Simple Count Research Articles

Validation of the Hungarian version of the General Oral Health Assessment Index (GOHAI) in clinical and general populations

BackgroundCOSMIN (Consensus-based Standards for the selection of health Measurement INstruments) provides a framework for selecting and validating patient-reported outcome measurements (PROMs). This study aims to validate the Hungarian version of the GOHAI and, for the first time, to assess its Standard Error of Measurement (SEM), Smallest Detectable Change (SDC), and Measurement Invariance (MI) across general and clinical populations as well as different age groups, following COSMIN guidelines.Materials and methodsThe translation was performed using a forward-backward process. A mixed sample (n = 306) was recruited in Budapest from May 2023 to February 2024, consisting of the general population (45.1%), recruited from health kiosks and a nursing home, and the clinical population (54.9%), sourced from Semmelweis University’s care units. The sample was further divided into two age groups: 18–64 years old (54.9%) and 65 + years old (45.1%). GOHAI was administered twice to 108 stable participants. For both the additive score (ADD-GOHAI) and simple count (SC-GOHAI), structural validity and measurement invariance by subgroups were assessed via Confirmatory Factor Analysis (CFA). Internal consistency was evaluated using Cronbach’s alpha, and test-retest reliability was measured using the intraclass correlation coefficient (ICC). SEM was calculated using the SEM agreement formula, and SDC using: \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\:SDC=1.96*\\sqrt{2}*SEM$$\\end{document}. Convergent and known-group validity were tested against predefined hypotheses for structural validity.ResultsContrary to a three factor model, a single-factor model showed good fit in all subgroups for both scoring methods, with adequate internal consistency (Cronbach \U0001d6fc: 0.76–0.85). Four of the six hypotheses for convergent validity and all ten hypotheses for known-groups validity supported the predefined criteria. Measurement invariance between clinical and general populations, or by age, was not demonstrated, so GOHAI’s different measurement properties should be considered when comparing subpopulations. Test-retest reliability was adequate (ICC: 0.87–0.96). SDC was ≈5 points using ADD-GOHAI and 2–3 points using SC-GOHAI.ConclusionThe Hungarian version of GOHAI demonstrates satisfactory psychometric properties across both general and clinical populations, as well as among both younger and older age groups. While the measurement properties of SC-GOHAI may be more stable between populations, ADD-GOHAI seems more suitable for individual follow-up. However, observed changes must be considered in relation to the measurement error associated with GOHAI.

Implementation of Basic Education Learning Continuity Plan at Anomar National High School, Surigao City, Philippines

This study assessed the implementation of the Basic Education Learning Continuity Plan (BE-LCP) at Anomar National High School, focusing on Grades 11 and 12 students' engagement with Most Essential Learning Competencies (MELCs) delivered via modular learning. Drawing on cognitive and behavioral learning theories, the study examined the roles of students’ interest and attitude, parental involvement, and teachers' support in shaping educational outcomes in a self-directed learning modality. Using a descriptive research design, data were collected through structured surveys and analyzed with statistical tools Simple Frequency Count and Percentages, Mean and Standard Deviation, Analysis of Variance, T-test, Pearson's R Correlation, and Multiple Regression Analysis. Findings indicated that while Grade 11 students achieved a "Satisfactory" level in learning assessment, Grade 12 outcomes were "Average," suggesting a need for additional support. High levels of interest and positive attitudes were noted among students, yet challenges with progressive skill development and external support highlighted areas for improvement. Parental involvement positively influenced learning environments but showed variability in effectiveness. The weak correlation between interest, attitude, and learning outcomes suggests that additional factors may impact student success. Recommendations include tailored interventions, enhanced parental guidance, and further exploration of curriculum adaptability and resource availability.

A modeling approach to forecast local demographic trends in metapopulations.

