High-risk pooling for mitigating risk selection incentives in health insurance markets with sophisticated risk equalization: an application based on health survey information

BACKGROUND

Despite sophisticated risk equalization, insurers in regulated health insurance markets still face incentives to attract healthy people and avoid the chronically ill because of predictable differences in profitability between these groups. The traditional approach to mitigate such incentives for risk selection is to improve the risk-equalization model by adding or refining risk adjusters. However, not all potential risk adjusters are appropriate. One example are risk adjusters based on health survey information. Despite its predictiveness of future healthcare spending, such information is generally considered inappropriate for risk equalization, due to feasibility challenges and a potential lack of representativeness.

METHODS

We study the effects of high-risk pooling (HRP) as a strategy for mitigating risk selection incentives in the presence of sophisticated- though imperfect- risk equalization. We simulate a HRP modality in which insurers can ex-ante assign predictably unprofitable individuals to a 'high risk pool' using information from a health survey. We evaluate the effect of five alternative pool sizes based on predicted residual spending post risk equalization on insurers' incentives for risk selection and cost control, and compare this to the situation without HRP.

RESULTS

The results show that HRP based on health survey information can substantially reduce risk selection incentives. For example, eliminating the undercompensation for the top-1% with the highest predicted residual spending reduces selection incentives against the total group with a chronic disease (60% of the population) by approximately 25%. Overall, the selection incentives gradually decrease with a larger pool size. The largest marginal reduction is found moving from no high-risk pool to HRP for the top 1% individuals with the highest predicted residual spending.

CONCLUSION

Our main conclusion is that HRP has the potential to considerably reduce remaining risk selection incentives at the expense of a relatively small reduction of incentives for cost control. The extent to which this can be achieved, however, depends on the design of the high-risk pool.

Who continues to work after retirement age?

BACKGROUND

Demographic changes in all industrialized countries have led to a keen interest in extending working lives for older workers. To achieve this goal, it is essential to understand the patterns of retirement and specifically what characterizes individuals who continue to work beyond retirement age. Thus, the aim of this paper was to contribute to the international body of empirical knowledge about individuals who continue in the workforce after retirement age. We present evidence from Denmark and examine what characterizes individuals who continue in the workforce after retirement age and investigate the likelihood of continued work after retirement age while controlling for a set of socio-economic and lifestyle factors.

METHODS

The study population consisted of 5,474 respondents to the Copenhagen Aging and Midlife Biobank (CAMB) 2021 survey, divided into two groups. The first group included subjects (n = 1,293) who stayed longer in the workforce even though they had the possibility to retire. The second group consisted of subjects who had retired full-time at the time of the survey (n = 4,181). Survey data was linked to register data to provide a broader dataset. In order to investigate the heterogeneity between the two groups in terms of important socio-economic, work-related and health-related variables, t-test, Mann-Whitney U (Wilcoxon Rank) test, and chi-square tests were employed. Further, to examine the probability of an individual working after retirement age a logit model with step-wise inclusion was utilized.

RESULTS

Overall, individuals who continue to work even though they could retire tend to be wealthier, healthier, and males compared to individuals who are retired full-time. Further, there are more older workers who have partners and are co-habitants than retirees. The likelihood of continuing in the workforce past retirement age is affected by several work-related factors as well as life-style factors. The likelihood of working past retirement age decreases by years spent in the workforce (marginal effect of -0.003), if you have a partner (-0.080) and if your partner is outside of the workforce (marginal effect of -0.106). The likelihood increases by health (marginal effect of -0.044 of moving from excellent/very good health to good health or to fair/poor health, physical working capability (marginal effect of -0.083 of moving from no/some problems to severe problems or cannot work at all) and income (marginal effect of 0.083 from moving from the lowest income-quantile to higher quantiles).

CONCLUSION

These results are in line with the previous literature and suggest the importance of designing retirement policies that tailor the transition toward retirement according to specific characteristics of both the individual and the segment of occupation.

Perceptions of environmental changes among a climate-vulnerable population from Bangladesh

Effective climate change adaptation requires a thorough understanding of whether and how affected populations perceive climatic and environmental changes. Existing research has been inconclusive regarding the consistency of these perceptions compared to objective meteorological indicators. Moreover, no systematic comparison has been done for the perception of discrete environmental events such as floods or erosion. This study relies on novel panel survey data of approximately 1700 households residing along the Jamuna River in Bangladesh as well as on unique individual-level, satellite-based erosion data. It compares respondents' perceptions of environmental events, namely riverbank erosion, and three climate change indicators, specifically long-term temperature change and changes in precipitation during wet and dry seasons, to objective measurements using satellite imagery and climatic time-series data (CRU TS). I find that long-term temperature change is perceived more accurately than long-term changes in precipitation. Given that educational attainment and climate change literacy among the study population are low, this indicates that global temperature increases are felt even by remote populations who have never heard the term climate change. Erosion is strongly overestimated, especially by those respondents who had been personally affected by it. Since human behavior is guided by perceptions rather than objective data, this has important policy implications, underlining the importance of considering people's perceptions if the goal is to assist them in adapting to environmental changes.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10584-024-03678-6.

Defining and Identifying Only Children: A Research Note on the Concept and Measurement Illustrated With UK Survey Data

Despite increasing interest in the circumstances and outcomes of only children in the demographic literature, the conceptualization of this group has received limited scholarly attention. This research note argues for greater engagement by demographers and social scientists in the conceptualization and identification of only children by addressing three aims. First, we outline potential definitions of only children, present a framework to guide researchers' decisions, and evaluate whether only children can be reliably identified using the British birth cohort studies. Second, we show that the prevalence estimates are contingent on the timing of measurement in childhood, indicating the need for caution when deriving only-child status from cross-sectional household grid data. Third, we demonstrate that both the size and the characteristics of the only-child group may differ across definitions, highlighting that the accurate operationalization of some definitions is particularly restricted by survey designs that prioritize mothers for data collection on children and families. We argue that researchers interested in sole children's outcomes must choose the most appropriate measure for a given research question and, given that many datasets limit how accurately any indicator of only children can capture the chosen definition, reflect on how the operationalization of their measure might affect the results.

A bivariate Poisson regression to analyse impact of outlier women on correlation between female schooling and fertility in Malawi

BACKGROUND

Women's levels of education and fertility are commonly associated. In Sub-Saharan Africa, the pace of decreasing fertility rates varies greatly, and this is linked to women's levels of education. However, this association may be influenced by unusual females who have uncommon measurements on both variables. Despite this, most studies that researched this association have only analysed the data descriptively, without taking into account the effect of potential outliers. This study aimed to examine the presence and impact of outlier women on the relationship between female education and fertility in Malawi, using regression methods.

METHODS

To analyse the correlation between women's schooling and fertility and evaluate the effect of outliers on this relationship, a bivariate Poisson model was applied to three recent demographic and health surveys in Malawi. The R software version 4.3.0 was used for model fitting, outlier computations, and correlation analysis. The STATA version 12.0 was used for data cleaning.

RESULTS

The findings revealed a correlation of -0.68 to -0.61 between schooling and fertility over 15 years in Malawi. A few outlier women were identified, most of whom had either attended 0 or at least 9 years of schooling and had born either 0 or at least 5 children. The majority of the outliers were non-users of modern contraceptive methods and worked as domestic workers or were unemployed. Removing the outliers from the analysis led to marked changes in the fixed effects sizes and slight shifts in correlation, but not in the direction and significance of the estimates. The woman's marital status, occupation, household wealth, age at first sex, and usage of modern contraceptives exhibited significant effects on education and fertility outcomes.

CONCLUSION

There is a high negative correlation between female schooling and fertility in Malawi. Some outlier women were identified, they had either attended zero or at least nine years of schooling and had either born zero or at least five children. Most of them were non-users of modern contraceptives and domestic workers. Their impact on regression estimates was substantial, but minimal on correlation. Their identification highlights the need for policymakers to reconsider implementation strategies for modern contraceptive methods to make them more effective.

