Smartphone-based App Research Articles

A Personalized Management Approach of OHSS: Development of a Multiphase Prediction Model and Smartphone-Based App.

ObjectiveThis study aimed to develop multiphase big-data-based prediction models of ovarian hyperstimulation syndrome (OHSS) and a smartphone app for risk calculation and patients’ self-monitoring.MethodsMultiphase prediction models were developed from a retrospective cohort database of 21,566 women from January 2017 to December 2020 with controlled ovarian stimulation (COS). There were 17,445 women included in the final data analysis. Women were randomly assigned to either training cohort (n = 12,211) or validation cohort (n = 5,234). Their baseline clinical characteristics, COS-related characteristics, and embryo information were evaluated. The prediction models were divided into four phases: 1) prior to COS, 2) on the day of ovulation trigger, 3) after oocyte retrieval, and 4) prior to embryo transfer. The multiphase prediction models were built with stepwise regression and confirmed with LASSO regression. Internal validations were performed using the validation cohort and were assessed by discrimination and calibration, as well as clinical decision curves. A smartphone-based app “OHSS monitor” was constructed as part of the built-in app of the IVF-aid platform. The app had three modules, risk prediction module, symptom monitoring module, and treatment monitoring module.ResultsThe multiphase prediction models were developed with acceptable distinguishing ability to identify OHSS at-risk patients. The C-statistics of the first, second, third, and fourth phases in the training cohort were 0.628 (95% CI 0.598–0.658), 0.715 (95% CI 0.688–0.742), 0.792 (95% CI 0.770–0.815), and 0.814 (95% CI 0.793–0.834), respectively. The calibration plot showed the agreement of predictive and observed risks of OHSS, especially at the third- and fourth-phase prediction models in both training and validation cohorts. The net clinical benefits of the multiphase prediction models were also confirmed with a clinical decision curve. A smartphone-based app was constructed as a risk calculator based on the multiphase prediction models, and also as a self-monitoring tool for patients at risk.ConclusionsWe have built multiphase prediction models based on big data and constructed a user-friendly smartphone-based app for the personalized management of women at risk of moderate/severe OHSS. The multiphase prediction models and user-friendly app can be readily used in clinical practice for clinical decision-support and self-management of patients.

Predictors of mHealth use in promoting adherence to pre-exposure prophylaxis among female sex workers: an evaluation of the Jichunge intervention in Dar es Salaam, Tanzania

BackgroundThere is evidence that pre-exposure prophylaxis (PrEP) is effective in preventing HIV transmission, and PrEP is recommended by the World Health organization (WHO) for use by individuals at high risk of HIV infection. However, low adherence has been reported to hamper its effectiveness. Some evidence indicates that mHealth interventions may be a promising way of promoting PrEP adherence. Nevertheless, evaluations of mHealth interventions in Africa, the region most affected by HIV, are scarce. This study aimed at identifying the extent of and predictors for use of a smartphone based mHealth application among female sex workers in Dar es Salaam, Tanzania.MethodsAs part of a quasi-experimental study in Tanzania, 470 female sex workers who were eligible for PrEP and who owned a smartphone were recruited using respondent driven sampling. All participants were provided with an mHealth application called Jichunge, a smartphone-based app designed to promote adherence to PrEP by offering users information, advise and support during start-up and use of PrEP. We collected data through structured interviews at baseline and extracted user data from the app for a period of 30 days. Modified Poisson regression model with robust standard errors was used to identify predictors for the optimal use of the Jichunge app.ResultsOverall, the optimal use of the Jichunge app was 46.4%. Optimal use was significantly higher among women who were older (aPR = 1.3, 95% CI: 1.10-1.65, p = 0.004 for age 25-34 years, and aPR = 1.6, 95% CI: 1.19-2.07, p = 0.001 for age at least 35 years), who had secondary education or higher (aPR = 1.8, 95% CI: 1.08-2.94, p = 0.023), who had suboptimal social support (aPR = 1.2, 95% CI: 1.02-1.48, p = 0.030), who had high awareness of PrEP (aPR = 1.3, 95% CI: 1.08-1.55, p = 0.005), and who had experience using common mainstream social media applications (aPR = 1.4, 95% CI: 1.08-1.71, p = 0.009).ConclusionOptimal use of the Jichunge app was substantially higher among women with higher age, higher education, higher PrEP awareness, less social support, and experience using common social media applications. Individual and interpersonal factors should be considered in planning mHealth interventions. Further studies to determine predictors of longer-term mHealth engagement are needed.Trial registrationInternational Clinical Trials Registry Platform PACTR202003823226570; 04.03.2020.

