activities, publication patterns, and research hotspot tendencies were computed using the HistCite software.

Results

The search identified 5235 hits, of which 1473 publications were included in the analyses. Publication output increased an average of 17.02% per year since 1995, but the growth rate of research papers significantly increased to 45.15% from 2014 to 2019. The major health problems studied in AI research are cancer, depression, Alzheimer disease, heart failure, and diabetes. Artificial neural networks, support vector machines, and convolutional neural networks have the highest impact on health care. Nucleosides, convolutional neural networks, and tumor markers have remained research hotspots through 2019.

Conclusions

This analysis provides a comprehensive overview of the AI-related research conducted in the field of health care, which helps researchers, policy makers, and practitioners better understand the development of health care–related AI research and possible practice implications. Future AI research should be dedicated to filling in the gaps between AI health care research and clinical applications.
An Untapped Potential in Primary Care: Semi-Structured Interviews with Clinicians on How Patient Portals Will Work for Caregivers in the Safety Net
Authors: Casillas Alejandra , Cemballi Anupama Gunshekar , Abhat Anshu , Lemberg Miya , Portz Jennifer D , Sadasivaiah Shobha , Ratanawongsa Neda , Semere Wagahta , Brown Arleen , Lyles Courtney Rees
Published: May 2020

Background

Patients within safety-net settings are less likely to access health information on patient portals, despite expressed interest. Family and friends are important resources to assist these patients (ie, Medicaid recipients, older patients, patients with limited English proficiency) in navigating health systems, and provider support of the use of patient portals among these groups may also facilitate caregivers’ use of their patients’ portal.

Objective

Because safety net providers work closely with caregivers to care for their patients, we used qualitative methods to explore safety net providers’ perspectives on portal use among caregivers for their patients, especially as there is limited literature about caregivers’ use of portals in the safety net.

Methods

We conducted 45- to 60-min semistructured telephone interviews with providers from three large California safety-net health systems. The interviews focused on providers’ experiences with caregivers, caregiver roles, and how the portal could be leveraged as a tool to support caregivers in their responsibilities. A total of three coders analyzed the interview transcripts using both deductive and inductive approaches and established a consensus regarding major themes.

Results

Of the 16 participants interviewed, 4 specialized in geriatrics, and all held a leadership or administrative role. We described themes highlighting providers’ recognition of potential benefits associated with caregiver portal use and specific challenges to caregiver engagement.

Conclusions

Providers recognized the potential for portals to improve information delivery and communication by helping caregivers assist socially and medically complex patients in the safety net. Providers in safety net sites also discussed a clear need for better ways to keep in touch with patients and connect with caregivers, yet security and privacy are perhaps of higher importance in these settings and may pose challenges to portal adoption. They noted that caregivers of patients in the safety net likely face similar communication barriers as patients, especially with respect to digital literacy, health literacy, and English proficiency. Further research is needed to assess and support caregivers’ interest and ability to access portals across barriers in health and digital literacy, and English proficiency. Portal platforms and health systems must also address specific strategies to uphold patient preferences while maintaining privacy and security.
Mobile Health App (AGRIPPA) to Prevent Relapse After Successful Interdisciplinary Treatment for Patients With Chronic Pain: Protocol for a Randomized Controlled Trial
Authors: Elbers Stefan , Pool Jan , Wittink Harriët , Köke Albère , Scheffer Else , Smeets Rob
Published: May 2020

Background

To facilitate adherence to adaptive pain management behaviors after interdisciplinary multimodal pain treatment, we developed a mobile health app (AGRIPPA app) that contains two behavior regulation strategies.

Objective

The aims of this project are (1) to test the effectiveness of the AGRIPPA app on pain disability; (2) to determine the cost-effectiveness; and (3) to explore the levels of engagement and usability of app users.

Methods

We will perform a multicenter randomized controlled trial with two parallel groups. Within the 12-month inclusion period, we plan to recruit 158 adult patients with chronic pain during the initial stage of their interdisciplinary treatment program in one of the 6 participating centers. Participants will be randomly assigned to the standard treatment condition or to the enhanced treatment condition in which they will receive the AGRIPPA app. Patients will be monitored from the start of the treatment program until 12 months posttreatment. In our primary analysis, we will evaluate the difference over time of pain-related disability between the two conditions. Other outcome measures will include health-related quality of life, illness perceptions, pain self-efficacy, app system usage data, productivity loss, and health care expenses.

