24-Hour warning signs for adolescent suicide attempts.

BACKGROUND: Little is known about when youth may be at greatest risk for attempting suicide, which is critically important information for the parents, caregivers, and professionals who care for youth at risk. This study used adolescent and parent reports, and a case-crossover, within-subject design to identify 24-hour warning signs (WS) for suicide attempts. METHODS: Adolescents (N = 1094, ages 13 to 18) with one or more suicide risk factors were enrolled and invited to complete bi-weekly, 8-10 item text message surveys for 18 months. Adolescents who reported a suicide attempt (survey item) were invited to participate in an interview regarding their thoughts, feelings/emotions, and behaviors/events during the 24-hours prior to their attempt (case period) and a prior 24-hour period (control period). Their parents participated in an interview regarding the adolescents' behaviors/events during these same periods. Adolescent or adolescent and parent interviews were completed for 105 adolescents (81.9% female; 66.7% White, 19.0% Black, 14.3% other). RESULTS: Both parent and adolescent reports of suicidal communications and withdrawal from social and other activities differentiated case and control periods. Adolescent reports also identified feelings (self-hate, emotional pain, rush of feelings, lower levels of rage toward others), cognitions (suicidal rumination, perceived burdensomeness, anger/hostility), and serious conflict with parents as WS in multi-variable models. CONCLUSIONS: This study identified 24-hour WS in the domains of cognitions, feelings, and behaviors/events, providing an evidence base for the dissemination of information about signs of proximal risk for adolescent suicide attempts.

Impact of veteran-led peer mentorship on posttraumatic stress disorder.

Peer mentorship shows promise as a strategy to support veteran mental health. A community-academic partnership involving a veteran-led nonprofit organization and institutions of higher education evaluated a collaboratively developed peer mentor intervention. We assessed posttraumatic stress disorder (PTSD), postdeployment experiences, social functioning, and psychological strengths at baseline, midpoint, and 12-week discharge using the PTSD Checklist for DSM-5 (PCL-5), Deployment Risk and Resilience Inventory-2, Social Adaptation Self-evaluation Scale, and Values in Action Survey. Brief weekly check-in surveys reinforced mentor contact and assessed retention. The sample included 307 veterans who were served by 17 veteran peer mentors. Mixed-effects linear models found a modest effect for PTSD symptom change, with a mean PCL-5 score reduction of 4.04 points, 95% CI [-6.44, -1.64], d = 0.44. More symptomatic veterans showed a larger effect, with average reductions of 9.03 points, 95% CI [-12.11, -5.95], d = 0.77. There were no significant findings for other outcome variables. Compared to younger veterans, those aged 32-57 years were less likely to drop out by 6 weeks, aORs = 0.32-0.26. Week-by-week hazard of drop-out was lower with mentors ≥ 35 years old, aHR = 0.62, 95% CI [0.37, 1.05]. Unadjusted survival differed by mentor military branch, p = .028, but the small mentor sample reduced interpretability. Like many community research efforts, this study lacked a control group, limiting the inferences that can be drawn. Continued study of veteran peer mentorship is important as this modality is often viewed as more tolerable than therapy.

Increasing Lung Cancer Screening for High-Risk Smokers in a Frontier Population.

Northern Plains American Indians (AIs) have some of the highest smoking and lung cancer mortality rates in the USA. They are a high-risk population in which many are eligible for low-dose computed tomography (LDCT) screening, but such screening is rarely used. This study investigated methods to increase LDCT utilization through both a provider and community intervention to lower lung cancer mortality rates. This study used the Precaution Adoption Model for provider and community interventions implemented in four study regions in western South Dakota. The goal was to increase LDCT screening for eligible participants. Intake surveys and LDCT screenings were compared at baseline and 6 months following the education programs for both interventions. A total of 131 providers participated in the provider intervention. At the 6-month follow-up survey, 31 (63%) referred at least one patient for LDCT (p < 0.05). Forty (32.3%) community participants reported their provider recommended an LDCT and of those, 30(75%) reported getting an LDCT (p < 0.05). A total of 2829 patient surveys were completed at the imaging sites and most (88%, n = 962) cited provider recommendation as their reason for obtaining an LDCT. Almost half (46%; n = 131) of the referring providers attended a provider education workshop, and 73% of the providers worked at a clinic that hosted at least one community education session. Over the study period, LDCT utilization increased from 640 to 1706, a 90.9% increase. The provider intervention had the strongest impact on LDCT utilization. This study demonstrated increased LDCT utilization through the provider intervention but increases also were documented for the other intervention combinations. The community-based education program increased both community and provider awareness on the value of LDCTs to lower lung cancer mortality rates.

