bluuebunny/crossref_metadata_2025_split huggingface dataset:
Variational Theory and Algorithms for a Class of Asymptotically Approachable Nonconvex Problems
Authors: Li Hanyang , Cui Ying 
Published: January 2025

We investigate a class of composite nonconvex functions, where the outer function is the sum of univariate extended-real-valued convex functions and the inner function is the limit of difference-of-convex functions. A notable feature of this class is that the inner function may fail to be locally Lipschitz continuous. It covers a range of important, yet challenging, applications, including inverse optimal value optimization and problems under value-at-risk constraints. We propose an asymptotic decomposition of the composite function that guarantees epi-convergence to the original function, leading to necessary optimality conditions for the corresponding minimization problem. The proposed decomposition also enables us to design a numerical algorithm such that any accumulation point of the generated sequence, if it exists, satisfies the newly introduced optimality conditions. These results expand on the study of so-called amenable functions introduced by Poliquin and Rockafellar in 1992, which are compositions of convex functions with smooth maps, and the prox-linear methods for their minimization. To demonstrate that our algorithmic framework is practically implementable, we further present verifiable termination criteria and preliminary numerical results. Funding: Financial support from the National Science Foundation Division of Computing and Communication Foundations [Grant CCF-2416172] and Division of Mathematical Sciences [Grant DMS-2416250] and the National Cancer Institute, National Institutes of Health [Grant 1R01CA287413-01] is gratefully acknowledged.
A mixed methods study investigating factors affecting adherence to Plasmodium vivax malaria primaquine radical cure regimens among migrants along the Myanmar-Thailand border
Authors: Ansari April T. , Aung Ko Ko , Win Htun Htun , Beau Candy , Nu Be , Soe Nay Lin , Htoo Klay , San Thida , Wah Tha Gay , Keereevijit Arunrot , Phyo Aung Pyae , Chotivanich Kesinee , White Nicholas J. , Nosten François , Hashmi Ahmar H. , Chu Cindy S. 
Published: January 2025

Background
The countries within the Greater Mekong Region of Southeast Asia have pledged to eliminate malaria by 2030. Elimination of Plasmodium vivax malaria is challenging as it requires radical cure to prevent relapse. Understanding and facilitating adherence to primaquine radical cure regimens is necessary for malaria elimination.

Methods
A convergent parallel mixed methods study was conducted to investigate the barriers to and facilitators for completing primaquine treatment of P. vivax infection among mobile migrant communities on the Myanmar-Thailand border. Quantative data were derived from routine malaria consultations. Qualitative data, informed by the social cognitive theory and health belief model, were collected through in-depth interviews with patients and focus group discussions with local health providers and community leaders.

Results
Of 729 adult patients with primaquine treatment outcomes, 45% did not complete the follow-up of 28 days and were assumed to be non-adherent to primaquine treatment. Patients of Karen ethnicity (OR 1.7, 95% CI 1.2–2.3; p = 0.001) or having a previous episode of malaria from any species (OR 1.6, 95% CI 1.1–2.3; p = 0.007) were more likely to report completing the 14-day primaquine radical cure regimen. Five focus group discussions with front-line healthcare workers and community members and 16 in-depth interviews with patients who were prescribed P. vivax radical cure were conducted. Key themes related to the social cognitive theory included behavioral factors where work outweighed the choice to complete treatment; environmental factors where access to care determined primaquine treatment completion; and cognitive factors having a positive but limited influence on treatment completion. According to the health belief model, prioritizaton of work reduced seeking diagnosis and completing treatment, and often outweighed facilitating factors such as malaria literacy, health education, and social norms; and affected the perceived susceptibility and severity of P. vivax infections.

Discussion
Work and productivity were identified as primary behavioral factors affecting adherence to primaquine radical cure and follow up in a migrant population. Community support and cultural cues may overcome these barriers. Understanding the rationale of patient adherence to primaquine may help guide programming for P. vivax elimination among migrant populations in resource-constrained settings.
Psychological distress in adolescence and later economic and health outcomes in the United States population: A retrospective and modeling study
Authors: Counts Nathaniel Z. , Kreif Noemi , Creedon Timothy B. , Bloom David E. 
Published: January 2025

Background
Federal policy impact analyses in the United States do not incorporate the potential economic benefits of adolescent mental health policies. Understanding the extent to which economic benefits may offset policy costs would support more effective policymaking. This study estimates the relationship between adolescent psychological distress and later health and economic outcomes and uses these estimates to determine the potential economic effects of a hypothetical policy.