Results

The study was approved by the local Medical Research Ethics Committee in October 2019. As of March 20, 2020, we have recruited 88 patients.

Conclusions

This study will be the first step in systematically evaluating the effectiveness and efficiency of the AGRIPPA app. After 3 years of development and feasibility testing, this formal evaluation will help determine to what extent the app will influence the maintenance of treatment gains over time. The outcomes of this trial will guide future decisions regarding uptake in clinical practice.

Trial Registration

Netherlands Trial Register NL8076; https://www.trialregister.nl/trial/8076

International Registered Report Identifier (IRRID)

DERR1-10.2196/18632
Assessing Patient Experience and Healthcare Quality of Dental Care Using Patient Online Reviews in the United States: Mixed Methods Study
Authors: Lin Ye , Hong Y Alicia , Henson Bradley S , Stevenson Robert D , Hong Simon , Lyu Tianchu , Liang Chen
Published: May 2020

Background

Over the last two decades, patient review websites have emerged as an essential online platform for doctor ratings and reviews. Recent studies suggested the significance of such websites as a data source for patients to choose doctors for healthcare providers to learn and improve from patient feedback and to foster a culture of trust and transparency between patients and healthcare providers. However, as compared to other medical specialties, studies of online patient reviews that focus on dentists in the United States remain absent.

Objective

This study sought to understand to what extent online patient reviews can provide performance feedbacks that reflect dental care quality and patient experience.

Methods

Using mixed informatics methods incorporating statistics, natural language processing, and domain expert evaluation, we analyzed the online patient reviews of 204,751 dentists extracted from HealthGrades with two specific aims. First, we examined the associations between patient ratings and a variety of dentist characteristics. Second, we identified topics from patient reviews that can be mapped to the national assessment of dental patient experience measured by the Patient Experience Measures from the Consumer Assessment of Healthcare Providers and Systems (CAHPS) Dental Plan Survey.

Results

Higher ratings were associated with female dentists (t71881=2.45, P<.01, g=0.01), dentists at a younger age (F7, 107128=246.97, P<.001, g=0.11), and those whose patients experienced a short wait time (F4, 150055=10417.77, P<0.001, g=0.18). We also identified several topics that corresponded to CAHPS measures, including discomfort (eg, painful/painless root canal or deep cleaning), and ethics (eg, high-pressure sales, and unnecessary dental work).

Conclusions

These findings suggest that online patient reviews could be used as a data source for understanding the patient experience and healthcare quality in dentistry.
Email Use Reconsidered in Health Professions Education: Viewpoint
Authors: De Gagne Jennie C , Yang Yesol , Rushton Sharron , Koppel Paula D , Hall Katherine
Published: May 2020

Email has become a popular means of communication in the past 40 years, with more than 200 billion emails sent each day worldwide. When used appropriately, email can be an effective and useful form of correspondence, although improper practices, such as email incivility, can present challenges. Email is ubiquitous in education and health care, where it is used for student-to-teacher, provider-to-provider, and patient-to-provider communications, but not all students, faculty members, and health professionals are skilled in its use. This paper examines the challenges and opportunities posed by email communication in health professions education and reveals important deficiencies in training, as well as steps that can be taken by health professions educators to address them. Recommendations are offered to help health professions educators develop approaches for teaching email professionalism.
Web-Based Self-Management for Patients With Lymphoma: Assessment of the Reach of Intervention of a Randomized Controlled Trial (Preprint)
Authors: Arts Lindy P J , Oerlemans Simone , Posthuma Eduardus F M , Issa Djamila E , Oosterveld Margriet , van der Griend René , Nijziel Marten R , van de Poll-Franse Lonneke V
Published: May 2020

BACKGROUND

Randomized controlled trials (RCTs) often provide accurate estimates of the internal validity of an intervention but lack information on external validity (generalizability). We conducted an RCT on the effectiveness of a self-management intervention among patients with lymphoma in a population-based setting.

OBJECTIVE

The objectives of the current study were to describe the proportion of RCT participants compared to all patients invited to participate, and compare sociodemographic and clinical characteristics of RCT participants with all respondents, all patients invited to participate, and all patients selected from the Netherlands Cancer Registry (NCR) to determine the reach of the intervention. An additional objective was to assess differences on RCT outcome variables between RCT and paper respondents.

