Similar Scores Research Articles

Smartphone-Based Cognitive Behavioral Therapy and Customized Sound Therapy for Tinnitus: A Randomized Controlled Trial.

To evaluate the efficacy of a smartphone-based application providing tinnitus-specific cognitive behavioral therapy and customized sound therapy for tinnitus. In a prospective randomized controlled trial, the treatment group participated in daily sound therapy and weekly interactive CBT modules, and the control group did not receive the program (waitlisted). Outcome measures after 8 weeks included the Tinnitus Functional Index (TFI), Generalized Anxiety Disorder (GAD-7), Patient Health Questionnaire (PHQ-9), Perceived Stress Scale (PSS), and Pittsburgh Sleep Quality Index (PSQI). Ninety-two patients (mean age = 57.2 ± 11.9 years) were included. The treatment (n = 47) and control (n = 45) cohorts had similar TFI, PHQ-9, GAD-7, PSS, and PSQI scores at presentation (all P > .05). Treatment-group patients had significantly higher improvements than controlled patients in their TFI (16.7 ± 14.9 vs 1.9 ± 10.8, P < .001), PHQ-9 (1.9 ± 4.2 vs -0.7 ± 3.4, P = .002), GAD-7 (1.1 ± 3.6 vs -0.9 ± 3.3, P = .009), and PSQI scores (2.5 ± 3.2 vs -1.1 ± 2.1, P < .001). Treatment-group subjects also significantly improved in 7 of the 8 TFI domains (all P < .05). TFI improvements of ≥20 occurred in 18 (38.3%) treatment subjects. Of the 9 treatment-group patients presenting with moderate-severe depression, 4 (44.4%) improved to minimal depression. Of the 4 treatment-group patients with moderate-severe anxiety, 2 (50.0%) improved to minimal anxiety. Of the 17 treatment-group patients with moderate-severe sleep difficulties, 10 (55.6%) had considerable sleep improvement. This novel smartphone application providing cognitive behavioral therapy and customized sound therapy was effective in reducing symptom severity and improving anxiety, sleep, and mood for tinnitus patients.

Longitudinal validation of the PROMIS-16 in a sample of adults in the United States with back pain.

This longitudinal study evaluates whether the Patient-Reported Outcomes Measurement and Information System (PROMIS)-16 domains capture average change over time comparable to the PROMIS-29 + 2 and have similar associations with change in overall health rating and two disability indices. Data were collected using Amazon's Mechanical Turk at baseline, 3 months, and 6 months among individuals reporting chronic low back pain. The analytic sample includes respondents who completed baseline and at least one follow-up assessment (N = 1137). We estimated latent growth models for eight PROMIS domains and compared growth parameters between the PROMIS-16 and PROMIS 29 + 2 with a z-test. Additionally, for each domain, random intercept and slope scores for individuals were computed for the PROMIS-29 + 2 and PROMIS-16 and correlated to estimate concordance. Using growth parameters for physical function and pain interference, we predicted average change in the Oswestry Disability Index (ODI), Roland Morris Disability Questionnaire (RMDQ), the overall health rating, and compared regression coefficients between the PROMIS-16 and PROMIS 29 + 2. All growth models fit the data well. Intercept and slope parameters were statistically comparable (p's > 0.05) in magnitude across all domains between the PROMIS-16 and PROMIS-29 + 2. Correlations between random intercept and slope scores for individuals across domains were high. Additionally, the regression coefficients between slopes for pain interference and physical function and ODI, RMDQ, and overall health rating were statistically comparable (p's > 0.05) between the PROMIS-16 and PROMIS 29 + 2. Results provide between-level support for the longitudinal and predictive validity of the PROMIS-16. Similar average baseline scores and changes over time were observed between PROMIS-16 and PROMIS-29 + 2. Further, average change estimates comparably predicted average change in distal outcomes. This work provides evidence supporting the utility of the PROMIS-16 as a viable, short-profile option for use in clinical and research settings.

Exploring Personality Profiles as a Source of Phenotypic Diversity in Autistic Children and Adolescents.

