bluuebunny/crossref_metadata_2025_split huggingface dataset:
Evaluation of community health worker's performance at home-based newborn assessment supported by mHealth in rural Bangladesh
Authors: Jahan Farjana , Foote Eric , Rahman Mahbubur , Shoab Abul Kasham , Parvez Sarker Masud , Nasim Mizanul Islam , Hasan Rezaul , El Arifeen Shams , Billah Sk Masum , Sarker Supta , Hoque Md. Mahbubul , Shahidullah Mohammad , Islam Muhammad Shariful , Ashrafee Sabina , Darmstadt Gary L. 
Published: April 2022

Abstract
Background
In low to middle-income countries where home births are common and neonatal postnatal care is limited, community health worker (CHW) home visits can extend the capability of health systems to reach vulnerable newborns in the postnatal period. CHW assessment of newborn danger signs supported by mHealth have the potential to improve the quality of danger sign assessments and reduce CHW training requirements. We aim to estimate the validity (sensitivity, specificity, positive and negative predictive value) of CHW assessment of newborn infants aided by mHealth compared to physician assessment.

Methods
In this prospective study, ten CHWs received five days of theoretical and hands-on training on the physical assessment of newborns including ten danger signs. CHWs assessed 273 newborn infants for danger signs within 48 h of birth and then consecutively for three days. A physician repeated 20% (n = 148) of the assessments conducted by CHWs. Both CHWs and the physician evaluated newborns for ten danger signs and decided on referral. We used the physician’s danger sign identification and referral decision as the gold standard to validate CHWs’ identification of danger signs and referral decisions.

Results
The referrals made by the CHWs had high sensitivity (93.3%), specificity (96.2%), and almost perfect agreement (K = 0.80) with the referrals made by the physician. CHW identification of all the danger signs except hypothermia showed moderate to high sensitivity (66.7–100%) compared to physician assessments. All the danger signs assessments except hypothermia showed moderate to high positive predictive value (PPV) (50–100%) and excellent negative predictive value (NPV) (99–100%). Specificity was high (99–100%) for all ten danger signs.

Conclusion
CHW's identification of neonatal danger signs aided by mHealth showed moderate to high validity in comparison to physician assessments. mHealth platforms may reduce CHW training requirements and while maintaining quality CHW physical assessment performance extending the ability of health systems to provide neonatal postnatal care in low-resource communities.

Trial registration
clinicaltrials.gov NCT03933423, January 05, 2019.
A randomized controlled trial to examine the effectiveness of the Dutch version of the Program for the Education and Enrichment of Relational Skills (PEERS®)
Authors: Idris Sakinah , van Pelt Bjorn Jaime , Jagersma Gabrine , Duvekot Jorieke , Maras Athanasios , van der Ende Jan , van Haren Neeltje , Greaves-Lord Kirstin 
Published: April 2022

Abstract
Background
This study examines the effectiveness of the culturally adapted Dutch version of The Program for the Education and Enrichment of Relational Skills (PEERS®), utilizing a randomized control trial (RCT) with an active treatment control condition.

Methods
106 adolescents with ASD, aged 12–18 years, were randomly assigned to one of two group interventions: the experimental condition (PEERS®; n = 54) or the active treatment control condition (Regulation, Organization and Autonomy Didactics; ROAD; n = 52). Effects of interventions on social skills were primarily assessed using an observational measure (CASS – Contextual Assessment Social Skills). Secondary indices of social skills were self, parent and teacher reported questionnaire data (i.e., Social Responsiveness Scale; SRS, and Social Skills Improvement System; SSIS). Treatment satisfaction was also obtained from adolescents and their parents.

Results
Results on the observational measure of social skills revealed improvements in positive affect, overall quality of rapport, as well as starting and ending a conversation, irrespective of condition. Compared to ROAD, PEERS® participants showed increased overall self-reported social skills (SSIS). Parent reports showed decreased overall social skill impairment (SRS) as well as improved social communication (SSIS subscale), with significantly more progress in the PEERS® group. Furthermore, parents of adolescents in the PEERS® group were significantly more satisfied with the intervention (M = 8.20, SD = 1.46) than parents of adolescents in the ROAD group (M = 7.52, SD = 1.45). The self-reported treatment satisfaction of adolescents did not differ between conditions. Teacher data showed decreased social skill impairment as measured with the SRS, irrespective of condition.

Conclusions
This study reveals promising indications that the Dutch version of PEERS® enhances social skills in adolescents with ASD. Yet, further research is needed into how effectiveness can be optimized.

