Generalized Linear Mixed Models Research Articles

Using equivalence tests in higher tier studies of honey bees under the revised EFSA Bee Guidance-How?

The proposed use of equivalence tests instead of difference tests in the revised guidance on the risk assessment of plant protection products for bees is a reasonable approach given an adverse effect was observed in the lower tier studies, using the hypothesis that there is a risk as the null hypothesis places the burden to prove the opposite on the other side. However, some uncertainties regarding the application of equivalence tests in field studies are discussed in the present study. Here, we compare equivalence and difference testing methods using a control dataset of a honey bee field effect study conducted in northern Germany in 2014. Half of the 48 colonies were assigned to a hypothetical test item group, and the colony strength data were analyzed using t-tests, a generalized linear mixed model (GLMM), and the corresponding equivalence tests. The data reflected the natural variability of honey bee colonies, with initially approximately 12 000 adult bees. Although the t-test and GLMM confirmed that 24 + 24 colonies are sufficient to show "no adverse effect," the equivalence tests of the t-test and GLMM were not able to reject the null hypothesis and classified at least some of the assessments as "high risk," indicating a power that was too low. Based on this, different operating options to reduce the variability are discussed. One possible option, which may provide a more realistic application of equivalence to avoid false high risk, is to consider the lower confidence interval of the control as a baseline and use GLMMs. With this option, we demonstrate a relatively acceptable probability to prove that no high risk for initially similar groups can be achieved. Further studies with different numbers of colonies are still needed to develop and validate the suggested approach. Integr Environ Assess Manag 2024;20:1496-1503. © 2024 SETAC.

Irregular longitudinal data analysis with statistical and machine learning methods for hazardous asteroids

Observations of the asteroids have been performed as long as it has been feasible by the available observational equipment. Recorded data, going back to 18th century, allowed a classification of these celestial objects’ hazardous status. Unfortunately, previous studies used methods that ignore subject dependency in Near-Earth Asteroids (NEA) data. This study aims to perform hazard classification of asteroids by proposing various statistical and machine learning methods on NEA data to overcome these shortcomings. We analyze data from 751 asteroids observed at irregular time intervals through the NASA. We compare algorithms suitable for longitudinal data structure, such as the Generalized Linear Mixed Models (GLMM), marginal model, GLMM-Tree, Historical Random Forest, GPBoost, and Spline. To the best of our knowledge and based on a comprehensive review of the existing literature, our study stands as the pioneering in the utilization of these advanced methodologies for the in-depth analysis of Near-Earth Asteroid (NEA) data. According to the findings, the accuracies of the models range from 0.89 to 0.99. The GPBoost model has the highest performance, while the marginal model has the poorest one.

Using infrared thermography to determine changes in teat skin surface temperature after machine milking in dairy cows

Mastitis is among the costliest diseases affecting dairy cows, partly due to the resulting permanent reduction in the quantity and quality of milk produced. Most mastitis cases involve pathogenic organisms entering the cow's mammary gland through the teat canal. The teat has natural defenses against these pathogens that can be disrupted during milk harvesting. These disruptions of the teat's circulatory system and tissue integrity can predispose them to mastitis. Traditionally, machine milking–induced changes in teat blood circulation and tissue integrity have been assessed by means of manual evaluation and ultrasonography. Infrared thermography has previously been shown to produce precise and consistent measurements of skin surface temperatures (SST) on cows' hind teats. Our objective was to describe the variability in the teat SST following machine milking. Describing the variability in teat SST before and after milking could be useful to guide further studies to elucidate the physiology of the effects of milking on teat defense mechanisms. In this observational study, thermographic images of both hind teats from 140 cows immediately pre- and postmachine milking were analyzed. The average SST were subsequently determined at the proximal, middle, and distal aspects of each hind teat using image analysis software. The LSM (95% CI) from general linear mixed models of the pre- and postmilking SST, respectively, were 33.6 (33.5–33.8)°C and 35.4 (35.3–35.5)°C at the proximal aspect, 33.2 (33.1–33.4)°C and 35.2 (35.1–35.3)°C at the middle aspect, and 32.3 (32.1–32.5)°C and 34.0 (33.9–34.1)°C at the distal aspect. The observed increase in SST from pre- to postmilking SST at all 3 aspects of the teat suggest that some of the variability in the SST can be attributed to the milking event. Future research is warranted to investigate the biological relevance of SST changes during machine milking and any potential change in teat defense mechanisms, risk of mastitis, or other pathologies.

