Family background and classroom belonging among adolescent students in Finland

We study whether a family’s economic situation and parental educational level are associated with classroom belonging among students in comprehensive secondary, upper secondary general and upper secondary vocational education in Finland. We also study whether there are educational-level differences in this possible association. We use survey data from the Finnish School Health Promotion study from 2017 (N = 114,528). We conduct random effect linear probability models with schools as the second-level grouping variable. The results show that family’s low economic situation predicts a higher probability of lack of sense of classroom belonging in Finland, despite the country having one of the world’s most equal educational systems and comparably low economic inequality. Neither mother’s nor father’s educational level has any association. A family’s low economic situation seems to predict the lack of a sense of belonging most strongly in comprehensive secondary education and most weakly in upper secondary vocational education. Our results slightly support the proposed significance of context-specific hierarchies in determining the association between economic resources and sense of belonging. A family having a poor economic situation is not reflected in the sense of classroom belonging as strongly in schools where students have a low average economic situation compared to those where students have a high average economic situation. We suggest measures, in addition to alleviating economic inequalities, to support the sense of school belonging, especially for low-income students.

Educational Differences in Cycling: Evidence from German Cities

Cycling is an environmentally sustainable social practice that contributes to liveable cities and provides affordable and healthy transport. People with lower education could particularly benefit from cycling, as they tend to fare worse regarding finances and health. However, in bivariate analyses, those with lower education cycle less. This article discusses the social meaning of cycling and investigates whether the education–cycling association holds after accounting for (1) confounders and (2) factors that determine decision leeway between different transport modes. I analyse approximately 80,000 short-distance trips (0.5–7.5 km) reported by 28,000 working-age individuals from cities in Germany using multilevel linear probability regression models. Results support that higher education systematically and substantially increases the propensity to cycle. This education gap implies major untapped potential for environmental sustainability, that current pro-cycling policies in cities disproportionally favour the highly educated and that cycling patterns contribute to inequalities in finances and health.

Metastatic gastroesophageal cancer in older patients – is this patient cohort represented in clinical trials?

Background Older patients are underrepresented in the clinical trials that determine the standards of care for oncological treatment. We conducted a review to identify whether there have been age-restrictive inclusion criteria in clinical trials over the last twenty five years, focusing on patients with metastatic gastroesophageal cancer. Methods A search strategy was developed encompassing Embase, PubMed and The Cochrane Library databases. Completed phase III randomised controlled trials evaluating systemic anti-cancer therapies in metastatic gastroesophageal malignancies from 1st January 1995 to 18th November 2020 were identified. These were screened for eligibility using reference management software (Covidence; Veritas Health Innovation Ltd). Data including age inclusion/exclusion criteria and median age of participants were recorded. The percentage of patients ≥ 65 enrolled was collected where available. The change over time in the proportion of studies using an upper age exclusion was estimated using a linear probability model. Results Three hundred sixty-three phase III studies were identified and screened, with 66 trials remaining for final analysis. The majority of trials were Asian (48%; n = 32) and predominantly evaluated gastric malignancies, (86%; n = 56). The median age of participants was 62 (range 18–94). Thirty-two percent (n = 21) of studies specified an upper age limit for inclusion and over half of these were Asian studies. The median age of exclusion was 75 (range 65–80). All studies prior to 2003 used an upper age exclusion (n = 12); whereas only 9 that started in 2003 or later did (17%). Among later studies, there was a very modest downward yearly-trend in the proportion of studies using an upper age exclusion (-0.02 per year; 95%CI -0.05 to 0.01; p = 0.31). Fifty-two percent (n = 34) of studies specified the proportion of their study population who were ≥ 65 years. Older patients represented only 36% of the trial populations in these studies (range 7–60%). Conclusions Recent years have seen improvements in clinical trial protocols, with many no longer specifying restrictive age criteria. Reasons for poor representation of older patients are complex and ongoing efforts are needed to broaden eligibility criteria and prioritise the inclusion of older adults in clinical trials.

Transitions Into and Out of Voluntary Work Over the Life Course: What is the Effect of Major Life Events?

The aim of the current study is to investigate which major life events are associated with transitions into and out of volunteering over the life course and, especially, why these associations exist. Social Production Function theory is used to derive hypotheses, which are tested using longitudinal data (adult subsample) from Lifelines. Associations between major life events and (a) volunteer take-up, nonvolunteer sample ( N = 59,773) and (b) volunteer cessation, volunteer sample ( N = 32,143) are studied by applying Linear Probability Modeling. Results show clear associations between specific major life events and starting and quitting volunteering. The influence on the latter is stronger than on the former. Most findings are in line with our theory-based expectations indicating that (a) voluntary work contributes especially to the fulfillment of the needs for status, stimulation, and behavioral confirmation and (2) life events causing losses (gains) in these needs are associated with a higher likelihood to take-up (quit) volunteering.

