From admissions to licensure: education data associations from a multi-centre undergraduate medical education collaboration.

This paper reports the findings of a Canada based multi-institutional study designed to investigate the relationships between admissions criteria, in-program assessments, and performance on licensing exams. The study's objective is to provide valuable insights for improving educational practices across different institutions. Data were gathered from six medical schools: McMaster University, the Northern Ontario School of Medicine University, Queen's University, University of Ottawa, University of Toronto, and Western University. The dataset includes graduates who undertook the Medical Council of Canada Qualifying Examination Part 1 (MCCQE1) between 2015 and 2017. The data were categorized into five distinct sections: demographic information as well as four matrices: admissions, course performance, objective structured clinical examination (OSCE), and clerkship performance. Common and unique variables were identified through an extensive consensus-building process. Hierarchical linear regression and a manual stepwise variable selection approach were used for analysis. Analyses were performed on data set encompassing graduates of all six medical schools as well as on individual data sets from each school. For the combined data set the final model estimated 32% of the variance in performance on licensing exams, highlighting variables such as Age at Admission, Sex, Biomedical Knowledge, the first post-clerkship OSCE, and a clerkship theta score. Individual school analysis explained 41-60% of the variance in MCCQE1 outcomes, with comparable variables to the analysis from of the combined data set identified as significant independent variables. Therefore, strongly emphasising the need for variety of high-quality assessment on the educational continuum. This study underscores the importance of sharing data to enable educational insights. This study also had its challenges when it came to the access and aggregation of data. As such we advocate for the establishment of a common framework for multi-institutional educational research, facilitating studies and evaluations across diverse institutions. This study demonstrates the scientific potential of collaborative data analysis in enhancing educational outcomes. It offers a deeper understanding of the factors influencing performance on licensure exams and emphasizes the need for addressing data gaps to advance multi-institutional research for educational improvements.

The factors of job crafting in emergency nurses: regression models versus qualitative comparative analysis.

BACKGROUND: Job crafting is defined as a series of proactive behaviors exhibited by employees in order to balance work resources and needs, which has a significant positive impact on the nurses. It is necessary to find the core factors that influence the job crafting, as emergency nurses deal with the most complex tasks, so as to improve their job satisfaction. OBJECTIVES: To investigate the core factors of job crafting among emergency nurses. METHODS: A cross-sectional design was used in the study. A total of 255 nurses were recruited from two hospitals in Zhengzhou and Shenzhen, China in December 2021. 255 nurses completed an online questionnaire. Hierarchical regression models and fsQCA models were used to explore the factors influencing job crafting among emergency nurses and helped us to identify core factors. RESULTS: The hierarchical regression model and the fsQCA model found that the occupational benefit, psychological empowerment, and research experience were the core factors affecting their job crafting. Job involvement was not significant in the regression model, but the QCA model indicated that it needs to be combined with other factors to impact on job crafting. The QCA model uncovered seven key conditional configurations that led to high and low job crafting among emergency nurses, explaining 80.0% of the results for high job crafting and 82.6% of the results for the low job crafting, respectively. CONCLUSIONS: The results of this study provide valuable insights into the job crafting experienced by emergency nurses. Junior emergency nurses should be granted a high level of psychological empowerment without assigning them overly complex tasks, such as research tasks, as these challenges can stop their job crafting. Intermediate and senior emergency nurses, on the other hand, can be assigned research tasks coupled with high psychological empowerment to enhance their job crafting.

The relationship between personality traits and dysfunctional attitudes in individuals with or without major depressive disorder: a case control study.