Safety and efficacy of pelvic arterial embolization for primary postpartum hemorrhage in hemodynamically stable and hemodynamically unstable patients: Is it “time” for a paradigm change?

BackgroundPelvic artery embolization (PAE) is an effective and safe technique for treating postpartum hemorrhage (PPH) with hemodynamic stability. However, its use in hemodynamically unstable patients remains controversial. PurposeTo determine the safety and efficacy of pelvic arterial embolization (PAE) according to the hemodynamic state of primary postpartum hemorrhage (PPH) patients. MethodsThis cohort study was conducted retrospectively, using data from January 2004 to December 2021, in a resource-rich setting at a tertiary Level 1 trauma academic center. A total of 437 patients were diagnosed with PPH during the study period. Of these 437 patients, 161 with primary PPH who underwent PAE were enrolled in the study. The outcomes assessed included the clinical success rate, mortality, the overall success rate, predictive factors for failed PAE, and time-dependent changes in hemodynamic parameters, such as systolic blood pressure (SBP), heart rate (HR), and shock index (SI). Propensity score (PS) matching analysis was performed to assess the influence of specific variables or conditions on the outcomes. ResultsOf the 161 patients who underwent PAE for primary PPH (mean age, 32.9 ± 4.3 [SD]), 85 were retrospectively categorized as having hemodynamic stability (mean age, 32.6 ± 4.1 [SD]), while 76 were categorized as having hemodynamic instability (mean age, 33.3 ± 4.4 [SD]). This study showed PAE for primary PPH had a success rate of 91.9 %, with no significant difference in mortality rates between the groups. The clinical success rate was 98.8 % for patients with hemodynamic stability and 84.2 % for those with hemodynamic instability (p < .001). The overall success rate was 98.8 % for hemodynamic stability and 89.5 % for hemodynamic instability (p = .014). After propensity score matching, the clinical success rate was higher in hemodynamically stable patients than in unstable ones (100 % vs. 86.3 %, p = .013). However, there was no significant difference in the overall success rate (100 % vs. 90.2 %, p = .056). Among the PS-matched population, predictive factors for the failed PAE in primary PPH were hemodynamic instability (adjusted odds ratio [aOR] 21.22, 95 % CI 1.27-355.76; p = .034) and emergency Cesarean delivery with accompanying hemorrhag (aOR 54.00, 95 % CI 11.93-244.56; p = .008). In three groups within a PS-matched population — hemodynamically stable, unstable with successful outcomes, and unstable with unsuccessful outcomes, a generalized linear mixed model (GLMM) analysis for time-dependent changes in hemodynamic parameters revealed a statistically significant difference in SBP, HR, and SI at various time points. ConclusionPelvic arterial embolization of primary postpartum bleeding in hemodynamic instability has been identified as an alternative, safe, and effective life-saving procedure for multidisciplinary treatment in resource-rich environments even after the baseline characteristics are balanced by the PS matching, suggesting it is a primary care option.

Impact and process evaluation of a primary-school Food Education and Sustainability Training (FEAST) program in 10-12-year-old children in Australia: pragmatic cluster non-randomized controlled trial

BackgroundEnvironmentally sustainable food initiatives accompanying nutrition education, such as the Food Education and Sustainability Training (FEAST) program, have gained traction in school settings. The aim of this trial was to conduct an impact and process evaluation of FEAST, to evaluate its effect on children’s fruit and vegetable (F&V) intakes, and secondary outcomes: F&V variety consumed, nutrition knowledge, food preparation/cooking skills, self-efficacy and behaviours, food waste knowledge and behaviours, and food production knowledge.MethodsFEAST was a 10-week curriculum-aligned program, designed to educate children about healthy eating, food waste, and sustainability, while teaching cooking skills. It was implemented by classroom teachers, face-to-face and online, during COVID-19 school closures, in Australia in 2021. A custom designed survey was used to collect baseline and post-intervention data from students. Generalised linear mixed models (GLMM) estimated group differences in pre-post changes for primary and secondary outcomes. Surveys were also administered to students and teachers to evaluate intervention implementation.ResultsTwenty schools participated and self-selected to be either intervention schools (n = 10) or wait-list control (WLC) schools (n = 10). A total of 977, 5th and 6th grade children participated in the trial with a mean age of 11.1 years (SD ± 0.7). The FEAST intervention, compared to WLC, did not result in significant increases in primary outcomes nor secondary outcomes. The process evaluation revealed FEAST was well-received by students and teachers, but COVID-19 school closures hindered implementation fidelity with a less intense program delivered under the constraints of pandemic lockdowns.ConclusionsThis is the first cluster non-randomized controlled trial designed to independently evaluate FEAST in the primary-school setting. No evidence was found for improved F&V intakes in children, nor secondary outcomes. However, the positive process evaluation results suggest that further trials of the program are warranted. If implemented as originally designed (pre-pandemic), with increased duration and complemented by supporting school policies, such programs have the potential to improve children’s daily F&V intakes, cooking skills and food waste behaviours. This would support the Australian curriculum and contribute to: health promotion within schools and sustainable schools initiatives, the national agenda to reduce food waste and sustainable development goals.Australian and New Zealand Clinical Trials Registry[ACTRN12620001347954]- Registered prospectively on 14/12/2020.