P019 Validation of a Smartphone-Based App for Assessing Energy Intake: A Pilot Study

<h3>Background</h3> Smartphone-based methods are innovative and promising tools to accurately quantify energy intake (EI). The PortionSize^TM app measures dietary intake using embedded templates and provides real-time feedback. PortionSize also sends food images to a server where they can be analyzed using the Remote Food Photography Method (RFPM). The RFPM accurately measures EI; however, it requires human raters to analyze food images; therefore, the RFPM does not provide dietary feedback in real-time. <h3>Objective</h3> To compare the validity of EI estimates from PortionSize and RFPM to weighed meals (WM). <h3>Study Design, Setting, Participants</h3> Fifteen adults used the PortionSize app during covertly-weighed simulated meals in a laboratory setting. Trained personnel also quantified EI from the images captured from the PortionSize using the RFPM. <h3>Measurable Outcome/ Analysis</h3> Demographics and body mass index (BMI). Dependent t-tests were performed to investigate whether EI measured with templates in PortionSize or using the RFPM differed to EI from WM. <h3>Results</h3> Mean (± SD) age and BMI of participants were 28 (± 12) years and 24.1 ± 6.6 kg/m2, respectively, and 73.3% were female. PortionSize estimated EI was 743 ± 328 kcal, EI RFPM-estimated intake was 660 ± 196 kcal, and weighed intake was 659 ± 191 kcal. The mean differences of EI estimation between PortionSize and WM (84 ± 288 kcal) and between RFPM and WM (1 ± 32 kcal) were not significant (<i>P</i> > .05). The mean difference in EI estimation (83 ±284 kcal) between PortionSize and RFPM was not significant (<i>P</i> > .05). <h3>Conclusions</h3> RFPM produced very close estimates of EI to WM but requires a human rater and is not easily scalable. These findings are important as PortionSize provides real-time feedback on dietary intake, which may assist with timely behavior change. Improvements to make PortionSize more scalable are ongoing. This work warrants future well-powered trials. <h3>Funding</h3> NIH; Pennington Biomedical (PBRC)/Louisiana Nutrition Obesity Research Center; Louisiana Clinical and Translational Science Center

Predicting the survival of kidney transplantation: design and evaluation of a smartphone-based application

BackgroundPrediction of graft survival for Kidney Transplantation (KT) is considered a risky task due to the scarcity of donating organs and the use of health care resources. The present study aimed to design and evaluate a smartphone-based application to predict the survival of KT in patients with End-Stage Renal Disease (ESRD).MethodBased on the initial review, a researcher-made questionnaire was developed to assess the information needs of the application through urologists and nephrologists. By using information obtained from the questionnaire, a checklist was prepared, and the information of 513 patients with kidney failure was collected from their records at Sina Urological Research Center. Then, three data mining algorithms were applied to them. The smartphone-based application for the prediction of kidney transplant survival was designed, and a standard usability assessment questionnaire was used to evaluate the designed application.ResultsThree information elements related to the required data in different sections of demographic information, sixteen information elements related to patient clinical information, and four critical capabilities were determined for the design of the smartphone-based application. C5.0 algorithm with the highest accuracy (87.21%) was modeled as the application inference engine. The application was developed based on the PhoneGap framework. According to the participants’ scores (urologists and nephrologists) regarding the usability evaluation of the application, it can be concluded that both groups participating in the study could use the program, and they rated the application at a "good" level.ConclusionSince the overall performance or usability of the smartphone-based app was evaluated at a reasonable level, it can be used with certainty to predict kidney transplant survival.

A Yoga Exercise App Designed for Patients With Axial Spondylarthritis: Development and User Experience Study

