Individual Categories Research Articles

Heterogeneity in Prescription Opioid Misuse Motives by Age in Adolescents and Young Adults in the United States.

Adolescent (12-17 years) and young adult (18-25 years) prescription opioid misuse (POM) is linked to poor health outcomes. We investigated how POM motives vary across these ages and the potential links between motives and other substance use, mental health, and sociodemographic characteristics to help guide screening and prevention. Pooled 2015-2019 US National Survey on Drug Use and Health data were used, with 137,858 participants. Cross-tabulations estimated prevalence of individual motives and motive category by age. Mutually exclusive motive categories were no past-year POM, pain relief only, pain/sleep/relax (ie, some combination of only these motives), and any non-self-treatment motives (eg, get high, experiment). Logistic regression models evaluated links between motive category and sociodemographic, mental health, and substance use (eg, alcohol, cannabis, nicotine, other prescription misuse) outcomes by age group, versus reference groups of no past-year POM or pain relief only. Pain relief was the most common POM motive (estimated at >50% at all ages), but POM for non-self-treatment motives was the most common category after 14 years. POM for non-self-treatment motives had the highest adjusted odds ratios (aORs) of all substance use and mental health characteristics (eg, past-year substance use disorder aORs of 6.11 in adolescents [95% confidence interval (CI), 4.23-8.85] and 4.81 [95% CI, 4.01-5.77] in young adults, versus the pain relief only reference). POM for any non-self-treatment motives is linked to the highest prevalence of other substance use and mental health concerns, whereas POM for pain relief also signals a need for substance use and mental health screening.

Morphometric Changes in a Sample of Various Age Groups of the Thai Population: A Panoramic Radiographic Study

Objective The current investigation was conducted to examine the alterations in oral conditions and panoramic image parameters that occur with age. Methods The study sample consisted of 300 male participants and 300 female participants, ranging in age from 10 to 69 years. The age-related changes in intraoral circumstances and morphometric parameters, as observed in panoramic photographs, were explored. A two-way parametric analysis of variance was used to examine the effects of age group and sex. The frequencies and percentages were calculated and compared among groups using the chi-squared test for category variables. A p-value below 0.05 was considered to be statistically significant. Results The prevalence of intraoral conditions showed a positive correlation with advancing age. Males exhibited significantly higher crown, root, and tooth lengths in both the upper and lower canines. There was a significant difference between males and females in terms of the pulp area, the pulp-tooth ratio of the upper first molars, and the pulp area of the lower first molars (p < 0.05). The study found a substantial correlation between the radiomorphometric parameters and age, with similar trends observed in both males and females. Conclusion The findings of our research have the potential to contribute to the evaluation of an individual's age category and offer insights into the patterns of several observable factors on panoramic radiographs.

The Association Between Periconceptual Maternal Dietary Patterns and Miscarriage Risk in Women With Recurrent Miscarriages: A Multicentre Cohort Study.

To examine the association between periconceptual maternal diet and miscarriage risk among women with recurrent miscarriages. Prospective multicentre cohort study (Tommy's Net). Three university hospital research centres in the United Kingdom. 1035 women with a baseline history of two or more miscarriages. We analysed baseline dietary data from a 10-item Food Frequency Questionnaire (FFQ). For individual food category analyses, we used multivariable Poisson regression following adjustment for maternal confounders and paternal dietary patterns. For whole diet analyses, ordinal principal component analysis (PCA) was used to identify common dietary patterns. Results were presented as relative risks (RR) with 95% confidence intervals (CI) and accompanying p-values. Miscarriage rate, defined as the rate of spontaneous pregnancy loss (< 24 weeks of gestation) relative to the total number of pregnancies (miscarriages and live births). High consumption of fruit and nuts (almonds and walnuts) was associated with lower miscarriage risk (fruit 226/662 (34.1%) vs. 38/77 (49.4%), RR 0.66, 95% CI 0.51 to 0.85, p = 0.001; nuts 47/152 (30.9%) vs. 220/613 (35.9%), RR 0.73, 95% CI 0.54 to 0.98, p = 0.039). High red meat intake was associated with a possible increase in miscarriage risk (6/12 (50.0%) vs. 165/469 (35.2%), RR 1.86, 95% CI 1.10 to 3.16, p = 0.022). The association with miscarriage risk was unclear for other food groups, including fresh vegetables, white meat, fish, dairy, eggs, soya and chocolate, due to imprecise point estimates. Through PCA, we identified three data-derived dietary patterns. Yet, no distinct relationship emerged between these dietary patterns and miscarriage risk. A maternal diet rich in fresh fruits and nuts is associated with a lower miscarriage risk among women with a history of recurrent miscarriage. Tommy's Net (ISRCTN17732518) https://www.isrctn.com/ISRCTN17732518. Analysis plan (OSF zp7cs) https://osf.io/zp7cs.