Trial registration
Dutch trail register NTR6255 (NL6117) 08/02/2017 https://www.trialregister.nl/trial/6117
Identifying patient-specific behaviors to understand illness trajectories and predict relapses in bipolar disorder using passive sensing and deep anomaly detection: protocol for a contactless cohort study
Authors: Ortiz Abigail , Hintze Arend , Burnett Rachael , Gonzalez-Torres Christina , Unger Samantha , Yang Dandan , Miao Jingshan , Alda Martin , Mulsant Benoit H. 
Published: April 2022

Abstract
Background
Predictive models for mental disorders or behaviors (e.g., suicide) have been successfully developed at the level of populations, yet current demographic and clinical variables are neither sensitive nor specific enough for making individual clinical predictions. Forecasting episodes of illness is particularly relevant in bipolar disorder (BD), a mood disorder with high recurrence, disability, and suicide rates. Thus, to understand the dynamic changes involved in episode generation in BD, we propose to extract and interpret individual illness trajectories and patterns suggestive of relapse using passive sensing, nonlinear techniques, and deep anomaly detection. Here we describe the study we have designed to test this hypothesis and the rationale for its design.

Method
This is a protocol for a contactless cohort study in 200 adult BD patients. Participants will be followed for up to 2 years during which they will be monitored continuously using passive sensing, a wearable that collects multimodal physiological (heart rate variability) and objective (sleep, activity) data. Participants will complete (i) a comprehensive baseline assessment; (ii) weekly assessments; (iii) daily assessments using electronic rating scales. Data will be analyzed using nonlinear techniques and deep anomaly detection to forecast episodes of illness.

Discussion
This proposed contactless, large cohort study aims to obtain and combine high-dimensional, multimodal physiological, objective, and subjective data. Our work, by conceptualizing mood as a dynamic property of biological systems, will demonstrate the feasibility of incorporating individual variability in a model informing clinical trajectories and predicting relapse in BD.
Frontotemporal EEG as potential biomarker for early MCI: a case–control study
Authors: Mitsukura Yasue , Sumali Brian , Watanabe Hideto , Ikaga Toshiharu , Nishimura Toshihiko 
Published: April 2022

Abstract
Background
Previous studies using EEG (electroencephalography) as biomarker for dementia have attempted to research, but results have been inconsistent. Most of the studies have extremely small number of samples (average N = 15) and studies with large number of data do not have control group. We identified EEG features that may be biomarkers for dementia with 120 subjects (dementia 10, MCI 33, against control 77).

Methods
We recorded EEG from 120 patients with dementia as they stayed in relaxed state using a single-channel EEG device while conducting real-time noise reduction and compared them to healthy subjects. Differences in EEG between patients and controls, as well as differences in patients’ severity, were examined using the ratio of power spectrum at each frequency.

Results
In comparing healthy controls and dementia patients, significant power spectrum differences were observed at 3 Hz, 4 Hz, and 10 Hz and higher frequencies. In patient group, differences in the power spectrum were observed between asymptomatic patients and healthy individuals, and between patients of each respective severity level and healthy individuals.

Conclusions
A study with a larger sample size should be conducted to gauge reproducibility, but the results implied the effectiveness of EEG in clinical practice as a biomarker of MCI (mild cognitive impairment) and/or dementia.
Educators’ experiences and perspectives of child weight discussions with parents in primary school settings
Authors: Coupe Nia , Peters Sarah , Ayres Matilda , Clabon Katie , Reilly Alexandra , Chisholm Anna 
Published: April 2022

Abstract
Background
The role of schools in addressing rising childhood obesity levels has been acknowledged, and numerous diet- and physical activity-related interventions exist. Aside from formal interventions, opportunistic parent-educator conversations about child weight can arise, particularly in primary school settings, yet little is known about how useful these are. This study aimed to understand the utility of child weight related conversations with parents through exploring educators’ experiences and perspectives.

Methods
This qualitative study consisted of semi-structured interviews conducted with primary school teaching staff in the United Kingdom (N = 23), recruited through purposive and subsequent snowball sampling. Interviews were audio-recorded, transcribed, and analysed using thematic analysis.

Results
Participants identified opportunities and need for child weight discussions in schools. However, conversations were prevented by the indirect and sensitive nature of conversations, and educators’ professional identity beliefs. Using pre-existing face-to-face opportunities, good parent-teacher relationships and holistic approaches to child health and wellbeing were reported as important in optimising these conversations.