Methods and findings
This analysis estimated the relationship between psychological distress in those aged 15 to 17 years in 2000 and economic and health outcomes approximately 10 years later, accounting for an array of explanatory variables using machine learning–enabled methods. The cohort was from the National Longitudinal Study of Youth 1997 and nationally representative of those aged 12 to 18 years in 1997. The cohort included 3,343 individuals under age 18 years in round 4 who completed the Mental Health Inventory-5 (MHI-5). Round 1 captured 50 explanatory variables that covered domains of potential confounders, including basic demographics, neighborhood environment, family resources, family processes, physical health, school quality, and academic skills. The exposure included a binary variable of clinically significant psychological distress (MHI-5 score of less than or equal to 3) and a categorical variable of symptom severity on the MHI-5. Outcomes covered domains of employment, income, total assets at age 30 years, education, and health approximately 10 years later.
Forty-seven percent of the cohort were black and Hispanic, and 4.4% had past-month clinically significant psychological distress. Past-month clinically significant psychological distress in adolescence led to a 6-percentage-point (95% confidence interval [CI] [−0.08, −0.03]) reduction in past-year labor force participation 10 years later and $5,658 (95% CI [−6,772, −4,545]) USD fewer past-year wages earned. We used these results to model the labor market impacts of a hypothetical policy that expanded access to mental health preventive care and reached 10% of youth who would have otherwise developed clinically significant psychological distress. We found that the hypothetical policy could lead to $52 (95% credible interval [51,54]) billion USD in federal budget benefits over 10 years from labor supply impacts alone. This study faced limitations, including potential unmeasured confounding, missing data, and challenges to generalizability.

Conclusions
Our findings showed the impacts of adolescent mental health policies on the federal budget and found potentially large effects on the economy if policies achieve population-level change.
Childhood appendectomy and subsequent psychiatric illness
Authors: Arana Håkanson Cecilia , Stiger Fredrik , Brusselaers Nele , Engstrand Lilja Helene 
Published: January 2025

Aim
The appendix is considered a reservoir for the gut microbiome to restore the gut microbiota after disruptions. Therefore, removal of the appendix because of appendicitis, might result in long-term disruption of the microbiome with related health consequences. The aims of the study were to explore if there is an association between childhood appendectomy, the risk of psychiatric illness and healthcare consumption later in life.

Methods
Individuals (N = 752) who underwent childhood appendectomy in a tertiary paediatric surgical department in Sweden were included, individually-matched to 5 non-exposed individuals (N = 3760). Data on psychiatric diagnoses, healthcare visits, and use of psychiatric drugs were collected from population-based registers. Stratified Cox and Poisson regression analyses were used, adjusted for antibiotics, proton pump inhibitors and non-steroidal anti-inflammatory drugs.

Results
Median age at appendectomy was 11 (2–16) years and median follow-up time 15.5 (6–21) years. The risk of psychiatric illness in general (HR 1.19; 95% CI 1.04–1.37; p-value 0.013) and affective disorders (HR 1.20, 95% CI 1.01–1.42; p-value 0.038) was higher among those with appendectomy. Out- (IRR 1.20; 95% CI 1.18–1.23; p-value <0.001) and in-patient visits (IRR 1.19, 95% CI 1.10–1.28; p-value <0.001) were more common among those with appendectomy.

Conclusion
Childhood appendectomy was associated with an increased risk of psychiatric illness and healthcare consumption.
Sexual and reproductive health needs of women with severe mental illness in low- and middle-income countries: A scoping review
Authors: Sisodia Shilpa , Hammond Zara , Leonardi-Bee Jo , Hanlon Charlotte , Asher Laura 
Published: January 2025

Background
This scoping review aimed to understand the extent and type of evidence in relation to sexual and reproductive health needs of women with severe mental illness (SMI) in low- and middle-income countries (LMIC) and to summarise those needs.

Methods
Inclusion criteria were 1) focus on sexual and reproductive health needs 2) women or girls with SMI, professionals, caregivers of women with SMI and community members 3) study set in a LMIC 4) peer reviewed literature (no restriction on study date or design). Studies were identified from comprehensive searches of Medline, EMBASE, CINAHL and PsycINFO (to July 2023).

Results
The review included 100 papers. Most studies were cross-sectional and set in hospital outpatient departments. Only 20 of 140 LMIC countries were included in this review and only 15 studies were set-in low-income countries (LIC). Included studies often had multiple focus areas and were grouped by frequency of topic into categories of HIV (prevalence, risk behaviour and knowledge), other sexually transmitted infections (STIs), sexual function, contraception use and family planning, sexual violence, fertility, pregnancy and postpartum. Included studies indicated women with SMI have worse outcomes and worse sexual and reproductive health compared to both women without SMI and men with SMI. Women with SMI were shown to have higher rates of HIV and low levels of contraception knowledge and use, with little advice offered by professionals.