Reviewing the implementation of the voluntary disclosure program as a database provider in exploring the potential of income tax article 25/29 for high-wealth individuals

This research is conducted to determine the role of the Voluntary Disclosure Program (PPS) in providing a database to the Directorate General of Taxes in extracting the potential of Income Tax Article 25/29 on Individual Taxpayers with the High Wealth Individual (HWI) category. This study also aims to determine the condition of income tax Article 25/29 of Individuals at KPP Madya Dua Medan and the obstacles in the application of PPS in extracting the potential of Income Tax Article 25/29 of Individuals. The method used in this research is qualitative method by conducting interviews, documentation and literature study. Interviews were conducted with employees of the Directorate General of Taxes and academics. Documentation is done on the data provided by KPP Madya Dua Medan. The reference sources used were obtained from journal provider platforms on the internet. The results of this study indicate that PPS can provide a database for the activities of extracting the potential of ITA 25/29 of HWI WPOP. The obstacles to the use of PPS data are the misalignment of information on the use of data between the DGT head office unit and the vertical unit, the communication between tax officers and taxpayers, the exploration of the potential of HWI which is still partial, and the tax planning of HWI taxpayers. Keywords: Extracting Potensial, Income Tax Article 25/29 on Individual Taxpayers, Voluntary Disclosure Program, High Wealth Individual, KPP Madya Dua Medan.

Significance-based decision tree for interpretable categorical data clustering

Numerous clustering algorithms prioritize accuracy, but in high-risk domains, the interpretability of clustering methods is crucial as well. The inherent heterogeneity of categorical data makes it particularly challenging for users to comprehend clustering outcomes. Currently, the majority of interpretable clustering methods are tailored for numerical data and utilize decision tree models, leaving interpretable clustering for categorical data as a less explored domain. Additionally, existing interpretable clustering algorithms often depend on external, potentially non-interpretable algorithms and lack transparency in the decision-making process during tree construction. In this paper, we tackle the problem of interpretable categorical data clustering by growing a decision tree in a statistically meaningful manner. We formulate the evaluation of candidate splits as a multivariate two-sample testing problem, where a single p-value is derived by combining significance evidence from all individual categories. This approach provides a reliable and controllable method for selecting the optimal split while determining its statistical significance. Extensive experimental results on real-world data sets demonstrate that our algorithm achieves comparable performance in terms of cluster quality, running efficiency, and explainability relative to its counterparts.

Dynamic process simulation for life cycle inventory data acquisition – Environmental assessment of biological and chemical phosphorus removal

In Sweden, phosphorus is commonly removed from municipal wastewater treatment by chemical precipitation (CP). Recently, such alternatives as enhanced biological phosphorus removal (EBPR) have garnered interest due to the increased risk of chemical shortage. In this study, a life cycle assessment (LCA) was performed to compare EBPR and CP in three scenarios: 1) baseline – precipitation chemicals available, 2) stricter effluent requirements – precipitation chemicals available, and 3) chemical shortage – no precipitation chemicals available. Data acquisition that was based on dynamic process simulation was useful, yielding more site-specific results, in contrast to standard literature values. The results indicated substantial differences in greenhouse gas emissions between configurations (around three times higher methane emissions for EBPR compared to CP configurations – although this finding requires further validation). These differences suggest that different emission factors for EBPR and CP should be considered. Furthermore, it is suggested to include waterline methane emissions, at least when the configuration incorporates anaerobic reactors in the water line. Further validation of emissions is necessary, especially for EBPR plants with side-stream hydrolysis and digester reject water treatment. The LCA results showed a similar overall environmental impact for both configurations, but the results of individual impact categories differed. EBPR caused greater climate impact due to the larger direct emissions of methane. Toxicity was more important for CP, based on the inherent heavy metal content in precipitation chemicals. Freshwater eutrophication was similar for both configurations, assuming that precipitation chemicals were available. However, if the recipient is sensitive, implementing EBPR reduces the freshwater eutrophication potential by 75% during a chemical shortage, and should be considered.