This study adopts a person-centered approach to evaluate personality diversity as a source of interpersonal variability in autistic children and adolescents, and how personality subgroup membership relates to variability in autistic characteristics, social-emotional presentations, and parenting outcomes. Latent Profile Analysis was used to analyze 569 parent reports on a child-based Five-Factor-Model personality measure (aged 6-18 years; Mage = 11.8 years, SD = 3.1; 70% boys). Four distinct personality profile groups were identified, showing varying levels in the low to average range of all five personality domains. All groups scored lowest on Extraversion and Emotional Stability. They differed the most in Imagination and the least in Emotional Stability. Group 1 (n = 72) exhibited the lowest mean-level scores on all five domains, whereas Group 4 (n = 90) had the highest domain scores. Group 2 (n = 307) and Group 3 (n = 100) showed more diverse patterns. Group membership was meaningfully associated with variation in characteristics of social interaction and communication, internalizing, externalizing, and attentional problems, psychosocial strengths, and positive parenting strategies. Only modest group differences were found in parenting stress. All groups had similar scores on repetitive and restrictive behaviors. These findings help to better understand and support natural subgroups within the autism phenotype by exploring shared personality attributes.

Chasing the Neutrino Blazar Candidates

In our study of the correlations between IceCube-detected neutrino events and γ-ray properties of blazars, we recognize the inherent challenges posed by the limited detection of neutrinos. In this paper, we explore few-shot learning to deal with the class imbalance and few-shot issues presented in the incremental version of the 12 yr Fermi-LAT γ-ray source catalog (4FGL_ DR3). Specifically, we train a triplet network to transform the blazars with neutrino emission (NBs) and nonblazar samples into an embedding space where their similarities can be measured. With two-way three-shot learning, 199 out of 3708 blazars without neutrino emission (non-NBs) are considered as the potential blazars emitting neutrinos (NB candidates, or NBCs for short), with a similarity score against NBs exceeding 98%. Moreover, the Kolmogorov–Smirnov test supports our identification of NBCs.

Pre-trained models for linking process in data washing machine

Entity Resolution (ER) has been investigated for decades in various domains as a fundamental task in data integration and data quality. The emerging volume of heterogeneously structured data and even unstructured data challenges traditional ER methods. This research mainly focuses on the Data Washing Machine (DWM). The DWM was developed in the NSF DART Data Life Cycle and Curation research theme, which helps to detect and correct certain types of data quality errors automatically. It also performs unsupervised entity resolution to identify duplicate records. However, it uses traditional methods that are driven by algorithmic pattern rules such as Levenshtein Edit Distances and Matrix comparators. The goal of this research is to assess the replacement of rule-based methods with machine learning and deep learning methods to improve the effectiveness of the processes using 18 sample datasets. The DWM has different processes to improve data quality, and we are currently focusing on working with the scoring and linking processes. To integrate the machine model into the DWM, different pre-trained models were tested to find the one that helps to produce accurate vectors that can be used to calculate the similarity between the records. After trying different pre-trained models, distilroberta was chosen to get the embeddings, and cosine similarity metrics were later used to get the similarity scores, which helped us assess the machine learning model into DWM and gave us closer results to what the scoring matrix is giving. The model performed well and gave closer results overall, and the reason can be that it helped to pick up the important features and helped at the entity matching process.

External validation of a multimodality deep-learning normal tissue complication probability model for mandibular osteoradionecrosis trained on 3D radiation distribution maps and clinical variables

Background and purposeWhile the inclusion of spatial dose information in deep learning (DL)-based normal-tissue complication probability (NTCP) models has been the focus of recent research studies, external validation is still lacking. This study aimed to externally validate a DL-based NTCP model for mandibular osteoradionecrosis (ORN) trained on 3D radiation dose distribution maps and clinical variables. Methods and materialsA 3D DenseNet-40 convolutional neural network (3D-mDN40) was trained on clinical and radiation dose distribution maps on a retrospective class-balanced matched cohort of 184 subjects. A second model (3D-DN40) was trained on dose maps only and both DL models were compared to a logistic regression (LR) model trained on DVH metrics and clinical variables. All models were externally validated by means of their discriminative ability and calibration on an independent dataset of 82 subjects. ResultsNo significant difference in performance was observed between models. In internal validation, these exhibited similar Brier scores around 0.2, Log Loss values of 0.6–0.7 and ROC AUC values around 0.7 (internal) and 0.6 (external). Differences in clinical variable distributions and their effect sizes were observed between internal and external cohorts, such as smoking status (0.6 vs. 0.1) and chemotherapy (0.1 vs. −0.5), respectively. ConclusionTo our knowledge, this is the first study to externally validate a multimodality DL-based ORN NTCP model. Utilising mandible dose distribution maps, these models show promise for enhancing spatial risk assessment and guiding dental and oncological decision-making, though further research is essential to address overfitting and domain shift for reliable clinical use.