BackgroundBesides anti-inflammatory medication, physical exercise represents a cornerstone of modern treatment for patients with axial spondyloarthritis (AS). Digital health apps (DHAs) such as the yoga app YogiTherapy could remotely empower patients to autonomously and correctly perform exercises.ObjectiveThis study aimed to design and develop a smartphone-based app, YogiTherapy, for patients with AS. To gain additional insights into the usability of the graphical user interface (GUI) for further development of the app, this study focused exclusively on evaluating users’ interaction with the GUI.MethodsThe development of the app and the user experience study took place between October 2020 and March 2021. The DHA was designed by engineering students, rheumatologists, and patients with AS. After the initial development process, a pilot version of the app was evaluated by 5 patients and 5 rheumatologists. The participants had to interact with the app’s GUI and complete 5 navigation tasks within the app. Subsequently, the completion rate and experience questionnaire (attractiveness, perspicuity, efficiency, dependability, stimulation, and novelty) were completed by the patients.ResultsThe results of the posttest questionnaires showed that most patients were already familiar with digital apps (4/5, 80%). The task completion rates of the usability test were 100% (5/5) for the tasks T1 and T2, which included selecting and starting a yoga lesson and navigating to an information page. Rheumatologists indicated that they were even more experienced with digital devices (2/5, 40% experts; 3/5, 60% intermediates). In this case, they scored task completion rates of 100% (5/5) for all 5 usability tasks T1 to T5. The mean results from the User Experience Questionnaire range from −3 (most negative) to +3 (most positive). According to rheumatologists’ evaluations, attractiveness (mean 2.267, SD 0.401) and stimulation (mean 2.250, SD 0.354) achieved the best mean results compared with dependability (mean 2.000, SD 0.395). Patients rated attractiveness at a mean of 2.167 (SD 0.565) and stimulation at a mean of 1.950 (SD 0.873). The lowest mean score was reported for perspicuity (mean 1.250, SD 1.425).ConclusionsThe newly developed and tested DHA YogiTherapy demonstrated moderate usability among rheumatologists and patients with rheumatic diseases. The app can be used by patients with AS as a complementary treatment. The initial evaluation of the GUI identified significant usability problems that need to be addressed before the start of a clinical evaluation. Prospective trials are also needed in the second step to prove the clinical benefits of the app.

Smartphone-based nystagmus diagnostics: development of an innovative app for the targeted detection of vertigo

BackgroundIn medicine, the symptom of dizziness is one of the most common multidisciplinary causes of emergency medical presentation. Attending physicians are often faced with difficult decisions when evaluating patients with dizziness. A rapid differential diagnostic decision must be made during the initial examination. The goal of this study, was to develop a smartphone-based app that can diagnose and qualify nystagmus. The app should enable differentiation between acute emergencies such as strokes ("central vertigo") and vestibular disorders ("peripheral vertigo") using and recognizing or analyzing the accompanying symptom "nystagmus".Materials and methodsThis prospective study was conducted at the Department of Otolaryngology, Head and Neck Surgery "Otto Körner", Rostock (Germany). The experimental study design consisted of two test runs and two control runs. In the two test runs, nystagmus was tracked and evaluated by caloric and optokinetic stimulation, respectively, through a custom-developed app. Sensitivity and correlation were calculated for the app's application performance and compared under different experimental conditions.ResultsThe patient sample included twenty healthy participants with a mean age of 25.6 years (± 2.2 SD) who participated in the study. The overall sensitivity of detection of nystagmus averaged 82.14% in the optokinetic stimulation test trials. There is no correlation regarding specific subject data and sensitivity.ConclusionsThe results of our experimental validation study show that a smartphone-based nystagmus app is a useful tool for vertigo diagnosis. The results of our analyses show that it is possible to diagnose nystagmus and determine shape or direction with the app.

How to Make a Smartphone-Based App for Agricultural Advice Attractive: Insights from a Choice Experiment in Mexico

Mobile phone apps can be a cost-effective way to provide decision support to farmers, and they can support the collection of agricultural data. The digitisation of agricultural systems, and the efforts to close the digital divide and to include smallholders, make data ownership and privacy issues more relevant than ever before. In Central and South American countries, smallholders’ preferences regarding data licenses and sharing have largely been ignored, and little attention has been paid to the potential of nonfinancial incentives to increase the uptake of digital solutions and participation by farmers. To investigate incentives for smallholder farmers to potentially use an agricultural advisory app in which they share their data, a Discrete Choice Experiment was designed. Based on a survey of 392 farmers in Mexico, preferences for attributes related to its usage were revealed using a conditional logit (CL) model. To explore heterogeneity, groups and profiles were explored through a latent class (LC) model. The CL model results revealed, for example, farmers’ positive preference to receive support at first use and access to training, while negative preference was found for sharing data with private actors. The LC identified three classes which differ in their preference for attributes such as the degree of data sharing. Furthermore, for example, a farmer’s connectedness to an innovation hub was found to be one of the significant variables in the class membership function. The main contribution of the study is that it shows the importance of nonfinancial incentives and the influence of data sharing on farmer preferences.