BACKGROUND: Dysfunctional attitudes, which are characterized by distorted self-cognitions, were considered to be linked to personality traits. It was found that certain personality traits may predict dysfunctional attitudes in patients with major depressive disorder (MDD). Nonetheless, the relationship between personality traits and dysfunctional attitudes remains under-researched. AIMS: The aim of this study is to examine the relationship between specific domains of Sixteen Personality Factor (16PF) and dysfunctional attitudes in Chinese participants with or without MDD. In addition, the present study explores the associations between 16PF and eight subtypes of dysfunctional attitudes, based on the proposed eight-factor structure of the Chinese version of the Dysfunctional Attitude Scale-Form A (C-DAS-A). METHODS: One hundred and sixty-eight participants with MDD and 130 healthy participants were included in the study (Trial Registration Number: ChiCTR1800014591). Personality was assessed using the 16PF Questionnaire. Dysfunctional attitudes were measured through the C-DAS-A. RESULTS: The 16PF dimensions associated with dysfunctional attitudes and the eight subtypes were mainly concentrated in the four anxiety facets including factors C, L, O, and Q4, in both MDD and HC groups. There were significant differences in the 16 PF dimensions that would explain dysfunctional attitudes between the two groups, which were as follows: factors C, G, and O in the MDD group, and factors L and Q4 in the HC group. CONCLUSIONS: Personality traits, especially the anxiety-related personality traits, were distinctly associated with the development of dysfunctional attitudes in people with or without MDD.

Mapping the risk of respiratory infections using suburban district areas in a large city in Colombia.

BACKGROUND: Acute respiratory infections (ARI) in Cúcuta -Colombia, have a comparatively high burden of disease associated with high public health costs. However, little is known about the epidemiology of these diseases in the city and its distribution within suburban areas. This study addresses this gap by estimating and mapping the risk of ARI in Cúcuta and identifying the most relevant risk factors. METHODS: A spatial epidemiological analysis was designed to investigate the association of sociodemographic and environmental risk factors with the rate of ambulatory consultations of ARI in urban sections of Cúcuta, 2018. The ARI rate was calculated using a method for spatial estimation of disease rates. A Bayesian spatial model was implemented using the Integrated Nested Laplace Approximation approach and the Besag-York-Mollié specification. The risk of ARI per urban section and the hotspots of higher risk were also estimated and mapped. RESULTS: A higher risk of IRA was found in central, south, north and west areas of Cúcuta after adjusting for sociodemographic and environmental factors, and taking into consideration the spatial distribution of the city's urban sections. An increase of one unit in the percentage of population younger than 15 years; the Index of Multidimensional Poverty and the rate of ARI in the migrant population was associated with a 1.08 (1.06-1.1); 1.04 (1.01-1.08) and 1.25 (1.22-1.27) increase of the ARI rate, respectively. Twenty-four urban sections were identified as hotspots of risk in central, south, north and west areas in Cucuta. CONCLUSION: Sociodemographic factors and their spatial patterns are determinants of acute respiratory infections in Cúcuta. Bayesian spatial hierarchical models can be used to estimate and map the risk of these infections in suburban areas of large cities in Colombia. The methods of this study can be used globally to identify suburban areas and or specific communities at risk to support the implementation of prevention strategies and decision-making in the public and private health sectors.

The influence of type of sexual partnership on male condom use: empirical evidence from the South African construction industry.

There are indications that gender has an effect on individual risk factors and pathways to HIV diagnoses and treatment. Furthermore, there is growing recognition that to improve HIV-related health outcomes for men, it is important to understand their experiences and perspectives. Perhaps because of the physical nature of construction work, the South African construction industry is dominated by men. Given that employed men are a hard-to-reach community population group, the construction workplace offers an ideal environment for data collection and delivery of non-health-facility-based HIV prevention and treatment interventions. Furthermore, workers in the construction industry have been identified as being at a heightened risk of acquiring HIV and AIDS because of work-related travel, the ubiquity of transactional sex around worker hostels and having an increased likelihood of multiple and concurrent sex partnerships. As a consequence, this study examines the association between condom use and sexual partnerships among men working in the construction industry. A purposive cross-sectional survey was used to collect data from 450 workers across 18 construction sites in the Western Cape province of South Africa. The types of sexual partnership had three categories: regular sex partnerships, casual sex partnerships and sex worker partnerships. Frequency of condom use was determined to be highest with casual sex partners (51.2%), followed by sex workers (40.6%) and regular sex partners (25.6%). Hierarchical multiple linear regression analysis was used to examine the demographic, experiential, behavioural and cognitive predictors of condom use across the three categories of sexual partnership. The results indicate that an individual's perception of control over condom use, and the perceived threat posed by HIV and AIDS are significantly associated with consistent condom use, even after accounting for differences in partner type. Implications of the findings are discussed, and directions for future research on the association between sexual partnerships and condom use are offered.