Longitudinal Assessment of Acute Concussion Outcomes Through SMS Text (ConText Study).

OBJECTIVE: Mild traumatic brain injury (mTBI), or concussion, is a common health problem that has seen a recent increase in US adolescents. This study uses SMS text messaging (a mobile health [mHealth] tool) to report patient symptoms. We aim to better characterize mTBI recovery and hypothesize that this mHealth tool will have high retention rates and correlate with a conventional means of assessing symptoms, the Post-Concussion Symptom Inventory (PCSI). METHODS: A prospective observational cohort pilot study. Thirty-one pediatric patients with acute mTBI were recruited to characterize their injury and report their symptoms via text messaging. Patients reported symptoms once every 3 days for the first 21 days, then once a week for 6 weeks. RESULTS: There was a strong and positive correlation between the PCSI and the mHealth tool (rs = 0.875, P < 0.000, n = 22). Retention was 74% until symptom resolution and 42% until study completion. Patients with balance deficits had a significantly higher somatization score than those with normal balance (6.53 ± 3.25 vs 2.56 ± 2.30, t(22) = 3.211, P < 0.01). CONCLUSIONS: This pilot study demonstrates that this tool is a valid and easy-to-use method of reporting pediatric mTBI symptoms-it replicates and identifies novel findings. Our results suggest that there may be a relationship between balance and the manifestation of somatic symptoms. Retention rates were lower than predicted, indicating that text messaging may not be the ideal format in this population. Text messaging may still have other applications for short-term communication/symptom measurement.

Eye-gaze control of a wheelchair mounted 6DOF assistive robot for activities of daily living.

BACKGROUND: Building control architecture that balances the assistive manipulation systems with the benefits of direct human control is a crucial challenge of human-robot collaboration. It promises to help people with disabilities more efficiently control wheelchair and wheelchair-mounted robot arms to accomplish activities of daily living. METHODS: In this study, our research objective is to design an eye-tracking assistive robot control system capable of providing targeted engagement and motivating individuals with a disability to use the developed method for self-assistance activities of daily living. The graphical user interface is designed and integrated with the developed control architecture to achieve the goal. RESULTS: We evaluated the system by conducting a user study. Ten healthy participants performed five trials of three manipulation tasks using the graphical user interface and the developed control framework. The 100% success rate on task performance demonstrates the effectiveness of our system for individuals with motor impairments to control wheelchair and wheelchair-mounted assistive robotic manipulators. CONCLUSIONS: We demonstrated the usability of using this eye-gaze system to control a robotic arm mounted on a wheelchair in activities of daily living for people with disabilities. We found high levels of acceptance with higher ratings in the evaluation of the system with healthy participants.

Giving Voice to Parents in the Development of the Preemie Prep for Parents (P3) Mobile App.

BACKGROUND: Parents at risk for preterm birth frequently receive prematurity education when the mother is hospitalized for premature labor. Parental ability to learn and consider the information is limited because of the stress of the hospitalization. A promising approach is dissemination of information to at-risk parents before the birth hospitalization. PURPOSE: This article describes formative research used to develop smartphone-based prematurity education app for parents at-risk for preterm birth. METHODS: Stakeholders were parents with a prior preterm birth. Using stakeholder meeting transcripts, constant comparative analysis was used to reflect upon the parental voice. RESULTS: The parents named the app, Preemie Prep for Parents (P3). Parent perspectives revealed desire for information in the following 5 categories. (1) Power in knowledge and control: parents want autonomy when learning information that may influence medical decision-making. (2) Content and framing of information: they desire information from a trusted resource that helps promote prenatal health and provides neonatal intensive care information. (3) Displaying content: parents want personalization, push notifications, photographs displaying fetal development, and easy-to-understand statistics. (4) Providing information without causing harm: they desire non-value-laden information, and they do not support "gamifying" the app to enhance utilization. (5) Decision making: parents want information that would benefit their decision making without assuming that parents have a certain outlook on life or particular values. IMPLICATIONS FOR PRACTICE: These findings support the need for the P3 App to aid in decision making when parents experience preterm birth. IMPLICATIONS FOR RESEARCH: The findings highlight the need to study the effects of smartphone-based prematurity education on medical decision-making.

