Late Respondents Research Articles

Evolution of conflict management style during first year of paediatric residency.

First-year residents frequently encounter conflict during their training. Residents' conflict management strategies can influence patient safety, quality of care and perceptions of performance on competency evaluations. Existing literature inadequately describes how first-year resident conflict management styles evolve over time. The objective of this study is to assess if and how conflict management styles change during first year of paediatric residency in the United States. In 2021-2022, we conducted a non-experimental, longitudinal, survey study of first-year residents from 16 US-based paediatric residency programmes. Using the Thomas-Kilmann Conflict Mode Instrument, we scored first-year residents' use of five conflict management modes twice, 6 months apart. We calculated the percentage of first-year residents who experienced a change in predominant conflict management mode and assessed for changes in score and variance for each conflict management mode. Fifty-seven (18%) first-year residents participated in the first survey. Of those, 45 (14%) also completed the follow-up survey. Nonresponse bias analysis showed no significant difference in scores for early and late respondents or for second-survey respondents and non-respondents. Half of respondents experienced a change in predominant conflict management mode, but the distribution of predominant modes remained largely unchanged. When residents changed modes, they typically moved from one low-assertiveness mode, such as avoiding or accommodating, to the other. Only the use of the compromising conflict management mode significantly decreased. Variance did not significantly change. The overall lack of change in conflict management style may suggest the need for specific and focused educational interventions to help residents adjust their conflict handling strategies.

Living conditions, lifestyle habits and health among adults before and after the COVID-19 pandemic outbreak in Sweden - results from a cross-sectional population-based study

BackgroundStudies on the public health consequences of COVID-19 pandemic showing data based on robust methods are scarce. The aim of this study was to investigate mental and physical health as well as living conditions and lifestyle habits in the general population before and after the COVID-19 outbreak in Sweden.MethodsThe study is based on 2273 persons 16-84 years who responded to the national public health survey in February-May 2020 in Värmland county (overall response rate 45%). The differences between early respondents (before the outbreak, n = 1711) and late respondents (after the outbreak, n = 562) were studied using multivariate logistic regression, adjusting for background characteristics: age, gender, educational level, and country of birth. The same analyses were also completed in the corresponding survey carried out in February-June 2018.ResultsStatistically significant differences between the groups were obtained for economic difficulties and worry about losing one’s job, which were more common among late respondents, and for sleeping difficulties, which were more common among early respondents after adjusting for background characteristics. There were no differences in other living conditions nor in lifestyle factors. Prevalence of good self-rated health, high blood pressure, aches in shoulders or neck, anxiety or worry and stress did not differ between the groups. In 2018, the only statistically significant difference between early and late respondents concerned economic difficulties.ConclusionsVery few differences in living conditions, lifestyle factors and health were observed in the study population before and after the COVID-19 outbreak. The results suggest that, in addition to a possible decrease in sleeping difficulties, the prevalence of being worried about losing one’s job increased among the employed after the outbreak.

Living conditions, lifestyle habits and health among adults before and after the COVID-19 outbreak

BackgroundStudies on the public health consequences of COVID-19 pandemic based on robust data and methods are scarce. The aim of this study was to investigate mental and physical health as well as living conditions and lifestyle habits in the general population before and after the COVID-19 outbreak in Sweden in spring 2020.MethodsThe study is based on 2,273 persons 16-84 years who responded to the national public health survey in spring 2020 in Värmland county (overall response rate 45%). The differences between early (n = 1,711) and late (n = 562) respondents were studied using multivariate logistic regression, adjusting for background characteristics age, gender, educational level, and country of birth. Similar analyses were also completed in the corresponding survey carried out in spring 2018.ResultsStatistically significant differences between the groups were obtained for economic difficulties and worry about losing onés job, which were more common among late respondents, and for sleeping difficulties, which were more common among early respondents. There were no differences in other living conditions nor in lifestyle factors. Prevalence of good self-rated health, high blood pressure, aches in shoulders or neck, anxiety or worry and stress did not differ between the groups. In 2018, the only statistically significant difference between early and late respondents concerned economic difficulties.ConclusionsVery few differences in living conditions, lifestyle factors and health were observed in the study population before and after the COVID-19 outbreak when adjusted for background characteristics. The results suggest that, in addition to a possible decrease in sleeping difficulties, the prevalence of being worried about losing one's job increased among the employed after the outbreak.Key messages The results suggest that the prevalence of being worried about losing one’s job increased among the employed after the outbreak.More research on the short- and long-term public health consequences of the pandemic in the general populations and in different subgroups, using robust data and methods, is needed.

