School to jail transition – early warnings from the primary school

Social participation is a crucial condition for successful learning in inclusive primary schools. Unfortunately, students with non-compliant classroom behaviour are at risk of being socially excluded from their class. Recently, students’ attitudes have been identified as the central indicator of the social participation of students with non-compliant behaviour in the classroom. However, the determinants of students’ attitudes are unclear. In accordance with the ‘contact theory’ and the principle of ‘homophily’, we investigated the relationship between students’ attitudes towards peers with non-compliant behaviour, their contact experiences with peers with non-compliant behaviour, and their experiences of having behavioural difficulties or formally assessed special educational needs (SEN) themselves. 589 fourth grade primary school students completed a questionnaire on their contact experiences and attitudes towards peers with non-compliant behaviour. Additionally, teachers provided information on students’ behavioural difficulties and formal SEN. Results from a multilevel regression analysis revealed that students’ attitudes towards peers with non-compliant behaviour could be explained by their contact experiences. Overall, our findings emphasise the importance of students’ contact experiences in relation to their attitudes towards peers with non-compliant behaviour and mark an important initial point for the implementation of future interventions (e.g. peer-mediated learning) that foster valuable contacts and positive attitudes.

The study investigated whether school-level protective factors could moderate the effects cumulative risk has upon behavior difficulties in children with special educational needs and disabilities (SEND). The sample comprised 4,288 children identified with SEND: 2,660 pupils within 248 primary schools, and 1,628 pupils within 57 secondary schools. Risk factors associated with increases in behavior difficulties over an 18-month period were summed to a cumulative risk score. Various school-level factors were added to multilevel models, with interaction terms computed between cumulative risk and these variables to assess their potential protective effects. The primary school model revealed a significant interaction between cumulative risk and school academic achievement in predicting behavior difficulties. Higher levels of achievement in primary schools help reduce behavior difficulties for children most at risk. The secondary school model evidenced a significant interaction between cumulative risk and school percentage of students eligible for free school meals (FSM). Lower proportions within a school of children eligible for FSM were associated with reductions in behavior difficulties for children at high levels of risk. Interventions aimed at improving school-level academic achievement and targeting high-risk students attending schools with large proportions of children eligible for FSM would be beneficial.

This two-year, mixed-methods study explored teacher learning during a year-long professional development programme and during the year following the programme. The study examined patterns of change in primary school teachers’ inquiry practices, inquiry beliefs and physical science content knowledge during both years as well as the effects of school-level and individual-level factors on these changes in the year following the programme. Fifteen fourth-grade through sixth-grade teachers from three low-performing US schools participated. Results indicated that the programme was effective in advancing teacher change during the programme year, as scores in all three measures increased at statistically significant rates. Only content knowledge scores increased significantly in the year following the professional development. A combination of school-level and individual-level factors impacted the year 2 changes. School-level factors were: having supportive same-grade teams and/or a supportive mentor who advocated inquiry science and who prioritized science as a subject; principal prioritization of science; and having easy access to and training in the use of relevant materials. The primary individual-level factor was the degree of teachers’ willingness and readiness to change beliefs in fundamental ways. Implications for professional development providers and school administrators are discussed.

This study examines how school-level and student-level factors influence primary school dropout in Burkina Faso. School-level factors were found to have a moderate effect in grade three and a small effect in grade five, while student performance on end-of-term class tests significantly affected students’ decisions to drop out in both grades. Other factors were found to have limited or no effects. A researcher-designed test showed that many children dropped out before acquiring basic literacy and numeracy skills. These findings seemed to suggest that basic skill acquisition was not a matter of concern among students and their parents.

Timely progression through school is an important measure for school performance, completion and the onset of other life transitions for adolescents. This study examines the risk factors for grade repetition and establishes the extent to which age-for-grade heterogeneity contributes to subsequent grade repetition at early and later stages of school. Using data from a demographic surveillance site in Karonga district, northern Malawi, a cohort of 8174 respondents (ages 5–24 years) in primary school was followed in 2010 and subsequent grade repetition observed in 2011. Grade repetition was more common among those at early (grades 1–3) and later (grades 7–8) stages of school, with little variation by sex. Being under-age or over-age in school has different implications on schooling outcomes, depending on the stage of schooling. After adjusting for other risk factors, boys and girls who were under-age at early stages were at least twice as likely to repeat a grade as those at the official age-for-grade (girls: adjusted OR 2.06 p<0.01; boys: adjusted OR 2.37 p<0.01); while those over-age at early stages were about 30% less likely to repeat (girls: adjusted OR 0.65 p<0.01; boys: adjusted OR 0.72 p<0.01). Being under/over-age at later grades (4–8) was not associated with subsequent repetition but being over-age was associated with dropout. Other risk factors identified that were associated with repetition included both family-level factors (living away from their mother, having young children in the household, lower paternal education) and school-level factors (higher student-teacher ratio, proportion of female teachers and schools without access to water). Reducing direct and indirect costs of schooling for households; and improving school quality and resources at early stages of school may enable timely progression at early stages for greater retention at later stages.