Pilot study protocol of a mHealth self-management intervention for family members of pediatric transplant recipients.

Solid-organ transplantation is the treatment of choice for end-stage organ failure. Parents of pediatric transplant recipients who reported a lack of readiness for discharge had more difficulty coping and managing their child's medically complex care at home. In this paper, we describe the protocol for the pilot study of a mHealth intervention (myFAMI). The myFAMI intervention is based on the Individual and Family Self-Management Theory and focuses on family self-management of pediatric transplant recipients at home. The purpose of the pilot study is to test the feasibility of the myFAMI intervention with family members of pediatric transplant recipients and to test the preliminary efficacy on postdischarge coping through a randomized controlled trial. The sample will include 40 family units, 20 in each arm of the study, from three pediatric transplant centers in the United States. Results from this study may advance nursing science by providing insight for the use of mHealth to facilitate patient/family-nurse communication and family self-management behaviors for family members of pediatric transplant recipients.

Symptoms in Nepali Patients with Incurable Cancers: Implications for Interventions.

AIM: The poor quality and limited extent of palliative care services are of concern across the globe. To identify and measure patients' symptoms in Nepal, using a cell phone questionnaire platform, the investigators conducted and previously reported a cross-sectional study of Nepali adults. The unreported details of pain and other symptoms in these study data are here considered together with possible explanations and implications for interventions to lessen these symptoms. METHODS: In a "snapshot" cross-sectional study of patients under regular care in three tertiary care Nepalese centers, we questioned 383 patients with incurable cancers using a 15-item cell phone-validated instrument to describe their major current symptoms and their intensities. The distributions of 11 symptom-level scores and the correlations between pain and different symptom scores were determined. RESULTS: Thirty-eight percent of the population (142/383) had maximal pain scores which were in the severe range, and 25% (97/383) had such scores where they were evaluated. Patients reported moderate-to-severe tiredness 48% (183/383), depression 45% (172/383), anxiety 56% (217/383), poor appetite 64% (246/383), sleep quantity 64% (246/383), and sleep quality 64% (247/383). CONCLUSIONS: The significant fractions of patients with severe maximal and at-evaluation pain scores suggest that inadequate recognition and treatment of such symptoms characterized care of these regularly seen patients. The high fractions of patients with mood and sleep disturbances support this reading, suggesting helplessness and hopelessness, all addressable with psychosocial, environmental, and nontoxic, inexpensive pharmacological interventions.

Life-Threatening Allergies: Using a Patient-Engaged Approach.

BACKGROUND: Adolescents at risk for anaphylaxis are a growing concern. Novel training methods are needed to better prepare individuals to manage anaphylaxis in the community. INTRODUCTION: Didactic training as the sole method of anaphylaxis education has been shown to be ineffective. We developed a smartphone-based interactive teaching tool with decision support and epinephrine auto-injector (EAI) training to provide education accessible beyond the clinic. METHODS: This study consisted of two parts: (1) Use of food allergy scenarios to assess the decision support's ability to improve allergic reaction management knowledge. (2) An assessment of our EAI training module on participant's ability to correctly demonstrate the use of an EAI by comparing it to label instructions. RESULTS: Twenty-two adolescents were recruited. The median (range) baseline number of correct answers on the scenarios before the intervention was 9 (3-11). All subjects improved with decision support, increasing to 11 (9-12) (p < .001). The median (range) demonstration score was 6 (5-6) for the video training module group and 4.5 (3-6) for the label group (p < 0.001). DISCUSSION: Results suggest that the use of this novel m-health application can improve anaphylaxis symptom recognition and increase the likelihood of choosing the appropriate treatment. In addition, performing EAI steps in conjunction with the video training resulted in more accurate medication delivery with fewer missed steps compared to the use of written instructions alone. CONCLUSION: The results suggest that mobile health decision support technology for anaphylaxis emergency preparedness may support traditional methods of training by providing improved access to anaphylaxis training in the community setting.

