Out-of-hospital cardiac arrests (OOHCAs) occur at sporting events. In the United Kingdom (UK), the outcomes remain unclear. This study aimed to perform a systematic literature review to establish the outcomes of OOHCA associated with sports in the UK, alongside a literature search of online media. PubMed, ISI Web of Knowledge, and Embase were searched from inception to March 2025 (PROSPERO CRD42024557120). Data were extracted relating to demographics, sports, medical care received, and outcomes. A quality review was undertaken with the Newcastle-Ottawa scale. In addition, an online media search of Google News and BBC News between June 2021 and October 2025 was performed, with similar data extracted. From 10,026 studies, 12 studies were included, totaling 578 patients. Most were male (91%), with a mean age of 43.2 years. Limited data were presented regarding the actual OOHCA event, for example, presenting rhythm. Twelve patients were detailed as having a full neurological recovery. Postmortem data suggested that cardiomyopathy and sudden arrhythmic death syndrome were common causes. In addition, 82 OOHCAs (95% male) were identified from the media search, with 29% younger than 40 years and an estimated survival rate of 62%. The exact outcomes of OOHCA associated with sports in the UK are difficult to establish, with the incidence potentially under-reported. Survival rates do seem to be higher than the general population, based mainly on online media evidence. A prospective data collection tool would allow a greater understanding of the outcomes, incidence, and contributing factors for a UK population, to help plan prehospital medical input.
Health Play Specialists (HPSs) play an important role in supporting children and young people's emotional wellbeing in healthcare, yet their contribution remains poorly understood and is inconsistently recognised within paediatric multidisciplinary teams (MDTs). This study examined how HPSs and MDT members understand a HPS's role and work. An online qualitative survey, distributed via professional networks and social media across the UK, was completed by 101 professionals (56 HPSs and 45 MDT members). Data were analysed using inductive qualitative content analysis. Participants shared recognition of the HPS's impact, particularly through play, emotional support, and distraction but differed in their appreciation of the role's scope and complexity. Four key themes were identified: role understanding, impacts, enabling factors and barriers to the HPS role. Participants identified a need for greater MDT integration and standardised education on the HPS's role across health professional training. Whilst the findings demonstrate an understanding of a HPS's role and work, there is a need for increased recognition of wider aspects of their role beyond play and distraction to procedural preparation, therapeutic and normalising play, post-procedural support, advocating for children and families, and delivering education to other members of the MDT.
Color difference detection remains a critical challenge in textile manufacturing, where traditional visual inspection and offline measurement methods suffer from subjectivity, low efficiency, and delayed feedback. This study emphasizes engineering integration for online industrial fabric inspection rather than proposing a single new color-difference algorithm. The proposed system integrates a custom-designed optical acquisition platform with a lightweight color analysis pipeline, including bilateral filtering for noise suppression, K-means clustering for representative color extraction, RGB-to-CIELab color space conversion, and perceptually weighted [Formula: see text] computation. The system was deployed on an actual textile production line and evaluated using ten fabric rolls with different colors and materials. Experimental results show roll-level agreement with manual inspection in the tested samples and indicate the feasibility of continuous monitoring of chromatic variations along the fabric length. The proposed system provides a practical engineering solution for automated textile color quality control and may support production-line decision making while reducing dependence on subjective visual inspection in industrial environments.
The study of human behaviour has shifted in the past 15 years. It increasingly relies on opt-in non-probability online data sources. Here we offer an analysis of nine such sources (N = 13,053), aiming to inform researchers conducting experiments or correlational studies. We assess response validity (attentiveness, effort, honesty, speeding and attrition), the extent to which samples represent the underlying population (demographics, attitude representativeness and experimental treatment effects) and professionalism (number and frequency of studies taken and modality of device on which studies are taken). We document substantial variation across samples on each dimension. Samples using demographic quotas display relatively higher amounts of representativeness across multiple indicators (beyond demographics) but often exhibit less response validity. However, inclusion of two attention checks early in a survey can enhance response validity without negatively impacting representativeness. We offer guidance for choosing opt-in samples, depending on the purpose of the research and resource constraints.