Assessing the "healthy immigrant effect" in mental health: Intra- and inter-cohort trends in mood and/or anxiety disorders

BACKGROUND

The healthy immigrant effect implies that, at the time of immigration, new immigrants are typically healthier than the Canadian-born population. Furthermore, this health advantage fades the longer cohorts of immigrants remain in the host country.

METHODS

Most studies assessing the healthy immigrant effect rely on strong, untestable assumptions to extract unique effects for length of stay (LOS) (i.e., how long an immigrant has been in a host country), period (i.e., year of observation), and cohort (i.e., year of immigration). Rather than attempting to parse out separate effects for LOS, period, and cohort, we adopt a descriptive, cohort-centric approach to study immigrant mental health, which examines intra- and inter-cohort trends, that is, joint LOS-period and cohort-period parameters, respectively. While intra-cohort trends show how immigrants' mental health change with LOS across periods, inter-cohort trends reveal how the mental health of successive cohorts of immigrants differ across time periods. To provide a thorough assessment of the healthy immigrant effect, we use both survey and administrative data on cohorts of Canadian immigrants from 2003 to 2013.

RESULTS

The survey data reveal that mental health declines steeply (i.e., there is an increase in mood and/or anxiety disorders) within and across immigrant cohorts, while the administrative data show little overall change in mental health care utilization within and across cohorts. The divergent results may reflect issues related to barriers in access to mental health services because the administrative data, which are based on health care utilization, do not the capture the increase in mental disorders seen in the survey data.

CONCLUSION

This study highlights the benefit of a cohort-based approach to assess the healthy immigrant effect as it pertains to mental health as well as the importance of using different types of data, which may be measuring different aspects of immigrant mental health and health care utilization.

Inventory of Survey Databases for Native Hawaiian, Pacific Islander, and Filipino Health Disparities Research

The aim of this scoping review was to assist researchers who want to use survey data, either in academic or community settings, to identify and comprehend health disparities affecting Native Hawaiian (NH), Pacific Islander (PI), and/or Filipino populations, as these are groups with known and numerous health disparities. The scoping review methodology was used to identify survey datasets that disaggregate data for NH, PI, or Filipinos. Healthdata.gov was searched, as there is not an official index of databases. The website was established by the United States (US) Department and Health and Human Services to increase accessibility of health data for entrepreneurs, researchers, and policy makers, with the ultimate goal of improving health outcomes. Using the search term 'survey,' 332 datasets were retrieved, many of which were duplicates from different years. Datasets were included that met the following criteria: (1) related to health; (2) disaggregated NH, PI, and/or Filipino subgroups; (3) administered in the US; (4) publicly available; (5) individual-level data; (6) self-reported information; and (7) contained data from 2010 or later. Fifteen survey datasets met the inclusion criteria. Two additional survey datasets were identified by colleagues. For each dataset, the dataset name, data source, years of the data availability, availability of disaggregated NH, PI, and/or Filipino data, data on health outcomes and social determinants of health, and website information were documented. This inventory of datasets should be of use to researchers who want to advance understanding of health disparities experienced by NH, PI, and Filipino populations in the US.

Risk preferences, preventive behaviour, and the probability of a loss: Empirical evidence from the COVID-19 pandemic

RATIONALE

A theoretical model of optimal choice under risk, in which an individual chooses the level of prevention to avoid a loss, has the ambiguous prediction that a higher risk-taking preference increases the probability of a loss.

OBJECTIVE

To empirically investigate the prediction in the case of COVID-19 with individual-level survey data.

DATA

Survey data from the Understanding America Study (UAS). The UAS Coronavirus Tracking Survey followed 8628 respondents from March 2020 until July 2021 (29 survey waves) and data was gathered on having contracted COVID-19, vaccination, and preventive behaviour. Separate UAS modules gathered data on individuals' risk preferences; twice before and once during the COVID-19 pandemic. UAS also gathered data on pre-pandemic health and socio-economic status. Combining these data, and dropping missing observations, provided longitudinal data for 4335 respondents (96,370 observations) of whom 530 contracted COVID-19.

RESULTS

In support of the theoretical prediction, the empirical findings show that a one-standard deviation higher risk-taking preference is associated with about a one-third higher probability of contracting COVID-19 within two weeks. Furthermore, the findings show that individuals' risk-taking preference is negatively associated with the preventive behaviour of social distancing and not associated with getting vaccinated. There is, however, no support for preventive behaviour being associated with the probability of contracting COVID-19. The exception is for being vaccinated, which is negatively associated with the probability of contracting COVID-19. The findings, therefore, do not support that the positive association of the risk-taking preference with the probability of contracting COVID-19 is mediated through observed preventive behaviour.

CONCLUSIONS

The findings support the importance of individuals' risk-taking behaviour for contracting COVID-19 and, more generally, the importance of loss prevention as a risk management tool for individuals.

Attitude Towards Deposit Limits and Relationship with Their Account-Based Data Among a Sample of German Online Slots Players

Social responsibility and duty of care have become major cornerstones for gambling operators. This has led to the introduction of many different responsible gambling tools such as limit-setting, mandatory play breaks, and personalized messaging. In the present study, the authors were given access to two secondary datasets provided by a German online slots game operator. The first dataset was from an online survey carried out by the gambling operator among 1000 of its players concerning their attitude towards deposit limits as well as self-reported problem gambling. In addition to the survey responses, the authors were given access to a second dataset of account-based data concerning each customer's wagers, wins, monetary deposits, and monetary withdrawals. These datasets were then combined. The majority of players had a positive attitude towards the maximum deposit monthly deposit limit which was introduced by the German State Treaty on Gambling in 2021. Players who disagreed with the maximum monthly deposit limit, deposited significantly more money in the 30 days prior to answering the survey questions compared to players who agreed with the monthly deposit limit. The tracking data found only 7.6% of players had deposited the maximum amount of money allowed in one month. However, 60.5% of players in the survey data said that they did so. Players who said that they continued to gamble after reaching the deposit limit wagered and deposited significantly more money in the 30 days prior to the survey compared to players who said they stopped gambling after reaching the deposit limit. Two-fifths of players said they continued to gamble after reaching the monthly deposit limit (42%). The majority of the players said they chose a personal deposit limit because it helped them to better control their gambling expenditure. A quarter of the players reported gambling problems using the Brief Biosocial Gambling Screen (27%). Self-reported problem gambling was not correlated with depositing, wagering or any other player tracking metric.

Versorgung geriatrischer Krankheitsbilder unter ausgewählten ambulanten Facharztgruppen: Kombination von Befragungs- und GKV-Routinedaten zur Abbildung des Leistungsgeschehens

BACKGROUND

In light of an aging population, the German health system faces the challenge of adapting regional health care structures to the changing care needs of geriatric patients. Since geriatric care is interprofessional, a structural analysis of the service providers involved is required. Therefore, the aim of this study is to determine the primary and joint care responsibilities for geriatric patients with specific characteristics, to estimate the associated effort for selected outpatient medical service providers and to identify resulting care concentrations.

METHODS

The analysis includes six selected specialist disciplines in the outpatient sector and is based on two databases: 1) A representative survey among outpatient physicians related to geriatric care (n = 400) to examine both the primary geriatric care needs that professionals treat regularly and aggravating geriatric morbidity. 2) A claims data analysis determines services and efforts for approximately 300,000 geriatric patients for every year from 2014 to 2018. For the specialists included in the analysis, care concentration was determined by association analysis comparing the care efforts of outpatient physicians for patients with different geriatric characteristics.

RESULTS

General practitioners, in particular, serve as primary care providers for all geriatric characteristics; there is no concentration of care on specific patient groups. Concentrations associated with care efforts and joint care responsibilities for patients with certain geriatric characteristics are found among the more specialized physician groups. Across all professions, the physicians surveyed believe that geriatric-specific immobility, depression, anxiety disorders and cognitive deficits make the provision of care more difficult.