Impact of instructors' online teaching readiness on satisfaction in the emergency online teaching context.

This study aims at investigating the predictive effects of online teaching readiness factors on instructors' satisfaction and confidence in the emergency online teaching context. The target population is instructors who experienced online teaching during the COVID-19 pandemic, particularly in South Korea. Two hundred and thirteen instructors from 15 universities in South Korea responded to a survey asking about online teaching readiness (technological, pedagogical, online communication, time and environment management, and institutional support readiness), satisfaction, and confidence. Hierarchical regression analysis showed that pedagogical and online communication readiness have significant positive effects on both satisfaction and confidence, while showing lower means than other online teaching readiness sub-categories. This research concludes that specific strategies and skills for pedagogical and online communication readiness have to be stressed in professional development programs for online teaching.

Patient and surgeon factors contributing to bailout cholecystectomies: a single-institutional retrospective analysis.

BACKGROUND: Laparoscopic cholecystectomies continue to pose trouble for surgeons in the face of severe inflammation. In the advent of inability to perform an adequate dissection, a "bailout cholecystectomy" is advocated. Conversion to open or subtotal cholecystectomy is among the standard bailout procedures in such instances. METHODS: We performed a retrospective single institution review from January 2016 to August 2019. All patients who underwent a cholecystectomy were included, while those with a concurrent operation, malignancy, planned as an open cholecystectomy, or performed by a low volume surgeon were excluded. Patient characteristics, operative reports, and outcomes were collected, as were surgeon characteristics such as years of experience, case volume, and bailout rate. Univariable and multivariable analysis were performed. RESULTS: 2458 (92.6%) underwent laparoscopic total cholecystectomy (LTC) and 196 (7.4%) underwent a bailout cholecystectomy (BOC). BOC patients tended to be older (p < 0.001), male (p < 0.001), have a longer duration of symptoms (p < 0.001), and higher ASA class (p < 0.001). They also had more signs of biliary inflammation, as evidenced by increased leukocytosis (p < 0.001), tachycardia (p < 0.001), bilirubinemia (p = 0.003), common bile duct dilation (p < 0.001), and gallbladder wall thickening (p < 0.001). The BOC cohort also had increased rates of complications, including bile leak (16%, p < 0.001), retained stone (5.1%, p = 0.005), operative time (114 min vs 79 min, p < 0.001), and secondary interventions (22.7%, p < 0.001). Male gender (aOR = 2.8, p < 0.001), preoperative diagnosis of acute cholecystitis (aOR = 2.2, p = 0.032), right upper quadrant tenderness (aOR = 3.0, p = 0.008), Asian race (aOR = 2.7, p = 0.014), and intraoperative adhesions (aOR = 13.0, p < 0.001) were found to carry independent risk for BOC. Surgeon bailout rate ≥ 7% was also found to be an independent risk factor for conversion to BOC. CONCLUSIONS: Male gender, signs of biliary inflammation (tachycardia, leukocytosis, dilated CBD, and diagnosis of acute cholecystitis), as well as surgeon bailout rate of 7% were independent risk factors for BOC.

Veterans receiving a second course of cognitive processing therapy or prolonged exposure therapy: is it better to switch or stay the same?