Predicting animal population trajectories into the future has become a central exercise in both applied and fundamental ecology. Because demographic models classically assume population closure, they tend to provide inaccurate predictions when applied locally to interconnected subpopulations that are part of a larger metapopulation. Ideally, one should explicitly model dispersal among subpopulations, but in practice this is prevented by the difficulty of estimating dispersal rates in the wild. To forecast the local demography of connected subpopulations, we developed a new demographic model (hereafter, the two-scale model) that disentangles two processes occurring at different spatial scales. First, at the larger scale, a closed population model describes changes in metapopulation size over time. Second, total metapopulation size is redistributed among subpopulations, using time-varying proportionality parameters. This two-step approach ensures that the long-term growth of every subpopulation is constrained by the overall metapopulation growth rate. It implicitly accounts for the interconnectedness among subpopulations and avoids unrealistic trajectories. Using realistic simulations, we compared the performance of this new model with that of a classical closed population model at predicting subpopulations' trajectories over 30 years. While the classical model predicted future subpopulation sizes with an average bias of 30% and produced predictive errors sometimes >500%, the two-scale model showed very little bias (<3%) and never produced predictive errors >20%. We also applied both models to a real dataset on European shags (Gulosus aristotelis) breeding along the Atlantic coast of France. Again, the classical model predicted highly unrealistic growths, as large as a 200-fold increase over 30 years for some subpopulations. The two-scale model predicted very sensible growths, never larger than a threefold increase over the 30-year time horizon, which is more in accordance with this species' life history. This two-scale model provides an effective solution to forecast the local demography of connected subpopulations in the absence of data on dispersal rates. In this context, it is a better alternative than closed population models and a more parsimonious option than full-dispersal models. Because the only data required are simple counts, this model could be useful to many large-scale wildlife monitoring programs.

Polypharmacy in Older Patients.

Polypharmacy is common among older people and is associated with multiple adverse outcomes. Assessing whether it is appropriate or inappropriate for an individual is more informative than relying on a simple pill count. Modern medicine is based on single disease guidelines that promote prescribing but tend not to have deprescribing criteria. Barriers to deprescribing promote the accumulation of medicines over time. Clinical trial data have limitations due to the selected populations recruited. Some evidence suggests older people with multi-morbidity may benefit less and people with frailty are at increased risk of harm. Prescribing can be inappropriate if it is not evidence-based, harm is likely to exceed the benefit, includes hazardous medications or combinations of medicines, the patient experiences therapeutic burden, there is reduced adherence or prescribing cascades. Medicines optimisation aims to improve prescribing quality for an individual patient and may include deprescribing. It is a complex process that includes shared decision-making, careful follow-up, and communication of any resulting prescription changes.

Corporate Social Responsibility as A Strategic Tool for Sustainable Organizational Image and Development

Corporate social responsibility has becomes so popular that almost every corporate organization applies it to meet communal and corporate needs. However, the existing studies which centre on the influence of corporate social responsibility on Nigerian breweries’ corporate image remain controversial as they could not have any convergent point. Therefore, this study examined the impact of Nigerian breweries’ corporate social responsibility on its corporate image. The study adopted survey design in form of cross-sectional study through systematic random and purposive sampling. The sample size of 370 members of the host community of Nigerian breweries, Ibadan was derived through Taro Yamane’s proportional sampling formula. The Head of the factory’s Corporate Affairs was also purposively selected for qualitative aspect of the study. Two research instruments were used to collect data: self-designed structured questionnaire (a four-point modified Likert scale method) and a structured interview guide. The instruments were validated and subjected to reliability test using Cronbach’s Alpha analysis; a value of 0.81 was obtained. Data obtained were presented and analyzed using simple frequency counts and percentages, and content analysis. Findings reveal that the Nigerian breweries CSR is effective and meticulously implemented; it’s significantly impacts the corporate image of the company positively. It is recommended that certain aspects of the company’s corporate social responsibility should be reconsidered, including road maintaince, housing support programmes and environmental sanitation. It is concluded that Nigerian breweries should strengthen efforts that will sustain its corporate social responsibility programme.

Design and Stress Analysis of Bevel Line Gears with Vertical Flank Suitable for Micro Machining

The line gear (LG) exhibits promising applications in micromachinery owing to its simple structure and minimal teeth count. This paper aims to advance the meshing theory of LG and introduce a conical LG tooth configuration specifically tailored for micro-machining that is capable of driving with high performance. Based on the meshing principle of LG, a conical line gear pair with vertical flank (VFLG) of the driving gear was designed. Subsequently, adhering to the curvature non-interference principle that no local interference occurs in the meshing process and the specified range of fitting error in one direction, the design parameters for LG were determined. A comparison of the contact stress between two sets of different contact line types revealed the distinct advantage of VFLG with parameters identical to those of traditional LG. The experimental results conclusively demonstrate a transmission ratio error of 0.004, affirming the feasibility of the design. The curvature non-interference design formula proposed in this paper refines the LG design theory, and the novel LG design method presented holds significant implications for subsequent micromachining.