Significant social, technological and medical changes highlight a need for timely and representative sexual and reproductive health surveys, while also posing challenges to their design. This paper describes methods of the Third Australian Study of Health and Relationships (ASHR3). From March 2023 to April 2024, data were collected from people aged 16-69 years via an anonymous survey of holistic sexual and reproductive health. ASHR3 collected data via random selection of mobile phone numbers for an interviewer-administered survey and via an online probability panel for a self-administered digital survey. Potential differences between the two modes of sampling and data collection were investigated. Sample-specific design weights were applied and calibrated to the 2021 Australian Census regarding gender, country of birth, education, religion and area of residence. The final sample was 12,833 people: 5693 men (48.63% weighted proportion), 6984 women (49.98%), and 156 non-binary people (1.39%) from every state and territory. Telephone interviews were conducted with 7226 participants and online surveys with 5607. The survey cooperation and response rates for the telephone sample were 86.11% and 3.54%, respectively, whereas the online completion rate was 98.73%. Few participants said the survey made them feel embarrassed (10.96%) and most said they were very honest in their responses (96.54%). Comparisons with the most recent Census found the weighted ASHR3 sample was generally representative of the general population of Australia, with a mean of 1.22% difference across key sociodemographic characteristics (s.d. 2.37). There were no differences observed in sociodemographic characteristics and other responses between the telephone and online samples. ASHR3 compiled rich, robust, and representative data on sexual and reproductive health from a large national sample. The inclusion of an online probability panel complemented the more traditional telephone-based methods. With more than 20 years of data, ASHR is an important resource for monitoring trends in sexual and reproductive health.
The use of generative artificial intelligence (AI) by pharmaceutical companies and other organizations for preparing patient-facing documents reporting results of clinical research is becoming more common. This raises concerns about whether the accuracy and quality of these documents could be affected, as well as the potential impact on patient perceptions and trust. Accurate and trustworthy information is critical to health care decision-making. Little is known about patient perceptions of AI-generated content. This study aimed to better understand patient experience and familiarity with AI, their resulting confidence in the abilities of AI, and their trust in the use of AI by research organizations to generate clinical research documents. An online survey was conducted using an online health care panel of patients in Europe and the United States to assess familiarity with AI, trust in organizations reporting on research, and trust in the use of AI to prepare clinical research documents. The survey also asked directly about the importance of human involvement and of transparency in disclosing AI use. A total of 1010 respondents completed the online survey. About half of respondents were from the United States and half from Europe. Survey results showed that 63.6% (642/1010) of respondents had used AI before with 74.9% (756/1010) reporting being "Somewhat" or "Very" familiar with AI. AI use was influenced by country, gender, education level, race/ethnicity, and clinical trial experience. Higher familiarity with AI was observed among younger participants. Respondents were generally confident in the capabilities of AI, as more than half believed AI use would reduce grammar and data errors. Trust in clinical trial documents generally increased with greater human oversight, as trust was lowest for documents created by AI with no human involvement (12.3% "A lot" of trust, 124/1010) and highest for documents created by humans without AI (39.1% "A lot" of trust, 395/1010). 95.0% (959/1010) of respondents considered human involvement in clinical trial document review as "Very important" or "Somewhat important." The majority (62.4%, 630/1010) of respondents felt it was "Very important" for pharmaceutical companies and academic institutions to be transparent about their use of AI in public-facing documents. Transparency was considered more important among respondents in the United States and the United Kingdom compared to those in the European Union. The survey results reveal high familiarity with, and confidence in the capabilities of, AI. Despite this confidence, respondents emphasized the need for human involvement in the creation of clinical trial documents and the importance of disclosing AI usage, underscoring the critical role of human oversight in maintaining patient trust. Transparent integration of AI with deliberate human involvement remains essential to ensure trust in patient-facing documents.