Cognitive processing therapy (CPT) and prolonged exposure therapy (PE) are effective psychotherapies for post-traumatic stress disorder (PTSD). However, these treatments also have high rates of dropout and non-response. Therefore, patients may need a second course of treatment. We compared outcomes for patients who switched between CPT/PE and those who repeated CPT/PE during a second course of treatment. We collected data from Iraq and Afghanistan war veterans (n = 2,958) who received a second course of CPT/PE in the Veterans Health Administration from 2001 to 2017 and had symptom outcomes (PTSD checklist; PCL). We measured the association between treatment sequence and change in PCL score over the second course of treatment using hierarchical Bayesian regression, adjusted for sociodemographic and clinical characteristics. All treatment sequences showed a significant reduction in PCL score over time (ß = -4.80; HDI95: -5.74, -3.86). Veterans who switched from CPT to PE had modestly greater PCL reductions during the second course than those who repeated CPT. However, no significant difference in PCL change during the second course was observed between veterans who repeated PE and those who switched from PE to CPT. Veterans participating in a second course of CPT/PE can benefit, and switching treatment may be slightly more beneficial following CPT.

Factors influencing alertness to premonitory symptoms in stroke patients with pre-hospital delay.

OBJECTIVE: The purpose was to explore the alertness of premonitory symptoms in stroke patients with prehospital delay, and to analyze the influencing factors. DESIGN AND SAMPLE: A cross-sectional study using the convenience sampling method was conducted in the neurology department of a general hospital between November 2018 and July 2019. A total of 352 stroke patients were participated in the survey. MEASURES: A hierarchical multiple regression was performed to analyze the factors related to the alertness of premonitory symptoms (0-9 scores) in stroke patients with prehospital delay. RESULTS: The alertness score was 6.53 ± 2.377. The lowest score of 0.55 ± 0.498 was for "Continuous yawning occurs continuously despite no tiredness or lack of sleep is okay, and need not be treated." The hierarchical regression results revealed that symptom onset, symptom change before admission, knowledge, social support were the influencing factors delaying the alertness of premonitory symptoms. Knowledge and support from friends could improve the alertness, while support from family and other support had a notable negative impact. CONCLUSIONS: Stroke patients need to be more alert toward premonitory symptoms. This alertness is related to stroke knowledge and social support. Nurses should formulate interventions and advise stroke patients to improve their stroke knowledge and expand their social network.

Assessment of health-related quality of life among parents of children with solid tumors in Serbia.

PURPOSE: The aim of the study was to assess health-related quality of life (HRQoL) and contributing factors among parents of children with solid tumors in Serbia. METHODS: The cross-sectional study included 51 parents of children treated for different solid tumors at the Institute of Oncology and Radiology of Serbia. Parents filled out validated Serbian version of SF-36 questionnaire. Hierarchical multiple regression analysis was conducted to identify predictors of total score of SF-36. RESULTS: Almost all parents (94.1%) were mothers and average age was 38.6 ± 6.7 years. Majority of children had brain tumors (43.1%), followed by bone tumors (37.3%). The hierarchical regression analysis showed that socio-demographic characteristics explained 26% of the variance (p > 0.05) of the total score of SF-36. Addition of quality of life of children assessed by parents in the second model caused an increase of 21% in the variance explained (p < 0.05). After adding the Beck Depression Inventory score in the third block, an additional 18% of the variance in total score was explained (p < 0.05). CONCLUSIONS: This study showed that HRQoL measured by SF-36 in parents of children with cancer is strongly influenced by depression and quality of life of children assessed by parents.

Shared leadership in interprofessional teams: beyond team characteristics to team conditions.