DISCUSSION

The results contribute to the understanding of primary and interdisciplinary care responsibilities of outpatient physicians related to the treatment of geriatric conditions and can thus represent an important basis for the structural planning of geriatric care. Nevertheless, it should be noted that within the scope of the analysis presented, only general practitioners and five specialist disciplines could be taken into account. Therefore, the considerations primarily allow initial conclusions about the care responsibility of outpatient physicians with regard to geriatric morbidity. To enable comprehensive structural planning, however, the analyses would have to be expanded to include all specialists involved in geriatric care.

CONCLUSION

The joint care responsibility of outpatient physicians for specific geriatric patients underlines the relevance for interdisciplinary care models and the need for expansion of geriatric expertise in the outpatient sector. In view of the ageing population and an increase in morbidity, the planning of care structures should be based on the needs of geriatric patients and the associated expenses incurred by the various health care providers.

Survey data on Families' perceptions of ed-tech corporations, educational digital platforms and children's rights

This data article describes the dataset of the project "edDIT: Technological corporations, digital educational platforms and guarantee of children's rights with a gender approach". This study has analysed the impact of the use of corporate digital platforms in public schools in Catalonia. A series of data were collected through an online survey, with a total sample of 2347 parents/caregivers. The description of the data contained in this article is divided into two main parts. The first one is a descriptive analysis of all the items included in the survey and has been carried out using tables and figures. The second one refers to the construction of scales. Three scales were constructed and included in the data set: 'Opinions about Educational Digital Platforms', 'Concerns about the use of the data generated on the utilisation of the digital platform' and 'Parental Engagement'. The scales were created using Confirmatory Factor Analysis (CFA) and Multigroup Confirmatory Analysis (MG-CFA). This dataset will be relevant for researchers in different fields, in particular for those interested in digital inclusion public policies and educational policies.

Conscientious use of patient-reported outcome measures in supportive care

PURPOSE

Patient-reported outcome measures (PRO) are critical tools to developing an understanding of cancer patients' experience. This paper presents some of the lesser-understood implications of using patient-reported outcome measures in clinical research.

METHODS

This study uses a combination of literature sources, real-world examples from supportive care studies, and statistical simulations to demonstrate the operating characteristics of patient-reported measures.

RESULTS

It is demonstrated that care must be taken in the analysis of PROs as the assumptions of the most common mean-based approaches are often violated including linearity, normally distributed errors, interference with asymptotic convergence via boundary values, and more. Further, the implications of subjective discretization are shown to reduce the apparent statistical power of PRO-based studies.

CONCLUSIONS

PRO-based studies must be designed conscientiously as each PRO item will demonstrate a varying degree of subjectivity in a given population. Sample sizes of randomized studies using PROs must be inflated to account for this. Analyses should consider using ordinal statistical models until such time as the assumptions of mean-based models can be verified.

Predictable profits and losses in a health insurance market with risk equalization: A multiple-contract period perspective

Many social health insurance systems rely on 'regulated competition' among insurers to improve efficiency. In the presence of community-rated premiums, risk equalization is an important regulatory feature to mitigate risk-selection incentives in such systems. Empirical studies evaluating selection incentives have typically quantified group-level (un)profitability for one contract period. However, due to switching barriers, a multiple contract period perspective might be more relevant. In this paper, using data from a large health survey (N≈380k) we identify subgroups of chronically ill and healthy individuals in year t and follow these groups over three consecutive years. Using administrative data covering the entire Dutch population (N≈17m), we then simulate the mean per person predictable profits and losses (i.e. spending predicted by a sophisticated risk-equalization model minus actual spending) of these groups over the three follow-up years. We find that most of the groups of chronically ill are persistently unprofitable on average, while the healthy group is persistently profitable. This implies that selection incentives might be stronger than initially thought, underscoring the necessity of eliminating predictable profits and losses for the adequate functioning of competitive social health insurance markets.

The "Great Lockdown" and cultural consumption in the UK

In this paper, we exploit a unique weekly longitudinal survey of adults in the UK purposefully collected to study consumption choices with respect to cultural content types during the first Covid-19 national lockdown (the "Great Lockdown"). We look for changes in the probability of consuming different cultural and creative types of content (Music, Movies, TV, Games, Books, Magazines and Audiobooks), as well as changes in the overall variety of consumption. We find that changes in consumption depend on the type of content. In particular, other things being equal, the likelihood of listening to Music and playing Games went up and the likelihood of reading Books went down. We find little statistically significant evidence of changes in the probability of consumption of the other types of content. We find that, while on average individuals increased the variety of their consumption, the statistical significance of this increase varied depending on the socio-demographic and economic characteristic of interest. In particular, we find evidence of an increase in the variety of consumption for those at the bottom of the distribution of socio-economic status, which speaks to the importance of access to culture and creativity during lockdown for this specific social class.

Tail and Center Rounding of Probabilistic Expectations in the Health and Retirement Study

We study rounding of numerical expectations in the Health and Retirement Study (HRS) between 2002 and 2014. We document that respondent-specific rounding patterns across questions in individual waves are quite stable across waves. We discover a tendency by about half of the respondents to provide more refined responses in the tails of the 0-100 scale than the center. In contrast, only about five percent of the respondents give more refined responses in the center than the tails. We find that respondents tend to report the values 25 and 75 more frequently than other values ending in 5. We also find that rounding practices vary somewhat across question domains and respondent characteristics. We propose an inferential approach that assumes stability of response tendencies across questions and waves to infer person-specific rounding in each question domain and scale segment and that replaces each point-response with an interval representing the range of possible values of the true latent belief. Using expectations from the 2016 wave of the HRS, we validate our approach. To demonstrate the consequences of rounding on inference, we compare best-predictor estimates from face-value expectations with those implied by our intervals.

Economic forecasting in a pandemic: some evidence from Singapore

This paper aims to investigate whether the predictive performance and behaviour of professional forecasters are different during the COVID-19 pandemic as compared with the global financial crisis of 2008 and normal times. To this end, we use a survey of professional forecasters in Singapore collated by the central bank to analyse the forecasting records for GDP growth and CPI inflation for the period 2000Q1-2021Q4. We first examine the point forecasts to document the extent of forecast failure during the two crises and explore various explanations for it, such as leader-following and herding behaviour. Then, using percentile-based summary measures of probability distribution forecasts, we study how the degree of consensus and extent of subjective uncertainty among forecasters were affected by crisis conditions. A trend break is observed in the subjective uncertainty associated with growth projections after the onset of the COVID-19 crisis. In contrast, both subjective uncertainty and the degree of consensus in inflation projections were essentially unchanged in crises, suggesting that the short-term inflation expectations of forecasters were strongly anchored.

Economic impacts of harmful algal blooms on fishery-dependent communities

The recreational razor clam fishery is the largest recreational bivalve fishery in the Pacific Northwest and a major source of tourism-related income to small communities in the region. Delays and closures of recreational shellfisheries due to the increasing frequency of harmful algal blooms (HABs) threaten to have significant negative impacts on fishery dependent communities. Coupling previous recreational shellfishing expenditure estimates from the literature with a novel dataset of daily visits to local businesses, we estimate a range of economic impacts resulting from the cancellation of razor clam digs at Long Beach, WA, the most popular beach in the State for recreational clam diggers. Our results indicate that a full season closure can lead to lost sales revenues of $16,875 for gas stations, $117,600 for food stores, $217,800 for accommodations and $491,400 for food service places for a total lower bound economic impact of $843,675. We discuss the opportunity for early warning systems, like the Pacific Northwest HAB Bulletin, to guide policy and facilitate business decisions that hedge the risk of revenue losses associated with dig cancellations.

Associations between illness burden and care experiences among Medicare beneficiaries before or after a cancer diagnosis

INTRODUCTION

To understand associations between a new measure of illness burden and care experiences in a large, national sample of Medicare beneficiaries surveyed before or after a cancer diagnosis.