Feasibility and Acceptability of a Cognitive Behavioral Therapy-Based Smartphone App for Smoking Cessation in China: A Single-Group Cohort Study

BackgroundPrevious research has suggested that mobile phone applications (apps) may potentially increase quit rates. The purpose of this single-group cohort study sought to examine the feasibility and acceptability of a novel smartphone-based smoking cessation app designed for smoking cessation in China: smoking quit rate.MethodsA total of 180 smokers from two cities of mainland China with willingness to make a quit attempt were invited to this smoking cessation app program, a cognitive behavioral theory (CBT)-based smoking cessation intervention via a smartphone app. Participants received 37- to 44-day intervention (including 7- to 14-day pre-quit preparation and 33-day intervention from quit date). Feasibility and acceptability of the program, and smoking status were assessed at baseline stage (initial installation), pre-quit stage, and post-quit stage (days 7, 15, and 33 after quit date).ResultsA total of 163 (90.6%) participants completed the study. Among them, 76–89% of the participants logged into the app ≥1 time per day across stages (at baseline, during pre-quit stage, and on days 7, 15, and 33 of post-quit stage); approximately 90% of the participants were satisfied with the app across stages. A significant rise in self-reported overall satisfaction with the app is observed from baseline (93% at Time 1) to the end of the program (98% at Time 2, 33 days after quit date) (p = 0.021). Participants who believed/agreed this app can help them to quit smoking significantly increased from 69% at baseline to 97% at day 33 after quit date (p < 0.001). Participants were satisfied with most (80–90%) of the features, especially the information feature. Intention-to-treat analysis showed that the percentage of 33-day self-reported continuous prevalence abstinence was 63.9%, and 7-day point prevalence abstinence rate was 81.7, 87.2, and 77.8% on days 7, 15, and 33 after quit date, respectively.ConclusionsThis study demonstrated the feasibility and acceptability of the smartphone app intervention for smoking cessation and introduced a new digital treatment model, which is expected to overcome barriers facing accessing traditional in-person smoking cessation services and extend nationwide smoking cessation services in China.

Increasing the Effectiveness of a Physical Activity Smartphone Intervention With Positive Suggestions: Randomized Controlled Trial.

BackgroundeHealth interventions have the potential to increase the physical activity of users. However, their effectiveness varies, and they often have only short-term effects. A possible way of enhancing their effectiveness is to increase the positive outcome expectations of users by giving them positive suggestions regarding the effectiveness of the intervention. It has been shown that when individuals have positive expectations regarding various types of interventions, they tend to benefit from these interventions more.ObjectiveThe main objective of this web-based study is to investigate whether positive suggestions can change the expectations of participants regarding the effectiveness of a smartphone physical activity intervention and subsequently enhance the number of steps the participants take during the intervention. In addition, we study whether suggestions affect perceived app effectiveness, engagement with the app, self-reported vitality, and fatigue of the participants.MethodsThis study involved a 21-day fully automated physical activity intervention aimed at helping participants to walk more steps. The intervention was delivered via a smartphone-based app that delivered specific tasks to participants (eg, setting activity goals or looking for social support) and recorded their daily step count. Participants were randomized to either a positive suggestions group (69/133, 51.9%) or a control group (64/133, 48.1%). Positive suggestions emphasizing the effectiveness of the intervention were implemented in a web-based flyer sent to the participants before the intervention. Suggestions were repeated on days 8 and 15 of the intervention via the app.ResultsParticipants significantly increased their daily step count from baseline compared with 21 days of the intervention (t107=−8.62; P<.001) regardless of the suggestions. Participants in the positive suggestions group had more positive expectations regarding the app (B=−1.61, SE 0.47; P<.001) and higher expected engagement with the app (B=3.80, SE 0.63; P<.001) than the participants in the control group. No effects of suggestions on the step count (B=−22.05, SE 334.90; P=.95), perceived effectiveness of the app (B=0.78, SE 0.69; P=.26), engagement with the app (B=0.78, SE 0.75; P=.29), and vitality (B=0.01, SE 0.11; P=.95) were found. Positive suggestions decreased the fatigue of the participants during the 3 weeks of the intervention (B=0.11, SE 0.02; P<.001).ConclusionsAlthough the suggestions did not affect the number of daily steps, they increased the positive expectations of the participants and decreased their fatigue. These results indicate that adding positive suggestions to eHealth physical activity interventions might be a promising way of influencing subjective but not objective outcomes of interventions. Future research should focus on finding ways of strengthening the suggestions, as they have the potential to boost the effectiveness of eHealth interventions.Trial RegistrationOpen Science Framework 10.17605/OSF.IO/CWJES; https://osf.io/cwjes

The Efficacy of a Smartphone-Based App on Stress Reduction: Randomized Controlled Trial.