Despite laws for non-discriminatory medical care, people with disabilities often perceive their primary care as insufficient. They report barriers to access and uncertainties among medical staff. The aim of this study was to examine the primary care situation for people with disabilities in Munich. In this cross-sectional study, between August and October 2024, people with disabilities in Munich were surveyed about their primary care experience using a questionnaire. No exclusion criteria were applied. The survey was conducted both online and in written form, using plain- and easy-to-read language. Data were analyzed using descriptive statistics, and bivariate analyses were conducted to examine associations. Logistic regression analysis was used to calculate predictors for the likelihood of having or having had difficulties in finding a general practitioner. A total of 306 people participated in the survey; 95% (n=291) reported having a GP, and over 80% were satisfied with medical (n=253) and practice staff (n=252). Nevertheless, 39% (n=111) reported difficulties in finding a GP, and 33% (n=91) had been refused by a practice at least once. Differences in care were observed regarding the utilization of appointments, the need to visit a GP due to disability, difficulties in finding a medical practice, freedom of choice of physician, and acceptance into a GP practice, depending on gender, living situation, and type of disability, as well as with regard to the need for home visits. In addition, multivariate analyses showed that people with disabilities had a significantly higher risk of experiencing difficulties in finding a GP if they had previously been refused by a practice, were restricted during medical visits, or needed home visits. The study shows that, from the perspective of people with disabilities, primary care was rated as satisfactory; however, access problems persist due to structural, communication and social barriers. The results can help provide stakeholders with practical arguments to improve the care situation. Trotz gesetzlicher Vorgaben zur diskriminierungsfreien ärztlichen Versorgung empfinden Menschen mit Behinderungen (MmB) ihre hausärztliche Versorgung häufig als unzureichend. Sie berichten von Barrieren beim Zugang zur Versorgung und Unsicherheiten des medizinischen Personals. Während Kinder in sozialpädiatrischen Zentren betreut werden, gibt es für Erwachsene mit Behinderungen keine Alternativen. Zwar etablieren sich Medizinische Zentren für Erwachsene mit Behinderungen, allerdings sind diese nicht dafür gedacht, Mängel in der ambulanten Versorgung von MmB abzufangen. Ziel dieser Studie war es, die hausärztliche Versorgungssituation von MmB aus Sicht der MmB in München zu untersuchen.In einer Querschnittstudie wurden MmB ohne Ausschlusskriterien in München mittels eines Fragebogens von August bis Oktober 2024 zu ihrer hausärztlichen Versorgung befragt. Die Befragung konnte in Alltags- und leichter Sprache online und schriftlich durchgeführt werden. Mit Hilfe deskriptiver Statistik und bivariater Analysen wurden Häufigkeiten und Zusammenhänge untersucht. Durch eine logistische Regressionsanalyse wurden Prädiktoren für die Wahrscheinlichkeit, Schwierigkeiten bei der Suche nach einem Hausarzt zu haben oder gehabt zu haben berechnet.An der Befragung nahmen 306 Personen teil. Davon gaben 95% (n=291) an, eine Hausärztin/ einen Hausarzt zu haben und über 80% waren mit ärztlichem (n=253) bzw. Praxispersonal (n=252) zufrieden. Dennoch berichteten 39% (n=111) von Schwierigkeiten bei der Ärztin-/Arztsuche und 33% (n=91) wurden schon einmal von einer Praxis abgewiesen. Es zeigten sich Unterschiede in der Versorgung hinsichtlich der Inanspruchnahme von Terminen, der Notwendigkeit des Besuches des Hausarztes/ der Hausärztin aufgrund der Beeinträchtigung, Schwierigkeiten bei der Suche nach einer ärztlichen Praxis sowie bei der freien Ärztin/Arztwahl und der Aufnahme in eine hausärztliche Praxis, in Abhängigkeit von Geschlecht, Wohnform und Art der Beeinträchtigung sowie bei der Notwendigkeit von Hausbesuchen. Zudem ergaben die multivariaten Analysen, dass MmB ein signifikant höheres Risiko für Schwierigkeiten bei der Suche nach einer Hausärztin/ einem Hausarzt haben, wenn sie schon einmal von einer Praxis abgewiesen wurden, beim Arztbesuch eingeschränkt sind oder Hausbesuche benötigen.Die Studie zeigt, dass die hausärztliche Versorgung aus Sicht der MmB als zufriedenstellend eingestuft wurde, jedoch Zugangsprobleme aufgrund baulicher, sprachlicher sowie sozialer Barrieren bestehen. Sie bietet erste Ergebnisse und Hinweise auf daraus entstehende Herausforderungen bei Hausarztbesuchen. Die Ergebnisse können dazu beitragen, Akteur*innen praxisnahe Argumente für eine Verbesserung der Versorgungssituation zu liefern.