Associations of adverse childhood events with disordered eating behaviors among US adolescents

The purpose of our study was to use recent nationally-representative data to 1) determine whether reported adverse childhood experiences (ACEs) were associated with individual disordered eating behaviors (DEBs) for the US- based early and middle adolescent population; and 2) the extent to which individual ACE categories were associated with DEBs for this population. The study used cross-sectional data from the 2022 National Survey of Children's Health, which used parent-reported data. Inclusion criteria included all early (10–13 years of age) and middle-aged adolescents (14–17 years of age) (n = 24,173). Multiple logistic regressions were used to test the association between ACEs and DEBs while controlling for covariates. Both categories for ACEs (i.e. 1–2 ACEs and 3+ ACEs) exhibited a statistically significant association with three specific DEBs: skipping meals or fasting, low interest in food, and binge eating. Additionally, six of the seven ACE categories exhibited a statistically significant association with DEBs which included parent or guardian divorced, parent or guardian time in jail, adults slap, hit, kick, punch others, victim of violence, lived with mentally ill, and lived with person with alcohol/drug problem. Further studies are needed to examine mechanisms contributing to the increased risk of DEBs among those with ACE exposure.

Homebuyer complaints during defect liability period: critical analysis of individual presumptions, defect discovery and post-rectifications factors

Purpose This study aims to investigate factors leading to homebuyer complaints during defect liability periods (DLP). The specific study objectives are to: identify critical factors leading to homebuyer complaints during DLP; compare the factors among regions, house price and developer recognition; group the factors into subcategories; and evaluate the criticality of the categories. Design/methodology/approach A systematic literature review and semi-structured interviews with 20 homebuyers were carried out, generating 37 factors. A survey was developed with the factors categorized into three categories: individual presumptions, defects discovery and post-rectifications. The survey data were collected from 104 homebuyers who had acquired new houses within the last five years. The collected data were subjected to statistical analyses, including normalized mean analysis, Kruskal–Wallis H test, factor analysis and fuzzy synthetic evaluation. Findings The results indicate that individual presumptions, defects discovery and post-rectifications have 8, 14 and 6 critical factors. Then, there are high similarities in the criticality of the factors among regions, house price and developer recognition. The defect discovery factors can be grouped into function- and precision-related factors. Finally, the defect discovery category has the highest overall criticality, followed by post-rectification and individual presumption categories. Originality/value To the best of the authors’ knowledge, this study is the first to quantitatively investigate factors leading to homebuyers’ complaints during DLP. The study findings offer a new perspective for policymakers in the development of housing regulations.

Neuronal sequences in population bursts encode information in human cortex.

Neural coding has traditionally been examined through changes in firing rates and latencies in response to different stimuli1-5. However, populations of neurons can also exhibit transient bursts of spiking activity, wherein neurons fire in a specific temporal order or sequence6-8. The human brain may utilize these neuronal sequences within population bursts to efficiently represent information9-12, thereby complementing the well-known neural code based on spike rate or latency. Here we examined this possibility by recording the spiking activity of populations of single units in the human anterior temporal lobe as eight participants performed a visual categorization task. We find that population spiking activity organizes into bursts during the task. The temporal order of spiking across the activated units within each burst varies across stimulus categories, creating unique stereotypical sequences for individual categories as well as for individual exemplars within a category. The information conveyed by the temporal order of spiking activity is separable from and complements the information conveyed by the units' spike rates or latencies following stimulus onset. Collectively, our data provide evidence that the human brain contains a complementary code based on the neuronal sequence within bursts of population spiking to represent information.