A new double observer‐based census framework to improve abundance estimations in mountain ungulates and other gregarious species with a reduced effort

Abstract Estimating animal abundance has a key role to play in ecology and conservation, but survey methods are always challenged by imperfect detection. Among the techniques applied to deal with this issue, Double Observer (DO) is increasing in popularity due to its cost‐effectiveness. However, the effort of using DO for surveying large territories can be significant. A DO‐based survey method that allows accurate abundance estimations with reduced effort would increase the applicability of the method. This would have positive effects on the conservation of species which are challenging to survey such as mountain ungulates. We used computer simulations based on real data and a field test to assess the reliability of the DO and of a new proposed survey procedure, the Double Observer Adjusted Survey (DOAS). DOAS is based on total block counts adjusted with some DO surveys conducted in a proportion of the total area only. Such DO surveys are then used to estimate detection probability with a mark‐recapture‐derived approach. We found that full DO is much more accurate than simple block counts for abundance estimations. DOAS is a less demanding alternative to full DO and can produce comparable abundance estimates, at the cost of a slightly lower precision. However, in the DOAS overall detectability has to be estimated within a sufficient number of sites (around a quarter of the total) to obtain a higher precision and avoid large overestimations. Practical implications. DO methods could increase the reliability of abundance estimations in mountain ungulates and other gregarious species. Full DO in particular could allow researchers to obtain unbiased estimations with high precision and its usage is therefore suggested instead of block counts in wildlife monitoring. Given the high costs of full DO, the DOAS procedure could be a viable and cost‐effective survey strategy to improve abundance estimates when resources are scarce.

Nutritional quality and diversity in Ghana’s school feeding programme: a mixed-methods exploration through caterer interviews in the Greater Accra Region

BackgroundThe Ghana School Feeding Programme (GSFP) provides public primary school pupils with a free daily meal. Each meal is expected to follow set menus, providing 30% of children’s’ (6-12 years) energy requirements. This study assessed the nutritional quality and diversity of planned and provided GSFP meals, engaging school caterers to identify how meal quality in the Greater Accra Region could be enhanced.MethodsA cross-sectional mixed methods study design was used. Multistage sampling was used to select 129 schools implementing the GSFP in six districts of the Greater Accra Region. GSFP district menus were collected as well as a one-week school caterer recall of provided school meals. The meal served on the day of data collection was recorded and photographed. Nutritional quality was evaluated based on nutrient profiling methods: energy density (low<125kcal/100g; medium 125-225kcal/100g; high>225kcal/100g) and nutrient density (low<5%; medium 5-10%; high>10%). Meal diversity was assessed by a simple count composed of 5 food groups: cereals, pulses/nuts/seeds, animal-source, vegetables and fruits. Caterers’ views on programme facilitators and barriers were also explored.ResultsPlanned menus included 14-20 weekly options, composed of eight minimally processed traditional dishes. All meals, except white rice, had a high nutrient density/100g. Energy density was varied (low, n=2; medium, n=2; high, n=4). Meals included only 2/5 or 3/5 food groups, mainly starchy staples, pulses/nuts/seeds, and sometimes vegetables. Fruit was never reported. About half of caterers (51.1%) reported deviating from the planned menus: 11.7% served alternative meals, with some including animal-sourced food (17.0%), and 39.4% repeated meals provided during the week, often based on starchy staples, influencing overall nutritional quality. Most caterers reported food item cost and lack of food purchase guidelines as barriers to providing school meals, while food safety training and guidelines for food preparation were facilitators.ConclusionsWhile school meals are composed of minimally processed, nutrient dense, local foods, there are notable gaps in meal diversity and compliance, as reflected in provided meals. Caterer compliance to planned menus varied greatly, reflecting recent food price inflation. Upwardly adjusting the current meal allocation of 1.2 cedis (0.22USD) per child per day could enhance access to more affordable, nutritious and diverse foods in school meals.