BackgroundStress management in the workplace is essential for a healthy mental and physical state. Due to technological advancements, individually tailored therapy and online cognitive behavioral therapy (CBT) are on the rise.ObjectiveThis study analyzed the efficacy of a smartphone app based on third-wave CBT tailored to an individual.MethodsA randomized controlled trial was conducted with 126 participants who were divided into 2 groups. The intervention group used the smartphone app BetterLife for 10 weeks, while the control group was placed on a waiting list for the same duration. The Perceived Stress Scale–10 (PSS), Korean Utrecht Work Engagement Scale–9 (UWES), World Health Organization Quality of Life Assessment (WHOQOL), Beck Depression Inventory–II (BDI), and Beck Anxiety Inventory (BAI) were administered at baseline and after 10 weeks to both groups.ResultsOf the 126 participants, 11 dropped out during the trial. A 2-way repeated measure analysis of covariance was conducted, controlling for baseline BDI. There were greater improvements in PSS (F=24.33, P<.001, η2=0.17) and UWESK scores (F=8.32, P=.0046, η2=0.06) in the intervention group than in the control group. WHOQOL scores exhibited statistically significant improvement in the intervention group in the overall quality of life (F=8.19, P=.0049, η2=0.06), physical health (F=8.87, P=.003, η2=0.07), psychological health (F=13.32, P<.001, η2=0.10), social relationships (F=19.43, P<.001, η2=0.14), and environmental domains (F=10.14, P=.002, η2=0.08) but not overall health (F=1.68, P=.20). BDI (F=7.17, P=.008, η2=0.06) and BAI (F=6.00, P=.02, η2=0.05) showed a statistically significant improvement in the intervention group, but this significance did not survive the Bonferroni correction (P<.005).ConclusionsThese results provide evidence that smartphone-based CBT is a viable option for reducing stress in the workplace.Trial RegistrationClinical Research Information Service KCT0003231; https://cris.nih.go.kr/cris/search/detailSearch.do/15137

A Comparison Between Ecological Momentary Assessment and the Adapted-Quick Drinking Screen: Alcohol Mixed With Energy Drinks.

AimsTo compare alcohol consumption and risk-taking behaviours on alcohol mixed with energy drink (AMED) and alcohol-only (AO) drinking occasions collected via ecological momentary assessment (EMA) versus retrospective survey methods (adapted-Quick Drinking Screen: a-QDS).MethodsCompleting participants were 52 university students who reported AMED consumption during the 30-day data collection period. Alcohol consumption and risk-taking behaviours were captured for recreational AMED and AO consumption occasions using a smartphone-based app across 30 days. Data were aggregated for comparison with the a-QDS conducted at the end of data collection.ResultsIrrespective of data collection method, alcohol was consumed more frequently and at higher quantities on the heaviest drinking occasions when consumed alone compared with when it was mixed with energy drinks. Consistent with this finding, more risk-taking behaviours were experienced on AO occasions compared with AMED occasions. Compared with the a-QDS, the quantity of alcohol consumed on the average and heaviest drinking occasion was significantly higher when reported via EMA. This was consistent across both AO and AMED drinking occasions.ConclusionEMA provides a more valid measure of consumption quantity compared with retrospective recall, which was susceptible to under-reporting, although this was not differentially affected across consumption occasions. In line with previous research, this study demonstrated that mixing alcohol with energy drinks does not increase alcohol consumption or risk-taking behaviours.

An mHealth App-Based Self-management Intervention for Family Members of Pediatric Transplant Recipients (myFAMI): Framework Design and Development Study.

BackgroundSolid-organ transplantation is the treatment of choice for children with end-stage organ failure. Ongoing recovery and medical management at home after transplant are important for recovery and transition to daily life. Smartphones are widely used and hold the potential for aiding in the establishment of mobile health (mHealth) protocols. Health care providers, nurses, and computer scientists collaboratively designed and developed mHealth family self-management intervention (myFAMI), a smartphone-based intervention app to promote a family self-management intervention for pediatric transplant patients’ families.ObjectiveThis paper presents outcomes of the design stages and development actions of the myFAMI app framework, along with key challenges, limitations, and strengths.MethodsThe myFAMI app framework is built upon a theory-based intervention for pediatric transplant patients, with aid from the action research (AR) methodology. Based on initially defined design motivation, the team of researchers collaboratively explored 4 research stages (research discussions, feedback and motivations, alpha testing, and deployment and release improvements) and developed features required for successful inauguration of the app in the real-world setting.ResultsDeriving from app users and their functionalities, the myFAMI app framework is built with 2 primary components: the web app (for nurses’ and superadmin usage) and the smartphone app (for participant/family member usage). The web app stores survey responses and triggers alerts to nurses, when required, based on the family members’ response. The smartphone app presents the notifications sent from the server to the participants and captures survey responses. Both the web app and the smartphone app were built upon industry-standard software development frameworks and demonstrate great performance when deployed and used by study participants.ConclusionsThe paper summarizes a successful and efficient mHealth app-building process using a theory-based intervention in nursing and the AR methodology in computer science. Focusing on factors to improve efficiency enabled easy navigation of the app and collection of data. This work lays the foundation for researchers to carefully integrate necessary information (from the literature or experienced clinicians) to provide a robust and efficient solution and evaluate the acceptability, utility, and usability for similar studies in the future.International Registered Report Identifier (IRRID)RR2-10.1002/nur.22010