MATERIALS AND METHODS

The SEER-CAHPS Illness Burden Index (SCIBI) was previously developed using Surveillance, Epidemiology, and End Results (SEER)-Consumer Assessment of Healthcare Providers and Systems (CAHPS) linked data. The SCIBI provides a standardized morbidity score based on self- and other-reported information from 8 domains and proxies relative risk of 12-month, all-cause mortality among people surveyed before or after a cancer diagnosis. We analyzed a population of Medicare beneficiaries (n = 116,735; 49% fee-for-service and 51% Medicare Advantage [MA]; 73% post-cancer diagnosis) surveyed 2007-2013 to understand how their SCIBI scores were associated with 12 different care experience measures. Frequentist and Bayesian multivariable regression models adjusted for standard case-mix adjustors, enrollment type, timing of cancer diagnoses relative to survey, and survey year.

RESULTS AND DISCUSSION

SCIBl scores were associated (P < .001) in frequentist models with better ratings of Health Plan (coefficient ± standard error: 0.33 ± 0.08) and better Getting Care Quickly scores (0.51 ± 0.09). In Bayesian models, individuals with higher illness burden had similar results on the same two measures and also reported reliably worse Overall Care experiences (coefficient ± posterior SD: -0.17 ± 0.06). Illness burden may influence how people experience care or report those experiences. Individuals with greater illness burdens may need intensive care coordination and multilevel interventions before and after a cancer diagnosis.

Does socioeconomic status impact the relationship between school absence and outcomes?

Absence from school, especially frequent or prolonged absence, is acknowledged as a potential factor in school dropout and suboptimal academic achievement. The issue of absence from school took on added significance in 2020 with the onset of the COVID-19 crisis, which resulted in schooling interruptions in several jurisdictions. However, there is little agreement in the literature on the exact relationship between absence and school outcomes as a function of socioeconomic status (SES). Using nationally representative pre-COVID longitudinal data of young Australians aged 12-13 and 14-15, this paper examines the relationship between absence from school on the one hand and school belonging and academic achievement (numeracy and reading test scores) on the other. The paper also examines whether SES intersects this relationship. Controlling for gender, prior educational achievement, computer access, and time spent doing homework, the study finds that absence impacts belonging, but that SES does not significantly influence this relationship. The effect of absence on reading is not significant either. However, absence is associated with numeracy outcomes, with the strongest associations among low SES young people at age 14. Policy implications of these findings are discussed.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13384-022-00535-2.

Addressing recall bias in (post-)conflict data collection and analysis: lessons from a large-scale health survey in Colombia

Background

Much applied research on the consequences of conflicts for health suffers from data limitations, particularly the absence of longitudinal data spanning pre-, during- and post-conflict periods for affected individuals. Such limitations often hinder reliable measurement of the causal effects of conflict and their pathways, hampering also the design of effective post-conflict health policies. Researchers have sought to overcome these data limitations by conducting ex-post surveys, asking participants to recall their health and living standards before (or during) conflict. These questions may introduce important analytical biases due to recall error and misreporting.

Methods

We investigate how to implement ex-post health surveys that collect recall data, for conflict-affected populations, which is reliable for empirical analysis via standard quantitative methods. We propose two complementary strategies based on methods developed in the psychology and psychometric literatures—the Flashbulb and test-retest approaches—to identify and address recall bias in ex-post health survey data. We apply these strategies to the case study of a large-scale health survey which we implemented in Colombia in the post-peace agreement period, but that included recall questions referring to the conflict period.

Results

We demonstrate how adapted versions of the Flashbulb and test-retest strategies can be used to test for recall bias in (post-)conflict survey responses. We also show how these test strategies can be incorporated into post-conflict health surveys in their design phase, accompanied by further ex-ante mitigation strategies for recall bias, to increase the reliability of survey data analysis—including by identifying the survey modules, and sub-populations, for which empirical analysis is likely to yield more reliable causal inference about the health consequences of conflict.

Conclusions

Our study makes a novel contribution to the field of applied health research in humanitarian settings, by providing practical methodological guidance for the implementation of data collection efforts in humanitarian contexts where recall information, collected from primary surveys, is required to allow assessments of changes in health and wellbeing. Key lessons include the importance of embedding appropriate strategies to test and address recall bias into the design of any relevant data collection tools in post-conflict or humanitarian contexts.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13031-022-00446-0.

Exchange rate expectation, abnormal returns, and the COVID-19 pandemic

This study analyzes the impact of the COVID-19 pandemic on exchange rates based on a comprehensive set of survey forecasts for more than 50 currency pairs. At the first stage, we assess whether the policy to manage the COVID-19 pandemic affects the expected path of exchange rates over the medium and long run. At the second stage, we adopt an event study analysis and identify the occurrences of abnormal returns on foreign exchange markets since the start of the COVID-19 pandemic. Our results suggest the presence of cumulated excess returns that are partly driven by macroeconomic fundamentals for major currencies. However, we find that policy responses to the COVID-19 pandemic have the strongest effect on cumulated excess returns, showing that foreign exchange markets take expected policy effects as an important determinant of future developments into account while expectations for minor currencies react stronger to response policies.

Top-income adjustments and official statistics on income distribution: the case of the UK

UK official statistics on income distribution have incorporated top-income adjustments to household survey data since 1992. This article reviews the work undertaken by the Department for Work and Pensions and the Office for National Statistics, and the academic research that influenced them, and reflects on the lessons to learn from the UK experience.

Does democracy make taller men? Cross-country European evidence

We study whether a democracy improves a measure of individual wellbeing: human heights. Drawing on individual-level datasets, we test the democracy and height hypothesis using a battery of eight different measures of democracy and we account for several potential confounders, regional and cohort fixed effects. We document that democracy - or its quality during early childhood - shows a strong and positive conditional correlation with male, but not female, adult stature. Our preferred estimates suggest that being born in a democracy increases average male stature from a minimum of 1.33 to a maximum of 2.4 cm. We also show a positive association when democracy increases from childhood to adolescence, and when we adopt measures of existing democratic capital before birth, and at the end of height plasticity in early adulthood. We also document that democracy is associated with a reduction in inequality of heights distribution. Our estimates are driven by period-specific heterogeneity, namely, early democratizations are associated with taller people more than later ones. Results are robust to the inclusion of countries exposed to communism.

Hitting where it hurts most: COVID-19 and low-income urban college students

Using data from a rich online student survey collected at an urban college during the summer of 2020, I estimate the causal impact of the pandemic on students' current and expected outcomes. I find that the COVID-19 disruptions on students' lives were significant. Because of the pandemic, between 14% and 34% of the students considered dropping a class during spring 2020, 30% modified their graduation plans, and the freshman fall retention rate dropped by 26%. The pandemic also deprived 39% of the students of their jobs and reduced the earnings of 35% and the expected household income of 64%. The economic consequences are grimmer for Pell recipients as they were 20% more likely to lose a job due to the pandemic and 17% more likely to experience earning losses than never Pell recipients. Despite being 36% more likely to receive financial support from the CARES Act than never Pell recipients, Pell recipients were 65% more likely to have faced food and shelter insecurity, and 15% more likely to expect lower annual household income. In contrast with economic outcomes, the only educational differential effect between the two groups is Pell recipients' 41% greater likelihood to consider dropping a course mostly because of concerns that their grade would jeopardize their financial assistance. Other vulnerable students, such as first-generation students and transfer students, were relatively harder hit. To the extent that they seem to rely less on financial aid and more on income from wage and salary jobs, both their educational and employment outcomes were more negatively impacted by the pandemic relative to students whose parents also attended college or those who began college as freshmen.

The impact of parental substance use disorder and other family-related problems on school related outcomes

Aims

To identify young people with different levels of family-related problems, including parental substance use disorder (PSUD), and investigate differences in grades at graduation from compulsory school and further enrollment in education.

Methods

Participants included 6784 emerging adults (aged 15-25 years) from samples drawn for two national surveys in Denmark 2014-2015. Latent classes were constructed using the following parental variables: PSUD, offspring not living with both parents, and parental criminality, mental disorders, chronic diseases and long-term unemployment. The characteristics were analyzed using an independent one-way ANOVA. Differences in grade point average and further enrollment were analyzed using linear regression and logistic regression, respectively.