Sociodemographic predictors and cross-cultural comparisons in tests performance from the Cambridge Neuropsychological Testing Automated Battery (CANTAB) among children aged 6-8 years from Montevideo, Uruguay.

Cross-culturally comparative data on measures of executive function (EF) are essential, but the 6-8-year group remains insufficiently described. This study examined the sociodemographic predictors of EF test performance employing the Cambridge Neuropsychological Testing Automated Battery (CANTAB). It also compared developmental trends in EF among children from Uruguay, the United States, and Mexico. EFs were assessed with the Intra-dimensional/Extra-dimensional shift, Spatial Span (SSP), and Stockings of Cambridge (SOC) tests from the CANTAB. The study sample consisted of 6-8-year-old children from the Salud Ambiental Montevideo (SAM) cohort in Uruguay. Differences between cohorts were examined, and we performed generalized linear regressions to assess the association between sociodemographic factors, and each EF domain. The final sample consisted of 525 participants (mean age in months 82.5 ± 6.0). Across all ages, SAM children had significantly lower performance in the SSP and SOC tasks compared to U.S. and Mexican children. On the Intra-dimensional/Extra-dimensional shift task, SAM children had similar scores to U.S. and Mexican children. Mother's intelligence quotient (IQ; β = 0.01; 95% CI [0.005, 0.02]), child's IQ (0.02 [0.02, 0.03]), the HOME total score (0.02 [0.01, 0.03]), as well as HOME subscales of accompaniment (0.13 [0.07, 0.20]), enrichment (0.11 [0.06,0.16]), and physical environment (0.07 [0.03, 0.10]) were positively associated with the span length (SSP task). Child's IQ (0.02 [0.01,0.03]) was positively associated with the number of problems solved on the SOC test. Uruguayan children perform lower in working memory and planning tests than U.S. children but similarly to Mexican children, while cognitive flexibility is consistent across all groups. Further, mother and child IQ, as well as the home environment, are important predictors of EF. These differences should be examined in the context of diverse cultural values and sociodemographic factors affecting CANTAB construct validity in this population. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Maximizing RAG efficiency: A comparative analysis of RAG methods

Abstract This paper addresses the optimization of retrieval-augmented generation (RAG) processes by exploring various methodologies, including advanced RAG methods. The research, driven by the need to enhance RAG processes as highlighted by recent studies, involved a grid-search optimization of 23,625 iterations. We evaluated multiple RAG methods across different vectorstores, embedding models, and large language models, using cross-domain datasets and contextual compression filters. The findings emphasize the importance of balancing context quality with similarity-based ranking methods, as well as understanding tradeoffs between similarity scores, token usage, runtime, and hardware utilization. Additionally, contextual compression filters were found to be crucial for efficient hardware utilization and reduced token consumption, despite the evident impacts on similarity scores, which may be acceptable depending on specific use cases and RAG methods.

ROSHAMBO: Open-Source Molecular Alignment and 3D Similarity Scoring.

Efficient virtual screening techniques are critical in drug discovery for identifying potential drug candidates. We present an open-source package for molecular alignment and 3D similarity calculations optimized for large-scale virtual screening of small molecules. This work parallels widely used proprietary tools and offers an approach complementary to structure-based virtual screening. Our package employs the PAPER software for optimizing molecular alignments based on Gaussian volume overlaps. GPU acceleration is utilized to significantly reduce computational time and resource requirements. After obtaining the optimal alignments between the target and the query molecules, both shape and color (based on pharmacophore features) scores are computed to assess molecular similarity, with aligned molecules optionally being output in sdf format. The package was benchmarked using the DUDE-Z public data sets. Results demonstrated the package's near-state-of-the-art performance and robustness across multiple target classes, with speed that enables many routine ligand-based drug discovery workflows. As an open-source and freely available resource (github.com/molecularinformatics/roshambo) with both a convenient Python API and command line interface, our package also addresses the need for accessible and efficient virtual screening tools in drug discovery.