Reality Versus Grant Application Research "Plans".

This article describes the implementation of the American Indian mHealth Smoking Dependence Study focusing on the differences between what was written in the grant application compared to what happened in reality. The study was designed to evaluate a multicomponent intervention involving 256 participants randomly assigned to one of 15 groups. Participants received either a minimal or an intense level of four intervention components: (1) nicotine replacement therapy, (2) precessation counseling, (3) cessation counseling, and (4) mHealth text messaging. The project team met via biweekly webinars as well as one to two in-person meetings per year throughout the study. The project team openly shared progress and challenges and collaborated to find proactive solutions to address challenges as compared to what was planned in the original grant application. The project team used multiple strategies to overcome unanticipated intervention issues: (1) cell phone challenges, (2) making difficult staffing decisions, (3) survey lessons, (4) nicotine replacement therapy, (5) mHealth text messages, (6) motivational interviewing counseling sessions, and (7) use of e-cigarettes. Smoking cessation studies should be designed based on the grant plans. However, on the ground reality issues needed to be addressed to assure the scientific rigor and innovativeness of this study.

Symptoms In Bangladeshi Patients with Incurable Cancers: Implications for Interventions.

AIMS: The poor state of palliative care in low- and middle-income countries has been termed a global crisis by the Lancet Commission on Palliative Care. The investigators previously reported on a cross-sectional study of symptoms in 640 Bangladeshi adults with incurable cancers. Usual levels of pain were high. The not-reported details of pain and other symptoms offered an opportunity to consider explanations and implications for interventions to lessen these symptoms. METHODS: At one visit, 640 Bangladeshi patients completed a symptom questionnaire. The distributions of 12 symptom level scores and the correlations between pain and different symptom scores were determined. RESULTS: The population had significantly high and functionally compromising average usual pain scores, but low percentages of patients with very high and low pain scores. The distributions of scores for multiple symptoms were all skewed to higher mid-scale levels and modestly high (≥0.6) correlations of pain with nausea, anxiety, lack of appetite, constipation, and sleep quality were seen. CONCLUSIONS: While the types and direct effects of the cancers, the young age distribution, and the true symptomatic status of this Bangladeshi population studied may explain the described characteristics, the observations deserve exploration of other causes with specific therapeutic implications. These patients appear to have been partially treated for pain, and in particular, environmental factors such as extreme heat and its consequences appear more likely causes of moderate levels of multiple symptoms, which collectively magnified patients' suffering. Greater attention to gastrointestinal symptoms and sleep disturbance, in particular, seems indicated.

Effect of a social script iPad application for children with autism going to imaging.

This randomized controlled trial feasibility study tested the effectiveness of an iPad® application (app) social script intervention for children with autism spectrum disorder (ASD) going to imaging and their parent (n=32 parent/child dyads). Parents of the children exposed to the app (n=16) had lower state anxiety compared to the parents whose children were not exposed to the app (n=16) (effect size 0.33). Children exposed to the app had fewer externalized challenging behaviors than the control group (effect size 0.56). The results demonstrate feasibility and efficacy of the intervention. Further study of the iPad app is warranted.

UDBRNet: A novel uncertainty driven boundary refined network for organ at risk segmentation.