Shared leadership has been shown to enhance processes, effectiveness, and performances in interprofessional teams. While earlier studies suggest the association of internal team environment (ITE) and transactive memory system (TMS) with shared leadership, the relative influence of these team conditions vis-a-vis team characteristics (such as team size, stability, and interprofessional roles) on shared leadership is not well understood. This study aims to examine the comparative influence of team characteristics versus team conditions of ITE and TMS on shared leadership during interprofessional team meetings (IPTMs). We compared interprofessional teams from two departments, namely larger and more diverse teams of Geriatric Medicine versus the smaller and more homogeneous Palliative Medicine. We administered a questionnaire survey to healthcare professionals who attended IPTMs in both departments (N = 133). Our results revealed significantly higher scores in shared leadership, ITE and TMS in Palliative Medicine (p < .05). Using hierarchical regression analysis adjusting for team conditions, department and number of IPTMs attended were not significant in the final model (both p > .05). Instead, TMS (ß= 0.250, p < .01) and ITE (ß= 0.584, p < .01) outperformed team characteristics as conditions that are highly associated with shared leadership, explaining an additional 29.8% and 19.0%, respectively, of model variance. Further analysis revealed a stronger correlation between shared leadership subdomains with TMS in Geriatric Medicine and with ITE in Palliative Medicine. Our results demonstrate how a positive working environment with a high level of shared memory engendered a perception of shared leadership, and how these team conditions can be tapped upon to circumvent differences in team characteristics to facilitate shared leadership. Identifying key conditions that are highly associated with shared leadership is critical for the teaching of dynamic leadership roles to junior clinicians which in turn, can enhance patient care.

Estimation of an inter-rater intra-class correlation coefficient that overcomes common assumption violations in the assessment of health measurement scales.

BACKGROUND: Intraclass correlation coefficients (ICC) are recommended for the assessment of the reliability of measurement scales. However, the ICC is subject to a variety of statistical assumptions such as normality and stable variance, which are rarely considered in health applications. METHODS: A Bayesian approach using hierarchical regression and variance-function modeling is proposed to estimate the ICC with emphasis on accounting for heterogeneous variances across a measurement scale. As an application, we review the implementation of using an ICC to evaluate the reliability of Observer OPTION5, an instrument which used trained raters to evaluate the level of Shared Decision Making between clinicians and patients. The study used two raters to evaluate recordings of 311 clinical encounters across three studies to evaluate the impact of using a Personal Decision Aid over usual care. We particularly focus on deriving an estimate for the ICC when multiple studies are being considered as part of the data. RESULTS: The results demonstrate that ICC varies substantially across studies and patient-physician encounters within studies. Using the new framework we developed, the study-specific ICCs were estimated to be 0.821, 0.295, and 0.644. If the within- and between-encounter variances were assumed to be the same across studies, the estimated within-study ICC was 0.609. If heteroscedasticity is not properly adjusted for, the within-study ICC estimate was inflated to be as high as 0.640. Finally, if the data were pooled across studies without accounting for the variability between studies then ICC estimates were further inflated by approximately 0.02 while formerly allowing for between study variation in the ICC inflated its estimated value by approximately 0.066 to 0.072 depending on the model. CONCLUSION: We demonstrated that misuse of the ICC statistics under common assumption violations leads to misleading and likely inflated estimates of interrater reliability. A statistical analysis that overcomes these violations by expanding the standard statistical model to account for them leads to estimates that are a better reflection of a measurement scale's reliability while maintaining ease of interpretation. Bayesian methods are particularly well suited to estimating the expanded statistical model.

Bayesian hierarchical piecewise regression models: a tool to detect trajectory divergence between groups in long-term observational studies.