Silver nanoparticles embedded cotton swab as surface-enhanced Raman scattering substrate combination of smartphone app for detection of carbofuran residues

A surface-enhanced Raman scattering (SERS) substrate, consisting of a cotton swab with silver nanoparticles (AgNPs) embedded on common cotton, was fabricated in this study. The substrate consisted of AgNPs encapsulated in N-[3-(trimethoxysilyl)propyl]diethylenetriamine (ATS) hydrogels, and the resulting ATS-Ag SERS substrate presented good viscoelasticity, allowing it to conform to the surface of various materials of arbitrary roughness. The SERS peak intensity concentration change was rapidly captured and analyzed using a self-developed smartphone-based app system, which implements quantitative detection of carbofuran. The results showed that carbofuran can be detected with high sensitivity, with a linear range of 0.01–1.0 ppm and a detection limit of 0.05 ppm. In combination with a website, the proposed approach features high sensitivity, high simplicity of implementation, and a high throughput, which provides a promising means for the in situ determination of targets in practical applications.

Development and Validation of a Smartphone-Based App for the Longitudinal Assessment of Anxiety in Daily Life.

Current methods to assess human anxiety often ignore that anxiety is a dynamic process and have limitations such as high recall bias and low generalizability to real life. Smartphone apps using ecological momentary assessment (EMA) may overcome such limitations. We developed a smartphone app for the longitudinal evaluation of anxiety symptoms using EMA. We assessed the feasibility (retention and compliance) and psychometric properties (reliability and validity) of the app over 6 months in a sample of 99 participants with different levels of anxiety. The EMA-based smartphone app was highly feasible. It showed excellent within-person and between-person reliability, high convergent and moderate discriminant validity, and significant incremental validity. Assessing anxiety longitudinally using a smartphone and following EMA principles is feasible and can be reliable and valid. Studies combining EMA-based anxiety longitudinal assessments with other assessment methods deserve further research and may offer novel insights into human anxiety.

Psi Performance as a Function of Demographic and Personality Factors in Smartphone-Based Tests

Objective: We set out to gain a better understanding of human psychic or “psi” functioning by using a smartphone-based app to gather data from thousands of participants. Our expectations were that psi performance would often be revealed to be in the direction opposite to the participants’ conscious intentions (“expectation-opposing”; previously called “psi-missing”), and that gender and psi belief would be related to performance. Method:We created and launched three iOS-based tasks, available from 2017 to 2020, related to micro-psychokinesis (the ability to mentally influence a random number generator) and precognition (the ability to predict future randomly selected events). We statistically analyzed data from more than 2,613 unique logins and 995,995 contributed trials using null hypothesis significance testing as well as a pre-registered confirmatory analysis. Results: Our expectations were confirmed, and we discovered additional effects post-hoc. Our key findings were: 1) significant expectation-opposing effects, with a confirmatory pre-registered replication of a clear expectation-opposing effect on a micro-pk task, 2) performance correlated with psi belief on all three tasks, 3) performance on two of the three tasks related to gender, 4) men and women apparently used different strategies to perform micro-pk and precognition tasks. Conclusions: We describe our recommendations for future attempts to better understand performance on forced-choice psi tasks. The mnemonic for this strategy is SEARCH: Small effects, Early and exploratory, Accrue data, Recognize diversity in approach, Characterize rather than impose, and Hone in on big results.

Smartphone-based app for evaluating cardiothoracic residents: Feasibility and engagement.