The relationship between anxiety and diet quality in adolescent populations: a cross-sectional analysis.

Globally, more than 13 % of adolescents have clinically significant mental health problems, with anxiety and depression comprising over 40 % of cases. Despite the high prevalence of anxiety disorders among youth, dietary research has been focused on youth with depression, resulting in a significant knowledge gap regarding the impact of anxiety on adolescent diet quality. Adolescents with diagnosed anxiety disorders and healthy controls were included in this study. Anxiety symptoms were measured using the Screen for Child Anxiety-Related Disorders. Diagnosis of anxiety disorder was determined using the Kiddie Schedule for Affective Disorders and Schizophrenia interview. Five diet quality indices were scored from FFQ. Diet quality indices associated with anxiety symptoms in the correlation matrix were interrogated using multiple linear regression modelling. All models were adjusted for depression. One hundred and twenty-eight adolescents (mean age 14·8 years (sd: 2·1); 66·4 % female) were included in this cross-sectional analysis. Although healthy controls and outpatient participants had similar unhealthy dietary index subscale scores, outpatient participants had lower healthy index scores. Higher anxiety symptoms were associated with lower healthy dietary indices in univariate analysis; after adjusting for comorbid depression; however, anxiety symptoms were no longer associated with dietary indices following adjustment for multiple testing (P = 0·038 to P = 0·077). The association between anxiety symptoms and a poor diet is attenuated by depression. The results of this study support the need for an integrated approach to the assessment of mental and physical well-being and further research aimed at understanding the unique contribution of depression to healthy dietary patterns.

Defining digital health literacy profiles in Spanish adults: a latent class analysis

Abstract Background According to different reports, Spain is among the European countries that use digital health technologies the most. However, to develop inclusive and fair digital health services, there is the need to feature digital health knowledge, skills, confidence, and a positive attitude about their significance. This work aims to draw a picture of digital health literacy levels in Spain. Methods A stratified sample of the Spanish population regarding gender, age group and area of residence was used. Participants were recruited from an online panel and by direct approach to balance quotas. Between May 2021- May 2022, participants filled a self-administered online survey, including the Spanish version of the eHealth Literacy Questionnaire (eHLQ) and the eHealth Literacy Scale (eHEALS). Results Digital health literacy showed similar mean scores, between 2.6-2.7 out of 5 with similar SD on each of the 7 dimensions of the eHLQ. The highest scores were related to knowledge about filling data in digital health services and knowledge about health and how the body works, and feelings about the usefulness of digital technology for health. In contrast, lower scores were related to sharing health information by technology, thinking that using technology gives access to better health services, and the possibility to contact usual health professionals with technology. Latent profile analysis identified 5 user profiles. Significant differences were found according to age, inhabitants per municipality, technology use, self-perceived health status, educational level, socioeconomic index and eHEALS scores; not by gender. Conclusions As the scores are similar in the different subscales, competencies, attitudes and confidence in digital health that they measure are balanced. However, the main challenge appears in granting users access to digital services that work, which involves the definition and monitoring of strategies until the final implementation. Key messages • Digital Health literacy in Spain differs according to different aspects, not only age, educational or socioeconomic level. • Confidence in usefulness is a common denominator among the five digital health service user profiles identified.

Telehealth-aided outpatient management of acute heart failure in a specialist virtual ward compared to standard care