BACKGROUND: Bayesian hierarchical piecewise regression (BHPR) modeling has not been previously formulated to detect and characterise the mechanism of trajectory divergence between groups of participants that have longitudinal responses with distinct developmental phases. These models are useful when participants in a prospective cohort study are grouped according to a distal dichotomous health outcome. Indeed, a refined understanding of how deleterious risk factor profiles develop across the life-course may help inform early-life interventions. Previous techniques to determine between-group differences in risk factors at each age may result in biased estimate of the age at divergence. METHODS: We demonstrate the use of Bayesian hierarchical piecewise regression (BHPR) to generate a point estimate and credible interval for the age at which trajectories diverge between groups for continuous outcome measures that exhibit non-linear within-person response profiles over time. We illustrate our approach by modeling the divergence in childhood-to-adulthood body mass index (BMI) trajectories between two groups of adults with/without type 2 diabetes mellitus (T2DM) in the Cardiovascular Risk in Young Finns Study (YFS). RESULTS: Using the proposed BHPR approach, we estimated the BMI profiles of participants with T2DM diverged from healthy participants at age 16 years for males (95% credible interval (CI):13.5-18 years) and 21 years for females (95% CI: 19.5-23 years). These data suggest that a critical window for weight management intervention in preventing T2DM might exist before the age when BMI growth rate is naturally expected to decrease. Simulation showed that when using pairwise comparison of least-square means from categorical mixed models, smaller sample sizes tended to conclude a later age of divergence. In contrast, the point estimate of the divergence time is not biased by sample size when using the proposed BHPR method. CONCLUSIONS: BHPR is a powerful analytic tool to model long-term non-linear longitudinal outcomes, enabling the identification of the age at which risk factor trajectories diverge between groups of participants. The method is suitable for the analysis of unbalanced longitudinal data, with only a limited number of repeated measures per participants and where the time-related outcome is typically marked by transitional changes or by distinct phases of change over time.

The influence of unmet supportive care needs on anxiety and depression during cancer treatment and beyond: a longitudinal study of survivors of haematological cancers.

OBJECTIVES: This paper aims to examine the cross-sectional and longitudinal associations between patient-reported unmet needs and anxiety and depression for survivors of diffuse large B cell lymphoma (DLBCL) and multiple myeloma (MM). METHODS: In a longitudinal study design, self-reported data were collected through telephone interviews at two time points approximately 7 (T1) and 15 (T2) months post-diagnosis. The sample was recruited through the population-based Victorian Cancer Registry. At T1 and T2, the study outcomes, anxiety and depression, were assessed using the Hospital Anxiety and Depression Scale (HADS) and unmet needs were measured using the Supportive Care Needs Survey (SCNS-SF34). Questions related to social/family problems, relationship problems and financial problems were also asked. A three-step multivariable hierarchical logistic regression analysis examined the relative role of T1 anxiety and depression, T1 and T2 unmet needs and other psychosocial factors with T2 anxiety and depression. RESULTS: Both cross-sectional and longitudinal associations were observed between unmet needs and psychological distress. T2 anxiety was associated with T1 anxiety (OR 4.75, 95% CI 1.86-11.09), T2 psychological needs (OR 1.68, 95% CI 1.34-2.11) and with T1 social problems (OR 2.33, 95% CI 1.03-5.05) in multivariate analysis. T2 depression was associated with both T1 (OR 1.28, 95% CI 1.06-1.57) and T2 psychological needs (OR 1.35, 95% CI 1.06-1.70), T2 physical needs (OR 1.89, 95% CI 1.27-2.81) and T1 depression (OR 4.52, 95% CI 1.88-10.86). CONCLUSIONS: Unmet needs that manifest following diagnosis and treatment may persist into early survivorship and contribute to psychological distress. Addressing these needs during treatment may diminish the risk of current and future anxiety and depression.

A Tutorial on Multilevel Survival Analysis: Methods, Models and Applications.

Data that have a multilevel structure occur frequently across a range of disciplines, including epidemiology, health services research, public health, education and sociology. We describe three families of regression models for the analysis of multilevel survival data. First, Cox proportional hazards models with mixed effects incorporate cluster-specific random effects that modify the baseline hazard function. Second, piecewise exponential survival models partition the duration of follow-up into mutually exclusive intervals and fit a model that assumes that the hazard function is constant within each interval. This is equivalent to a Poisson regression model that incorporates the duration of exposure within each interval. By incorporating cluster-specific random effects, generalised linear mixed models can be used to analyse these data. Third, after partitioning the duration of follow-up into mutually exclusive intervals, one can use discrete time survival models that use a complementary log-log generalised linear model to model the occurrence of the outcome of interest within each interval. Random effects can be incorporated to account for within-cluster homogeneity in outcomes. We illustrate the application of these methods using data consisting of patients hospitalised with a heart attack. We illustrate the application of these methods using three statistical programming languages (R, SAS and Stata).