Some objective factors influencing delinquent behavior of regional youth in the 2000s

Delinquent behavior and objective factors influencing it have been considered. It should be noted that crime is a complex phenomenon, which is influenced by many factors. Modern scientists combine these factors into two large groups such as subjective (or socio-cultural) and objective (or socio-economic). In order to study the latter and establish the existence of a relationship between them and youth crime, we have selected the most common criminal acts committed in the youth environment such as theft and robbery, as well as the most numerous crimes committed by young people against life and health such as infliction of minor and moderate harm to health. Among objective factors, we have chosen the indicators that can have the strongest impact on youth crime as a whole and on its individual categories such as ­average monthly accrued wages in the region, cash income per capita, and average per capita consumer spending. According to the conducted simple statistical analysis results, an inverse correlation between the number of criminals committing property crimes and the selected socio-economic factors has been revealed. Due to the use of a simple research method, it was not possible to establish any dependence of the number of young people committing crimes against property on the selected objective (socio-economic) factors.

The effect of building bottlenecks on crowd dynamics involving individuals with simulated disabilities

With the development of urbanization and the growth of population, there is a growing demand for safety in public building facilities. As one of the essential building components of urban architecture, bottlenecks have a significant impact on the evacuation efficiency of crowds. Furthermore, the heterogeneity of crowds also contributes to the complexity of crowd movement through bottlenecks, while aggravating the magnitude of congestion induced by bottlenecks. The objective of this paper is to explore the movement characteristics of heterogeneous crowds passing through a corridor with a bottleneck by conducting a controlled experiment. There were three variables in this experiment, namely the individual categories (i.e., able-bodied individuals, simulated individuals on crutches and simulated wheelchair users), bottleneck width (i.e., 1.2, 1.6 and 2.0 m) and proportion of simulated disabilities in crowds (i.e., 0 %, 5 % and 10 %). Then offset angle, passing efficiency, fundamental diagram, etc., were analyzed. In trials involving simulated individuals on crutches, a higher detouring degree is observed compared to trials involving simulated wheelchair users or mixed groups of two types of simulated disabilities. There is an increase in flow rate induced by increasing the bottleneck width and decreasing the proportion of simulated disabilities. The passing efficiency at the upstream of the bottleneck in all tests is primarily influenced by the bottleneck width, while by the type and proportion of simulated disabilities at the downstream or inside the bottleneck. The findings are intended to complement the dynamic theory of heterogeneous crowds at building bottlenecks, while providing a reference for congestion control of crowds at bottlenecks.

Concordance between Clinical and Histopathological Diagnosis among Various Dermatoses in the Elderly: A 5-year Retrospective Cross-sectional Assessment from a Tertiary Care Center in Southern India