Effect of particulate matter on continuous positive airway pressure adherence in obstructive sleep apnea patients.

Sleep quality could be affected by air pollution, especially for particulate matter with a diameter of less than 10 microns (PM10) and particulate matter with a diameter of less than 2.5 microns (PM2.5). However, no direct study demonstrates the relationship and impact of air pollution especially PM10 and PM2.5 on continuous positive airway pressure (CPAP) adherence. Thus, we aimed to study the correlation between PM10, PM2.5, and low CPAP adherence in subjects with obstructive sleep apnea (OSA). We conducted a time-series study from August 2016 to May 2022 in Chiang Mai, Thailand. The data from 2,686 visits of CPAP compliance records from 839 OSA patients' electronic medical records at the Sleep Disorders Center, Center of Medical Excellence, Chiang Mai University, Chiang Mai, Thailand were reviewed. The level of adherence was determined utilizing the provided data. Low CPAP adherence was defined as using CPAP for less than 240 minutes per night or less than 70% of nights (i.e., <5 nights/week) in the previous month. The correlation between the monthly average of PM10 and PM2.5 and the rate of low CPAP adherence was analyzed using generalized linear mixed model (GLMM) after adjustment for confounding factors. There was no effect of an increase in PM10 and PM2.5 on low CPAP adherence [adjusted risk ratio (RR) =0.97; 95% confidence interval (CI): 0.87, 1.09; P value =0.624 and adjusted RR =0.93; 95% CI: 0.81, 1.08; P value =0.350 for PM10 and PM2.5, respectively]. There was no effect of particulate matter on CPAP adherence in OSA patients.

Pairwise fitting of piecewise mixed models for the joint modeling of multivariate longitudinal outcomes, in a randomized crossover trial.

Many statistical models have been proposed in the literature for the analysis of longitudinal data. One may propose to model two or more correlated longitudinal processes simultaneously, with a goal of understanding their association over time. Joint modeling is then required to carefully study the association structure among the outcomes as well as drawing joint inferences about the different outcomes. In this study, we sought to model the associations among six nutrition outcomes while circumventing the computational challenge posed by their clustered and high-dimensional nature. We analyzed data from a 2 2 randomized crossover trial conducted in Kenya, to compare the effect of high-dose and low-dose iodine in household salt on systolic blood pressure (SBP) and diastolic blood pressure (DBP) in women of reproductive age and their household matching pair of school-aged children. Two additional outcomes, namely, urinary iodine concentration (UIC) in women and children were measured repeatedly to monitor the amount of iodine excreted through urine. We extended the model proposed by Mwangi etal. (2021, Communications in Statistics: Case Studies, Data Analysis and Applications, 7(3), 413-431) allowing flexible piecewise joint models for six outcomes to depend on separate random effects, which are themselves correlated. This entailed fitting 15 bivariate general linear mixed models and deriving inference for the joint model using pseudo-likelihood theory. We analyzed the outcomes separately and jointly using piecewise linear mixed-effects (PLME) model and further validated the results using current state-of-the-art Jones and Kenward methodology (JKME model) used for analyzing randomized crossover trials. The results indicate that high-dose iodine in salt significantly reduced blood pressure (BP) compared to low-dose iodine in salt. Estimates for the random effects and residual error components showed that SBP and DBP had strong positive correlation, with effect of the random slope indicating that significantly related outcomes are strongly associated in their evolution. There was a moderately strong inverse relationship between evolutions of UIC and BP both in women and children. These findings confirmed the original hypothesis that high-dose iodine salt has significant lowering effect on BP. We further sought to evaluate the performance of our proposed PLME model against the widely used JKME model, within the multivariate joint modeling framework through a simulation study mimicking a crossover design. From our findings, the multivariate joint PLME model performed exceptionally well both in estimation of random-effects matrix (G) and Hessian matrix (H), allowing satisfactory model convergence during estimation. It allowed a more complex fit to the data with both random intercepts and slopes effects compared to the multivariate joint JKME model that allowed for random intercepts only. When a hierarchical viewpoint is adopted, in the sense that outcomes are specified conditionally upon random effects, the variance-covariance matrix of the random effects must be positive definite. In some cases, additional random effects could explain much variability in the data, thus improving precision in estimation of the estimands (effect size) parameters. The key highlight in this evaluation shows that multivariate joint JKME model is a powerful tool especially while fitting mixed models with random intercepts only, in crossover design settings. Addition of random slopes may lead to model complexities in most cases, resulting in unsatisfactory model convergence during estimation. To circumvent convergence pitfalls, extention of JKME model to PLME model allows a more flexible fit to the data (generated from crossover design settings), especially in the multivariate joint modelingframework.