Abstract Background/Introduction Acute decompensated heart failure (ADHF) leads to hospitalisations, frequent re-hospitalisations and mortality. The safety and efficacy of telehealth-guided outpatient ADHF management (virtual ward-VW) as an alternative to hospitalisation has not been assessed previously. Aim The aim of this study was to assess the safety and outcomes of our acute heart failure virtual ward (HFVW) pathway (Figure 1) when compared to hospitalised ADHF patients. Methods This cohort study (May 2022-October 2023) assessed the outcomes of telehealth-guided outpatient ADHF management using bolus intravenous furosemide in a HF-specialist VW. We compared baseline patient characteristics, NTproBNP, ejection fraction, NYHA Class, clinical risk score (Get With the Guidelines-Heart Failure-GWTG-HF), comorbidities (Charlson Co-morbidity Index-CCI), frailty (Rockwood Clinical Frailty Score-CFS), HF therapies and measured clinical outcomes at 1, 3, 6 and 12 months (re-hospitalisations, mortality) in the HFVW cohort versus standard care (ADHF patients managed without telehealth in 2021). Results 554 HFVW ADHF patients (age 73.1±10.9 years; 46% female) were compared with 402 ADHF patients (74.2±11.8; p=0.15 and 49% female) in the standard care cohort (SC). Despite similar baseline patient characteristics, GWTG-HF score, CCI and CFS, re-hospitalisations were significantly lower in the HFVW compared to standard care (1 month - 11.6% vs. 21%, p=0.002; 3 months - 20.4% vs. 30%, p=0.001; 6 months -29.3% vs 41%, p=0.02 and 12 months-48% vs. 57%,p=0.03) whereas mortality was lower at 1 month (6% vs. 14%; p&amp;lt;0.001), 3 months (10.5% vs. 15%; p=0.02) and 6 months (15.5% vs. 21%; p=0.04) (Figure 2). Multivariate logistic regression analysis showed that an increased daily step count whilst on HFVW independently predicted reduced odds of re-hospitalisations at 1 month (OR 0.85; 95% CI 0.7-0.9; p=0.005), 3 months [OR 0.95 (0.93-0.98); p=0.003] and 1 month mortality [OR 0.85 (0.7-0.95), p=0.01]. Whereas CCI predicted adverse 12-month outcomes [OR 1.2 (1.1-1.4), p=0.03]. Higher GWTG-HF score independently predicted increased odds of re-hospitalisation [1-month OR 1.2 (1.1-1.3), p=0.01; 12-month OR 1.1, 1.05-1.2, p=0.03) as well as mortality [1-month OR 1.2 (1.1-1.4), p=0.01; 12-month OR 1.3 (1.1-1.7), p=0.02]. Similarly higher CFS also independently predicted increased odds of re-hospitalisations [1-month OR 1.5 (1.1-2.2), p=0.03; 12-month OR 1.9 (1.2-3, p=0.01] and mortality [1-month OR 2 (1.1-3.5), p=0.02; 12-month OR 2.6 (1.6-10); p=0.02] throughout the follow-up period. Conclusions A telehealth-guided specialist HFVW management strategy for ADHF may offer a safe and efficacious alternative to hospitalisation in suitable patients. Daily step count, GWTG, CCI and CFS can play a vital role in assessing suitability for VW and in predicting risk of adverse clinical outcomes.Heart Failure Virtual Ward PathwayMortality &amp; Re-hospitalisations outcomes

Early Internal Short Circuit Diagnosis for Lithium-Ion Battery Packs Based on Dynamic Time Warping of Incremental Capacity

Timely identification of early internal short circuit faults, commonly referred to as micro short circuits (MSCs), is essential yet poses significant challenges for the safe and reliable operation of lithium-ion battery (LIB) energy storage systems. This paper introduces an innovative diagnostic method for early internal short circuits in LIB packs, utilizing dynamic time warping (DTW) applied to incremental capacity (IC). Initially, the terminal voltages of all cells within the LIB pack are ordered at any moment to determine the median terminal voltage, which is then used to generate the median IC curve. This curve acts as a reference benchmark that represents the condition of healthy cells in the pack. Subsequently, the DTW algorithm is utilized to measure the similarity between each cell’s IC curve and the median IC curve. Cells exhibiting similarity scores that exceed a specified threshold are identified as having MSC faults. Lastly, for the cells diagnosed with MSC conditions, a method for estimating short-circuit resistance (SR) based on variations in maximum charging voltage is devised to quantitatively evaluate the severity and evolution of the MSC. Experimental findings reveal that the proposed method effectively identifies MSC cells in the LIB pack and estimates their SRs without the necessity of a battery model, thereby affirming the method’s validity.