Variable selection and regression analysis for the prediction of mortality rates associated with foodborne diseases.

The purpose of this study was to apply a novel statistical method for variable selection and a model-based approach for filling data gaps in mortality rates associated with foodborne diseases using the WHO Vital Registration mortality dataset. Correlation analysis and elastic net regularization methods were applied to drop redundant variables and to select the most meaningful subset of predictors. Whenever predictor data were missing, multiple imputation was used to fill in plausible values. Cluster analysis was applied to identify similar groups of countries based on the values of the predictors. Finally, a Bayesian hierarchical regression model was fit to the final dataset for predicting mortality rates. From 113 potential predictors, 32 were retained after correlation analysis. Out of these 32 predictors, eight with non-zero coefficients were selected using the elastic net regularization method. Based on the values of these variables, four clusters of countries were identified. The uncertainty of predictions was large for countries within clusters lacking mortality rates, and it was low for a cluster that had mortality rate information. Our results demonstrated that, using Bayesian hierarchical regression models, a data-driven clustering of countries and a meaningful subset of predictors can be used to fill data gaps in foodborne disease mortality.

Temporal variation in phenotypic gender and expected functional gender within and among individuals in an annual plant.

BACKGROUND AND AIMS: Adaptive explanations for variation in sex allocation centre on variation in resource status and variation in the mating environment. The latter can occur when dichogamy causes siring opportunity to vary across the flowering season. In this study, it is hypothesized that the widespread tendency towards declining fruit-set from first to last flowers on plants can similarly lead to a varying mating environment by causing a temporal shift in the quality (not quantity) of siring opportunities. METHODS: A numerical model was developed to examine the effects of declining fruit-set on the expected male versus female reproductive success (functional gender) of first and last flowers on plants, and of early- and late-flowering plants. Within- and among-plant temporal variation in pollen production, ovule production and fruit-set in 70 Brassica rapa plants was then characterized to determine if trends in male and female investment mirror expected trends in functional gender. KEY RESULTS: Under a wide range of model conditions, functional femaleness decreased sharply in the last flowers on plants, and increased from early- to late-flowering plants in the population. In B. rapa, pollen production decreased more rapidly than ovule production from first to last flowers, leading to a within-plant increase in phenotypic femaleness. Among plants, ovule production decreased from early- to late-flowering plants, causing a temporal decrease in phenotypic femaleness. CONCLUSIONS: The numerical model confirmed that declining fruit-set can drive temporal variation in functional gender, especially among plants. The discrepancy between observed trends in phenotypic gender in B. rapa and expected functional gender predicted by the numerical model does not rule out the possibility that male reproductive success decreases with later flowering onset. If so, plants may experience selection for early flowering through male fitness.

The impact of giving support to others on older adults' perceived health status.

BACKGROUND: Social support that may contribute to the physical and mental health of older adults is widely studied. However, much of the existing research has focused on the impact of receiving support; the effects of giving support have largely been neglected. Using the biopsychosocial perspective, this study aimed to examine the independent impact of giving support to others on older adults' perceived health status. METHODS: Data for this study were obtained from a nationwide community-based cross-sectional survey entitled 'Determinants of Wellness among Older Malaysians: A Health Promotion Perspective', which was conducted in 2010. To assess the unique effects of giving support on perceived health status, above and beyond other possible known factors, a four-step hierarchical regression model using SPSS was used to test the hypothesis. RESULTS: The findings from the analysis revealed that giving support to others was a significant positive predictor of older adults' perceived health status after receiving support, demographic variables and chronic medical conditions were considered. Further results showed that giving support to others had almost twice the effect on perceived health status (ß = 0.11, P < 0.001) as receiving support (ß = 0.06, P < 0.05). CONCLUSION: The findings from this study underscore the need to develop programmes that encourage older adults' participation in productive activities such as caring for and helping others and volunteering.