Results

Four classes of families were identified: 1. "Low adverse childhood experiences (ACE) families", 2. "Families with PSUD", 3. "Families with unemployment" and 4. "High ACE families". There were significant differences in grades, with the highest average among youth from "Low ACE families" (males = 6.83; females = 7.40) and significant lower averages among both males and females from the other types of families, but lowest among young people from "High ACE families" (Males = 5.58; females = 5.79). Youth from "Families with PSUD" (Males: OR = 1.51; 95% CI: 1.01-2.26; females: OR = 2.16; 95% CI: 1.22-3.85) and "High ACE families" (Males: OR = 1.78; 95% CI: 1.11-2.26) were significantly more likely not to be enrolled in further education compared with "Low ACE families".

Conclusions

Young people who experience PSUD, both as the primary family-related problem as well as among multiple family-related problems, are at increased risk for negative school-related outcomes.

A systematic literature review of how and whether social media data can complement traditional survey data to study public opinion

In this article, we review existing research on the complementarity of social media data and survey data for the study of public opinion. We start by situating our review in the extensive literature (N = 187) about the uses, challenges, and frameworks related to the use of social media for studying public opinion. Based on 187 relevant articles (141 empirical and 46 theoretical) - we identify within the 141 empircal ones six main research approaches concerning the complementarity of both data sources. Results show that the biggest share of the research has focused on how social media can be used to confirm survey findings, especially for election predictions. The main contribution of our review is to detail and classify other growing complementarity approaches, such as comparing both data sources on a given phenomenon, using survey measures as a proxy in social media research, enriching surveys with SMD, recruiting individuals on social media to conduct a second survey phase, and generating new insight on "old" or "under-investigated" topics or theories using SMD. We discuss the advantages and disadvantages associated with each of these approaches in relation to four main research purposes, namely the improvement of validity, sustainability, reliability, and interpretability. We conclude by discussing some limitations of our study and highlighting future paths for research.

Improved estimates for individual and population-level alcohol use in the United States, 1984-2020

Aims

While nationally representative alcohol surveys are a mainstay of public health monitoring, they underestimate consumption at the population level. This paper demonstrates how to adjust individual-level survey data using aggregated alcohol per capita (APC) data for improved individual- and population-level consumption estimates.

Design and Methods

For the period 1984-2020, data on self-reported alcohol consumption in the past 30 days were taken from the Behavioral Risk Factor Surveillance System (BRFSS) involving participants (18+ years) in the United States (US). Monthly abstainers were reallocated into lifetime abstainers, former drinkers, and 12-month drinkers using the 2005 National Alcohol Survey data. To correct for under-coverage of alcohol use, we triangulated APC and survey data by upshifting quantity (average grams/day) and frequency (drinking days/week) of alcohol use based on national- and state-level APC data. Results were provided for the US as a whole and for selected states to represent different drinking patterns.

Findings

The corrections described above resulted in improved correspondence between survey and APC data. Following our procedure, national estimates of alcohol quantity increased from 45% to 77% of APC estimates. Both quantity and frequency of alcohol use were upshifted; by upshifting to 90% of APC, we were able to fit trends and distributions in APC patterns for individual states and the US.

Conclusions

An individual-level dataset which more accurately reflects the alcohol use of US citizens was achieved. This dataset will be invaluable as a research tool and for the planning and evaluation of alcohol control policies for the US. The methodology described can also be used to adjust individual-level alcohol survey data in other geographical settings.

Innovative methods to analyse the impact of gender norms on adolescent health using global health survey data

Background

Understanding how gender norms affect health is an important entry point into designing programs and policies to change norms and improve gender equality and health. However, it is rare for global health datasets to include questions on gender norms, especially questions that go beyond measuring gender-related attitudes, thus limiting gender analysis.

Methods

We developed five case studies using health survey data from six countries to demonstrate approaches to defining and operationalising proxy measures and analytic approaches to investigating how gender norms can affect health. Key findings, strengths and limitations of our norms proxies and methodological choices are summarised.

Findings

Case studies revealed links between gender norms and multiple adolescent health outcomes. Proxys for norms were derived from data on attitudes, beliefs, and behaviours, as well as differences between attitudes and behaviours. Data were cross-sectional, longitudinal, census- and social network-based. Analytic methods were diverse. We found that gender norms affect: 1) Intimate partner violence in Nigeria; 2) Unhealthy weight control behaviours in Brazil and South Africa; 3) HIV status in Zambia; 4) Health and social mobility in the US; and 5) Childbirth in Honduras.

Interpretation

Researchers can use existing global health survey data to examine pathways through which gender norms affect health by generating proxies for gender norms. While direct measures of gender norms can greatly improve the understanding of how gender affects health, proxy measures for norms can be designed for the specific health-related outcome and normative context, for instance by either aggregating behaviours or attitudes or quantifying the difference (dissonance) between them. These norm proxies enable evaluations of the influence of gender norms on health and insights into possible reference groups and sanctions for non-compliers, thus informing programmes and policies to shape norms and improve health.

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This article presents effective methods to study gender norms in existing global health survey data.

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We devised conceptual pathways linking gender norms to gender-based health disparities.

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We identified gender norms proxies and reference groups enforcing the norm.

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We tested hypotheses linking gender norms to health.

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These methods can aid policy and programme design to advance gender equality and health.

Children with genetic conditions in the United States: Prevalence estimates from the 2016-2017 National Survey of Children's Health

PURPOSE

Estimating the overall prevalence of genetic conditions among children in the United States and the burden of these conditions on children and their families has been challenging. The redesigned National Survey of Children's Health provides an opportunity to examine the prevalence and burden.

METHODS

We used the combined 2016-2017 National Survey of Children's Health to estimate the prevalence of genetic conditions among children aged 0 to 17 years (N = 71,522). Bivariate analyses were used to assess differences in sociodemographic characteristics, health-related characteristics, and health care utilization between children with and without genetic conditions.

RESULTS

In 2016-2017, the prevalence of children aged 0 to 17 years with a reported genetic condition was approximately 0.039, roughly equating to 2.8 million children. A greater percentage of children with genetic conditions had a physical (50.9% vs 24.8%), mental (27.9% vs 5.8%), or behavioral/developmental/intellectual condition (55.6% vs 14.4%) than children without a genetic condition. Furthermore, they used more care and had more unmet health needs (7.6% vs 2.9%).

CONCLUSION

This study provides an estimate of the overall prevalence of children living with genetic conditions in the United States based on a nationally representative sample. It also highlights the physical, mental, and behavioral health needs among children with genetic conditions and their unmet health care needs.

How to Measure Retirement Age? A Comparison of Survey and Register Data

Due to an increasing heterogeneity in retirement transitions, the measurement of retirement age constitutes a major challenge for researchers and policymakers. In order to better understand the concept of retirement age, we compare a series of measures for retirement age assessed on the basis of survey and register data. We use data from Sweden, where flexible retirement schemes are implemented and register data are available. We link survey data from the Swedish Level of Living Survey with register data from the Swedish Longitudinal Integration Database for Health Insurance and Labour Market Studies. We create four measures of retirement age based on these datasets, applying approaches that have been used in previous literature. We analyse the means and distributions of these measures and evaluate the correlations between them. Finally, we regress common predictors of retirement age such as gender or education on the four measures of retirement age to examine potential differences in size, direction and statistical significance of the associations. We find that the survey measure of retirement age resembles the following two ways of defining retirement age in the register data: first, the age at which people receive more than half their income from old-age or disability pension and, second, the age at which they were not gainfully employed for at least 2 years. This insight gives us a better understanding of when in the retirement transition process, individuals identify with retirement. Moreover, it provides decision support for researchers working with register data to determine which measure to use.