Background: Dermatoses in the elderly differ from those in the younger age group due to additional effects of intrinsic and extrinsic aging, increased prevalence of comorbidities, effects of polypharmacy, socioeconomic factors, and geographical factors. Various prevalence studies on the dermatoses in geriatric age group are available from the Indian subcontinent. Studies focusing on the agreement between their clinical and histopathological diagnosis, however, are scarce. Aims and Objectives: The study aimed at categorizing and describing the various dermatoses in the geriatric population subjected to biopsy and to determine the level of agreement between the clinical diagnosis made and the histopathological diagnosis offered in them. Materials and Methodology: Histopathological records of skin biopsies performed in patients belonging to the age group of ≥60 years in the past 5 years were analyzed. Demographic characteristics, clinical diagnosis made or the differential diagnoses considered, and histopathological diagnosis offered in each case were noted. The various dermatoses among the patients in whom a histopathological diagnosis was offered were categorized into inflammatory (infections and noninfectious dermatoses), neoplastic, and other dermatoses groups. The level of agreement between clinical and histopathological diagnosis was described as complete agreement, partial agreement, and disagreement. Statistical significance was assessed using the Chi-square test, and the strength of association was assessed using kappa statistics. Results: A total of 109 biopsies meeting the inclusion criteria were analyzed. The mean age of the study population was 67.02 ± 6.624 years, with a male-to-female ratio of 1.6:1. Majority of the dermatoses belonged to the noninfectious inflammatory group (52 [47.70%]) followed by neoplasms (28 [25.68%]). Overall, complete agreement between the clinical diagnosis made or one of the differential diagnoses considered and the histopathological diagnosis offered was seen in 91 of 109 cases (83.5%), which was statistically significant (P = 0.0001). A higher level of complete agreement was noted among the inflammatory dermatoses (67 of 79 cases [84.81%]) when compared to neoplastic dermatoses (22 of 28 cases [78.57%]). Among the inflammatory dermatoses, complete agreement was more for the noninfectious (46 [88.46%]) than the infectious (21 [77.78%]) dermatoses. All the cases (2) belonging to the other group of dermatoses showed complete agreement. Disagreement was highest among the neoplasms (6 [21.43%]), followed by the noninfectious inflammatory dermatoses (5 [9.62%]). Partial agreement with the clinical diagnosis was maximum for the infectious diseases (5 [18.51%]). Conclusion: This study noted a statistically significant high rate of concordance (Chi-square test –P = 0.0001) between the clinical and histopathological diagnosis among the dermatoses in the geriatric population when taken together as well as among individual categories. Noninfectious inflammatory dermatoses constituted the major group with the highest and statistically significant concordance between the clinical and histopathological diagnosis. Furthermore, there was almost perfect strength of association (kappa statistics –P = 0.000) noted among the individual categories of dermatoses.

Consequences of Workplace Bullying From Nurses' Perspectives: A Qualitative Descriptive Study in Iran.

The aim of this study is to explore Iranian nurses' experiences regarding the consequences of bullying. A qualitative descriptive study is carried out using conventional content analysis and Granheim and Lundman's method. Data for this study were collected through 12 in-depth, semi-structured individual interviews with nurses employed at a teaching hospital in REDACTED, western Iran. Purposeful sampling was employed until data saturation was achieved. Data management was conducted using MAXQDA software. The participants consisted of 12 nurses, with a mean age of 36.1 ± 8.6 years. Their experiences of workplace bullying were analysed and categorised into a main theme called 'Consequences of Workplace Bullying', with two categories identified as 'Organisational Consequences' and 'Individual Consequences'. The organisational consequences were further elaborated through two subcategories: 'work performance consequences' and 'patient care consequences'. The individual consequences category included subcategories including 'psychosomatic consequences', 'psychological consequences' and 'family consequences'. Workplace bullying among nurses can have negative impacts on patients, nurses and organisations. In order to mitigate these effects, nurse managers can take proactive measures by implementing management strategies and fostering a positive work culture. By addressing the underlying factors and promoting a supportive environment, the adverse consequences of workplace bullying can be reduced or prevented. Yes.

Adhering to Patient Safety Standards: A Healthcare Imperative for the 21st Century

The ethics of healthcare processes aim to protect patient safety by emphasizing the importance of adhering to rules and avoiding harmful practices. They also suggest practical solutions to prevent such failures. Non-compliance, whether due to human error or technical failure, can result in operational failures and pose severe hazards to patients, healthcare workers, and hospital facilities. This paper discusses intentional non-compliance with healthcare standards and guidelines, referred to as deviation, and demonstrates how adhering to these rules can reduce the risk of harm. Noncompliance can have severe consequences, as it may reveal an organization's fail-safe mechanisms, defenses, or safety nets, potentially resulting in catastrophic events and causing significant harm. These errors typically occur when active errors combine with latent errors, such as flaws or vulnerabilities in a system's defenses. This habit allows the latter to overcome the defenses, gain patient access, and cause harm. There is no such thing as a completely safe environment, even the most advanced ones. Additionally, all humans, regardless of their intelligence, have weaknesses. In healthcare processes, every signal has the potential to cause harm, leading to tragic outcomes or even death. The factors contributing to non-compliance fall under individual, collective, organizational, or sociocultural categories. Reducing non-compliance in healthcare processes and ensuring patient safety requires all stakeholders to commit to patient safety ethics.