Siamese neural networks can identify subjects from anonymised ECGs

Abstract Background/Introduction Many research databases contain anonymised electrocardiograms (ECGs) linked to other sensitive information. ECGs hold features unique to individuals, potentially enabling subject identification from anonymised ECGs. Purpose We assessed if artificial intelligence approaches to output ECG pair similarity can re-identify individuals from anonymised ECGs. Additionally, we aimed to explore clinical risk prediction using ECG similarity over time. Methods We used a convolutional Siamese neural network (SNN), with a triplet loss function, to train a deep learning model determining if two ECGs belong to the same individual (Figure 1). The model aims to encode ECG inputs from same subjects closer than ECG inputs from different subjects. An ECG similarity score is output, corresponding to the probability two ECGs belong to the same subject. This continuous metric can be used in a binary manner. Below a threshold, two ECGs are classed as from the same individual. Our dataset comprised 72,455 secondary care subjects from a USA cohort with 4 to 75 ECGs each, totalling 864,283 ECGs. These were split 50:10:40% at the subject level for training, validation and testing. Results In 2,689,124 same-subject pairs and 2,689,124 different-subject pairs from the test set, the model achieves an accuracy of 91.68% against the binary threshold. This improves to 93.61% and 95.97% in outpatient and normal ECG subsets, respectively. We tested the model using a subject’s ECG to identify them from a group where only one ECG also belongs to that subject. 89.4% success rates occur in groups of 100 normal ECGs (if random, success would be 1%). 91.4%, 95.1%, and 96.3% success occurs when supplemented with subject gender, age (decade-bracket), and both, respectively. We calculated a model certainty score for this task. 99% success occurs when &amp;gt;95% certain. This is in 65% of group size 100 trials. In groups of 1000 normal ECGs, the success rate is 72.5% with no additional information, and 75.9%, 84.2% and 87.5% when supplemented as before (if random, success would be 0.1%). &amp;gt;95% certainty occurs in 33% of group size 1000 trials. For a given subject, ECG pair similarity proved clinically informative. The model accounts for slight variations within a subject’s ECGs, even when far apart in time (Figure 2A). However, it incorrectly predicts two ECGs as being from different individuals for substantial ECG morphology changes (Figure 2B), which could be used to identify clinical deterioration. The temporal evolution of ECG pair similarity reflects clinical trajectory, with greater dissimilarity associating with all-cause mortality (Hazard ratio, 1.22 per 1 standard deviation change, p &amp;lt; 0.0001). Conclusion(s) Anonymised ECGs retain information useful for subject re-identification. Whilst this implies possible ethical and data protection issues with large datasets, such approaches offer potential for continuous monitoring and identifying clinical deterioration.Figure 1Figure 2

Evaluation of the measurement properties of the parental perceptions of children's exposure to tobacco smoke instrument translated and adapted to the Brazilian context.

Given the need to measure parents' perceptions of their children's exposure to tobacco smoke, the Parental Perceptions of Children's Exposure to Tobacco Smoke (PPE) instrument was developed and validated in Hebrew and later translated into English and Portuguese. The PPE has already been translated and adapted to the Brazilian context but a more robust sample is necessary to investigate the measurement properties. Thus, this study evaluated the measurement properties of the Brazilian version of the PPE instrument. Reliability and validity study were conducted with 161 parents with children up to 18 years of age. Perception of parental smoking status was investigated using analysis of variance. The instrument showed excellent reliability (Cronbach α = 0.92 and intraclass correlation coefficient = 0.91). The exploratory factor analysis identified 4 factors with a total accumulated variance of 71.6%. Confirmatory factor analysis validated this structure with 4 factors. It was necessary to exclude a question that presented low commonality. Analysis of variance demonstrated that nonsmoking and former smoking parents have similar scores, although they are higher than those of current smokers. Our findings provide evidence that the PPE version translated and adapted for the Brazilian context is a reliable and valid instrument. Thus, it can help us understand how parents cope with exposure to tobacco smoke.