Biases in Survey Estimates of Neonatal Mortality: Results From a Validation Study in Urban Areas of Guinea-Bissau

Neonatal deaths (occurring within 28 days of birth) account for close to one-half of all deaths among children under age 5 worldwide. In most low- and middle-income countries, data on neonatal deaths come primarily from household surveys. We conducted a validation study of survey data on neonatal mortality in Guinea-Bissau (West Africa). We used records from an urban health and demographic surveillance system (HDSS) that monitors child survival prospectively as our reference data set. We selected a stratified sample of 599 women aged 15-49 among residents of the HDSS and collected the birth histories of 422 participants. We cross-tabulated survey and HDSS data. We used a mathematical model to investigate biases in survey estimates of neonatal mortality. Reporting errors in survey data might lead to estimates of the neonatal mortality rate that are too high, which may limit our ability to track progress toward global health objectives.

Socio-Demographics, Gambling Participation, Gambling Settings, and Addictive Behaviors Associated with Gambling Modes: A Population-Based Study

Online and land-based gambling differ in terms of participation and harms. Multimode gambling has also been distinguished as a separate mode. The current study uses the Finnish Gambling 2019 population study sample of 18–74-year-old past-year gamblers (N = 3,077) to evaluate how these gambling modes differ in terms of socio-demographics, gambling participation, gambling settings, and addictive behaviors. We used land-based gambling as the reference group in a multinomial regression model. Male gender (OR 1.48), age between 18 and 54 (OR 1.88), and high income (OR 1.87) were associated with online gambling. The odds of online gambling were higher among those who gambled at least monthly (OR 1.34) and among those with the highest gambling spending (OR 3.62). Younger age (OR 2.31), high income (OR 1.51), gambling at least four game types (OR 2.96), spending the most money on gambling (OR 4.56), and gambling in at least three gambling settings were associated with multimode gambling. Socio-demographics and gambling participation were indicators of gambling modes. Online gambling was more intensive while multimode gambling was more frequent and versatile than land-based gambling. However, this was not reflected as increased addictive behaviors, probably due to the harmful nature of Finnish land-based gambling.

Serial cross-sectional data on the public's perception on the coronavirus during the first months of the pandemic in Germany

The coronavirus pandemic poses major challenges for governments and public health authorities. In order to implement appropriate measures, it is important to understand how the population is coping with the pandemic. This dataset contains serial cross-sectional survey data from the first months of the coronavirus pandemic in Germany. Data were collected between 24 March and 26 May 2020 in ten weekly surveys (ns ranging between 500 and 515, in total N = 5,076) as part of omnibus telephone interviews. Samples were drawn at random from landline and mobile telephone numbers. The main topics of the questionnaire were (a) the expected impact of the coronavirus on one's personal life, (b) perception of infection risk, (c) protective measures and (d) information behaviour. Data were weighted to ensure sociodemographic representativeness. To account for the rapidly changing situation of the coronavirus pandemic in Germany, the questionnaire underwent several adjustments during the data collection period.

Utility of linking survey and registry data to evaluate interventions and policies to address disparities in breast cancer survivorship among young women

PURPOSE

There is limited research linking data sources to evaluate the multifactorial impacts on the quality of treatment received and financial burden among young women with breast cancer. To address this gap and support future evaluation efforts, we examined the utility of combining patient survey and cancer registry data.

PATIENT AND METHODS

We administered a survey to women, aged 18-39 years, with breast cancer from four U.S. states. We conducted a systematic response-rate analysis and evaluated differences between racial groups. Survey responses were linked with cancer registry data to assess whether surveys could reliably supplement registry data.

RESULTS

A total of 830 women completed the survey for a response rate of 28.4 %. Blacks and Asian/Pacific Islanders were half as likely to respond as white women. Concordance between survey and registry data was high for demographic variables (Cohen's kappa [k]: 0.879 to 0.949), moderate to high for treatments received (k: 0.467 to 0.854), and low for hormone receptor status (k: 0.167 to 0.553). Survey items related to insurance status, employment, and symptoms revealed racial differences.

CONCLUSION

Cancer registry data, supplemented by patient surveys, can provide a broader understanding of the quality of care and financial impacts of breast cancer among young women.

Is South Africa closing the health gaps between districts? Monitoring progress towards universal health service coverage with routine facility data

BACKGROUND

South Africa is committed to advancing universal health coverage (UHC). The usefulness and potential of using routine health facility data for monitoring progress towards UHC, in the form of the 16-tracer WHO service coverage index (SCI), was assessed.

METHODS

Alternative approaches to calculating the WHO SCI from routine data, allowing for disaggregation to district level, were explored. Data extraction, coding, transformation and modelling processes were applied to generate time series for these alternatives. Equity was assessed using socio-economic quintiles by district.

RESULTS

The UHC SCI at a national level was 46.1 in 2007-2008 and 56.9 in 2016-2017. Only for the latter period, could the index be calculated for all indicators at a district level. Alternative indicators were formulated for 9 of 16 tracers in the index. Routine or repeated survey data could be used for 14 tracers. Apart from the NCD indicators, a gradient of poorer performance in the most deprived districts was evident in 2016-2017.

CONCLUSIONS

It is possible to construct the UHC SCI for South Africa from predominantly routine data sources. Overall, there is evidence from district level data of a trend towards reduced inequity in relation to specific categories (notably RMNCH). Progress towards UHC has the potential to overcome fragmentation and enable harmonisation and interoperability of information systems. Private sector reporting of data into routine information systems should be encouraged.

Patient Experiences With Telemedicine in a National Health Service Rheumatology Outpatient Department During Coronavirus Disease-19

The coronavirus disease-19 pandemic changed rheumatology practice with remote consultations being increasingly utilized where appropriate. We evaluated patient experiences with telephone consultations and report on patient attitudes toward current health care delivery and perspectives of telemedicine in a UK National Health Service rheumatology outpatient department. We analyzed 297 questionnaires from a postal survey conducted during the summer of 2020 after a telephone follow-up consultation. The mean age of respondents was 67 years and 68% were female. The 161 respondents (54%) reported it was their first telephone consultation and overall, 239 (84%) were satisfied with their health assessment. 60% would be happy to have future routine follow-up telephone consultations. Patients advised to shield shared similar satisfaction to the whole sample. However, with increasing age we identified a higher proportion were dissatisfied with telephone consultations and unlikely to have accessibility to video consultation or preferentially opt for this modality.

Estimating perceived parental substance use disorder: Using register data to adjust for non-participation in survey research

AIMS

To estimate the prevalence of parental substance use disorder (PSUD) in the general population based on young adults' reports adjusted for non-participation using register-based indicators of PSUD.

DESIGN

A national sample survey study combined with a retrospective register-based study. Setting Denmark. Participants 10,414 young people (aged 15-25 years) invited to two national sample surveys in 2014 and 2015 (5,755 participants and 4,659 non-participants).

MEASUREMENTS

A crude prevalence of PSUD was calculated based on participants' reports. Parental data from medical, mortality, prescription, and treatment registers (from the young adults' birth until the time of the surveys) were used to estimate a register-based prevalence of PSUD for both participants and non-participants. Differences between participants and non-participants were analysed using bivariate comparisons. Inverse probability weighting was used to adjust for bias due to non-participation. The crude prevalence of PSUD based on survey data was adjusted using the ratio of incidence proportion of the register-based PSUD compared with the survey-based PSUD.

FINDINGS

A total of 731 (12.7%) of the 5,755 survey participants reported PSUD. Register-based PSUD was more common among non-participants (856/4,659; 18.4%) compared with participants (738/5,755; 12.8%, OR = 1.53, 95% CI 1.38-1.70). The adjusted estimate of the survey-based PSUD increased by 2.5 percentage points, from 12.7% to 15.2%.

CONCLUSIONS

In the absence of register data, youth-reported PSUD is likely to underestimate the number of young people experiencing PSUD.