How does diversity affect the effectiveness of capacity building training? Evidence from the Republic of Korea

AbstractMotivationPrevious studies on the effectiveness of capacity building training, drawn from the experience of traditional donors, have been limited in their understanding the impact of the diversity of trainees and the diversity of training on the effectiveness of training. This is particularly problematic given the increasing prevalence of such training and the emergence of new donors with different approaches.PurposeThis article investigates the effectiveness of capacity‐building training across different participants and different training types, through the case of an emerging donor, the Republic of Korea (Korea). Korea is distinctive and under‐researched as a country relatively late to join the OECD's Development Assistance Committee (DAC), with several policies explicitly locating capacity‐building training as a diplomatic strategy. Korea has made repeated efforts to diversify participants and types of training to gain a comparative advantage in international development and co‐operation.Methods and ApproachThe study constructs a generalized linear mixed model (GLMM) to analyse the effectiveness of training across layers of individual diversity (gender, rank, level of national income and extent of democracy) and group diversity (types of trainings). It draws on survey responses from 789 government officials in low‐ and middle‐income countries (LMICs).FindingsTraining effectiveness differs for diverse participants and training types. Effectiveness tends to decrease as job rank and national income rise, while it increases with the level of democracy. Training that fosters diverse interactions and experiences, such as multi‐country training and invitational training, tends to be more effective than other types.Policy ImplicationsOur results suggest implementing more collaborative and customized training to suit the heterogeneous needs of diverse participants. The results emphasize the need to develop and operate various training types that promote diverse interactions and experiences among participants.

PERFORMANCE OF NEURAL NETWORK IN PREDICTING MENTAL HEALTH STATUS OF PATIENTS WITH PULMONARY TUBERCULOSIS: A LONGITUDINAL STUDY

Comorbidity between pulmonary tuberculosis and mental health status requires effective psychiatric treatment. This study aims to predict anxiety and depression levels in patients with pulmonary tuberculosis and consider future mental health treatment for patients. A sample of 60 pulmonary tuberculosis patients in Malang were involved and evaluated longitudinally every two weeks over 13 periods. In this study, we use the Generalized Neural Network Mixed Model (GNMM) to obtain better results in predicting anxiety and depression levels in patients with pulmonary tuberculosis and compare the results with the Generalized Linear Mixed Model (GLMM). The flexibility of GLMM in modeling longitudinal data, and the power of neural network in performing a prediction makes GNMM a powerful tool for predicting longitudinal data. The result shows that neural network's prediction performance is better than the classical GLMM with a smaller MSPE and fairly accurate prediction. The MSPEs of the three compared models: 1-Layer GNMM, 2-Layer, and GLMM, respectively are 0.0067, 0.0075, 0.0321 for the anxiety levels, and 0.0071, 0.0002, and 0.0775 for the depression levels. Furthermore, future research needs to investigate the data with a larger sample size or high dimensional data with large network architectures to prove the robustness of GNMM.

Multilevel modeling in single-case studies with zero-inflated and overdispersed count data.