METHODS

Patients with lymphoma or chronic lymphocytic leukemia ≥18 years old at diagnosis from 13 hospitals in the Netherlands were selected from the population-based NCR, which routinely collects data on sociodemographic and clinical characteristics. Eligible patients were invited to participate in an RCT and complete a questionnaire. Web-based completion determined RCT enrollment, whereas paper respondents were followed observationally.

RESULTS

A total of 1193 patients were selected from the NCR, 892 (74.77%) of whom were invited to participate in the trial by their hematologist after verifying eligibility. Among those invited, 25.4% (227/892) completed the web-based questionnaire and were enrolled in the RCT. The RCT participants were younger and there was a higher proportion of men than nonparticipants (P<.001). In addition, 25.7% (229/892) of those invited opted to participate in the paper-based observational follow-up study. Compared with paper respondents, RCT participants were younger (P<.001), with a higher proportion of men (P=.002), and had higher education levels (P=.02). RCT participants more often wanted to receive all available information on their disease (P<.001), whereas paper respondents reported higher levels of emotional distress (P=.009).

CONCLUSIONS

From a population-based sample of eligible patients, the participation rate in the RCT was approximately 25%. RCT participants may not be representative of the target population because of different sociodemographic and clinical characteristics. Since RCT participants represent a minority of the target population, RCT results should be interpreted with caution as patients in the RCT may be those least in need of a self-management intervention.

CLINICALTRIAL

Netherlands Trial Register NTR5953; https://www.trialregister.nl/trial/5790
Evaluation of a Mobile App to Enhance Relational Awareness and Change During Cognitive Analytic Therapy: Mixed Methods Case Series (Preprint)
Authors: Kellett Stephen , Easton Katherine , Cooper Martin , Millings Abigail , Simmonds-Buckley Melanie , Parry Glenys
Published: May 2020

BACKGROUND

There has been a lack of technological innovation regarding improving the delivery of integrative psychotherapies. This project sought to evaluate an app designed to replace previous paper-based methods supporting relational awareness and change during cognitive analytic therapy (CAT).

OBJECTIVE

We aimed to assess patients’ and therapists’ experience of using the technology (ie, the “CAT-App”) and to evaluate the relationship between app usage and clinical outcome.

METHODS

The design was a mixed methods case series. Patients completed the Clinical Outcomes in Routine Evaluation-Outcome Measure pre- and post-CAT. Mood data plus the frequency and effectiveness of relational awareness and change were collected via the app. Therapists and patients were interviewed about their experiences using the app.

RESULTS

Ten patients (treated by 3 therapists) were enrolled; seven completed treatment and 4 had a reliable improvement in their mental health. App usage and mood change did not differ according to clinical outcome, but there was a statistically significant difference in app usage between completers and dropouts. The qualitative themes described by the therapists were (1) the challenge of incorporating the technology into their clinical practice and (2) the barriers and benefits of the technology. Clients’ themes were (1) data protection, (2) motivation and engagement, and (3) restrictions versus flexibility.

CONCLUSIONS

The CAT-App is capable of supporting relational awareness and change and is an upgrade on older, paper-based formats. Further clinical evaluation is required.
Teaching Adequate Prehospital Use of Personal Protective Equipment During the COVID-19 Pandemic: Development of a Gamified e-Learning Module (Preprint)
Authors: Suppan Mélanie , Gartner Birgit , Golay Eric , Stuby Loric , White Marion , Cottet Philippe , Abbas Mohamed , Iten Anne , Harbarth Stephan , Suppan Laurent
Published: May 2020

BACKGROUND

The coronavirus disease (COVID-19) pandemic has led to increased use of personal protective equipment (PPE). Adequate use of this equipment is more critical than ever because the risk of shortages must be balanced against the need to effectively protect health care workers, including prehospital personnel. Specific training is therefore necessary; however, the need for social distancing has markedly disrupted the delivery of continuing education courses. Electronic learning (e-learning) may provide significant advantages because it requires neither the physical presence of learners nor the repetitive use of equipment for demonstration.

OBJECTIVE

Inclusion of game mechanics, or “gamification,” has been shown to increase knowledge and skill acquisition. The objective of this research was to develop a gamified e-learning module to interactively deliver concepts and information regarding the correct choice and handling of PPE.