Family background, education, and earnings: the limited value of “test-score transmission”

AbstractThis paper investigates the relationship between the inter-generational transmission of educational achievement (“test-score transmission”) and the inter-generational transmission of higher earnings (“income transmission”). We use administrative data from Israel to track the evolution of education and earnings gaps between “second-generation” (SG) students, whose parents have some tertiary education, and “first-generation” (FG) students, whose parents have none. We find that SG students achieve much better results on the screening tests that regulate access to selective tertiary education than FG students with similar eighth-grade test scores. Consequently, they enjoy greater access to the most selective tertiary degree programs, crowding out FG students with higher eighth-grade achievement. Yet this advantage does not manifest itself in earnings differentials at age 29, similarly conditioned on eighth-grade achievement, which are not statistically significant, and we find no evidence that these patterns are driven by SG students choosing study fields with steeper earnings curves. We find evidence of two mechanisms that mediate the relationship between achievement gains and earnings: FG students compensate for fewer options in tertiary education by accumulating more labor market experience; and SG students are more likely to forgo higher earnings for non-pecuniary benefits in employment, particularly by choosing public-sector employment.

Comparison of Patient-Reported Outcomes after Local Flap Coverage versus Amputation for Complex Lower Extremity Trauma

Abstract Background There is a paucity of patient-reported outcomes (PROs) data in lower extremity salvage. Limb salvage can often be achieved with the use of local muscle flaps or fasciocutaneous flaps. The purpose of this study was to compare PROs of patients who underwent lower extremity salvage using local fasciocutaneous flaps or muscle flaps to lower extremity amputation. Materials and Methods The outcomes of 61 patients that underwent lower extremity local flap reconstruction (n = 33) or amputation (n = 28) between 2014 and 2020 were recorded. Chart reviews were performed to collect perioperative data. Patients were contacted via telephone for participation in the survey portion of our study. PROs were recorded utilizing both the Lower Extremity Functional Scale (LEFS) and the 36-Item Short-Form Health Survey (SF-36). Results Surveys were completed by 61 patients (response rate 59.2%). The mean time of survey after flap reconstruction or amputation was 2.7 ± 1.4 years. Recent trauma (within 90 days) was the most common indication for local flap coverage (n = 23). LEFS score and SF-36 physical functioning scores were significantly lower in patients who underwent muscle flaps compared with fasciocutaneous flaps (p = 0.021 and p = 0.022). Muscle flap patients had similar LEFS and SF-36 scores to amputation patients, while fasciocutaneous flap patients had significantly higher LEFS (p = 0.01), SF-36 physical functioning (p = 0.031), physical role functioning (p = 0.031), and emotional role functioning (p = 0.047) scores than amputation patients. Conclusion Patients who underwent local fasciocutaneous flaps for limb salvage reported higher PRO scores than those undergoing amputation, while patients undergoing muscle flaps reported outcomes similar to those undergoing amputation. PROs for muscle flap patients were significantly lower than those of fasciocutaneous flap patients. These data suggest that while fasciocutaneous and muscle flaps are both useful limb salvage procedures, fasciocutaneous flaps may confer advantages that result in improved patient-perceived outcomes. Further study is needed to better characterize outcomes in limb salvage.

Cervical ripening with a double balloon device for 6 h in patients with a long cervix: Secondary analysis of a randomized controlled trial.

To examine whether cervical ripening with a double balloon device for 6 h is as effective as 12 h in patients with a cervical length ≥ 30 mm measured on transvaginal ultrasound before induction of labor, and to determine whether patients with a long cervix need to have the balloon placed for a longer time. This is a secondary analysis of data from a randomized controlled trial that compared maternal and neonatal outcomes between women undergoing cervical ripening with a double balloon device for 6 h (study group) versus 12 h (control group). In this secondary analysis, we included only patients who had cervical length ≥ 30 mm measured on transvaginal ultrasound on admission. Our primary outcome was a Bishop score change after removal of the device. Secondary outcomes included insertion to delivery interval, mode of delivery, and oxytocin infusion duration. Sixty-seven women met the inclusion criteria and were included in the analysis: 33 in the 6-h group and 34 in the 12-h group. Maternal characteristics were similar between both groups. Bishop score difference between the preinsertion and the postremoval scores were similar in the two groups (2.67 ± 1.8 vs. 2.53 ± 1.69, P = 0.76), while insertion to delivery time was 10 h shorter in the 6-h group (20.95 vs. 31.21, P = 0.02; mean difference, -10.26 [95% CI, -19.0 to -1.51]). The other secondary outcomes remained similar in both groups. In women undergoing induction of labor who have a cervical length ≥ 30 mm measured on admission transvaginal ultrasound, removing a double balloon device after 6 h achieved similar Bishop score changes as removal after 12 h, but significantly reduced the time to delivery. REGISTRATION AT CLINICAL TRIALS: https://classic. gov/ct2/show/NCT03045939.