Count outcomes are frequently encountered in single-case experimental designs (SCEDs). Generalized linear mixed models (GLMMs) have shown promise in handling overdispersed count data. However, the presence of excessive zeros in the baseline phase of SCEDs introduces a more complex issue known as zero-inflation, often overlooked by researchers. This study aimed to deal with zero-inflated and overdispersed count data within a multiple-baseline design (MBD) in single-case studies. It examined the performance of various GLMMs (Poisson, negative binomial [NB], zero-inflated Poisson [ZIP], and zero-inflated negative binomial [ZINB] models) in estimating treatment effects and generating inferential statistics. Additionally, a real example was used to demonstrate the analysis of zero-inflated and overdispersed count data. The simulation results indicated that the ZINB model provided accurate estimates for treatment effects, while the other three models yielded biased estimates. The inferential statistics obtained from the ZINB model were reliable when the baseline rate was low. However, when the data were overdispersed but not zero-inflated, both the ZINB and ZIP models exhibited poor performance in accurately estimating treatment effects. These findings contribute to our understanding of using GLMMs to handle zero-inflated and overdispersed count data in SCEDs. The implications, limitations, and future research directions are also discussed.

Physical activity and menopausal symptoms: evaluating the contribution of obesity, fitness, and ambient air pollution status.

The menopausal transition is accompanied by transient symptoms that have been linked to subclinical cardiovascular disease (CVD); CVD has also been linked to air pollution. Physical activity (PA) reduces CVD, improves body composition, and can reduce menopausal symptoms. The purpose of this study was to assess the links between PA and menopausal symptoms and whether obesity, fitness, and air pollution status play a role in this relationship. Women (40-60 y; N = 243; mean [SD] age, 47.8 [5.6] y) from areas with high versus low air pollution enrolled in the Healthy Aging in Industrial Environment Program 4 prospective cohort study completed psychological, cardiorespiratory fitness, body composition, and menopausal status screening followed by a 14-day prospective assessment of menopausal symptoms (Menopause Rating Scale) using a mobile application. Daily PA was assessed objectively across 14 days via Fitbit Charge 3 monitor. General linear mixed models were conducted and controlled for age, menopausal status, day in the study, wear time, and neuroticism. Peri/postmenopausal women ( β = 0.43, P < 0.001) and those residing in a high-air-pollution environment ( β = 0.45, P < 0.05) reported more somatovegetative symptoms. Hot flashes alone were associated with peri/postmenopausal status ( β = 0.45, P < 0.001), and for women residing in a high-air-pollution environment, lower reporting of hot flashes was observed on days when a woman was more physically active than usual ( β = -0.15, P < 0.001). No associations were found for cardiorespiratory fitness and visceral fat with any of the symptoms. PA may enhance resilience to hot flashes, especially when residing in high-air-pollution environments where we also observed higher reporting of somatovegetative menopausal symptoms.

Impact of weirs in altering benthic macroinvertebrate assemblages and composition structure in the Luvuvhu River Catchment, South Africa

Stream flow weirs disrupt river flow regimes, physical conditions, and biological composition of rivers, posing significant threat to the river’s functionality, integrity, and sustainability. Home to diverse aquatic organisms, there is a lack of impact assessment of weirs on the stream of the Luvuvhu River Catchment (LRC). The aim of this study was to examine the impact of six weirs on aquatic macroinvertebrate assemblages and composition across five streams. A total of six sampling surveys on macroinvertebrates and physico-chemical parameters were conducted upstream and downstream of six weirs in 12 months between June 2021 and June 2022. The South African Scoring System score (SASS score) and Average Score per Taxon (ASPT) indices were used to compare organisms’ response between upstream and downstream of weirs. Generalized linear mixed models (GLMM) were used to determine the effect of physico-chemical variables on macroinvertebrate assemblage, while the CCA was employed to assess similarities between downstream and upstream sampling points across various sites. A total of 18,914 macroinvertebrate individuals were observed from 65 families during the survey. In upstream sections, the SASS score was driven by habitat integrity, electrical conductivity, and water depth, while ASPT responded significantly to habitat integrity, pH, dissolved oxygen and electrical conductivity. In the downstream sections, the SASS score increased with an increasing habitat integrity score and river width, while decreasing with elevation and pH levels. ASPT increased with increasing habitat integrity and elevation in the downstream sections, while decreasing with increasing river width and water temperature. This study’s findings suggest habitat integrity is largely driving aquatic abundance and assemblage in the LRC, and it is therefore important to maintain the ecological integrity of rivers.

