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This study explores the challenge of differentiating autism spectrum (AS) from non-AS conditions in adolescents and adults, particularly considering the heterogeneity of AS and the limitations of diagnostic tools like the ADOS-2. In response, we advocate a multidimensional approach and highlight lexicogrammatical analysis as a key component to improve diagnostic accuracy. From a corpus of spoken language we developed, interviews and story-recounting texts were extracted for 64 individuals diagnosed with AS and 71 non-AS individuals, all aged 14 and above. Utilizing machine learning techniques, we analyzed the lexicogrammatical choices in both interviews and story-recounting tasks. Our approach led to the formulation of two diagnostic models: the first based on annotated linguistic tags, and the second combining these tags with textual analysis. The combined model demonstrated high diagnostic effectiveness, achieving an accuracy of 80%, precision of 82%, sensitivity of 73%, and specificity of 87%. Notably, our analysis revealed that interview-based texts were more diagnostically effective than story-recounting texts. This underscores the altered social language use in individuals with AS, a crucial aspect in distinguishing AS from non-AS conditions. Our findings demonstrate that lexicogrammatical analysis is a promising addition to traditional AS diagnostic methods. This approach suggests the possibility of using natural language processing to detect distinctive linguistic patterns in AS, aiming to enhance diagnostic accuracy for differentiating AS from non-AS in adolescents and adults.

[This corrects the article DOI: 10.1371/journal.pone.0264204.].

Backgrounds Whether there is a true increase in autism spectrum disorder (ASD) frequency or not remains unclear. Additionally, the rates of co-existing neurodevelopmental disorders (NDD) in a total population sample has not been fully examined before. Therefore, using a total population sample in Japan, we aimed to estimate the prevalence and cumulative incidence of autism spectrum disorder (ASD) annually, to determine whether there is a true increase in ASD prevalence by estimating the cumulative incidence of ASD annually, and to examine the rates of co-existing neurodevelopmental disorders (NDD). Method In this cross-sectional sequential design study, all 5-year-old children in the catchment area underwent the screening annually from the year 2013–2016. Screen-positive children were invited to participate in a comprehensive assessment, including child and parent interview, behavioral observation, and cognitive and motor function testing. All cases were reviewed by a multidisciplinary research team. Results Caregivers of 3954 children returned the screening, among which 559 children underwent the assessment with 87 children receiving an ASD diagnosis. Adjusted ASD prevalence was 3.22% (95% confidence interval (CI) 2.66–3.76%). The male to female ratio of the crude prevalence was 2.2:1. The cumulative incidence of ASD up to 5 years of age for the total study years was 1.31% (95% CI 1.00–1.62%). A generalized linear model revealed no significant linear trends in 5-year cumulative incidence over the study years. Only 11.5% of children had ASD alone; the remaining 88.5% were found to have at least one co-existing NDD. Limitations Modest sample size for a total population study. Conclusions Our findings demonstrate the stability of the 5-year cumulative incidence of ASD, implying no true rise in ASD incident cases over the 4-year study period in the study catchment area. High rates of co-existing NDDs reflect the importance of investigating broad developmental challenges in children with ASD.

[This corrects the article DOI: 10.1371/journal.pone.0264204.].

Since the National Cancer Institute (NCI) alert of concurrent chemoradiotherapy, radiotherapy has been changed from external beam radiotherapy plus brachytherapy to platinum-based concurrent chemoradiotherapy. Therefore, concurrent chemoradiotherapy plus brachytherapy has become a standard treatment for locally advanced cervical cancer. Simultaneously, definitive radiotherapy has been changed gradually from external beam radiotherapy plus low-dose-rate intracavitary brachytherapy to external beam radiotherapy plus high-dose-rate intracavitary brachytherapy. Cervix cancer is uncommon in developed countries; hence, international collaborations have been critical in large-scale clinical trials. The Cervical Cancer Research Network (CCRN), created from the Gynecologic Cancer InterGroup (GCIG), has investigated various concurrent chemotherapy regimens and sequential methods of radiation and chemotherapy. Most recently, many clinical trials of combining immune checkpoint inhibitors with radiotherapy have been ongoing for sequential or concurrent settings. During the last decade, the method of standard radiation therapy has changed from three-dimensional conformal radiation therapy to intensity-modulated radiation therapy for external beam radiotherapy and from two-dimensional to three-dimensional image-guided approaches for brachytherapy. Recent improvements include stereotactic ablative body radiotherapy and MRI-guided linear accelerator (MRI-LINAC) using adaptive radiotherapy. Here we review the current progress of radiation therapy during the last two decades.