Channelopathies represent a group of diseases often caused by missense variants in ion channels affecting the functioning of tissues like the nervous system, heart, and muscle. The gold standard for functionally characterizing a variant is to measure the electrophysiological changes in channel properties using cell-based heterologous expression systems. As this method is time-consuming and generally unavailable, clinical practice often relies on in-silico models to predict the functional consequences of ion channel variants. We constructed a Missense ION (MissION) channel variant classifier based on a protein language model and trained it on 1996 gain- or loss-of-function variants, the largest set collected to date, in order to predict the functional effects of variants across a broad range of ion channels. MissION achieves a significant increase in predictive performance (Area Under the Receiver Operating Characteristic Curve (ROC-AUC): 0.918, compared to 0.884 and 0.779 for the current leading models). Moreover, the model generalizes well to ion channel genes for which little or no electrophysiological recordings are available. MissION provides functional predictions for over 600,000 ion channel variants, made available through an online interface that allows variant interpretation for a wide range of channelopathies.
The uniformity of tobacco blend mixing is a critical factor influencing cigarette quality. However, due to the dynamic nature of the blending process and the complex characteristics of the materials involved, current detection methods primarily rely on manual sampling or offline analysis. These approaches suffer from poor real-time performance and lack representativeness. To address these limitations, this study explores methods for generating tobacco-leaf image data and proposes a real-time semantic segmentation technique for tobacco-leaf images based on U-Net. First, a small set of tobacco leaf images was acquired to establish a raw dataset of composite tobacco leaf images. Three generative adversarial networks-CycleGAN, WGAN, and DCGAN-were employed to generate tobacco leaf images from this dataset. Based on image quality, the optimal image generation network was selected. Experimental results showed that CycleGAN produced the highest-quality tobacco leaf images. Next, the Squeeze Excitation Attention (SE) mechanism was integrated into the VGG16 backbone network. This enhancement improved the network's ability to extract features from various types of tobacco leaf images while suppressing interference from irrelevant pixels. The results demonstrated that, compared to mainstream models such as Segformer, DeepLabV3, PSPNet, and the unmodified U-Net, the proposed SE-UNet model achieved superior segmentation accuracy, excellent real-time performance, and overall optimal segmentation capabilities. Compared to Segformer, DeepLabV3, PSPNet, and the original model, the MIOU in the evaluation metrics improved by 17.46, 8.7, 13.39, and 2.77 percentage points, respectively. Finally, the pixel areas of different tobacco leaf types were extracted and calculated from the segmented images to determine the proportion of each leaf type within the images. This research offers a novel approach for practical tobacco production and quality inspection, while also providing a new pathway for real-time online detection of other agricultural products.
Aims The rise of social media has facilitated new forms of orthodontic marketing with legitimate concerns among laypeople and professionals concerning the veracity of publicly available information. We aimed to understand orthodontists' perceptions of social media marketing of orthodonticsMethods Qualitative study using one-to-one interviews on online video-conferencing software. A sampling matrix was used to obtain representative views from specialist orthodontists in the UK. Qualitative data were collected using a topic guide, until saturation was reached, and analysed using an interpretive approach with thematic analysis.Results Twelve participants were interviewed with three emergent themes and 12 sub-themes. Key findings included the observation that an uneven playing field existed within orthodontics on social media. Unsafe expectations and misinformation were cited, and a need to standardise social media marketing in orthodontics was highlighted. Pivotal factors influencing orthodontists' perceptions and experiences of social media marketing in orthodontics were identified with highly pervasive misinformation and potentially harmful content, and a need for greater orthodontic representation, guidance and self-regulation being cited.Conclusions Orthodontists and patients require awareness of pitfalls of social media marketing to prevent risks of harm and inappropriate treatment.