Associations Among Wound-Related Factors Including Biofilm, Wound-Related Symptoms and Systemic Inflammation in Older Adults with Chronic Venous Leg Ulcers.

Objective: The purposes of this observational prospective study were to (1) characterize the wound-related factors (wound area, the presence of biofilm, and total bacteria), wound-related symptoms (fatigue, pain, exudate, itching, and edema or swelling), and systemic inflammation (level of serum C-reactive protein [CRP]), and (2) explore associations between wound-related factors, wound-related symptoms, and systemic inflammation in older individuals with chronic venous leg ulcers (CVLUs) over 8 weeks of wound treatment. Approach: A total of 117 participants who received standardized care (weekly sharp debridement) for chronic venous ulcer were enrolled. We collected clinical data every 2 weeks during the 8 weeks of the study period or until the wound was healed (if healed before 8 weeks). Associations among variables were estimated using a Bayesian approach applied to general linear mixed models. Results: Based on Bayes factor (BF) value, there was extremely strong evidence for the association of biofilm with mean total bacteria (BF >1,000). There was moderate evidence of a direct association between biofilm presence and levels of CRP (BF 4.3) and moderate evidence of direct associations between biofilm and wound-related symptoms, pain and exudate (BF 5.12, 8.49, respectively). Innovation: Wound-related symptoms and the level of systemic CRP were associated with biofilm among patients who were receiving weekly sharp debridement. Symptom severity associated with CVLUs requires assessment and management of wound-related factors and levels of inflammation in addition to symptom assessment. Conclusion: This study is the first to examine associations among biofilm, as wound-related factors, systemic inflammation, wound-related symptoms, and wound healing in clinical settings. Symptom severity, level of systemic CRP, and wound-related factors should be considered as well as assessment of biofilm in CVLU in older individuals with CVLU.

The effects of maternal calcium status during late gestation on lamb growth and survival in twin-bearing Merino ewes grazing pasture.

Our project aimed to investigate whether low maternal calcium status during late gestation decreased weight, growth and survival of lambs born to twin-bearing Merino ewes grazing pasture. On day 130 of gestation, approximately a 10 mL blood sample was collected from 108 twin-bearing Merino ewes. Blood pH and calcium ion concentration were measured in whole blood and serum was analysed for calcium, magnesium, phosphate, beta hydroxy butyrate, non-esterified fatty acids and cholesterol. Six to 18 h after birth and at 49 days of age, lamb live weight was recorded. Ewe serum calcium level at day 130 of gestation were divided into tertiles (1.58-2.13, 2.14-2.30, and 2.31-2.99 mmol/L) with ewes classified as either Low, Med or High (n = 36 per group). A general linear mixed model was used to analyse the data. Survival to 1, 2, 3 and 7 days of age was lower for lambs born to ewes in the Low calcium group compared with those born in the Med and High calcium groups (P < 0.05). At day 49 of age, lamb survival tended to be lower for lambs in the Low (73.6%) compared with Med (86.8%) and High (85.3%) calcium groups (P < 0.1). There were no differences in lamb body weight (P > 0.05). Calcium levels of ewes in the Low calcium group were, on average, indicative of subclinical hypocalcaemia, with this group of ewes also having the lowest lamb survival rate, suggesting that maternal subclinical hypocalcaemia reduces lamb survival. Further studies, particularly on improving maternal calcium levels, are warranted.

DIF Detection for Multiple Groups: Comparing Three‐Level GLMMs and Multiple‐Group IRT Models

AbstractFor assessment scales applied to different groups (e.g., students from different states; patients in different countries), multigroup differential item functioning (MG‐DIF) needs to be evaluated in order to ensure that respondents with the same trait level but from different groups have equal response probabilities on a particular item. The current study compares two approaches for DIF detection: a multiple‐group item response theory (MG‐IRT) model and a generalized linear mixed model (GLMM). In the MG‐IRT model approach, item parameters are constrained to be equal across groups and DIF is evaluated for each item in each group. In the GLMM, groups are treated as random, and item difficulties are modeled as correlated random effects with a joint multivariate normal distribution. Its nested structure allows the estimation of item difficulty variances and covariances at the group level. We use an excerpt from the PISA 2015 reading domain as an exemplary empirical investigation, and conduct a simulation study to compare the performance of the two approaches. Results from the empirical investigation show that the detection of countries with DIF is similar in both approaches. Results from the simulation study confirm this finding and indicate slight advantages of the MG‐IRT model approach.