Providing postgraduate rural training programs has been recognised as central for successful recruitment and retention of medical workforce. While there have been many documented cases of rural training program development, documented program outcome evaluations are few. This review investigated how postgraduate training and educational programs for rural and remote medicine are evaluated worldwide. Through the use of a systematic review, the study explored three questions: 'What are the outcomes of postgraduate rural and remote training programs worldwide?', 'How are the program evaluations conducted?' and 'What evaluation models and approaches are used in evaluating the effectiveness of these training programs?' A qualitative synthesis was undertaken of evaluations of postgraduate rural training programs published in the English language in medical education journals. The study involved pooling quantitative and mixed-methods research data and findings from qualitative studies, which were aggregated, integrated and interpreted. PubMed, PsycINFO, ERIC and Web of Science databases were searched to identify studies that satisfy the search criteria. Of the 1297 articles identified through the database search, 26 studies were included in the analysis. Most of the evidence from the studies consists of descriptive studies with some longitudinal tracking programs and cohort studies. Nine themes were identified: practice location after training completion; training location and decentralised model; educational aspects; incentives, political contexts and regulations; personal, social and cultural issues; professional development; rural orientation and community engagement; support system; and gender and racial issues. Key outcomes were analysed and cross-validated against the 2020 WHO guideline on health workforce development, attraction, recruitment and retention in rural and remote areas. These studies' most frequent evaluation methods were surveys, followed by interviews, questionnaires and secondary data from existing databases. Methodological characteristics, the relationship between rural background and program outcomes, and implications for decentralised training, telehealth and tele-assessment during the COVID-19 pandemic are discussed. Analysis from the key outcomes suggests evaluation as a strategy to uncover outcomes in postgraduate rural and remote training and medical education. Regardless of the similar outcomes, the program evaluations implemented and the robustness of evidence vary across programs and medical schools. The absence of solid evaluation designs and their alignment to the program objectives will lessen the strengths of evidence. Better quality research and evaluation design, objective settings, qualitative inquiry to uncover the contexts, and developing appropriate indicators and benchmarks for monitoring and evaluating strategies must be considered during program development and implementation.

The central symptom of autism spectrum disorder (ASD) is deficiency in social communication, which is generally viewed as being caused by pragmatic impairment (PI). PI is difficulty in using language appropriately in social situations. Studies have confirmed that PI is the result of neurological, cognitive, linguistic, and sensorimotor dysfunctions involving intricately intertwined factors. To elucidate the whole picture of this impairment, an approach from a multifaceted perspective fusing those factors is necessary. To this end, comprehensive PI mapping is a must, since no comprehensive mapping has yet been developed. The aim of this research is to present a model of annotation scheme development and corpus construction to efficiently visualize and quantify for statistical investigation occurrences of PI, which enables comprehensive mapping of PI in the spoken language of Japanese ASD individuals. We constructed system networks (lexicogrammatical option systems speakers make choices from) in the theoretical framework of Systemic Functional Linguistics, from which we developed an annotation scheme to comprehensively cover PI. Since system network covers all possible lexicogrammatical choices in linguistic interaction, it enables a comprehensive view of where and in what lexicogrammar PI occurs. Based on this annotation scheme, we successfully developed the Corpus of ASD + Typically Developed Spoken Language consisting of texts from 1,187 audiotaped tasks performed by 186 ASD and 106 typically developed subjects, accommodating approximately 1.07 million morphemes. Moreover, we were successful in the automatization of the annotation process by machine learning, accomplishing a 90 percent precision rate. We exemplified the mapping procedure with a focus on the spoken use of negotiating particles. Our model corpus is applicable to any language by incorporating our method of constructing the annotation scheme, and would give impetus to defining PI from a cross-linguistic point of view, which is needed because PI of ASD reflects cross-linguistic differences.