National Pharmacist Workforce Study (NPWS): Description of 2019 Survey Methods and Assessment of Nonresponse Bias.

National Pharmacist Workforce Studies (NPWS) have been conducted in the U.S. every five years since 2000. This article describes the online survey methods used for the latest NPWS conducted in 2019 and provides an assessment for nonresponse bias. Three waves of emails containing a link to the online survey were sent to a random sample of about 96,000 pharmacists licensed in the United States. The survey asked about pharmacist employment, work activities, work–life balance, practice characteristics, pharmacist demographics and training. A total of 5467 usable responses were received, for a usable response rate of 5.8%. To assess for nonresponse bias, respondent characteristics were compared to the population of U.S. pharmacists and a benchmark, while a wave analysis compared early and late respondents. The pharmacist sample–population comparison and the benchmark comparison showed that the NPWS respondents had a higher percentage of female pharmacists and a lower proportion of young pharmacists compared to the population of U.S. pharmacists and the benchmark sample. In some contrast, the wave analysis showed that the early respondents had a higher percentage of males and older pharmacists compared to the late respondents. Both the wave analysis and the benchmark comparison showed that the NPWS respondents (and early respondents) had a lower percent of pharmacists with a PharmD degree than did the late respondents and the benchmark group. These differences should be considered when interpreting the findings from the 2019 NPWS.

Demographic and socioeconomic characteristics of Canadian medical students: a cross-sectional study

BackgroundWhile the importance of medical students’ demographic characteristics in influencing the scope and location of their future practice is recognized, these data are not systematically collected in Canada. This study aimed to characterize and compare the demographics of Canadian medical students with the Canadian population.MethodsThrough an online survey, delivered in 2018, medical students at 14 English-speaking Canadian medical schools provided their age, sex, gender identity, ethnicity, educational background, and rurality of the area they grew up in. Respondents also provided information on parental income, occupation, and education as markers of socioeconomic status. Data were compared to the 2016 Canadian Census.ResultsA total of 1388 students responded to the survey, representing a response rate of 16.6%. Most respondents identified as women (63.1%) and were born after 1989 (82.1%). Respondents were less likely, compared to the Canadian Census population, to identify as black (1.7% vs 6.4%) (P < 0.001) or Aboriginal (3.5% vs. 7.4%) (P < 0.001), and have grown up in a rural area (6.4% vs. 18.7%) (P < 0.001). Respondents had higher socioeconomic status, indicated by parental education (29.0% of respondents’ parents had a master’s or doctoral degree, compared to 6.6% of Canadians aged 45–64), occupation (59.7% of respondents’ parents were high-level managers or professionals, compared to 19.2% of Canadians aged 45–64), and income (62.9% of respondents grew up in households with income >$100,000/year, compared to 32.4% of Canadians). Assessment of non-response bias showed that our sample was representative of all students at English-speaking Canadian medical schools with respect to age, though a higher proportion of respondents were female. Additionally, there were no differences between early and late respondents with respect to ethnicity, rurality, and parental income, occupation, and education.ConclusionsCanadian medical students have different socioeconomic characteristics compared to the Canadian population. Collecting and analyzing these characteristics can inform evidence-based admissions policies.