Conclusions
This review highlights the need for a greater diversity of study methodology, robustness of ethical and consensual reporting when researching vulnerable populations and for further research on interventions and models of care aimed at addressing stigma, discrimination and improving the sexual and reproductive health of women with SMI. Future research should better represent the breadth of LMIC, investigate cultural adaptability of interventions and consider sexual health needs across the life course.
Development and validation of an interpretable machine learning model for predicting left atrial thrombus or spontaneous echo contrast in non-valvular atrial fibrillation patients
Authors: Huang Chaoqun , Shu Shangzhi , Zhou Miaomiao , Sun Zhenming , Li Shuyan 
Published: January 2025

Purpose
Left atrial thrombus or spontaneous echo contrast (LAT/SEC) are widely recognized as significant contributors to cardiogenic embolism in non-valvular atrial fibrillation (NVAF). This study aimed to construct and validate an interpretable predictive model of LAT/SEC risk in NVAF patients using machine learning (ML) methods.

Methods
Electronic medical records (EMR) data of consecutive NVAF patients scheduled for catheter ablation at the First Hospital of Jilin University from October 1, 2022, to February 1, 2024, were analyzed. A retrospective study of 1,222 NVAF patients was conducted. Nine ML algorithms combined with demographic, clinical, and laboratory data were applied to develop prediction models for LAT/SEC in NVAF patients. Feature selection was performed using the least absolute shrinkage and selection operator (LASSO) and multivariate logistic regression. Multiple ML classification models were integrated to identify the optimal model, and Shapley Additive exPlanations (SHAP) interpretation was utilized for personalized risk assessment. Diagnostic performances of the optimal model and the CHA2DS2-VASc scoring system for predicting LAT/SEC risk in NVAF were compared.

Results
Among 1,078 patients included, the incidence of LAT/SEC was 10.02%. Six independent predictors, including age, non-paroxysmal AF, diabetes, ischemic stroke or thromboembolism (IS/TE), hyperuricemia, and left atrial diameter (LAD), were identified as the most valuable features. The logistic classification model exhibited the best performance with an area under the receiver operating characteristic curve (AUC) of 0.850, accuracy of 0.812, sensitivity of 0.818, and specificity of 0.780 in the test set. SHAP analysis revealed the contribution of explanatory variables to the model and their relationship with LAT/SEC occurrence. The logistic regression model significantly outperformed the CHA2DS2-VASc scoring system, with AUCs of 0.831 and 0.650, respectively (Z = 7.175, P < 0.001).

Conclusions
ML proves to be a reliable tool for predicting LAT/SEC risk in NVAF patients. The constructed logistic regression model, along with SHAP interpretation, may serve as a clinically useful tool for identifying high-risk NVAF patients. This enables targeted diagnostic evaluations and the development of personalized treatment strategies based on the findings.
Empirically validating a computational model of automatic behavior shaping
Authors: Berardi Vincent , Lan Tian , Guirguis Ariane , Maoz Uri 
Published: January 2025

Background
Mobile sensing technology allows automated behavior shaping routines to be incorporated into health behavior interventions and other settings. In previous work, a computational model was built to investigate how to best arrange automatic behavior shaping procedures, but the degree to which this model reflects actual human behavior is not known.

Purpose
To translate a previously developed computational model of automatic behavior shaping into an experimental setting.

Methods
Participants (n = 54) operated a computer mouse and attempted to locate a hidden, randomly-placed target circle on a blank computer screen and clicks within some threshold distance of the target circle were reinforced by a pleasant auditory tone. As the trial progressed, the threshold distance narrowed according to a shaping function until eventually only clicks within the target circle were reinforced. Accumulated Area Under Trajectory Curves and Time Until 10 Consecutive Target Clicks were used to quantify the probability of the target behavior. Linear mixed effects models were used to assess differential outcomes for concave up, concave down, and linear shaping functions.

Results
In congruence with the computational model, concave-up functions most effectively shaped participants’ behavior, with linear and then concave-down shaping functions producing the next best outcomes.

Conclusion
Concave-up shaping routines most effectively generated target behavior, which should be confirmed in health behavior trials. The automatic shaping routines that this study helps develop can be applied in a number of domains, including exercise intensity and duration, tobacco/cannabis smoking, caloric intake, and screen time.
Experienced cognitive load in the emergency department. A prospective study
Authors: Appelboom Yael , Groenen Yvonne , Notten Dirk , De Bruin Anique , Buijs Jacqueline , Haak Harm R. , Broggreve Hella F. , Lambriks Lars , Stassen Patricia M. 
Published: January 2025

Background and importance
The emergency department (ED) is a hectic place, where many critically ill patients are treated. For residents working in the ED, this environment may be demanding.

Objectives
The aim of this study was to investigate the [1] cognitive load experienced by residents working in the ED, and [2] differences in cognitive load during the day.

Methods
In this multicentre, prospective study in three EDs in the Netherlands, the experienced cognitive load was graded by residents on three scales, agreed upon during Delphi meetings: the complexity (low-high: 1–3), mental effort (low-high: 1–9) and comfortability scale (low-high: 0–100%). We applied the scores per decision, 1-hour and 2-hour intervals, patient and shift.