What evidence exists on the effect of the main European lowland crop and grassland management practices on biodiversity indicator species groups? a systematic map

BackgroundThe intensification of the agricultural practices in Europe over the last decades has drastically transformed the agroecosystems. The simplification of the landscape, the loss of semi-natural habitats and the application of chemicals on crops led to biodiversity decline in agricultural landscapes, raising substantial concerns about the loss of essential ecosystem services, such as pollination or pest control. Depending on the location, the scale and the regional context, different indicator species groups (ISGs) are regularly surveyed to assess the state and trend of biodiversity changes in agroecosystems. Although the high diversity of these ISGs allows assessing different biodiversity aspects (e.g., trophic levels, bio-physical compartments, scale of indication), it complicates the interpretation of the results and thus their practical application. In addition, species diversity metrics are various, from simple species counts to more complex measurements of diversity indices, sometimes with antagonistic responses. Here, to meet the pressing need for synthesis in this complex topic, we follow a standardized systematic map protocol to collect and summarize the literature reporting field evidence of the effects of the main agricultural management practices (AMPs) in arable crops, grasslands and ecological infrastructures on a set of ISGs in European lowland farming areas.MethodsSearches of literature were made using online publication databases, search engine and specialist websites in English. Gathered publications were screened for relevance following inclusion/exclusion criteria published in a prior protocol. We extracted and mapped information about experimental design, monitoring methods, ISGs and AMPs studied and the diversity measures presented in each included publication. These parameters are structured in available data coding sheets.ResultsThe search gathered 20,162 references from which 1208 remained after full text eligibility screening. Main areas studied are in Western Europe, and the number of studies increased exponentially from 1984 to 2022. Most publications are experimental and on-farm studies which assess AMPs effects at the field scale. Main studied AMPs are fertilization, grazing, organic farming, tillage, mowing and herbicide application. Most ISGs used to study their impacts are flora, carabids, spiders, birds, bees and annelids, often combined with other ISGs. The combinations between AMPs and ISGs studied are detailed as well as monitoring methods. The most used diversity measures are abundance, species richness, Shannon index, evenness, and community composition.ConclusionsWe identified several knowledge clusters: (1) organic farming, fertilization, tillage, grazing and mowing impact on a wide range of ISGs, (2) flora response to agricultural practices, (3) annelids response to agronomic interventions that impact soil structure (e.g., tillage, fertilization, crop rotation, crop residue management), (4) butterflies and orthopterans response to mowing and grazing effects in grasslands, (5) the use of bird monitoring for the impact for assessing the efficiency of AES implementation at the landscape scale. We highlight that further research should be conducted on ISGs that are until now poorly studied regarding agricultural practices, such as amphibians, reptiles, gastropods, millipedes and centipedes. More field evidence of the effects of diversification practices such as intercropping, undersowing, intermediate cropping, and agroforestry are needed to draw conclusions on their benefits on biodiversity.

Evaluating the effects of safety incentives on worker safety behavior control through image-based activity classification.

Construction worker safety remains a major concern even as task automation increases. Although safety incentives have been introduced to encourage safety compliance, it is still difficult to accurately measure the effectiveness of these measures. A simple count of accident rates and lower numbers do not necessarily mean that workers are properly complying with safety regulations. To address this problem, this study proposes an image-based approach to monitor moment-by-moment worker safety behavior and evaluate the effects of different safety incentive scenarios. By capturing workers' safety behaviors using a model integrated with OpenPose and spatiotemporal graph convolutional network, this study evaluated the effects of safety-incentive scenarios on workers' compliance with rules while on the job. The safety incentive scenarios in this study were designed as 1) varying the type (i.e., providing rewards and penalties) of incentives and 2) varying the frequency of feedback about ones' own compliance status during tasks. The effects of the scenarios were compared to the average compliance rates of three safety regulations (i.e., personal protective equipment self-monitoring hazard avoidance, and arranging the safety hook) for each scenario. The results show that 1) rewarding a good-compliance is more effective when there is no feedback on compliance status, and 2) penalizing non-compliance is more effective when there are three feedbacks during the tasks. This study provides a more accurate assessment of safety incentives and their effectiveness by focusing on safe behaviors to promote safety compliance among construction workers.

Correlation Among Neighborhood-level Measures of the Tobacco Retail Environment.