Adult death registration in Matlab, rural Bangladesh: completeness, correlates, and obstacles

Civil registration of vital events such as deaths and births is a key part of the process of securing rights and benefits for individuals worldwide. It also enables the production of vital statistics for local planning of social services. In many low- and lower-middle-income countries, however, civil registration and vital statistics (CRVS) systems do not adequately register significant numbers of births and, especially, deaths. In this study, we aim to estimate the completeness of adult death registration (for age 15 and older) in the Matlab health and demographic surveillance system (HDSS) area in Bangladesh and to identify reasons for (not) registering deaths in the national CRVS system. We conducted a sample survey of 2538 households and recorded 571 adult deaths that had occurred in the 3 years preceding the survey. Only 17% of these deaths were registered in the national CRVS system, with large gender differences in registration rates (male = 26% vs. female = 5%). Respondents who reported that a recent death in the household was registered indicated that the primary reasons for registration were to secure an inheritance and to access social services. The main reasons cited for not registering a death were lack of knowledge about CRVS and not perceiving the benefits of death registration. Information campaigns to raise awareness of death registration, as well as stronger incentives to register deaths, may be needed to improve the completeness of death registration in Bangladesh.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1186/s41118-021-00125-7.

Changes in pregnancy desire after a pregnancy scare in a random sample of young adult women in a Michigan county

OBJECTIVES

We examined whether and how long young women became more or less likely to desire a pregnancy after experiencing a "pregnancy scare."

STUDY DESIGN

We used data from the Relationship Dynamics and Social Life (RDSL) study, based on a random, population-based sample of 992 young women from a county in Michigan. They were interviewed weekly for 2.5 years. We used fixed-effects logistic regression models to predict pregnancy desire after a pregnancy scare.

RESULTS

Of the 759 sexually experienced women we analyzed, 103 (14%) experienced 128 pregnancy scares. A woman's (adjusted) odds of desiring a pregnancy were 3.70 (95% CI 2.27-6.02) times higher during the week after, 3.04 (95% CI 2.30-4.10) times higher during the month after a pregnancy scare, and 2.31 (95% CI 1.71-3.11) times higher during all weeks after the pregnancy scare, compared to her other weeks during the study period. In a final model directly comparing each period to all weeks before the pregnancy scare, the odds of pregnancy desire were highest (aOR 5.08, 95% CI 3.06-8.42) during the first week, slightly smaller (aOR 3.01, 95% CI 2.11 - 4.30) during the subsequent three weeks, and remained elevated (aOR 1.58, 95% CI 1.19-2.09) throughout the remainder of the study period.

CONCLUSIONS

Our analyses suggest that the experience of a pregnancy "scare" does not scare young women away from wanting pregnancies. On the contrary, the state of possibly being pregnant actually made young women in our study more likely to want to be pregnant, on average.

IMPLICATIONS

Very few young women desire a pregnancy during the transition to adulthood; however, a salient life event like a pregnancy scare can abruptly generate a desire for pregnancy. Our study contributes to efforts to help women implement their pregnancy desires by furthering our understanding of those desires and the contexts in which they are formed.

Deferred Action for Childhood Arrivals (DACA) medical students - an examination of their journey and experiences as medical students in limbo

BACKGROUND

Although the value of DACA medical students has been hypothesized, no data are available on their contribution to US healthcare. While the exact number of DACA recipients in medical school is unknown, DACA medical students are projected to represent an increasing proportion of physicians in the future. The current literature on DACA students has not analyzed the experiences of these students.

METHODS

A mixed-methods study on the career intentions and experiences of DACA medical students was performed utilizing survey data and in-depth interviews. The academic performance of a convenience sample of DACA medical students was compared to that of matriculated medical students from corresponding medical schools, national averages, and first-year residents according to specialty.

RESULTS

Thirty-three DACA medical students completed the survey and five participated in a qualitative interview. The average undergraduate GPA (SD) of the DACA medical student sample was 3.7 (0.3), the same as the national GPA of 2017-2018 matriculated medical students. The most common intended residency programs were Internal Medicine (27.2%), Emergency Medicine (15.2%), and Family Medicine (9.1%). In interviews, DACA students discussed their motivation for pursuing medicine, barriers and facilitators that they faced in attending medical school, their experiences as medical students, and their future plans.

CONCLUSIONS

The intent of this sample to pursue medical specialties in which there is a growing need further exemplifies the unique value of these students. It is vital to protect the status of DACA recipients and realize the contributions that DACA physicians provide to US healthcare.

A note on multiply robust predictive mean matching imputation with complex survey data

Predictive mean matching is a commonly used imputation procedure for addressing the problem of item nonrespone in surveys. The customary approach relies upon the specification of a single outcome regression model. In this note, we propose a novel predictive mean matching procedure that allows the user to specify multiple outcome regression models. The resulting estimator is multiply robust in the sense that it remains consistent if one of the specified outcome regression models is correctly specified. The results from a simulation study suggest that the proposed method performs well in terms of bias and efficiency.

Short-term financial constraints and SMEs' investment decision: evidence from the working capital channel

This paper investigates the real effect of short-term financial constraints on small and medium-sized enterprises (SMEs). Under the working capital channel, cash credit constraints force entrepreneurs to forgo investment opportunities in order to finance their working capital needs. Building on survey data, I find that short-term credit constraints are as important as long-term ones in SMEs' investment decisions. Besides, the detrimental effect of cash credit constraints on corporate investment is stronger for SMEs with higher increase in working capital needs but lower for liquid ones that are able to adjust their accounts receivable and inventories. My results suggest that short-term finance is a major issue for SMEs. Plain English Summary Short-term credit constraints turn out to be as important as long-term ones in SMEs' investment decisions. Building on survey data, this paper investigates the real effects of short-term financial constraints on small businesses through an under-explored transmission mechanism. While the bulk of research on the effects of financial constraints focuses on long-term liabilities, I stress the importance of short-term finance. Owing to the competition between working and fixed capital in cash-flow uses, cash credit constraints force entrepreneurs to allocate additional cash-flow to finance the increase in their working capital needs to the detriment of long-term assets.The main implication of this work is that supports for short-term financing would provide a significant boost to long-term investment and economic growth.

Did state-owned enterprises do better during COVID-19? Evidence from a survey of company executives in China

In a survey of 1,182 company executives in China, state-owned enterprises (SOEs) reported less business reductions under COVID-19. This paper examines if SOEs' superior performance was resulted from government support rather than innate ability of coping with the pandemic. We construct a proxy for firm-level government support using firm's human resources (HR) action taken during the outbreak with firm's 2019 China revenue share as an instrument for the HR action variable. After controlling for the proxy for firm-level government support as well as other observed firm characteristics, we find SOEs in the sample performing significantly worse in the pandemic period.

A survey dataset to identify industry practices and challenges for mine rehabilitation completion criteria in Western Australia

The development of acceptable and achievable completion criteria is fundamental to the successful relinquishment of mined land to a post-mining use. Despite the central role of completion criteria, there is still a need to build capacity and understanding of how to set targets and develop measurable completion criteria that are accepted by all stakeholders involved. The work described in this paper aimed to elicit industry practice, barriers, and opportunities for the development of feasible and acceptable completion criteria. We developed a quantitative survey that was administered online. The target respondents consisted of mining companies, consulting businesses, and relevant regulators in Western Australia. The survey questionnaire, raw survey data, and summary statistics are provided in this paper to increase research transparency and facilitate reproducibility of the methods by researchers in other jurisdictions.

Using ranked survey data in education research: Methods and applications

Researchers and practitioners in education and school psychology regularly use ranked data to drive student- and systems-level decision-making. These types of data can be derived from assessments of individual preferences among researchers and practitioners, assessments of preferences among stakeholders including parents and children, and rankings of students on academic and social-emotional competency. However, the analysis of ranked data in education and psychology has typically been limited to simple approaches such as the examination of mean ranks assigned to items. This paper unifies a collection of classical methodologies, as well as proposes new techniques, for analyzing ranked data used across disciplines and applies the methods to data generated in school psychological research. The scope of the paper is to serve as a roadmap for researchers in education and school psychology who seek to more fully leverage information contained in ranked data. These methodologies include descriptive analyses, visualizations, tests of uniformity, cluster analyses, and predictive models. We demonstrate these techniques on the survey data of Fefer, DeMagistris, and Shuttleton (2016) and illustrate how using a broader set of tools can yield improved insights by researchers and practitioners.