Preventing elder maltreatment: Identification of high risk factors from LTC administrative data

Elder maltreatment is a serious problem endangering physical, emotional, and material well-being of older persons, especially those with physical and cognitive impairment. However, detecting the incident of elder maltreatment is difficult and its prevalence has been seriously underestimated. This study explores how LTC use relates to elder maltreatment report, using government LTC service records in Taiwan. A total of 88,633 reported cases in adult protection system in 2019 were merged with 443,952 valid cases in LTC service system. Descriptive statistics were firstly performed to examine the proportion and characteristics of repeated cases in both systems. Linear probability modeling was then used for analyses. 1. In 2019, 3,413 elder maltreatment clients can be identified in LTC service system, accounting for 27.3% of the elder maltreatment cases. 2. Older persons who used LTC service first and being reported as elder maltreatment cases later had a higher prevalence of being discovered by social workers and care attendants. 3. These group of clients also had higher proportion of being reported as neglected by others, abandonment, and self-neglected. 4. Characteristics in LTC service system, such as being older, low severity of disability, high cognitive impairments, low income status, and with a LTC service use record, were related to high probability of being detected with elder maltreatment problems. Characteristics in LTC service system could be effective indicators in discovering potentially abusive situations of disabled older persons. Training and education are essential for LTC service providers to enhance their literacy and ability of assessing elder maltreatment.

Local Opt-Out Provisions in a State Gambling Expansion: An Analysis of Pennsylvania Municipalities

A 2017 gambling expansion bill in Pennsylvania included a provision that gave municipalities the option to ban a new casino from opening within their borders. This paper examined how different factors influenced local decisions on whether to allow casino gambling. Multilevel linear probability models indicated that municipalities were influenced by economic characteristics, as evidenced by a higher likelihood of allowing casinos in communities with lower levels of household income. Results also suggested that municipalities were influenced by variables related to tax competition and the percentage of residents who were black. The findings of this study identify factors that may influence municipal governments when given the authority to opt out of a state gambling expansion capable of generating a new source of local tax revenue.

Why do households participate in the loan moratorium in Hungary? Theoretical and empirical considerations

In order to mitigate the economic effects from the COVID-19 epidemic, a moratorium on loan repayments was introduced in several countries, including Hungary. Essentially, a loan moratorium provides additional finance for participants, allowing theories of both credit demand and consumption to be tested on debtors’ decisions as to whether or not they participate in the programme. In this paper, we use a linear probability model on the Hungarian survey data to examine the driving factors behind the households’ decision to participate in the scheme. Our results show that the younger debtors and those with more children are more likely to utilise the programme. Stretched financial situations, i.e., lower incomes, lower savings and higher payment-to-income ratios, increase the probability of continued participation as well. The chance of participating in the scheme also increases significantly when a household has faced borrowing constraints over the past two years, i.e., it has not been or only partially been able to satisfy its credit demand.

Health, Personality Disorders, Work Commitment and Training to Employment Transitions

This study analyzes the influence of mental and physical health, coping abilities, cooperativeness, and work commitment on the transition from apprenticeship training to a first job. In doing so, we first investigate transitions to regular employment within six months post-graduation. Second, we analyze gapless transitions from training to a first job. Third, we investigate transitions to a decent first job. This study draws on a unique dataset of 1,061 individuals from Germany that combines rich survey and register data. The baseline survey takes place during the last year of training for these individuals and contains information on their schooling, health, personality disorders and work attitudes. The register data measure the training environment and labor market outcomes. The results from linear probability models reveal that only physical health is associated with finding a first job within six months. Physical and mental health are associated with gapless transitions. Overall health, coping abilities and work commitment are important in terms of finding decent employment. However, when conditioning on individual and training firm characteristics, these associations are weakened and become statistically insignificant. Thus, the constructs under study might drive school graduates into certain training firms and occupations leading to decent first jobs. Fourth, our results indicate that the effect of overall health on gapless transitions is largest for individuals with higher levels of education, while the overall health effect is almost zero for those who are least educated. Thus, this study provides evidence of a cumulative disadvantage of the least educated in the school-to-work transition.

The role of insurance in business recovery after a natural disaster: The case of the 2011 Christchurch earthquake

<p>We aim to investigate the role of insurance in business recovery following the devastating Christchurch earthquake in February, 22nd, 2011. We analyze data from two business surveys conducted after the earthquake to examine how insurance affected business operation in the aftermath of the earthquake both in the short-term and longer-term. For the short-term analysis, we use a combination of propensity score matching (PSM) and linear probability model (LPM) to analyze the data. We first estimate the propensity scores for insurance take-up of each firm conditional on the firm’s individual characteristics. Stratification based on the estimated propensity scores is used to match the treated (insured) and the control (uninsured) firms. We then estimate the probability of firms’ continuing operations with a set of control variables to account for the level of damage and disruption caused by the quake in each stratum. We find little evidence of any beneficial effect of insurance coverage on business continuity in the short-run. For the longer-term analysis, we analyze the available survey data using logistic regression. The result suggests that business interruption insurance significantly promotes increased level of long-term productivity for surviving firms following the earthquake.</p>

The role of insurance in business recovery after a natural disaster: The case of the 2011 Christchurch earthquake

<p>We aim to investigate the role of insurance in business recovery following the devastating Christchurch earthquake in February, 22nd, 2011. We analyze data from two business surveys conducted after the earthquake to examine how insurance affected business operation in the aftermath of the earthquake both in the short-term and longer-term. For the short-term analysis, we use a combination of propensity score matching (PSM) and linear probability model (LPM) to analyze the data. We first estimate the propensity scores for insurance take-up of each firm conditional on the firm’s individual characteristics. Stratification based on the estimated propensity scores is used to match the treated (insured) and the control (uninsured) firms. We then estimate the probability of firms’ continuing operations with a set of control variables to account for the level of damage and disruption caused by the quake in each stratum. We find little evidence of any beneficial effect of insurance coverage on business continuity in the short-run. For the longer-term analysis, we analyze the available survey data using logistic regression. The result suggests that business interruption insurance significantly promotes increased level of long-term productivity for surviving firms following the earthquake.</p>