Vehicle Detection and Counting for Traffic Congestion Estimation Using YOLOv5 and DeepSORT in Smart Traffic Light Application

The escalating number of vehicles on the roads has exacerbated trafficcongestion, presenting a significant and inevitable challenge for roadusers.Trafficcongestionnotonlyincreasesthetraveltimeofroadusers;it also causes air pollution since more vehicles are stuck on theroad. To address this issue, deep learning algorithms, including YOLOv5and DeepSORT, have been leveraged to enable vehicle detection and estimate the number of vehicles through image processing. This study focuses on training a custom YOLOv5 dataset of vehicles and compares its performance with a pretrained YOLOv5 dataset in terms of feasibility for detecting and estimating the number of vehicles. In the proposed approach, YOLOv5 is employed to detect vehicles in video streams, DeepSORT is used for vehicle tracking and counting as they pass through the detection zone, and the number of vehicles in each lane is estimated with the aid of Supervision. The custom dataset's validation demonstrates promising results, with the precision curve indicating convergence for all classes at 97.4% precision and an 87% accuracy in predicting vehicle classes. Additionally, the precision-recall curve assesses the ability to detect individual vehicle categories, such as bus, car, motorcycle, and truck, with accuracies of 68.2%, 95.2%, 79.9%, and 70.1%, respectively. Furthermore, the overall accuracy for detecting all vehicle classes combined is 78.3%. The F1 curve indicates that the system achieves a confidence level of 30.9% F1 score, ensuring 78% confidence in accurately predicting all classes. Both the pretrained and custom datasets exhibit similar accuracy in counting the total number of vehicles passing through the detection zone as well as estimating the number of vehicles in each lane. However, it is evident that the custom dataset's performance can be further improved by incorporating more extensive and diverse datasets during the training process to enhance the accuracy of vehicle detection and estimation. In conclusion, the integration of deep learning algorithms, specificallyYOLOv5 and DeepSORT, offers a promising solution for addressing traffic congestion byefficiently detecting and estimating vehicle numbers, which allow traffic systems to identify which lane is congested and prioritise ensuring the congested lane has a smooth traffic flow. Continued research with larger datasets can lead to further advancements and refined results in the field of traffic management and optimization.

Android malware defense through a hybrid multi-modal approach

The rapid proliferation of Android apps has given rise to a dark side, where increasingly sophisticated malware poses a formidable challenge for detection. To combat this evolving threat, we present an explainable hybrid multi-modal framework. This framework leverages the power of deep learning, with a novel model fusion technique, to illuminate the hidden characteristics of malicious apps. Our approach combines models (leveraging late fusion approach) trained on attributes derived from static and dynamic analysis, hence utilizing the unique strengths of each model. We thoroughly analyze individual feature categories, feature ensembles, and model fusion using traditional machine learning classifiers and deep neural networks across diverse datasets. Our hybrid fused model outperforms others, achieving an F1-score of 99.97% on CICMaldroid2020. We use SHAP (SHapley Additive exPlanations) and t-SNE (t-distributed Stochastic Neighbor Embedding) to further analyze and interpret the best-performing model. We highlight the efficacy of our architectural design through an ablation study, revealing that our approach consistently achieves over 99% detection accuracy across multiple deep learning models. This paves the way groundwork for substantial advancements in security and risk mitigation within interconnected Android OS environments.

Energy prices and the structure of inflation in European Union countries

Abstract Since 2022, in almost every inflation category, a strong divergence in price dynamics among the EU countries has become visible. The first aim of this paper is to assess the impact of changes in energy prices on the differentiation in price dynamics in individual inflation categories in EU countries. The second aim is to isolate those components of inflation that have significantly differentiated the countries in the crisis year of 2022. The research was conducted based on the vector-autoregressive model, the Granger causality test, cluster analysis and analysis of variance. It can be concluded that there is a causal relationship between energy prices and the differentiation in the price growth rate in certain inflation categories. In 2022, the EU member states were divided into two quite distinct clusters. This article adds value to current research by taking into account the level of variation in the inflation structure among EU countries.