Evaluation of the DN-Mini (miniaturized double net) trap for sampling host-seeking Anopheles mosquitoes in malaria-endemic villages of southern Tanzania.

Surveillance of malaria vectors is crucial for assessing the transmission risk and impact of control measures. Human landing catches (HLC) directly estimate the biting rates but raise ethical concerns due to the exposure of volunteers to mosquito-borne pathogens. A common alternative is the CDC-light trap, which is effective for catching host-seeking mosquitoes indoors but not outdoors. New, exposure-free methods are needed for sampling mosquitoes indoors and outdoors in ways that reflect their natural risk profiles. The aim of this study was therefore to evaluate the efficacy of the miniaturized double net trap (DN-Mini) for sampling host-seeking mosquitoes in south-eastern Tanzania, where malaria transmission is dominated by Anopheles funestus. Adult mosquitoes were collected from 222 randomly selected houses across three villages (74 per village) in Ulanga district, south-eastern Tanzania, using the DN-Mini traps, CDC-Light traps, and Prokopack aspirators. First, we compared CDC-light and DN-Mini traps for collecting indoor host-seeking mosquitoes, while Prokopack aspirators were used for indoor-resting mosquitoes. Second, we deployed the DN-Mini and Prokopack aspirators to collect host-seeking and resting mosquitoes indoors and outdoors. Generalized linear mixed models (GLMM) with a negative binomial distribution were used to compare the effectiveness of the traps for catching different mosquito species. The DN-Mini was 1.53 times more efficient in collecting An. funestus indoors (RR = 1.53, 95% CI: 1.190-1.98) compared to the CDC-Light trap. However, for Anopheles arabiensis, the DN-Mini caught only 0.32 times as many mosquitoes indoors as the CDC-Light traps (RR = 0.32, 95% CI: 0.183-0.567). Both An. funestus and An. arabiensis were found to be more abundant indoors than outdoors when collected using the DN-Mini trap. Similarly, the Prokopack aspirator was greater indoors than outdoors for both An. funestus and An. arabiensis. The DN-Mini outperformed the CDC-light trap in sampling the dominant malaria vector, An. funestus species, but was less effective in capturing An. arabiensis, and for both vector species, the biting risk was greater indoors than outdoors when measured using the DN-Mini trap. These findings highlight the importance of selecting appropriate trapping methods based on mosquito species and behaviors.

The influence of body mass index on airway resistance in children with sickle cell disease: A longitudinal study based on impulse oscillometry

BackgroundImpulse oscillometry (IOS) is an effective tool for assessing airway mechanics and diagnosing obstructive airway disease (OAD) in children with sickle cell disease (C-SCD). Obesity is known to be associated with OAD, and untreated OAD often leads to hypoxia-related complications in C-SCD. Considering the increasing prevalence of obesity in C-SCD, it is important to explore the influence of body mass index (BMI) on OAD in this disease population. MethodsA longitudinal retrospective chart review was conducted on 55 C-SCD (161 IOS observations) and 35 non-SCD asthmatic children (C-Asthma) (58 observations), primarily to investigate the association between BMI and airway resistance in C-SCD and C-Asthma. We conducted generalized linear mixed models (GLMM), adjusted for pharmacotherapies, to demonstrate the influence of BMI on total (R5), central (R20), and peripheral (R5-20) airway resistance and reactance (X5, resonant frequency (Fres)). We further compared age, BMI, and IOS indices between C-SCD and C-Asthma using the Mann-Whitney test. ResultsAge and BMI were not statistically different between the two groups. In C-SCD, BMI was associated with R5 (GLMM t-statistics:3.75, 95%CI:1.01,3.27, p-value<0.001*) and R20 (t-statistics:4.01, 95%CI:1.04,1.15, p-value<0.001*), but not with R5-20 or airway reactance. In asthmatics, BMI was not associated with IOS estimates except Fres (t-statistics: 3.93, 95%CI: −0.06, −0.02, p-value<0.001*). C-SCD demonstrated higher airway resistances (R5 and R20) and reactance (Fres) compared to C-Asthma (Mann-Whitney: p-values<0.05). ConclusionBMI significantly influenced total and central airway resistance in C-SCD. While higher airway resistances reflected increased OAD in C-SCD than asthmatics, higher Fres perhaps indicated progressive pulmonary involvement in C-SCD.