Organ segmentation has become a preliminary task for computer-aided intervention, diagnosis, radiation therapy, and critical robotic surgery. Automatic organ segmentation from medical images is a challenging task due to the inconsistent shape and size of different organs. Besides this, low contrast at the edges of organs due to similar types of tissue confuses the network's ability to segment the contour of organs properly. In this paper, we propose a novel convolution neural network based uncertainty-driven boundary-refined segmentation network (UDBRNet) that segments the organs from CT images. The CT images are segmented first and produce multiple segmentation masks from multi-line segmentation decoder. Uncertain regions are identified from multiple masks and the boundaries of the organs are refined based on uncertainty data. Our method achieves remarkable performance, boasting dice accuracies of 0.80, 0.95, 0.92, and 0.94 for Esophagus, Heart, Trachea, and Aorta respectively on the SegThor dataset, and 0.71, 0.89, 0.85, 0.97, and 0.97 for Esophagus, Spinal Cord, Heart, Left-Lung, and Right-Lung respectively on the LCTSC dataset. These results demonstrate the superiority of our uncertainty-driven boundary refinement technique over state-of-the-art segmentation networks such as UNet, Attention UNet, FC-denseNet, BASNet, UNet++, R2UNet, TransUNet, and DS-TransUNet. UDBRNet presents a promising network for more precise organ segmentation, particularly in challenging, uncertain conditions. The source code of our proposed method will be available at https://github.com/riadhassan/UDBRNet.

Acceptance of bite presentations and feeding behaviors of 8 to 12-month-old infants: A reflection of typical feeding development.

PURPOSE: The lack of age-appropriate expectations for feeding acceptance patterns in early childhood is a barrier to early and accurate identification of pediatric feeding disorder (PFD). The objective of the study was to describe the process by which typically developing children 8-12 months of age accept or refuse bite presentations and their corresponding feeding behaviors, aiming to establish age-appropriate normative data for feeding acceptance. METHOD: Using cross-sectional methodology, we studied the proportion of bite presentations accepted, the type of feeding behaviors-passive, disruptive, expulsion, feeding concerns- observed at presentation and acceptance or refusal, and the duration between presentation to acceptance or refusal in 63 healthy infants between 8 and 12 months of age. Descriptive statistics and a one-way ANOVA were conducted to compare the effect of age and texture. RESULTS: Findings reveal high levels of bite acceptance of 80 % or > for children across ages, but with lower texture-specific differences. Both passive and disruptive behaviors were present even during acceptance of bites without any expulsion. Feeding concerns showed developmental trends with rapid reduction by 12 months suggesting improvement in oral feeding skills. The duration of acceptance and refusals revealed clear patterns by age and texture with an average of 3 s for acceptance but <1 s for refusal. CONCLUSIONS: This study describes bite acceptance patterns in a cohort of typically developing infants between 8 and 12 months of age by examining the acceptance of bites, frequency and type of feeding behaviors, and duration differences when children accept versus refuse a bite. Findings may be applied in the future to provide more sensitive detection of problematic feeding patterns to aid in the detection of pediatric feeding disorder.

A Scoping Review on Mobile Health Technology for Assessment and Intervention of Upper Limb Motor Function in Children with Motor Impairments.

Upper limb (UL) motor dysfunctions impact residual movement in hands/shoulders and limit participation in play, sports, and leisure activities. Clinical and laboratory assessments of UL movement can be time-intensive, subjective, and/or require specialized equipment and may not optimally capture a child's motor abilities. The restrictions to in-person research experienced during the COVID-19 pandemic have inspired investigators to design inclusive at-home studies with child participants and their families. Relying on the ubiquity of mobile devices, mobile health (mHealth) applications offer solutions for various clinical and research problems. This scoping review article aimed to aggregate and synthesize existing research that used health technology and mHealth approaches to evaluate and assess the hand function and UL movement in children with UL motor impairment. A scoping review based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) model was conducted in March 2023 yielding 25 articles (0.32% of 7891 studies). Assessment characteristics included game or task-based tests (13/25, 52%), primarily for neurological disorders (e.g., autism spectrum disorder [ASD], dystonia, dysgraphia) or children with cerebral palsy (CP). Although several mHealth studies were conducted in the clinical environment (10/25, 40%), studies conducted at home or in nonclinical settings (15/25, 60%) reported acceptable and highly satisfactory to the patients as minimizing the potential risks in participation. Moreover, the remaining barriers to clinical translation included object manipulation on a touch screen, offline data analysis, real-world usability, and age-appropriate application design for the wider population. However, the results emphasize the exploration of mHealth over traditional approaches, enabling user-centered study design, family-oriented methods, and large-scale sampling in future research.