A new deepfake detection model for responding to perception attacks in embodied artificial intelligence

Embodied artificial intelligence (AI) represents a new generation of robotics technology combined with artificial intelligence, and it is at the forefront of current research. To reduce the impact of deepfake technology on embodied perception and enhance the security and reliability of embodied AI, this paper proposes a novel deepfake detection model with a new Balanced Contrastive Learning strategy, named BCL. By integrating unsupervised contrastive learning and supervised contrastive learning with deepfake detection, the model effectively extracts the underlying features of fake images from both individual level and category level, thereby leading to more discriminative features. In addition, a Multi-scale Attention Interaction module (MAI) is proposed to enrich the representative ability of features. By cross-fusing the semantic features of different receptive fields of the encoder, more effective deepfake traces can be mined. Finally, extensive experiments demonstrate that our method has good performance and generalization capabilities across intra-dataset, cross-dataset and cross-manipulation scenarios.

Dynamic HIV risk differentiation among youth: Validation of a tool for prioritization of prevention in East Zimbabwe.

Differentiating risk for HIV infection is important for providing focussed prevention options to individuals. We conducted a longitudinal study to validate a risk-differentiation tool for predicting HIV or HSV-2 acquisition among HIV-negative youth. Population-based household survey in east Zimbabwe. HIV and HSV-2 status and HIV behavioural risk factors were assessed in two surveys conducted 12 months apart among young people. Associations between risk-behaviours and combined HIV/HSV-2 incident infection were estimated using proportional hazards models. We calculated the sensitivity and specificity of risk-differentiation questions in predicting HIV/HSV-2 acquisition and quantified changes between surveys among low, medium, and high-risk categories. In total, 44 HIV/HSV-2 seroconversions were observed in 1812 person-years of follow up (2.43/100PY, 95%CI: 1.71-3.15); 50% of incident cases reported never having had sex at baseline. Risk of HIV/HSV-2 acquisition was higher for those reporting non-regular partners (women: HR=2.71, 95% CI:1.12-6.54, men: HR=1.37, 95%CI: 0.29-6.38) and those reporting having a partner with a sexually transmitted infection (STI) (HR=7.62 (1.22-47.51). Adding a question on non-regular partnerships increased tool sensitivity from 18.2% to 38.6%, and further to 77.3% when restricted to those who had ever had sex. Individual risk category increased for 28% of men and 17% of women over 12-months. The refined risk differentiation tool identified a high proportion of youth at risk of HIV acquisition. Despite this, half of incident infections were among individuals who reported no prior sexual activity. The shifting patterns of risk behaviours underscore the need for dynamic prevention engagement strategies in high HIV prevalence or incidence settings.

ThP7.17 - Improving completeness of operative notes for laparoscopic appendicectomy

Abstract Aim This study aimed to compare the quality of laparoscopic appendicectomy operation notes in the emergency setting to 'Get It Right First Time' (GIRFT) guidelines. To evaluate the effect of the teaching session and operative note checklist in improving the completion rate of operation notes for laparoscopic appendicectomy. Method Retrospective analysis of 19 consecutive operation notes of patients undergoing emergency laparoscopic appendicectomy. Prospective data was then collected on 15 consecutive appendicectomy operation notes post-intervention. 34 recommendations based on GIRFT recommendations 'Best practice for laparoscopic appendicectomy documentation' were used to audit laparoscopic appendicectomy operation notes. Documentation was reviewed by two independent reviewers and scores were given based on GIRFT recommendations. Student's T-test was used to calculate the significance of overall scores and Chi-Squared to calculate the difference between individual categories. Results Mean completeness of operation notes improved from the first cycle (58.5%) to the second cycle (85.5%, P&amp;lt;0.001). There was a significant improvement in documentation of patient positioning (P=0.001), skin preparation (0.035), diagnostic findings (P&amp;lt;0.001), health of caecum (P&amp;lt;0.036), extraction port (P=0.01) and follow-up plan (P=0.03). Conclusion There were many domains of the GIRFT recommendations not addressed prior to this audit. Teaching sessions and checklist distribution lead to a significant improvement in overall completeness of the operation note. Movement towards digitised templates should be made to further comply with guidelines.