IntroductionA healthy social–emotional functioning is vital for students’ general development and wellbeing. The school environment is a major determinant of social–emotional functioning, yet little is known about school-level and student-level characteristics related to healthy social–emotional functioning. In this study, we examined school-level characteristics (school size, school disadvantage score, urbanization level, and school denomination) and student-level characteristics (grade, secondary school track, participation in a COVID-19-related catch-up program, and measurement moment - during or after COVID-19) as predictors of students’ motivation for school, academic self-concept, social acceptance, and school wellbeing.MethodsIn school year 2020–2021, just after the first Covid-19 outbreak, 3,764 parents of primary school students from 242 Dutch primary schools and 2,545 secondary school students from 62 secondary schools filled out online questionnaires, before and after a Covid-19 related catch-up program was implemented at their school. Reliable and validated questionnaires were used to assess students’ motivation (Intrinsic Motivation Inventory), academic self-concept (Harter Self Perception Profile for Children; Self-Description Questionnaire-II), school wellbeing (Dutch School Questionnaire) and social acceptance (PRIMA Social Acceptance Questionnaire). School characteristics were derived from online databases. Student participation in a catch-up program and measurement moment (before or after the program) were taken into account. Data was analyzed via multilevel General Linear Mixed Models, separately for primary and secondary education.ResultsOf the school-level factors, only school disadvantage score was a significant predictor, specifically for primary school students’ motivation. Of the student-level characteristics, grade and catch-up participation were significant predictors of lower motivation, academic self-concept and school-wellbeing in primary school. In secondary school, students in higher grades had significantly lower motivation and school wellbeing; participants in catch-up program had a significantly lower academic self-concept; and perceived social-acceptance and school wellbeing were significantly lower just after COVID-19.ConclusionSchool-level characteristics only played a minor role in explaining differences in students’ social–emotional functioning. In both primary and secondary education, students in higher grades and participating in catch-up programs scored lower on their social–emotional functioning. Schools should be aware of students in higher grades being at risk for more problems in their social–emotional functioning.

Digital health literacy (DHL) is a key competency for individuals' daily decisions toward their health behavior and wellbeing. While there is much focus on health literacy (HL) among the general population, teachers have been rarely addressed. Given the shortages in the teaching workforce in Europe and the impact of demanding working conditions on their health, it is important to address DHL in teachers. This paper examines the DHL of primary and secondary teachers and its associations with sociodemographic and school-related factors. An online cross-sectional study was conducted with 1,600 German primary and secondary school teachers between October and December 2022. To assess DHL, the Digital Health Literacy Instrument (DHLI) including seven subscales was used. Statistical analyses were conducted on item and subscale level and an overall DHL score was calculated. Next to descriptive analyses, bivariate and regression analyses were conducted to explore potential associations with sociodemographic and school-related factors. The frequency of difficulty in using digital health information varied across DHL dimensions and was greatest for protecting privacy (70.9%) and evaluating reliability (40.0%). In multivariate analysis, females more often reported a sufficient ability of adding content (OR = 1.61, CI = 1.05-2.48), while males more often reported a sufficient ability to protect their privacy (OR = 0.45, CI = 0.27-0.75). Teachers with leadership positions more often reported a sufficient ability in adding content (OR = 1.78, CI = 1.07-2.98). Regarding the ability to determine the relevance of online health-related information, no associations with a predictor variable were found. The results suggest that it is important to examine the individual dimensions of DHL and their distinct associations with sociodemographic and school-level factors, rather than just to rely on the overall level of DHL. The differential patterns identified in this study suggest a greater intervention need for teachers from higher age groups, primary and secondary general schools, and those without leadership roles. However, based on the limited predictive power of the variables included, further individual and school-level factors and their potential association with DHL should be investigated in the future. The promotion of DHL should be integrated into both teacher education and in-service training.