Timely and high-quality feedback is important in cardiothoracic (CT) surgery education. Feedback on operative proficiency is an area for improvement in CT surgery programs. Traditional evaluations significantly lag behind operative interactions. We hypothesized that use of the System for Improving and Measuring Procedural Learning (SIMPL) app would improve operative feedback for trainees. Use of SIMPL was evaluated from December 2018 to January, 2021 within an academic CT surgery training program. Ratings include level of supervision, complexity of the operation, and trainee performance. Completion was limited to 72 h after the operation. Descriptive statistics of the users and ratings are presented. Over 28 months, 816 evaluations were completed, and of these, 495 had a rating from both the faculty and trainee. There were 19 trainees representing post-graduate years 1-8 and 19 faculty members who received or submitted at least one evaluation over the study period. The number of evaluations for each trainee ranged from 1 to 166 and from 1 to 81 for each of the faculty. The response rate for faculty ranged from 0% to 100%. "Active help" was the most common type of supervision (50.7% by the faculty, 60.4% from the trainees). Use of SIMPL within a CT surgery training program was feasible and engagement was observed from both trainees and faculty. SIMPL provided trainees with timely, concise feedback on operative performance. Further work will focus on correlating SIMPL ratings with pre-existing assessments of performance.

Efficacy of a transdiagnostic ecological momentary intervention for improving self-esteem (SELFIE) in youth exposed to childhood adversity: study protocol for a multi-center randomized controlled trial

BackgroundTargeting low self-esteem in youth exposed to childhood adversity is a promising strategy for preventing adult mental disorder, but psychological help remains difficult to access and accept for youth, calling for novel, youth-friendly approaches. Mobile Health (mHealth) and, most prominently, ecological momentary interventions (EMIs) provide a unique opportunity to deliver youth-friendly, personalized, real-time, guided self-help interventions. The aim of this study is to investigate the efficacy of a novel, accessible, transdiagnostic ecological momentary intervention for improving self-esteem (‘SELFIE’) in youth with prior exposure to childhood adversity.Methods/designIn a parallel-group, assessor-blind, multi-center randomized controlled trial, individuals aged 12–26 years with prior exposure to childhood adversity and low self-esteem will be randomly allocated to SELFIE in addition to treatment as usual (TAU) as the experimental condition or the control condition of TAU only, which will include access to all standard health care. SELFIE is a digital guided self-help intervention administered through a smartphone-based app to allow for interactive, personalized, real-time and real-world transfer of intervention components in individuals’ daily lives, blended with three training sessions delivered by trained mental health professionals over a 6-week period. Outcomes will be assessed at baseline, post-intervention, and 6-month follow-up by blinded assessors. The primary outcome will be the level of self-esteem as measured with the Rosenberg Self-Esteem Scale (RSES).DiscussionThe current study is the first to establish the efficacy of an EMI focusing on improving self-esteem transdiagnostically in youth exposed to childhood adversity. If this trial provides evidence on the efficacy of SELFIE, it has significant potential to contribute to minimizing the deleterious impact of childhood adversity and, thereby, preventing the development of mental disorder later in life.Trial registrationNetherlands Trial Register NL7129 (NTR7475). Registered on 9 November 2018

A Smartphone-Based App to Improve Adjuvant Treatment Adherence to Multidisciplinary Decisions in Patients With Early-Stage Breast Cancer: Observational Study.

BackgroundMultidisciplinary treatment (MDT) and adjuvant therapy are associated with improved survival rates in breast cancer. However, nonadherence to MDT decisions is common in patients. We developed a smartphone-based app that can facilitate the full-course management of patients after surgery.ObjectiveThis study aims to investigate the influence factors of treatment nonadherence and to determine whether this smartphone-based app can improve the compliance rate with MDTs.MethodsPatients who had received a diagnosis of invasive breast cancer and had undergone MDT between March 2013 and May 2019 were included. Patients were classified into 3 groups: Pre-App cohort (November 2017, before the launch of the app); App nonused, cohort (after November 2017 but not using the app); and App used cohort (after November 2017 and using the app). Univariate and multivariate analyses were performed to identify the factors related to MDT adherence. Compliance with specific adjuvant treatments, including chemotherapy, radiotherapy, endocrine therapy, and targeted therapy, was also evaluated.ResultsA total of 4475 patients were included, with Pre-App, App nonused, and App used cohorts comprising 2966 (66.28%), 861 (19.24%), and 648 (14.48%) patients, respectively. Overall, 15.53% (695/4475) patients did not receive MDT recommendations; the noncompliance rate ranged from 27.4% (75/273) in 2013 to 8.8% (44/500) in 2019. Multivariate analysis demonstrated that app use was independently associated with adherence to adjuvant treatment. Compared with the patients in the Pre-App cohort, patients in the App used cohort were less likely to deviate from MDT recommendations (odds ratio [OR] 0.61, 95% CI 0.43-0.87; P=.007); no significant difference was found in the App nonused cohort (P=.77). Moreover, app use decreased the noncompliance rate for adjuvant chemotherapy (OR 0.41, 95% CI 0.27-0.65; P<.001) and radiotherapy (OR 0.49, 95% CI 0.25-0.96; P=.04), but not for anti-HER2 therapy (P=.76) or endocrine therapy (P=.39).ConclusionsThis smartphone-based app can increase MDT adherence in patients undergoing adjuvant therapy; this was more obvious for adjuvant chemotherapy and radiotherapy.