Tobacco retailer density and distance to tobacco retailers are understood to influence tobacco-related behaviors; however, there is no general agreement on how to best characterize or measure the tobacco retail environment (TRE). In this data-driven analysis, we examine similarities among neighborhood-level measures of the TRE and assess how geographic resolution of the neighborhood units may affect them. We used locations of likely tobacco retailers in the United States (US) to calculate multiple retailer count, density, and distance measures. Measures were calculated at the Census block group, tract, and county (including county equivalents) levels of geographic aggregation. Spearman's correlation was used to evaluate similarity among the TRE measures. At the block group and tract level, correlation among all TRE measures ranged from slightly negative (ρ = -0.03) to nearly perfect (ρ = 0.99). At both levels of aggregation, distance-based TRE measures were highly correlated (ρ > 0.76). At the block group level, simple count of retailers was highly correlated with the density measures (ρ > 0.83), and at the tract level, simple count was moderately to highly correlated with the density measures (ρ > 0.5). Findings were generally similar at the county level; a notable deviation was that retailers per person was negatively correlated with all other TRE measures (range from ρ = -0.08 to ρ = -0.32). Some common measures were not correlated, suggesting they capture different aspects of the TRE; similarity among the various measures also varied by level of geographic aggregation. Because the tobacco retail environment shapes people's tobacco-related behaviors, using appropriate measures to characterize it at a neighborhood-level is paramount. Our work highlights both the similarities and differences among a set of common measures, thereby suggesting the measures may be capturing different aspects of the overall retail environment. Our findings regarding geographic level of aggregation underscore the importance of neighborhood definition in any tobacco retail environment analysis.

Continuous remote monitoring of neurophysiologic Immersion accurately predicts mood.

Mental health professionals have relied primarily on clinical evaluations to identify in vivo pathology. As a result, mental health is largely reactive rather than proactive. In an effort to proactively assess mood, we collected continuous neurophysiologic data for ambulatory individuals 8-10 h a day at 1 Hz for 3 weeks (N = 24). Data were obtained using a commercial neuroscience platform (Immersion Neuroscience) that quantifies the neural value of social-emotional experiences. These data were related to self-reported mood and energy to assess their predictive accuracy. Statistical analyses quantified neurophysiologic troughs by the length and depth of social-emotional events with low values and neurophysiologic peaks as the complement. Participants in the study had an average of 2.25 (SD = 3.70, Min = 0, Max = 25) neurophysiologic troughs per day and 3.28 (SD = 3.97, Min = 0, Max = 25) peaks. The number of troughs and peaks predicted daily mood with 90% accuracy using least squares regressions and machine learning models. The analysis also showed that women were more prone to low mood compared to men. Our approach demonstrates that a simple count variable derived from a commercially-available platform is a viable way to assess low mood and low energy in populations vulnerable to mood disorders. In addition, peak Immersion events, which are mood-enhancing, may be an effective measure of thriving in adults.

Protocol for the development and validation of a Polypharmacy Assessment Score

BackgroundAn increasing number of people are using multiple medications each day, named polypharmacy. This is driven by an ageing population, increasing multimorbidity, and single disease-focussed guidelines. Medications carry obvious benefits, yet polypharmacy is also linked to adverse consequences including adverse drug events, drug-drug and drug-disease interactions, poor patient experience and wasted resources. Problematic polypharmacy is ‘the prescribing of multiple medicines inappropriately, or where the intended benefits are not realised’. Identifying people with problematic polypharmacy is complex, as multiple medicines can be suitable for people with several chronic conditions requiring more treatment. Hence, polypharmacy is often potentially problematic, rather than always inappropriate, dependent on clinical context and individual benefit vs risk. There is a need to improve how we identify and evaluate these patients by extending beyond simple counts of medicines to include individual factors and long-term conditions.AimTo produce a Polypharmacy Assessment Score to identify a population with unusual levels of prescribing who may be at risk of potentially problematic polypharmacy.MethodsAnalyses will be performed in three parts:1. A prediction model will be constructed using observed medications count as the dependent variable, with age, gender and long-term conditions as independent variables. A ‘Polypharmacy Assessment Score’ will then be constructed through calculating the differences between the observed and expected count of prescribed medications, thereby highlighting people that have unexpected levels of prescribing.Parts 2 and 3 will examine different aspects of validity of the Polypharmacy Assessment Score:2. To assess ‘construct validity’, cross-sectional analyses will evaluate high-risk prescribing within populations defined by a range of Polypharmacy Assessment Scores, using both explicit (STOPP/START criteria) and implicit (Medication Appropriateness Index) measures of inappropriate prescribing.3. To assess ‘predictive validity’, a retrospective cohort study will explore differences in clinical outcomes (adverse drug reactions, unplanned hospitalisation and all-cause mortality) between differing scores.DiscussionDeveloping a cross-cutting measure of polypharmacy may allow healthcare professionals to prioritise and risk stratify patients with polypharmacy using unusual levels of prescribing. This would be an improvement from current approaches of either using simple cutoffs or narrow prescribing criteria.