Unraveling a blockchain-based framework towards patient empowerment: A scoping review envisioning future smart health technologies.

The COVID-19 pandemic shows us how crucial patient empowerment can be in the healthcare ecosystem. Now, we know that scientific advancement, technology integration, and patient empowerment need to be orchestrated to realize future smart health technologies. In that effort, this paper unravels the Good (advantages), Bad (challenges/limitations), and Ugly (lacking patient empowerment) of the blockchain technology integration in the Electronic Health Record (EHR) paradigm in the existing healthcare landscape. Our study addresses four methodically-tailored and patient-centric Research Questions, primarily examining 138 relevant scientific papers. This scoping review also explores how the pervasiveness of blockchain technology can help to empower patients in terms of access, awareness, and control. Finally, this scoping review leverages the insights gleaned from this study and contributes to the body of knowledge by proposing a patient-centric blockchain-based framework. This work will envision orchestrating three essential elements with harmony: scientific advancement (Healthcare and EHR), technology integration (Blockchain Technology), and patient empowerment (access, awareness, and control).

An Artificial Intelligence-Based Smartphone App for Assessing the Risk of Opioid Misuse in Working Populations Using Synthetic Data: Pilot Development Study.

BACKGROUND: Opioid use disorder (OUD) is an addiction crisis in the United States. As recent as 2019, more than 10 million people have misused or abused prescription opioids, making OUD one of the leading causes of accidental death in the United States. Workforces that are physically demanding and laborious in the transportation, construction and extraction, and health care industries are prime targets for OUD due to high-risk occupational activities. Because of this high prevalence of OUD among working populations in the United States, elevated workers' compensation and health insurance costs, absenteeism, and declined productivity in workplaces have been reported. OBJECTIVE: With the emergence of new smartphone technologies, health interventions can be widely used outside clinical settings via mobile health tools. The major objective of our pilot study was to develop a smartphone app that can track work-related risk factors leading to OUD with a specific focus on high-risk occupational groups. We used synthetic data analyzed by applying a machine learning algorithm to accomplish our objective. METHODS: To make the OUD assessment process more convenient and to motivate potential patients with OUD, we developed a smartphone-based app through a step-by-step process. First, an extensive literature survey was conducted to list a set of critical risk assessment questions that can capture high-risk behaviors leading to OUD. Next, a review panel short-listed 15 questions after careful evaluation with specific emphasis on physically demanding workforces-9 questions had two, 5 questions had five, and 1 question had three response options. Instead of human participant data, synthetic data were used as user responses. Finally, an artificial intelligence algorithm, naive Bayes, was used to predict the OUD risk, trained with the synthetic data collected. RESULTS: The smartphone app we have developed is functional as tested with synthetic data. Using the naive Bayes algorithm on collected synthetic data, we successfully predicted the risk of OUD. This would eventually create a platform to test the functionality of the app further using human participant data. CONCLUSIONS: The use of mobile health techniques, such as our mobile app, is highly promising in predicting and offering mitigation plans for disease detection and prevention. Using a naive Bayes algorithm model along with a representational state transfer (REST) application programming interface and cloud-based data encryption storage, respondents can guarantee their privacy and accuracy in estimating their risk. Our app offers a tailored mitigation strategy for specific workforces (eg, transportation and health care workers) that are most impacted by OUD. Despite the limitations of the study, we have developed a robust methodology and believe that our app has the potential to help reduce the opioid crisis.

Multimedia tablet or paper handout to supplement counseling during preterm birth hospitalization: a randomized controlled trial.