BackgroundThe nature and structure of the school environment has the potential to shape children's health and well being. Few studies have explored the importance of school-level factors in explaining a child's likelihood of experiencing violence from school staff, particularly in low-resource settings such as Uganda.MethodsTo quantify to what extent a student's risk of violence is determined by school-level factors we fitted multilevel logistic regression models to investigate associations and present between-school variance partition coefficients. School structural factors, academic and supportive environment are explored.Results53% of students reported physical violence from staff. Only 6% of variation in students' experience of violence was due to differences between schools and half the variation was explained by the school-level factors modelled. Schools with a higher proportion of girls are associated with increased odds of physical violence from staff. Students in schools with a high level of student perceptions of school connectedness have a 36% reduced odds of experiencing physical violence from staff, but no other school-level factor was significantly associated.ConclusionOur findings suggest that physical violence by school staff is widespread across different types of schools in this setting, but interventions that improve students' school connectedness should be considered.

Previous studies found lower substance use in schools achieving better examination and truancy results than expected, given their pupil populations (high value-added schools). This study examines whether these findings are replicated in West Scotland and whether school ethos indicators focussing on pupils' perceptions of schooling (environment, involvement, engagement and teacher–pupil relations) mediate the associations. Teenagers from forty-one schools (S2, aged 13, n = 2268; S4, aged 15, n = 2096) previously surveyed in primary school (aged 11, n = 2482) were surveyed in the late 1990s. School value-added scores were derived from standardised residuals of two regression equations separately predicting from pupils' socio-demographic characteristics (1) proportions of pupils passing five Scottish Standard Grade Examinations, and (2) half-day truancy loss. Outcomes were current smoking, monthly drinking, ever illicit drug use. Random effects logistic regression models adjusted for potential pupil-level confounders were used to assess (1) associations between substance use and school-level value-added scores and (2) whether these associations were mediated by pupils' perceptions of schooling or other school-level factors (school roll, religious denomination and mean aggregated school-level ethos scores). Against expectations, value-added education was positively associated with smoking (Odds Ratios [95% confidence intervals] for one standard deviation increase in value-added scores were 1.28 [1.02–1.61] in S2 and 1.13 [1.00–1.27] in S4) and positively but weakly and non-significantly associated with drinking and drug use. Engagement and positive teacher–pupil relations were strongly and negatively associated with all substance use outcomes at both ages. Other school-level factors appeared weakly and largely non-significantly related to substance use. Value-added scores were unrelated to school ethos measures and no ethos measure mediated associations between value-added education and substance use. We conclude that substance use in Scotland is more likely in high value-added schools, among disengaged students and those with poorer student–teacher relationships. Understanding the underpinning mechanisms is a potentially important public health concern.

PurposeThis purpose of this study is to outline an inclusive development strategy for crime prevention interventions. Crime prevention interventions are delivered to the target audience to convey an evidence-based message to dissuade would-be offenders from carrying out crimes. However, rarely is the target audience involved when designing crime prevention interventions.Design/methodology/approachUsing the Delphi method, this paper documents the design of an intervention aimed at improving young drivers’ compliance with road rules, incorporating feedback from both a panel of experts and the target audience of the intervention. While expert feedback guided the content and the context of the intervention, the feedback from the target audience was critical in ensuring that effective delivery and messaging of the crafted intervention would occur.FindingsBy drawing on expert and experiential insights, this exploratory method of intervention design provided a simple and effective way of ensuring the effective delivery of a crime prevention message.Research limitations/implicationsAlthough this study focussed on a road safety intervention, the crime prevention applications of this method are broad.Originality/valueThis paper outlines a collaborative methodology that utilises expert and experiential knowledge towards the design and development of a crime prevention intervention, in this case, targeted at young drivers.

Adult health and its determinants are influenced by the environment in childhood. The school attended is known to affect the health behaviours of pupils while still at school. Little is known about the long-term influence of school attended on health. A total of 7,095 respondents (mean age 47 years) to a follow-up questionnaire who attended primary school in Aberdeen, UK, provided information on self-reported health; self-reported high blood pressure; GHQ-4; smoking status; alcohol intake; and obesity. Variance partition coefficients (VPCs) summarized the variation in adult health outcomes and behaviours across schools. Multilevel logistic regression was used to estimate the contribution of school to variation in the outcomes taking into account individual-level and school-level factors. There was some variation across schools in the proportion of adults reporting poor self-rated health (VPC = 0.020) and smoking (0.019). Higher VPCs were found for factors potentially confounded with school: paternal social classes (I&II) (0.45) and gender (0.44). Age at leaving secondary education (0.28) and income (0.10) varied across schools. The effects of primary school diminished after adjusting for individual-level childhood risk factors. The further addition of adult risk factors attenuated these childhood effects. After full adjustment there was no effect of the primary school attended for high blood pressure, current smoking, alcohol intake, and obesity, and negligible effects for the other outcomes. Contrary to our expectations, we found little evidence of any relationship between primary school and adult self-reported health or behaviour. This is surprising given the extent to which characteristics known to be associated with adult health were clustered within schools.