Frozen shoulder, also known as adhesive capsulitis, is a common and disabling condition that causes shoulder pain and progressive stiffness. Patient information leaflets (PILs) are produced by UK National Health Service (NHS) Trusts to help patients understand frozen shoulder and treatment options. However, the content and consistency of these PILs and their alignment with national clinical guidance are currently unclear. This study aimed to identify, analyse and describe the non-surgical management recommendations presented in publicly available NHS Trust PILs for frozen shoulder and to assess their alignment with the National Institute for Health and Care Excellence (NICE) Clinical Knowledge Summary and British Elbow and Shoulder Society (BESS) best practice resources. An online search was undertaken by one reviewer to identify publicly available PILs produced by NHS Trusts detailing non-surgical management of frozen shoulder. Relevant data were extracted and analysed by one reviewer and verified by five reviewers. Descriptive statistics were used to summarise findings. Thirty-eight PILs were identified from 38 NHS Trusts with publication dates ranging from April 2013 to March 2025. Considerable variation was observed in the content, including reference to analgesia, activity modification, exercise prescription and corticosteroid injections. No single PIL reflected all key elements recommended in the NICE Clinical Knowledge Summary and BESS best practice. The findings demonstrate substantial variation in content, frequent misalignment with current national guidance and best practice exercise recommendations. Such variation may limit and may reduce the clarity, consistency and usefulness of information provided to patients.
Aims To explore teachers' perspectives on incorporating oral health education within schools, since its statutory introduction in the National Curriculum in England in 2020.Methods An online survey including open and closed questions was designed and distributed via postal invitations to selected schools in North West England, and via social media between September 2024 and January 2025. Quantitative data were analysed descriptively, while directed content analysis was used for free-text responses.Results Fifty-four responses were received. Oral health education was reported as inconsistent with different methods and frequencies of delivery reported; 21% (n = 11) teachers taught the topic less than once a year. Challenges included lack of curriculum time (44%, n = 23), and resources to help deliver (27%, n = 14) or plan the teaching (19%, n = 10). Most teachers (93%, n = 50) expressed confidence in their oral health knowledge, but free-text responses highlighted that teachers valued dental professionals' involvement with schools, and parental engagement to reinforce oral health at home.Conclusions Oral health education in schools remains inconsistent despite statutory requirements. Sustainable resources and multi-agency partnerships can help embed oral health promotion within a whole-school framework.
To address the dilemma of homogeneous talent training and the efficiency bottleneck of human resource management in universities, this study proposes an innovative personalized training framework integrating artificial intelligence, big data, and deep learning. Based on the 18-dimensional full-cycle behavior dataset of 5,000 students and OULAD dataset, a multimodal heterogeneous data fusion pipeline is constructed. This study adopts Generative Adversarial Network (GAN) for data imputation and bias optimization, designs Hierarchical Attention Graph Neural Network (HA-GNN) to capture hierarchical correlations among features, and uses Long Short-Term Memory (LSTM) to model temporal behavior patterns. The experimental results demonstrate that, under 10 independent repeated runs with random seed variation, the Hierarchical Attention Graph Neural Network-Long Short-Term Memory (HA-GNN-LSTM) model achieves lower prediction error on the academic performance prediction task, with a Mean Absolute Error (MAE) of 4.2 ± 0.3. Compared with the Temporal Fusion Transformer (TFT) baseline model, MAE is reduced by 31.1%. Welch's two-tailed t-tests based on independent run results remain statistically significant after Holm-Bonferroni multiple comparison correction [Formula: see text]. The Normalized Discontinued Cumulative Gain at Top 5 (NDCG @ 5) index of personalized recommendation system reaches 0.90, which verifies the effectiveness of spatio-temporal feature modeling. At the management application level, the improvements in advisor allocation response time and resource idle rate are derived from simulation experiments based on historical data replay, rather than online deployment in real campus management systems. The simulation results demonstrate that, under established constraints and historical sample distributions, advisor allocation response time could be reduced by 60% and resource idle rate could be decreased by 63.4%. These findings indicate the framework's potential for optimizing educational resource allocation. However, its managerial benefits require further validation through subsequent real-world deployment and long-term follow-up studies.