METHODS

The SERES framework was used to define and describe the development process, including scientific and design foundations. After we defined the target audience and learning objectives by interviewing the stakeholders, we searched the scientific literature to establish relevant theoretical bases. The learning contents were validated by infection control and prehospital experts. Learning mechanics were then determined according to the learning objectives, and the content that could benefit from the inclusion of game mechanics was identified.

RESULTS

The literature search resulted in the selection and inclusion of 12 articles. In addition to gamification, pretesting, feedback, avoiding content skipping, and demonstrations using embedded videos were used as learning mechanics. Gamification was used to enhance the interactivity of the PPE donning and doffing sequences, which presented the greatest learning challenges. The module was developed with Articulate Storyline 3 to ensure that it would be compatible with a wide array of devices, as this software generates HTML5-compatible output that can be accessed on smartphones, tablets, and regular computers as long as a recent browser is available.

CONCLUSIONS

A gamified e-learning module designed to promote better knowledge and understanding of PPE use among prehospital health care workers was created by following the SERES framework. The impact of this module should now be assessed by means of a randomized controlled trial.
Blending Cognitive Analytic Therapy With a Digital Support Tool: Mixed Methods Study Involving a User-Centered Design of a Prototype App (Preprint)
Authors: Easton Katherine , Kellett Stephen , Cooper Martin , Millings Abigail , Varela Jo , Parry Glenys
Published: May 2020

BACKGROUND

Patients can struggle to make good use of psychotherapy owing to deficits in awareness, and digital technologies that support awareness are at a premium. Currently, when patients participate in cognitive analytic therapy (CAT), the technology supporting relational awareness work involves completion of paper-based worksheets as between-session tasks.

OBJECTIVE

We aimed to design, with therapists and patients, a prototype digital mobile app. This was to help patients better engage in the “recognition” phase of the CAT treatment model by providing an unobtrusive means for practicing relational awareness with dynamic feedback on progress.

METHODS

A national online survey was conducted with CAT therapists (n=50) to determine readiness for adoption of a mobile app in clinical practice and to identify core content, functionality, and potential barriers to adoption. A prototype mobile app based on data and existing paper-based worksheets was built. Initial face-to-face user testing of the prototype system was completed with three therapists and three CAT expatients.

RESULTS

Among the therapists surveyed, 72% (36/50) reported not currently using any digital tools during CAT. However, the potential value of a mobile app to support patient awareness was widely endorsed. Areas of therapist concern were data security, data governance, and equality of access. These concerns were mirrored during subsequent user testing by CAT therapists. Expatients generated additional user specifications on the design, functionality, and usability of the app. Results from both streams were integrated to produce five key changes for the reiteration of the app.

CONCLUSIONS

The user-centered design process has enabled a prototype CAT-App to be developed to enhance the relational awareness work of CAT. This means that patients can now practice relational awareness in a much more unobtrusive manner and with ongoing dynamic feedback of progress. Testing the acceptability and feasibility of this technological innovation in clinical practice is the next stage in the research process, which has since been conducted and has been submitted. The important challenges of data protection and governance must be navigated in order to ensure implementation and adoption if the CAT-App is found to be acceptable and clinically effective.
Classical simulation of linear optics subject to nonuniform losses
Authors: Brod Daniel Jost , Oszmaniec Michał
Published: May 2020

We present a comprehensive study of the impact of non-uniform, i.e. path-dependent, photonic losses on the computational complexity of linear-optical processes. Our main result states that, if each beam splitter in a network induces some loss probability, non-uniform network designs cannot circumvent the efficient classical simulations based on losses.To achieve our result we obtain new intermediate results that can be of independent interest. First we show that, for any network of lossy beam-splitters, it is possible to extract a layer of non-uniform losses that depends on the network geometry. We prove that, for every input mode of the network it is possible to commutesilayers of losses to the input, wheresiis the length of the shortest path connecting theith input to any output. We then extend a recent classical simulation algorithm due to P. Clifford and R. Clifford to allow for arbitraryn-photon input Fock states (i.e. to include collision states). Consequently, we identify two types of input states where boson sampling becomes classically simulable: (A) whenninput photons occupy a constant number of input modes; (B) when all butO(log⁡n)photons are concentrated on a single input mode, while an additionalO(log⁡n)modes contain one photon each.