Comparative analysis of genetic risk scores for predicting biochemical recurrence in prostate cancer patients after radical prostatectomy

BackgroundIn recent years, Genome-Wide Association Studies (GWAS) has identified risk variants related to complex diseases, but most genetic variants have less impact on phenotypes. To solve the above problems, methods that can use variants with low genetic effects, such as genetic risk score (GRS), have been developed to predict disease risk.MethodsAs the GRS model with the most incredible prediction power for complex diseases has not been determined, our study used simulation data and prostate cancer data to explore the disease prediction power of three GRS models, including the simple count genetic risk score (SC-GRS), the direct logistic regression genetic risk score (DL-GRS), and the explained variance weighted GRS based on directed logistic regression (EVDL-GRS).Results and ConclusionsWe used 26 SNPs to establish GRS models to predict the risk of biochemical recurrence (BCR) after radical prostatectomy. Combining clinical variables such as age at diagnosis, body mass index, prostate-specific antigen, Gleason score, pathologic T stage, and surgical margin and GRS models has better predictive power for BCR. The results of simulation data (statistical power = 0.707) and prostate cancer data (area under curve = 0.8462) show that DL-GRS has the best prediction performance. The rs455192 was the most relevant locus for BCR (p = 2.496 × 10–6) in our study.

The Role of Depression, Anxiety, Stress, and Aggression in the Developing Hypertension Tendencies among Young Adults

The main purpose of this study is to determine how depression, anxiety, stress, and aggression relate to young adults diagnosed with hypertension. In this study, a correlational research design is used. The target population for this study was chosen using a purposive technique. The final sample comprised 200 people, equally divided across the genders (n = 100) female and (n = 100) male. Simple counts, simple percentages, mean, and standard deviation were all part of the descriptive analysis. The study's hypotheses are tested using inferential statistics, such as person correlation, multiple linear regression, and the t-test of independent samples analysis. Depression, anxiety, stress, and aggression are measured using the appropriate scales. SPSS is used to examine the data. Recommendations, consequences, and limits of the current study are discussed in the conclusion of the thesis.

ASUU Strike in Nigerian Universities: Implications for Students in Olabisi Onabanjo University, Nigeria

Abstract The strike embarked upon by the Academic Staff Union of Universities (ASUU) in Nigeria has significant impact on different stakeholders. Hence, this study investigated the implication of ASUU strike on students in Olabisi Onabanjo University, Ago-Iwoye, Ogun State, by examining the lifestyle of students during ASUU strike; its effects; and the coping strategies employed by the students during the strike. This study was conducted among undergraduates of Olabisi Onabanjo University, Ago-Iwoye. Cross-sectional survey design was used and 132 undergraduates were sampled using convenience sampling. Primary data were collected through the questionnaire, and the data were analysed using descriptive statistics such as simple percentage and frequency count. Results showed that more students engaged in actively participating in social media and praying for the strike to be over, relaxation, and learning of skills while gardening, getting a certification course or interim job were the least engaged by students during the ASUU strike. The results above indicated that boredom was the highest effect of ASUU on students’ lifestyle, followed by worry and by anxiety while mental issues was the least felt consequence of ASUU strike by students. The study also revealed that the students employed some coping mechanism such as praying for an end to the strike, social media usage, learning a skill and even sleeping to mitigate the implications of ASUU strike. The study then concluded that the disruption of academic activities during the ASUU strike made students engage in different lifestyles while overcoming its effects by using coping strategies.

The relationship between clinical symptoms of oral lichen planus and quality of life related to oral health