This study is the first to examine awareness, knowledge, and attitudes towards dyslexia among the general public in Mainland China. Using an online survey, we collected data on (a) demographics, (b) awareness of dyslexia and other common neurodevelopmental conditions, (c) knowledge of dyslexia causes, symptoms, functional impact, and assessment/intervention, and (d) attitudes towards dyslexia. A total of 1,008 adults from across all major regions of China completed the suvey. Around 70% reported having heard of dyslexia, lower than awareness of autism and ADHD, but higher than that of developmental language disorder. Respondents answered 49% of knowledge items correctly and demonstrated greater knowledge of dyslexia symptoms, followed by functional impact and causes, with weaker knowledge of dyslexia assessment and intervention. Dyslexia awareness and knowledge were higher among younger adults, females, urban residents, non-parents, and those with higher education and income, with some variation across regions. Attitudes towards dyslexia were generally positive, following similar demographic patterns. Although greater awareness was associated with higher levels of knowledge, only dyslexia knowledge uniquely predicted attitudes towards dyslexia after controlling for demographic factors. These indings highlight the need for culturally relevant, awareness-raising campaigns that promote a more accurate understanding of dyslexia. The findings should be interpreted in light of the limitations linked to sampling bias and methods of data collection. Future studies should include the voices of individuals with dyslexia to better understand how social and cultural factors in China influence their lived experiences across development.
In the context of mating, individuals of the same sex often act as rivals in the pursuit, attraction, and retention of desirable partners. This study explored the relationships between intrasexual competition and various aspects of human mating psychology across three countries: Canada, Hungary, and Indonesia. A total of 661 adults (including women, men, non-binary, and gender-unspecified individuals) completed an online questionnaire assessing sensation seeking, aggression, beauty-enhancing behavior, openness to cosmetic surgery, sexual motivation, and sociosexuality. Hypotheses were tested via Bayesian multilevel modeling. Measurement invariance testing and alignment procedures were conducted to address potential cross-cultural non-invariance. Results indicated that the superiority enjoyment component of intrasexual competition showed consistent positive associations with the examined psychological variables. Associations involving inferiority frustration were generally weaker and less consistent. The findings for openness to cosmetic surgery, sociosexuality, and aggression replicate prior research, whereas the links with sensation seeking, beauty-enhancing behavior, and sexual motivation extend the literature. Cross-national comparisons revealed no significant country differences in superiority enjoyment, whereas Canadian participants scored significantly lower than Hungarian and Indonesian participants in inferiority frustration, with no significant difference between the latter two groups. Overall, the findings suggest that intrasexual competition-particularly its superiority enjoyment component-shows consistent associations with mating-relevant psychological traits across cultural contexts, even when mean levels differ between societies.
Sample pretreatment plays a central role in analytical workflows, particularly for complex matrices where efficiency, reproducibility, and sustainability are essential. In recent years, increasing levels of automation have driven a gradual transition from labor-intensive manual procedures toward integrated and standardized pretreatment strategies. This review examines two representative automation paradigms that have significantly influenced recent developments in sample pretreatment: surface-based liquid microjunction sampling and flow-based automated platforms. Liquid microjunction techniques, including liquid extraction surface analysis, liquid microjunction surface sampling probe, and the MasSpec Pen, enable localized and minimally invasive extraction directly from solid or semi-solid substrates. These approaches have extended the applicability of mass spectrometry to in situ biological and clinical analysis, while also presenting challenges related to spatial resolution, extraction selectivity, and quantitative consistency. In contrast, flow-based platforms such as lab-in-syringe and online solid-phase extraction emphasize controlled fluid handling, process integration, and operational reproducibility, and have become important tools for high-throughput and trace-level analysis in biomedicine, food safety, and environmental monitoring. This review focuses on the methodological characteristics, design considerations, and practical limitations of these automation strategies, highlighting how platform architecture influences analytical performance and application scope. Current trends toward greater integration, intelligent control, and improved standardization are also discussed, with reference to future directions in automated analytical workflows.