Hierarchical models that address measurement error are needed to evaluate the correlation between treatment effect and control group event rate.

OBJECTIVES: To apply a hierarchical model (HM) that addresses measurement error in regression of the treatment effect on the control group event rate (CR). We compare HM to weighted linear regression (WLR) which is subject to measurement error and mathematical coupling. STUDY DESIGN AND SETTING: We reviewed published HMs that address measurement error and implemented a Bayesian version in open-source code to facilitate adoption by meta-analysts. We compared WLR and HM across a very large convenience sample of meta-analyses published in the Cochrane Database of Systematic Reviews. RESULTS: We applied both approaches (WLR and an HM that addresses measurement error) to 3193 meta-analyses that included 33,071 studies (average 10.28 studies per meta-analysis). A statistically significant slope suggesting an association between the treatment effect and CR was demonstrated with both approaches in 568 (17.19%) meta-analyses, with neither approach in 2036 (63.77%) meta-analyses, only with WLS in 229 (7.17%) and only with HM in 360 (11.28%) meta-analyses. The majority of slopes was negative (WLR 85%, HM 83%). In the majority of cases, HM had wider confidence intervals (72.53%) and slopes farther from the null (64.77%). CONCLUSION: Approximately 28% of meta-analyses demonstrate a significant association between the treatment effect and CR when HM is used to address measurement error, which can suggest frequent lack of portability of the relative effect across baseline risks. User-friendly open-source code is provided to meta-analysts interested in exploring this association.

Academic optimism, capital indicators as predictors of cognitive, affective, and psychomotor learning outcome among students in secondary school. Hierarchical regression approach (HRA).

Background: Studies that were carried out previously on learning outcomes focused mainly on the student's cognitive domain while identifying factors that predicted it. More so, most of the learner's assessments in school are largely dependent on the score obtained from specific subjects by the learner, and efforts to address other domains of instruction such as affective and psychomotor domains have been minimal or absent in regard to the variables selected for the study. This study therefore sought to address that gap by finding out the relative and composite contribution of academic optimism and capital indicators to the learning outcomes (of students. Methods: The study adopted a correlational design with a multistage sampling technique to select a total of 534 senior secondary class II students. Two research instruments, the Academic Optimism and Capital Indicators Scale (AOCIS) and the Learning Outcomes Scale (LOS), were used for data collection. Exploratory and confirmatory factors analysis were used to assess the dimensionality of the items and factor structure of the scales. The psychometric properties obtained for scale were adequate for the instrument to be adjudged valid and reliable.The collected data were analysed using the hierarchical regression approach (HRA). Results: The findings of the study revealed that academic emphasis, collective efficacy, faculty trust, social capital, economic capital, and cultural capital, relatively and jointly, predict overall learning outcomes (cognitive, affective, and psychomotor construct). The result showed that there was an increased proportion of variance with each addition of a predictor to the model. Social capital reduced the percentage change at the initial time, but with the addition of economic capital, the proportion of change increased among others in the subsequent model examination. Conclusion: /implication: The study provides knowledge and empirical evidence that academic optimism and capital indicators, with their dimensions, affect composite learning outcomes among students. This study will help school ministries, policymakers, and curriculum planners make sure that the educational objectives, philosophies, and programmes are planned to reflect the total learner in order to produce the total learner that will effect changes in the society. This study has provided evidence that academic inputs and capital indicators are crucial indices of their learning outcomes in the three area of learning. The ability of the school to emphasise academics, ensure that all school agents are committed to instructional delivery, and gain the trust of parents is crucial for adequate support to enhance students learning outcomes. The outcome has implication for policy development and providing a climate that can stimulate equity, trust and motivation.