Conclusions
Whilst educator-parent child weight discussions are necessary, discussions are highly challenging, with contradictory views on responsibility sometimes resulting in avoidance. Educators’ roles should be clarified, and communication training tailored to increase teacher confidence and skills. Current social distancing will likely reduce opportunistic encounters, highlighting a need to further improve communication routes.
COVID-19: a catalyst for the digitization of surgical teaching at a German University Hospital
Authors: Wolf Milan Anton , Pizanis Antonius , Fischer Gerrit , Langer Frank , Scherber Philipp , Stutz Janine , Orth Marcel , Pohlemann Tim , Fritz Tobias 
Published: April 2022

Abstract
Background
The summer semester 2020, had to be restructured due to the SARS-CoV-2 pandemic and the associated contact restrictions. Here, for the first time, the established lectures in lecture halls and small group seminars could not be conducted in presence as usual. A possible tool for the implementation of medical teaching, offers the use of eLearning, online webinars and learning platforms. At present it is unclear how the SARS-CoV-2 pandemic will affect surgical teaching, how digitization will be accepted by students, and how virtual teaching can be expanded in the future.

Methods
The teaching, which was previously delivered purely through face-to-face lectures, was completely converted to digital media. For this purpose, all lectures were recorded and were available to students on demand. The seminars were held as a twice a week occurring online webinar. The block internship was also conducted as a daily online webinar and concluded with an online exam at the end.
At the end of the semester, a survey of the students was carried out, which was answered by n = 192 students with an anonymized questionnaire. The questionnaire inquires about the previous and current experience with eLearning, as well as the possibility of a further development towards a purely digital university.

Results
There were n = 192 students in the study population. For 88%, the conversion of classes to web-based lectures represented their first eLearning experience. For 77% of all students, the digitization of teaching led to a change in the way they prepare for class. 73% of the participating students are of the opinion that eLearning lectures should continue to be offered. 54% of the students felt that eLearning lectures made more sense than face-to-face lectures. A purely virtual university could be imagined by 41% of the students.

Conclusion
The conversion of teaching represented the first contact with eLearning for most students. Overall, the eLearning offering was experienced as positive. Due to the new teaching structure, the way of learning had already changed during the semester. Based on the new eLearning content, the already existing formats can be further expanded in the future. Nevertheless, it turned out that the practical-surgical contents and skills cannot be adequately represented by purely online offers; for this, the development of hybrid practice-oriented teaching concepts is necessary.
Environmental and clinical data utility in pediatric asthma exacerbation risk prediction models
Authors: Hurst Jillian H. , Zhao Congwen , Hostetler Haley P. , Ghiasi Gorveh Mohsen , Lang Jason E. , Goldstein Benjamin A. 
Published: April 2022

Abstract
Background
Asthma exacerbations are triggered by a variety of clinical and environmental factors, but their relative impacts on exacerbation risk are unclear. There is a critical need to develop methods to identify children at high-risk for future exacerbation to allow targeted prevention measures. We sought to evaluate the utility of models using spatiotemporally resolved climatic data and individual electronic health records (EHR) in predicting pediatric asthma exacerbations.

Methods
We extracted retrospective EHR data for 5982 children with asthma who had an encounter within the Duke University Health System between January 1, 2014 and December 31, 2019. EHR data were linked to spatially resolved environmental data, and temporally resolved climate, pollution, allergen, and influenza case data. We used xgBoost to build predictive models of asthma exacerbation over 30–180 day time horizons, and evaluated the contributions of different data types to model performance.

Results
Models using readily available EHR data performed moderately well, as measured by the area under the receiver operating characteristic curve (AUC 0.730–0.742) over all three time horizons. Inclusion of spatial and temporal data did not significantly improve model performance. Generating a decision rule with a sensitivity of 70% produced a positive predictive value of 13.8% for 180 day outcomes but only 2.9% for 30 day outcomes.

Conclusions
EHR data-based models perform moderately wellover a 30–180 day time horizon to identify children who would benefit from asthma exacerbation prevention measures. Due to the low rate of exacerbations, longer-term models are likely to be most clinically useful.
Trial Registration: Not applicable.
Evaluating the implementation and impact of navigator-supported remote symptom monitoring and management: a protocol for a hybrid type 2 clinical trial
Authors: Rocque Gabrielle B. , Dionne-Odom J. Nicholas , Stover Angela M. , Daniel Casey L. , Azuero Andres , Huang Chao-Hui Sylvia , Ingram Stacey A. , Franks Jeffrey A. , Caston Nicole E. , Dent D’ Ambra N. , Basch Ethan M. , Jackson Bradford E. , Howell Doris , Weiner Bryan J. , Pierce Jennifer Young 
Published: April 2022

Abstract
Background
Symptoms in patients with advanced cancer are often inadequately captured during encounters with the healthcare team. Emerging evidence demonstrates that weekly electronic home-based patient-reported symptom monitoring with automated alerts to clinicians reduces healthcare utilization, improves health-related quality of life, and lengthens survival. However, oncology practices have lagged in adopting remote symptom monitoring into routine practice, where specific patient populations may have unique barriers. One approach to overcoming barriers is utilizing resources from value-based payment models, such as patient navigators who are ideally positioned to assume a leadership role in remote symptom monitoring implementation. This implementation approach has not been tested in standard of care, and thus optimal implementation strategies are needed for large-scale roll-out.