Environmental concern is recognized as a primary determinant of preferences for carbon-labeled foods. However, empirical evidence on the mechanisms through which environmental concern shapes Chinese consumers' preferences for carbon-labeled foods remains limited. Based on data from online surveys and laboratory experiments, this study uses milk and yogurt as representative categories to assess consumers' preferences for carbon-neutral-labeled dairy products. It further investigates the effect of environmental concern on consumers' preferences, explores the underlying mechanisms, and examines the heterogeneity of these effects across gender, income, education, and region. The results indicate that consumers exhibit positive preferences for carbon-neutral-labeled milk and yogurt. Environmental concern significantly increases these preferences, and the effect is stronger among high-income, highly educated consumers and those in eastern China. Regarding the underlying mechanisms, environmental concern enhances consumers' preferences for carbon-neutral-labeled dairy products by improving their cognition of such labels and increasing visual attention to them. These findings highlight the importance of fostering stronger environmental concern to increase consumers' preferences for carbon-neutral-labeled foods and promote sustainable food consumption.
Orgasm can be an important component of sexual wellbeing broadly and specifically in the preconception period, yet epidemiologic research on orgasm is limited. We used cross-sectional data from Pregnancy Study Online (PRESTO), a cohort study of females attempting conception with one male partner (N = 6022; 2020-2025), to descriptively evaluate orgasm frequency, its correlates and its relationship to orgasm intensity. We used self-reported data to assess orgasm frequency (Likert scale: never/rarely to always/almost always) and intensity (0-10). Across correlates (e.g. encompassing sociodemographic, medical, behavioral factors), we calculated the absolute difference and 95% confidence interval (CI) in the percentage of participants reporting the highest versus lowest orgasm frequency within levels of each correlate, standardized relative to the difference in the full sample. Over half of the sample reported orgasming 'always', 'almost always' or 'most times' during sexual activity. Partner support was a strong correlate; participants whose partner 'rarely' provided love/affection and emotional support reported less frequent orgasms (standardized percentage-point differences of -11.0, 95% CI -36.7, 14.7 and -27.5, 95% CI -44.4, -10.6, respectively). Irritable bladder syndrome (standardized percentage point difference -15.4, 95% CI -25.5, -5.3), diabetes (standardized percentage point difference -5.8, 95% CI -18.2, 6.7) and depressive symptoms (highest category standardized percentage point difference -11.6, 95% CI -19.3, -4.0) were strong correlates of less frequent orgasms. Participants with lower function on other domains of sexual function reported fewer orgasms. Important correlates of preconception orgasm frequency spanned relational, clinical and sexual function factors. We discuss implications for conducting etiologic orgasm research.
Aims This study explored the training and working experiences of general dental practitioners (GDPs) in England in providing clear aligner treatment (CAT) to adult patients.Methods A mixed methods approach was adopted, including an online questionnaire and semi-structured interviews of GDPs in England providing CAT. Quantitative data were analysed descriptively using MS Excel and qualitative data using framework methodology.Results One hundred completed surveys were received, and 16 interviews were conducted. Most GDPs reported having attained aligner certification (n = 86) and nearly one-third (n = 31) gained some theoretical knowledge of CAT but highlighted key shortcomings of the training courses. GDPs felt confident in treating mild or moderate malocclusion traits and expressed several reasons for choosing a specific CAT and digital scanner and provider. Those GDPs qualified more than ten years could apply complex treatment mechanics. Laboratory-made fixed retainers were of higher preference following CAT, especially in complex malocclusions with high risk of relapse.Conclusions GDPs' limited understanding and diverse practices in CAT provision, suggest the need for policymakers to review the undergraduate dental curriculum and for educators to ensure the inclusion of theoretical and practical aspects of CAT, together with the ongoing support of specialist in orthodontics.