Main results
We observed 14 residents and analysed 74 1-hour and 45 2-hour intervals, 79 patients, 24 shifts and 592 separate decisions. The experienced cognitive load per decision was low. In contrast, the cognitive load was higher per 2-hour interval (mental effort: median 4.0 (IQR 4.0) and comfortability 80% (IQR 20)) and per shift (mental effort: median 5.5 (IQR 4.0) and comfortability 80% (IQR 20). Complexity was low for all measurements. Mental effort rose from 17h onwards higher values, whereas a decrease in comfortability was seen from 21h onwards.

Conclusion
From 17h onwards, residents working in the ED experienced rather high mental effort and reported feeling not optimally comfortable when making decisions. The mental effort was highest between 21-23h. This was found when cognitive load was measured per 2-hour interval and per shift, but not per decision. This study may provide an insights to optimise cognitive load by reorganisation of the ED.
CooccurrenceAffinity: An R package for computing a novel metric of affinity in co-occurrence data that corrects for pervasive errors in traditional indices
Authors: Mainali Kumar P. , Slud Eric 
Published: January 2025

1. Analysis of co-occurrence data with traditional indices has led to many problems such as sensitivity of the indices to prevalence and the same value representing either a strong positive or strong negative association across different datasets. In our recent study (Mainali et al 2022), we revealed the source of the problems that make the traditional indices fundamentally flawed and unreliable–namely that the indices in common use have no target of estimation quantifying degree of association in the non-null case–and we further developed a novel parameter of association, alpha, with complete formulation of the null distribution for estimating the mechanism of affinity. We also developed the maximum likelihood estimate (MLE) of alpha in our previous study.
2. Here, we introduce the CooccurrenceAffinity R package that computes the MLE for alpha. We provide functions to perform the analysis based on a 2×2 contingency table of occurrence/co-occurrence counts as well as a m×n presence-absence matrix (e.g., species by site matrix). The flexibility of the function allows a user to compute the alpha MLE for entity pairs on matrix columns based on presence-absence states recorded in the matrix rows, or for entity pairs on matrix rows based on presence-absence recorded in columns. We also provide functions for plotting the computed indices.
3. As novel components of this software paper not reported in the original study, we present theoretical discussion of a median interval and of four types of confidence intervals. We further develop functions (a) to compute those intervals, (b) to evaluate their true coverage probability of enclosing the population parameter, and (c) to generate figures.
4. CooccurrenceAffinity is a practical and efficient R package with user-friendly functions for end-to-end analysis and plotting of co-occurrence data in various formats, making it possible to compute the recently developed metric of alpha MLE as well as its median and confidence intervals introduced in this paper. The package supplements its main output of the novel metric of association with the three most common traditional indices of association in co-occurrence data: Jaccard, Sørensen–Dice, and Simpson.
Perceived stress across population segments characterized by differing stressor profiles—A latent class analysis
Authors: Larsen Finn Breinholt , Lasgaard Mathias , Willert Morten Vejs , Sørensen Jes Bak 
Published: January 2025

Objective
We aimed to 1) identify distinct segments within the general population characterized by various combinations of stressors (stressor profiles) and to 2) examine the socio-demographic composition of these segments and their associations with perceived stress levels.

Methods
Segmentation was carried out by latent class analysis of nine self-reported stressors in a representative sample of Danish adults (N = 32,417) aged 16+ years. Perceived stress level was measured by the Perceived Stress Scale (PSS).

Results
Seven classes were identified: Class 1 was labeled Low Stressor Burden (64% of the population) and the remaining six classes, which had different stressor combinations, were labeled: 2) Burdened by Financial, Work, and Housing Stressors (10%); 3) Burdened by Disease and Death among Close Relatives (9%); 4) Burdened by Poor Social Support and Strained Relationships (8%); 5) Burdened by Own Disease (6%); 6) Complex Stressor Burden Involving Financial, Work, and Housing Stressors (2%); and 7) Complex Stressor Burden Involving Own Disease and Disease and Death among Close Relatives (2%). Being female notably increased the likelihood of belonging to Classes 2, 3, 5, and 7. Higher age increased the likelihood of belonging to Class 3. Low educational attainment increased the likelihood of belonging to Classes 5 and 6. A significant difference was observed in perceived stress levels between the seven latent classes. Average PSS varied from 9.0 in Class 1 to 24.2 in Class 7 and 25.0 in Class 6.

Conclusion
Latent class analysis allowed us to identify seven population segments with various stressor combinations. Six of the segments had elevated perceived stress levels but differed in terms of socioeconomic composition and stressor combinations. These insights may inform a strategy aimed at improving mental health in the general population by targeting efforts to particular population segments, notably segments experiencing challenging life situations.