IntroductionOral Lichen Planus (OLP) is a chronic and relatively common mucocutaneous disease that often affects the oral mucosa. Although, OLP is generally not life-threatening, its consequences can significantly impact the quality of life in physical, psychological, and social aspects. Therefore, the aim of this research is to investigate the relationship between clinical symptoms of OLP and oral health-related quality of life in patients using the OHIP-14 (Oral Health Impact Profile-14) questionnaire.Materials and methodsThis descriptive-analytical study has a cross-sectional design, with case–control comparison. In this study, 56 individuals were examined as cases, and 68 individuals were included as controls. After recording demographic characteristics and clinical features by reviewing patients' records, the OHIP-14 questionnaire including clinical severity of lesions assessed using the Thongprasom scoring system, and pain assessed by the Visual Analog Scale (VAS) were completed. The ADD (Additive) and SC (Simple Count) methods were used for scoring, and data analysis was performed using the T-test, Mann–Whitney U test, Chi-Square, Spearman's Correlation Coefficient, and SPSS 24.ResultsNearly all patients (50 individuals, 89.3%) reported having pain, although the average pain intensity was mostly mild. This disease has affected the quality of life in 82% of the patients (46 individuals). The patient group, in comparison to the control group, significantly expressed a lower quality of life in terms of functional limitations and physical disability. There was a statistically significant positive correlation between clinical symptoms of OLP, gender, location (palate), and clinical presentation type (erosive, reticular, and bullous) of OLP lesions with OHIP-14 scores, although the number or bilaterality of lesions and patient age did not have any significant correlation with pain or OHIP scores.ConclusionIt appears that certain aspects of oral health-related quality of life decrease in patients with OLP, and that of the OLP patient group is significantly lower in terms of functional limitations and physical disability compared to the control group. Additionally, there was a significant correlation between clinical symptoms of OLP and pain as well as OHIP scores.

Using New Integrated Distance Sampling Models for Simple Point Counts

Using New Integrated Distance Sampling Models for Simple Point Counts

Strategies for Managing Born-Digital Record in University Libraries: A Study of Federal University of Petroleum Resources Effurun

This study used the Federal University of Petroleum Resources, Effurun Library as a case study to investigate strategies for managing born-digital records in the university library. The study aims to ascertain the types of born-digital records available in FUPRE library, the strategies used for managing born-digital records, challenges of managing born-digital records. To achieve these objectives, the descriptive survey research was adopted. This research method was considered appropriate by the researchers because it allows for systematic collection and analysis of data to describe characteristics, behaviors, or opinions within a specific population. Hence it will help to provide insights into the current strategies employed by FUPRE library for managing born-digital records. The questionnaire was the instrument used for data collection and the data collected for the study were analyzed using simple percentages, frequency counts, and bar charts. The study found that: born-digital records such as test-based documents (for example Word documents, and Google documents), etc., library presentations e.g., PowerPoint, spreadsheets e.g., Excel, digital documents e.g., PDFs, and electronic memos are the born-digital records are available in FUPRE library; the only policy in place regarding the management of born-digital records is the policy on storage of born-digital records. The study also found that the library’s strategies for preserving born-digital records are refreshing, migration, and replication and that their strategy for disposing of born-digital records is deletion while the challenges of managing born-digital records are technological obsolescence, lack/poor digital storage facilities, copyright, and intellectual property rights issues among others. These findings contribute to the understanding of current practices and challenges in managing born-digital records within university libraries, specifically at the Federal University of Petroleum Resources Effurun (FUPRE) library. The study recommends that the library management should formulate policies that will cater to the creation/generation, preservation, transfer/exchange as well as the disposition of born-digital records giving them direction when it comes to managing born-digital records in the library among others.

Integrated distance sampling models for simple point counts.

Point counts (PCs) are widely used in biodiversity surveys but, despite numerous advantages, simple PCs suffer from several problems: detectability, and therefore abundance, is unknown; systematic spatiotemporal variation in detectability yields biased inferences, and unknown survey area prevents formal density estimation and scaling-up to the landscape level. We introduce integrated distance sampling (IDS) models that combine distance sampling (DS) with simple PC or detection/nondetection (DND) data to capitalize on the strengths and mitigate the weaknesses of each data type. Key to IDS models is the view of simple PC and DND data as aggregations of latent DS surveys that observe the same underlying density process. This enables the estimation of separate detection functions, along with distinct covariate effects, for all data types. Additional information from repeat or time-removal surveys, or variable survey duration, enables the separate estimation of the availability and perceptibility components of detectability with DS and PC data. IDS models reconcile spatial and temporal mismatches among data sets and solve the above-mentioned problems of simple PC and DND data. To fit IDS models, we provide JAGS code and the new "IDS()" function in the R package unmarked. Extant citizen-science data generally lack the information necessary to adjust for detection biases, but IDS models address this shortcoming, thus greatly extending the utility and reach of these data. In addition, they enable formal density estimation in hybrid designs, which efficiently combine DS with distance-free, point-based PC or DND surveys. We believe that IDS models have considerable scope in ecology, management, and monitoring.