The magnitude and potential impact of missing data in a sexual violence campus climate survey

Objective: Assess the impact of survey non-response and non-completion for a campus climate survey. Participants: Intended for all degree-seeking students at a large, public, midwestern university, November 2014. Methods: The survey covered sexual assault experiences and related attitudes. We identify the magnitude and potential impact of survey non-response by comparing demographic data between respondents and non-respondents, sexual assault prevalence between early and late respondents, and demographic and attitudinal data between survey completers and partial completers. Results: Demographic groups were differentially represented in the survey. Sexual assault prevalence based on survey results may be underestimated for men, overestimated for women. Sensitive questions did not increase drop-off. Students completing more of the survey differed from those completing less. Conclusions: Colleges must plan survey administration and data sensitivity analysis to reduce potential for bias. Resources for sexual assault-related needs based on estimates from campus climate surveys with high non-response will likely be misallocated.

Early versus late respondents in web surveys: Evidence from a national health survey

Early versus late respondents in web surveys: Evidence from a national health survey

A Nonresponse Bias Analysis of the Health Information National Trends Survey (HINTS)

We conducted a nonresponse bias analysis of the Health Information National Trends Survey (HINTS) 4, Cycles 1 and 3, collected in 2011 and 2013, respectively, using three analysis methods: comparison of response rates for subgroups, comparison of estimates with weighting adjustments and external benchmarks, and level-of-effort analysis. Areas with higher concentrations of low socioeconomic status, higher concentrations of young households, and higher concentrations of minority and Hispanic populations had lower response rates. Estimates of health information seeking behavior were higher in HINTS compared to the National Health Interview Survey (NHIS). The HINTS estimate of doctors always explaining things in a way that the patient understands was not significantly different from the same estimate from the Medical Expenditure Panel Survey (MEPS); however, the HINTS estimate of health professionals always spending enough time with the patient was significantly lower than the same estimate from MEPS. A level-of-effort analysis found that those who respond later in the survey field period were less likely to have looked for information about health in the past 12 months, but found only small differences between early and late respondents for the majority of estimates examined. There is some evidence that estimates from HINTS could be biased toward finding higher levels of health information seeking.

Consequences of an Extended Recruitment on Participation in the Follow-Up of a Child Study: Results from the German IDEFICS Cohort.

Declining response proportions in population-based studies are often countered by extended recruitment efforts at baseline that may, however, result in higher attrition in a subsequent follow-up. This study analysed the effect of extended recruitment efforts on attrition at the first follow-up of a child cohort. We used paradata (i.e. information about the process of data collection) from the German IDEFICS cohort investigating dietary- and life style-induced health effects on children to quantify recruitment effort and classify respondents as completing the recruitment early vs. late for baseline and follow-up separately. Multilevel logistic regression models were used to investigate the association between recruitment effort and attrition at follow-up (loss to follow-up) adjusted for sociodemographic and health related variables. Individuals who were late respondents at baseline and early respondents at the follow-up had a higher chance of attrition (odds ratio 1.65, 95% confidence interval (CI) 1.19, 2.28) as compared to other groups. An investigation of reasons for non-participation revealed that members of this group were more likely to be not reachable by phone. An extended recruitment effort at baseline of a child cohort study is not per se associated with a higher chance of attrition at follow-up. Much care should be taken to collect valid telephone numbers.

Attitude, Knowledge, Skills and Decision Making Ability of Non-School Going Late Adolescents Towards Farming

The study was carried out to investigate the behavioural components of non-school going late adolescent with reference to farming and intervention for enhancing their abilities in Sonitpur district of Assam state of India. Multistage purposive cum random sampling were followed to select 110 numbers of late adolescents both male and female of equal size and their parents numbering 110. Suitable scales and statistical techniques were used for measurement of variables and analysis of data respectively. Data were collected through the personnel interval schedule. It was found that 71.36 per cent late adolescent respondents had a favourable attitude towards scientific agricultural practices. Only 14.55 per cent and 15.45 per cent late adolescent had a high level of knowledge and skills respectively in the areas of farming they were associated with. About 87.27 per cent parents expressed that their late adolescent children could not take right decision alone, family and peer mainly influenced in their decision making. Again 12.73 per cent parents expressed that their late adolescent's children could take fruitful and meaningful decisions independently and they could even analyze market conditions with regard to farming matters. The study recommended that the orientation of youth in modern agriculture should be properly honed up to provide meaningful employment to them.