Methods
This hybrid type 2 study design evaluates the implementation and effectiveness of remote symptom monitoring for all patients and for diverse populations in two Southern academic medical centers from 2021 to 2026. This study will utilize a pragmatic approach, evaluating real-world data collected during routine care for quantitative implementation and patient outcomes. The Consolidated Framework for Implementation Research (CFIR) will be used to conduct a qualitative evaluation at key time points to assess barriers and facilitators, implementation strategies, fidelity to implementation strategies, and perceived utility of these strategies. We will use a mixed-methods approach for data interpretation to finalize a formal implementation blueprint.

Discussion
This pragmatic evaluation of real-world implementation of remote symptom monitoring will generate a blueprint for future efforts to scale interventions across health systems with diverse patient populations within value-based healthcare models.

Trial registration
NCT04809740; date of registration 3/22/2021.
Cost-effectiveness analysis of paediatric mental health interventions: a systematic review of model-based economic evaluations
Authors: Kularatna Sanjeewa , Hettiarachchi Ruvini , Senanayake Sameera , Murphy Ciara , Donovan Caroline , March Sonja 
Published: April 2022

AbstractMental health disorders among children and youth are causing significant burden on health care systems. Hence, identifying cost-effective interventions is important for effective mental health care allocation. Although model-based economic evaluations are an essential component of assessing cost-effectiveness, evidence are limited in the context of child and youth mental health care. The objective was to systematically review the model-based economic evaluations of mental health interventions for children and youth.MethodsFour databases (MEDLINE, EMBASE, PsycINFO and Web of Science) were searched using appropriate search terms to retrieve model-based economic evaluations of mental health interventions for children and youth. The reporting quality of the included studies were appraised using the Consolidated health economic evaluation reporting standards (CHEERS) checklist.ResultsThe database search yielded 1921 records. Of the 12 selected for review, 66% were published after year 2015. Most of the studies were related to anxiety and post-traumatic stress disorder. There were eight cost-utility studies, three cost-effectiveness studies, and one study using both forms of analysis. Six studies used Markov models, three used decision trees, and three studies used both types of models. However, the model structure, health states, time horizon, and economic perspective showed wide variation. The reporting quality of the included studies varied from 91 to 96%.ConclusionModel based mental health economic evaluations among children and youth are increasingly being reported in recent research. The included studies used Markov models and decision trees, either alone or in combination, and the majority of the articles were of good reporting quality.
Ruptured endometrioma in a nonpregnant patient: a case report
Authors: Young Hayley , Bui Thanh-Lan , Cramer Scott E. , O’Connell Ryan , Houshyar Roozbeh 
Published: April 2022

Abstract
Background
Endometriomas are a type of ovarian cyst composed of degenerated blood products from hemorrhage of ectopic endometrial tissue. Endometriomas can rupture, causing hemoperitoneum, and present with signs and symptoms similar to other, more common abdominal emergencies. Therefore, they are not often diagnosed preoperatively. Ultrasound and cross-sectional imaging can assist in diagnosis of endometriomas. We present a case of ruptured endometrioma causing massive hemoperitoneum that was initially suspected to represent malignancy with carcinomatosis.

Case presentation
A 32-year-old Hispanic woman presented with sharp abdominal pain and 15-pound unintentional weight loss over 6 months. Laboratory work was significant for a negative pregnancy test and elevated cancer antigen-125. Computed tomography of the abdomen and pelvis demonstrated a 13-cm complex cystic mass in the left adnexa with moderate hyperdense ascites and omental nodularity. Ultrasound demonstrated a large left adnexal complex cystic structure with internal echoes, and chest computed tomography showed no signs of intrathoracic neoplastic or infectious processes. Her presentation was concerning for malignancy with carcinomatosis. Fluid from a paracentesis was sent for culture and cytology. Diagnostic laparoscopy revealed that the left ovary had been completely replaced by an endometrioma, which had a small ruptured area superiorly. Brown deposits of endometriosis were present on the cyst, omentum, and various peritoneal linings. Tissue samples of the endometrium, myometrium, cervix, ovaries, fallopian tubes, peritoneum, omentum, and paracolic spaces were taken and showed no hyperplastic, dysplastic, or malignant cells on pathology.

Conclusions
Ruptured endometrioma and ruptured hemorrhagic cyst should be included in the differential diagnosis when a premenopausal female presents with hemoperitoneum in combination with complex adnexal cystic masses in the absence of trauma. Cancer antigen-125 and cancer antigen 19-9 can be falsely elevated in the setting of ruptured endometrioma.