High quality internal control information disclosure can promote the healthy development of the capital market. This paper selects the Shanghai and Shenzhen A-share listed companies in 2017 as the research object, and selects the data of corporate finance, corporate governance, investor protection, market and executive characteristics and incentives to construct an early warning index system with the combination of financial and non-financial indicators, and uses Bayesian classification, Logistic regression, decision tree and K-proximity learning to predict the non-compliance behavior of internal control information disclosure. The study finds that after feature attribute selection, the prediction accuracy of non-compliance behavior is significantly improved, the highest is logistic regression model; secondly, it is found that non-financial information contributes more than financial information in the prediction process. Therefore, the integrity and self-discipline management of the main body of the enterprise, the external maintenance of high standards of professional ethics, and all-round efforts can jointly build and share a high-quality benign capital market environment.

How do we progress racial justice in education?

Objective: To analyze the association between hospital visit data and data of school absence due to illness in primary and secondary school students, and evaluate the performance of different monitoring data in early warning of infectious disease outbreaks. Methods: Thirteen primary and secondary schools in Dapeng New District, Shenzhen, were selected to conduct the study. Data of infectious disease-related hospital visits in local students from January 1, 2015 to December 31, 2019 were collected from Chinese Disease Prevention and Control Information System, and the monitoring data of school absence due to illness during the period were collected from Shenzhen Student Health Monitoring System. Spearman rank correlation analysis was used to evaluate the time-series correlation between the two types of data. An early warning strategy was established by using the moving average method combined with a fixed-threshold method. The performance of different early warning strategies were evaluated by using indicators such as positive predictive value (PPV) and sensitivity, the school outbreak data reported in Shenzhen Disease Cluster Surveillance System were used as the gold standard. Results: A total of 1 870 cases of school absence due to infectious diseases were found in local primary and secondary school students. The main diseases were influenza, varicella, and mumps, with fever, cough, and sore throat being the most common reasons for school absence. During the study period, 52 infectious disease outbreaks were reported in local primary and secondary schools, which were mainly caused by influenza and varicella. A lag correlation was observed between the hospital visit data and the school absence monitoring data (r=0.31, P<0.001), with the latter detecting outbreaks earlier. Hospital monitoring, school absence monitoring, serial monitoring and parallel monitoring triggered 385, 491, 298, and 876 early warning signals, respectively. The hospital monitoring alone achieved the highest positive prediction value (66.49%), the serial monitoring achieved the highest specificity (98.42%), and the parallel monitoring achieved the highest sensitivity (100.00%) and Youden index (80.52%). Conclusions: The information about infectious disease obtained from hospital visit data lags behind monitoring data of school absence due to illness in primary and secondary school students. A parallel early warning strategy combining both monitoring methods enables accurate and rapid outbreak detection, providing data support for epidemiological investigation and prevention and control resource allocation.

Understanding the impact of different types of social interactions is key to improving epidemic models. Here, we use extensive registry data—including PCR test results and population-level networks—to investigate the impact of school, family, and other social contacts on SARS-CoV-2 transmission in the Netherlands (June 2020–October 2021). We isolate and compare different contexts of potential SARS-CoV-2 transmission by matching pairs of students based on their attendance at the same or different primary school (in 2020) and secondary school (in 2021) and their geographic proximity. We then calculate the probability of temporally associated infections—i.e. the probability of both students testing positive within a 14-day period. Our results highlight the relative importance of household and family transmission in the spread of SARS-CoV-2 compared to school settings. The probability of temporally associated infections for siblings and parent-child pairs living in the same household ranged from 22.6–23.2%. Interestingly, a high probability (4.7–7.9%) was found even when family members lived in different households, underscoring the persistent risk of transmission within family networks. In contrast, the probability of temporally associated infections was 0.52% for pairs of students living nearby but not attending the same primary or secondary school, 0.66% for pairs attending different secondary schools but having attended the same primary school, and 1.65% for pairs attending the same secondary school. It is worth noting, however, that even small increases in school-related infection probabilities can trigger large-scale outbreaks due to the dense network of interactions in these settings. Finally, we used multilevel regression analyses to examine how individual, school, and geographic factors contribute to transmission risk. We found that the largest differences in transmission probabilities were due to unobserved individual (60%) and school-level (35%) factors. Only a small proportion (3%) could be attributed to geographic proximity of students or to school size, denomination, or the median income of the school area.