Assessment of the COVID-19 pandemic situation: Data from two countries with different security measures taken by authorities (Belarus and Russia)

The article presents the data on the evaluation of COVID-19 situation by adult respondents (age from 18 to 76) coming from countries with the common past, language and similar mentality but differing in governmental security measures during pandemic spring outbreak (no precautionary measures in Belarus (N = 267); lockdown and financial support in Russia (N = 397)). The data was collected via online survey platform (Google forms) from 2020.04.11 to 2020.06.04 (during the period of lock-down in Russia). The data contains socio-demographical information (sex, age, country of citizenship), survey answers and the results of standardized psychological tests (to measure dangerous and threatening social world view and hardiness). The survey consists of four blocks: specific impact of the COVID-19 situation on various aspects of respondents’ life; estimation of different fears; estimation of various aspects of COVID-19 situation, and estimation of personal resources. All the items require participants to rate them on a 11-point Likert scale from 0 (totally disagree, absolutely no fear or no impact) to 10 (totally agree, the strongest fear or impact). Descriptive statistics as well as the comparison results are given. The data may be used to investigate the influence of lockdown, social distancing, and isolation on psychological well-being as well as the impact of personal resources in psychological well-being in stressful situations.

Multiple imputation validation study: addressing unmeasured survey data in a longitudinal design

Background

Questionnaires used in longitudinal studies may have questions added or removed over time for numerous reasons. Data missing completely at a follow-up survey is a unique issue for longitudinal studies. While such excluded questions lack information at one follow-up survey, they are collected at other follow-up surveys, and covariances observed at other follow-up surveys may allow for the recovery of the missing data. This study utilized data from a large longitudinal cohort study to assess the efficiency and feasibility of using multiple imputation (MI) to recover this type of information.

Methods

Millennium Cohort Study participants completed the 9-item Patient Health Questionnaire (PHQ) depression module at 2 time points (2004, 2007). The suicidal ideation item in the module was set to missing for the 2007 assessment. Several single-level MI models using different sets of predictors and forms of suicidal ideation were used to compare self-reported values and imputed values for this item in 2007. Additionally, associations with sleep duration and smoking status, which are related constructs, were compared between self-reported and imputed values of suicidal ideation.

Results

Among 63,028 participants eligible for imputation analysis, 4.05% reported suicidal ideation on the 2007 survey. The imputation models successfully identified suicidal ideation, with a sensitivity ranging between 34 and 66% and a positive predictive value between 36 and 42%. Specificity remained above 96% and negative predictive value above 97% for all imputed models. Similar associations were found for all imputation models on related constructs, though the dichotomous suicidal ideation imputed from the model using only PHQ depression items yielded estimates that were closest with the self-reported associations for all adjusted analyses.

Conclusions

Although sensitivity and positive predictive value were relatively low, applying MI techniques allowed for inclusion of an otherwise missing variable. Additionally, correlations with related constructs were estimated near self-reported values. Therefore, the other 8 depression items can be used to estimate suicidal ideation that was completely missing from a survey using MI. However, these imputed values should not be used to estimate population prevalence.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12874-020-01158-w.

Random survival forests using linked data to measure illness burden among individuals before or after a cancer diagnosis: Development and internal validation of the SEER-CAHPS illness burden index

PURPOSE

To develop and internally validate an illness burden index among Medicare beneficiaries before or after a cancer diagnosis.

METHODS

Data source: SEER-CAHPS, linking Surveillance, Epidemiology, and End Results (SEER) cancer registry, Medicare enrollment and claims, and Medicare Consumer Assessment of Healthcare Providers and Systems (Medicare CAHPS) survey data providing self-reported sociodemographic, health, and functional status information. To generate a score for everyone in the dataset, we tabulated 4 groups within each annual subsample (2007-2013): 1) Medicare Advantage (MA) beneficiaries or 2) Medicare fee-for-service (FFS) beneficiaries, surveyed before cancer diagnosis; 3) MA beneficiaries or 4) Medicare FFS beneficiaries surveyed after diagnosis. Random survival forests (RSFs) predicted 12-month all-cause mortality and drew predictor variables (mean per subsample = 44) from 8 domains: sociodemographic, cancer-specific, health status, chronic conditions, healthcare utilization, activity limitations, proxy, and location-based factors. Roughly two-thirds of the sample was held out for algorithm training. Error rates based on the validation ("out-of-bag," OOB) samples reflected the correctly classified percentage. Illness burden scores represented predicted cumulative mortality hazard.

RESULTS

The sample included 116,735 Medicare beneficiaries with cancer, of whom 73 % were surveyed after their cancer diagnosis; overall mean mortality rate in the 12 months after survey response was 6%. SEER-CAHPS Illness Burden Index (SCIBI) scores were positively skewed (median range: 0.29 [MA, pre-diagnosis] to 2.85 [FFS, post-diagnosis]; mean range: 2.08 [MA, pre-diagnosis] to 4.88 [MA, post-diagnosis]). The highest decile of the distribution had a 51 % mortality rate (range: 29-71 %); the bottom decile had a 1% mortality rate (range: 0-2 %). The error rate was 20 % overall (range: 9% [among FFS enrollees surveyed after diagnosis] to 36 % [MA enrollees surveyed before diagnosis]).

CONCLUSIONS

This new morbidity measure for Medicare beneficiaries with cancer may be useful to future SEER-CAHPS users who wish to adjust for comorbidity.

A survey dataset to evaluate the changes in mobility and transportation due to COVID-19 travel restrictions in Australia, Brazil, China, Ghana, India, Iran, Italy, Norway, South Africa, United States

COVID-19 pandemic has heavily impacted the global community. To curb the viral transmission, travel restrictions have been enforced across the world. The dataset documents the mobility disruptions and the modal shifts that have occurred as a consequence of the restrictive measures implemented in ten countries: Australia, Brazil, China, Ghana, India, Iran, Italy, Norway, South Africa and the United States. An online questionnaire was distributed during the period from the 11st to the 31st of May 2020, with a total of 9 394 respondents. The first part of the survey has characterized the frequency of use of all transport modes before and during the enforcement of the restrictions, while the second part of the survey has dealt with perceived risks of contracting COVID-19 from different transport modes and perceived effectiveness of travel mitigation measures. Overall, the dataset (stored in a repository publicly available) can be conveniently used to quantify and understand the modal shifts and people's cognitive behavior towards travel due to COVID-19. The collected responses can be further analysed by considering other demographic and socioeconomic covariates.

Data on antimicrobial use in livestock: Lessons from Uganda

In 2016, the General Assembly of the United Nations recognised inappropriate Antimicrobial Use (AMU) in livestock as one of the leading causes of increasing Antimicrobial Resistance (AMR). This is happening at a time when livestock production is expected to increase dramatically particularly in Africa, in response to the large rise in aggregate demand due to population growth, urbanisation and increasing income levels. Therefore, understanding the characteristics and appropriateness of AMU in livestock in this region is of utmost importance, yet data is seldom available. We propose to collect information on AMU in livestock by including related questions in nationally representative agricultural surveys that are carried out regularly (annually or every 2-3 years) by National Statistical Offices. This approach, with its limitation though, is a viable and cost-effective way to gather essential information on AMU in livestock farming. The Uganda Bureau of Statistics (UBOS) in collaboration with the Food and Agriculture Organization of the United Nations (FAO) piloted the introduction of key AMU questions in the Annual Agricultural Survey (AAS), gathering data from 6 thousand agricultural households nation-wide. Results show that AMU is considerable among livestock keeping households (35%), who use antibiotics not only for curative treatment (~58%) but also for disease prevention (~44%) and growth promotion (~5%). Data from the AAS also allows users to explore linkages between antibiotics use, livestock production practices (e.g. herd composition and size, feeding, breeding techniques, etc.) and other household / farm characteristics (e.g. location, education, household size, etc.), thereby effectively informing policy decisions.