Absence of lunar phobia in European swarming vespertilionid bats

“Lunar phobia” in bats has been widely discussed since its description in tropical bats in 1978. The phenomenon has been frequently contested and supported and was first reported in European bats in 2020. Our study seeks to clarify the debate by describing the relationship between the activity of selected swarming vespertilionid bats (Family: Vespertilionidae) and moonlight levels. To verify a potential connection to the latter, a swarming dataset was analysed in respect of estimated moonlight illumination. Moonlight estimates were based on geographical location and several lunar parameters, to accurately characterise the non-linear relationship between moon phase and illumination (lux). The swarming data consisted of 32 netting and 14 echolocation recording sessions collected between August and October 2014 and 2015. Our data included 3,265 netted bats from 13 species and 15,919 bat calls from 10 confirmed species. Data was collected at the large Central European hibernation/swarming site – Natura 2000 PLH080003 “Nietoperek” in western Poland (N 52.394400, E 15.480600). Generalised linear mixed models (GLMMs) determined insignificant relationships between bats and moonlight illumination. Our analysis confirms an absence of impact of moonlight intensity on swarming bats and thereby rejects the lunar phobia phenomena in at least six insectivorous bat species (Myotis myotis, M. daubentonii, M. nattereri, M. bechsteinii, Barbastella barbastellus, Plecotus auritus) swarming in the autumn.

E-bibliotherapy for improving the psychological well-being of informal caregivers of people with dementia: a randomized controlled trial protocol

BackgroundProviding informal care for individuals with dementia is frequently a challenging and demanding experience that can have detrimental effects on the psychological well-being of caregivers. Regrettably, community-based caregiver services often prove inadequate, highlighting the necessity for innovative approaches to support caregivers.AimTo test the efficacy of e-bibliotherapy in improving the psychological well-being of informal caregivers of people with dementia.MethodThe study is divided into two phases. In phase 1, the research team will co-design the e-bibliotherapy app with caregivers. In phase 2, a randomized controlled trial will be conducted among 192 informal caregivers of people with dementia in Hong Kong. Caregivers will be randomly assigned to either the e-bibliotherapy group or the control group using simple randomization. Outcome measures will encompass caregivers’ psychological well-being, caregiving appraisal, mental health, saliva cortisol levels as an indicator of stress, and health-related quality of life for caregivers. Data will be collected at baseline, immediately post intervention, and 3 months and 6 months post intervention. General linear mixed model will be employed to analyze intervention effects. Qualitative interviews will be undertaken to explore caregiver experiences within this study and evaluate intervention acceptability using conventional content analysis methods.DiscussionThis study represents a pioneering effort in utilizing e-bibliotherapy to enhance the psychological well-being of informal caregivers of individuals with dementia, addressing the existing gap in caregiver services and facilitating knowledge dissemination within the community.Trial registrationThe trial has been registered on ClinicalTrial.gov (Ref: NCT05927805).

Abstract TMP30: The Impact of Social Influences on Rehabilitation Services Utilization After Stroke

Introduction: Evidence supports that early initiation of rehabilitation is important for patient outcomes after stroke. Thus, determination of patients needing rehabilitation during their acute hospitalization is critical. We assessed the impact of demographic, clinical, and county-level social influences on rate of transfer to a rehabilitation facility after acute stroke hospitalizations. Methods: Using Get with the Guidelines-Stroke registry data and Institute for Health Metrics and Evaluation data, we fitted univariate and multivariate generalized linear mixed models (GLMM) with demographic, clinical, and social variables to determine how social influences of health impacted variances in transfers to rehabilitation facilities. Specific county-level variables assessed were related to education, income, employment, home ownership, and being foreign born. Results: Among 912,488 patients who were assessed or received rehabilitation services due to acute ischemic or intracerebral hemorrhagic stroke, 33.4% of them were transferred to rehabilitation facilities. Multivariate analyses of patient-level demographic and clinical variables achieved an Akaike Information Criterion (AIC) of 925780 (21.0% reduction from the base model) largely driven by clinical factors (mRS at discharge, initial NIHSS, and initial exam findings). When county-level variables related to social influences of health were incorporated, AIC decreased by 23.4% to 871806, indicating a better model fit largely driven by education level. Conclusions: Social influences of health impact transfer to rehabilitation facilities after acute stroke hospitalization. Future studies should focus on individual (versus county-level) metrics of social influences of health and their impact on access to rehabilitation. This information should be used to develop interventions to improve the equity of rehabilitation utilization after stroke.