French Version of the User Mobile Application Rating Scale: Adaptation and Validation Study.

Managing noncommunicable diseases effectively requires continuous coordination and monitoring, often facilitated by eHealth technologies like mobile health (mHealth) apps. The end-user version of the Mobile Application Rating Scale is a valuable tool for assessing the quality of mHealth apps from the user perspective. However, the absence of a French version restricts its use in French-speaking countries, where the evaluation and regulation of mHealth apps are still lacking, despite the increasing number of apps and their strong relevance in health care. This study aims to translate and culturally adapt a French version of the user Mobile Application Rating Scale (uMARS-F) and to test its overall and internal reliability. Cross-cultural adaptation and translation followed the universalist approach. The uMARS-F was evaluated as part through a cohort study using the French mHealth app "MonSherpa" (Qare). Participants were French-speaking adults with Apple or Android phones, excluding those with difficulty understanding French, prior app use, or physical limitations. They assessed the app using the uMARS-F twice (T1 and T2) 1 week apart. Scores for each section and overall were assessed for normal distribution using the Shapiro-Wilk test and presented as mean (SD), and potential floor or ceiling effects were calculated accordingly. Overall reliability was evaluated using intraclass correlation coefficients and internal reliability using Cronbach α. Concordance between the 3 subscales (objective quality, subjective quality, and perceived impact), 4 sections, and 26 items at T1 and T2 was evaluated using the paired t test (2-tailed) and Pearson correlation. In total, 167 participants assessed the app at both T1 and T2 (100% compliance). Among them, 49.7% (n=83) were female, and 50.3% (n=84) were male, with a mean age of 43 (SD 16) years. The uMARS-F intraclass correlation coefficients were excellent for objective quality (0.959), excellent for subjective quality (0.993), and moderate for perceived impact (0.624). Cronbach α was good for objective quality (0.881), acceptable for subjective quality (0.701), and excellent for perceived impact (0.936). The paired t tests (2-tailed) demonstrated similar scores between the 2 assessments (P>.05), and the Pearson correlation coefficient indicated high consistency in each subscale, section, and item (r>0.76 and P<.001). The reliability and validity of the measures were similar to those found in the original English version as well as in the Spanish, Japanese, Italian, Greek, and Turkish versions that have already been translated and validated. The uMARS-F is a valid tool for end users to assess the quality of mHealth apps in French-speaking countries. The uMARS-F used in combination with the French version of the Mobile Application Rating Scale could enable health care professionals and public health authorities to identify reliable, high-quality, and valid apps for patients and should be part of French health care education programs.

Eating disorder debut cases during COVID-19 lockdown in adults. Exploring differences in treatment outcome contrasting with pre-pandemic onset cases.

Despite an increase in eating disorder (ED) cases during the COVID-19 pandemic, there are limited longitudinal studies exploring treatment outcomes. The aims of the present study were: (1) to compare the clinical features of patients with EDs whose onset was during the COVID-19 lockdown (pandemic cohort) against patients with EDs whose onset was prior to the pandemic (pre-pandemic cohort) and, (2) to compare therapy responses between the cohorts. The sample consisted of 115 adult women with an ED. N=37 new ED cases (pandemic cohort) were diagnosed and included in the study during the pandemic (May 2020-May 2021); these patients did not have any previous history of an ED. We also included N=78 ED cases (pre-pandemic cohort) diagnosed prior to the COVID-19 pandemic breakout (prior to March 2020). All ED subtypes were considered in both groups and several clinical variables were assessed. At baseline, pandemic cohort reported lower levels of impulsivity and higher emotional regulation capacities than the pre-pandemic cohort; however, no differences were found in aspects of general psychopathology and ED related severity. Following treatment, the pandemic cohort showed higher rates of good outcome and lower rates of dropouts than the pre-pandemic cohort. Although both cohorts showed similar ED-related symptoms and general psychopathology scores, treatment outcomes were more favourable in the pandemic cohort.