Introduction Insulin improves clinical outcomes in hospitalized patients; however, hypoglycemia hinders discharge transition in patients with insulin‐treated diabetes. Studies on hypoglycemic timeslots, rates, and risk factors during discharge transition are lacking. Materials and Methods Fifteen patients with type 2 diabetes (T2D) receiving multiple daily insulin (MDI) injections participated. Glucose variability metrics and hypoglycemia were monitored using a continuous glucose monitoring system starting a day pre‐discharge through 13 days of discharge transition. Hypoglycemia was analyzed chronobiologically using Cosinor analysis. Anthropometric measurements, C‐peptide, insulin dose, and glucagon were assessed. Results The mean patient age was 52.7 ± 12.6 years; 13/15 were male; body mass index was 28.1 ± 5.9 kg/m2, T2D duration was 8.6 ± 8.8 years, HbA1c was 12.4 ± 2.5%, and total daily insulin dose averaged 36.6 ± 15.1 units and hospitalization lasted 13.1 ± 2.3 days. Time in range decreased post‐discharge. Time below range increased from 7.0% at discharge to 17.6% by the study end (manova, P < 0.001). Hypoglycemic events peaked post‐breakfast, with the highest amplitude (42 points) recorded at 12:00. The highest and lowest numbers of hypoglycemia occurred at 12:00 and 17:30, respectively. However, the highest hypoglycemic timeslot (11:00–12:00) was not significantly associated with clinical and biochemical parameters. Conclusions The chronobiology of hypoglycemia exists during the discharge transition in patients with MDI‐treated T2D. Hypoglycemia frequency and severity peaked pre‐lunch, reached a nadir at 17:30, and exaggerated post‐discharge, emphasizing the need for pre‐breakfast insulin dose reductions on the discharge day. The frequency and severity of hypoglycemia peak before lunch and its nadir is 17:30 PM and increases through the post‐discharge days.

The aims of this study were to identify sensory processing profiles specific to preschoolers with DCD in a community sample and examine the association of sensory processing problems with motor coordination difficulties in these children. Sixty-three 5-year-old children with DCD and without other neurodevelopmental disorders and 106 age-matched typically developing children participated in this study. Sensory processing problems were assessed using the Sensory Profile. Our results demonstrated problems in wide sensory processing patterns (low registration, sensitivity and avoiding) and areas (auditory, vestibular, touch and oral) in children with DCD compared with typically developing children. Additionally, the association of problems in sensory processing patterns (sensitivity and avoiding) and areas (touch and auditory) with motor coordination difficulties were identified in children with DCD alone. Our findings indicate that sensory processing abnormalities may contribute to the pathophysiology of DCD, suggesting the importance of assessing sensory processing functions in children with DCD.

ObjectivesRural–urban healthcare disparities exist globally. Various countries have used a rurality index for evaluating the disparities. Although Japan has many remote islands and rural areas, no rurality index exists. This study aimed to develop and validate a Rurality Index for Japan (RIJ) for healthcare research.DesignWe employed a modified Delphi method to determine the factors of the RIJ and assessed the validity. The study developed an Expert Panel including healthcare professionals and a patient who had expertise in rural healthcare.SettingThe panel members were recruited from across Japan including remote islands, mountain areas and heavy snow areas. The panel recruited survey participants whom the panel considered to have expertise.ParticipantsThe initial survey recruited 100 people, including rural healthcare providers, local government staff and residents.Primary outcome measuresFactors to include in the RIJ were identified by the Expert Panel and survey participants. We also conducted an exploratory factor analysis on the selected factors to determine the factor structure. Convergent validity was examined by calculating the correlation between the index for physician distribution and the RIJ. Criterion-related validity was assessed by calculating the correlation with average life expectancy.ResultsThe response rate of the final survey round was 84.8%. From the Delphi surveys, four factors were selected for the RIJ: population density, direct distance to the nearest hospital, remote islands and whether weather influences access to the nearest hospital. We employed the factor loadings as the weight of each factor. The average RIJ of every zip code was 50.5. The correlation coefficient with the index for physician distribution was −0.45 (p<0.001), and the correlation coefficients with the life expectancies of men and women were −0.35 (p<0.001) and −0.12 (p<0.001), respectively.ConclusionThis study developed the RIJ using a modified Delphi method. The index showed good validity.