BACKGROUND: Parents of premature infants engage in shared decision-making regarding the care of their infant. The process of prenatal counseling typically involves a verbal conversation with a neonatal provider during hospitalization. Support people may not be available, and the pregnant person's memory is impaired by medications, pain, and stress. The American Academy of Pediatrics, American College of Obstetricians and Gynecologists, and the Eunice Kennedy Shriver National Institute of Child Health and Human Development have called for improvements to this process, including the development of educational aids. OBJECTIVE: This study aimed to investigate whether a multimedia tablet would be more effective than a paper handout in supplementing verbal clinician counseling during preterm birth hospitalization. STUDY DESIGN: This was a randomized controlled trial including English-speaking pregnant people aged ≥18 years and hospitalized at 22 to 33 weeks' gestation for preterm birth. Exclusion criteria were known fetal or chromosomal anomaly and delivery before study completion. Pregnant people received either a multimedia tablet or a paper handout before verbal clinician counseling. Preintervention assessment included demographics and State-Trait Anxiety Inventory, and postintervention assessment included the Parent Knowledge of Premature Birth Questionnaire and State-Trait Anxiety Inventory. Continuous variables were analyzed by t-test and categorical variables by Fisher exact test. RESULTS: A total of 122 pregnant people referred for counseling were screened; 76 were randomized, and 59 completed the study. Demographics were similar between groups, except that pregnant people in the handout group were older (mean 32 vs 29 years; P=.03). The multimedia tablet group (n=32) was less likely to report reviewing all the educational material than the paper handout group (n=27) (41% vs 72%; P=.037). Both groups correctly answered a similar number of knowledge items (P=.088). Postintervention state anxiety decreased in both groups (P<.0001), with no difference between groups. Computerized tracking showed that the multimedia group spent a median of 37 minutes reviewing the tablet. CONCLUSION: Contrary to our hypothesis, a paper handout and multimedia tablet were equally effective in the labor unit for supplementing verbal preterm birth counseling, and both decreased parental anxiety.

A Consecutive Series Study of the Frequencies, Intensities, and Natural History of Symptoms Following COVID-19 Infection in Nepali Men.

BACKGROUND: In Nepal, approximately one million individuals, two-thirds men, have tested positive for COVID-19. The recovery picture from this infection is undescribed. METHODS: At one major testing institution in Kathmandu, we attempted to contact men three-four months following documentation of a positive PCR Covid test. If the men contacted consented and reported that they had not completely recovered from their Covid infection, we then sought their answers about the presence and intensities of 23 symptoms. RESULTS: Of 2043 consecutive test-positive men, we successfully contacted 1254 men/or family members. 14 men had died before our calls, and two reported having cancer or tuberculosis, providing 1238 individuals. 318 (25.7%) reported that they were unrecovered and 311 of these men were successfully interviewed. At a median of 3.5 months from diagnosis, 216 (17.4%) men reported fatigue, 153 (12.4%) pain, 134 (10.8%) difficulty remembering, 133 (10.7%) reduced physical activity, 114 (9.2%) shortness of breath, and 114 (9.2%) poor sleep. By 6 and 9 months, 108 (8.7%) and 55 (4.4%) of men respectively were still unrecovered. CONCLUSIONS: In this PCR Covid test-positive series of symptomatic men, recovery was significantly prolonged compared with other viral illnesses.

A novel approach for standardizing clinical laboratory categorical test results using machine learning and string distance similarity.

Standardizing clinical laboratory test results is critical for conducting clinical data science research and analysis. However, standardized data processing tools and guidelines are inadequate. In this paper, a novel approach for standardizing categorical test results based on supervised machine learning and the Jaro-Winkler similarity algorithm is proposed. A supervised machine learning model is used in this approach for scalable categorization of the test results into predefined groups or clusters, while Jaro-Winkler similarity is used to map text terms into standard clinical terms within these corresponding groups. The proposed method is applied to 75062 test results from two private hospitals in Bangladesh. The Support Vector Classification algorithm with a linear kernel has a classification accuracy of 98%, which is better than the Random Forest algorithm when categorizing test results. The experiment results show that Jaro-Winkler similarity achieves a remarkable 99.93% success rate in the test result standardization for the majority of groups with manual validation. The proposed method outperforms previous studies that concentrated on standardizing test results using rule-based classifiers on a smaller number of groups and distance similarities such as Cosine similarity or Levenshtein distance. Furthermore, when applied to the publicly available MIMIC-III dataset, our approach also performs excellently. All these findings show that the proposed standardization technique can be very beneficial for clinical big data research, particularly for national clinical research data hubs in low- and middle-income countries.