The Age, Sex, and Geographical Distribution of Self-Reported Asthma Triggers on Children With Asthma in China.

Background: Asthma can be exacerbated by many triggers, and the heterogeneity of asthma triggers is clear among children with asthma. This study describes asthma triggers using a large-scale electronic dataset from the smartphone-based Chinese Children's Asthma Action Plan (CCAAP) app and aims to examine the difference in asthma triggers among different subgroups of children with asthma.Methods: Data from the smartphone-based CCAAP app between February 22, 2017, and November 23, 2020, were reviewed, and children with asthma who reported their asthma triggers were enrolled. Eight common asthma triggers were listed in the software: upper respiratory infection (URI), allergen sensitization, exercise, emotional disturbances, pungent odors, air pollution/smog, weather change, and tobacco smoke. We compared the incidence of asthma triggers among different subgroups (<6 years vs. 6–17 years; boy vs. girl; eastern region vs. central region vs. western region).Results: We enrolled 6,835 patients with self-reported asthma triggers. When compared by sex, boys had a higher proportion of exercise-triggered asthma than girls (boys vs. girls, 22.5 vs. 19.7%, p < 0.05). The proportion of patients <6 years of age with URI-triggered asthma was higher than that of patients 6–17 years of age (<6 vs. 6–17 years, 80.9 vs. 74.9%, p < 0.001). Patients 6–17 years of age were more likely than patients <6 years of age to report five of the asthma triggers: allergen sensitization (<6 vs. 6–17 years, 26.6 vs. 35.8%, p < 0.001), exercise (<6 vs. 6–17 years, 19.3 vs. 23.7%, p < 0.001), pungent odors (<6 vs. 6–17 years, 8.8 vs. 12.7%, p < 0.001), air pollution/smog (<6 vs. 6–17 years, 9.4 vs. 16.2%, p < 0.001), and tobacco smoke (<6 vs. 6–17 years, 3.5 vs. 5.3%, p < 0.001). In subgroups based on geographical distribution, asthma triggering of allergen sensitization was reported to be the most common in patients from the eastern region (eastern region vs. central region vs. western region, 35.0 vs. 24.6 vs. 28.0%, p < 0.001). Exercise-triggered asthma was found to be the most prevalent among patients from the central region (eastern region vs. central region vs. western region, 21.6 vs. 24.8 vs. 20.4%, p < 0.05). However, the proportion of patients with air pollution/smog as an asthma trigger was the lowest among those from the western region (eastern region vs. central region vs. western region, 14.1 vs. 14.1 vs. 10.8%, p < 0.05).Conclusion: Children with asthma present different types of asthma triggers, both allergenic and nonallergenic. Age, sex, and geographical distribution affect specific asthma triggers. Preventive measures can be implemented based on a patient's specific asthma trigger.

Unterstützung pflegender Angehöriger durch eine mobile, assistive App. Eine qualitative Analyse der Perspektive von Nutzerinnen und Nutzern der App MoCaB

BackgroundIn the joint project “Mobile Care Backup” funded by the German Federal Ministry of Education and Research, the smartphone-based app “MoCaB” was developed in close cooperation with informal caregivers. It provides individualized, algorithm-based information and can accompany and support caring relatives in everyday life. After a multi-step development, informal caregivers tested the MoCaB app in a home setting at the end of the research project. The goal was to find out how the test persons evaluate MoCaB and in which form the app can provide support to informal caregivers. MethodsEighteen test persons caring for relatives participated in a four-week test of MoCaB. Guideline-based qualitative interviews to record usage behavior and experiences with the app were conducted after two and four weeks of testing, transcribed and analyzed using qualitative content analysis. ResultsThe test persons described the care-related information as helpful. The individualized, algorithm-based mode of information delivery and the exercises provided for family caregivers were generally rated as helpful, but their use depends on the individual usage style. Three dimensions can describe the effects of MoCaB: 1) expansion of care-relevant knowledge, 2) stimulation of self-reflection, and 3) behavior towards the care recipients. DiscussionWith few exceptions, the testing caregivers felt that the MoCaB app was enriching. The support dimensions have an effect at different points in everyday life and vary in intensity, depending on the duration of the existing care activity and the individual preferences of the users. ConclusionThe way in which caregivers used the app was not always consistent with the expected behaviors. This demonstrates the relevance of open-ended, qualitative research methods in the evaluation of health apps.