A Note on Mechanisms Leading to Lower Data Quality of Late or Reluctant Respondents

Survey methodologists worry about trade-offs between nonresponse and measurement error. Past findings indicate that respondents brought into the survey late provide low-quality data. The diminished data quality is often attributed to lack of motivation. Quality is often measured through internal indicators and rarely through true scores. Using administrative data for validation purposes, this article documents increased measurement error as a function of recruitment effort for a large-scale employment survey in Germany. In this case study, the reduction in measurement quality of an important target variable is largely caused by differential measurement error in subpopulations and respective shifts in sample composition, as well as increased cognitive burden through the increased length of recall periods among later respondents. Only small portions of the relationship could be attributed to a lack of motivation among late or reluctant respondents.

The rhetoric and reality of home–work harmonization: a study of highly skilled Sri Lankan women from public and private sector organizations

In this paper, we report on a qualitative study of highly skilled Sri Lankan women. Based on in-depth interviews with early, mid- and late career respondents working for public and private sector organizations in Colombo, we explore the organizational constraints that women perceive to impact their home–work harmonization, while considering what they choose to do about prevailing obstacles. The findings provide insights into the different experiences of home–work harmonization between women from the two sectors and across various career stages. The diverse strategies respondents used to manage organizational constraints are discussed and their implications are noted. Finally, the contributions these findings make to existing understandings of women's home–work dynamics in the South Asia context and more widely are highlighted.

Should the Third Reminder be Sent? The Role of Survey Response Timing on Web Survey Results

Decreasing survey response rates are a growing concern as survey estimates may be biased by selective non-response. One method of assessing non-response bias is to examine the timing of survey response, specifically comparing those who respond late to a survey with those who respond early. This paper draws upon data obtained from multiple panel surveys conducted over a six-month period, and examines whether early, intermediate and late respondents differ significantly in demographics or in their responses to survey questions. By considering response timing as a repeated behaviour, or habit, spanning multiple surveys, a longitudinal measure of response timing is developed to identify the predictors of responding early to multiple surveys conducted over a period of time. Results indicate some directional differences in demographics and better data quality from early respondents, compared to their intermediate and late counterparts. We discuss the findings from the study and conclude with recommendations for future research.

Guidelines for Improving the Power Values of Statistical Tests for Nonresponse Bias Assessment in OM Research

ABSTRACTThe assessment of nonresponse bias in survey‐based empirical studies plays an important role in establishing the credibility of research results. Statistical methods that involve the comparison of responses from two groups (e.g., early vs. late respondents) on multiple characteristics, which are relevant to the study, are frequently utilized in the assessment of nonresponse bias. We consider the concepts of individual and complete statistical power used for multiple testing and show their relevance for determining the number of statistical tests to perform when assessing nonresponse bias. Our analysis of factors that influence both individual and complete power levels, yielded recommendations that can be used by operations management (OM) empirical researchers to improve their assessment of nonresponse bias. A power analysis of 61 survey‐based research papers published in three prestigious academic operations management journals, over the last decade, showed the occurrence of very low (&lt;0.4) power levels in some of the statistical tests used for assessing nonresponse bias. Such low power levels can lead to erroneous conclusions about nonresponse bias, and are indicators of the need for more rigor in the assessment of nonresponse bias in OM research.

Estimation of Model Variance Functions in Survey Sampling using Historical Micro-data

In this context, supposing a sampling survey framework and a model-based approach, the attention has been focused on the main features of the optimal prediction strategy of a given population mean, which implies estimation of some model parameters and functions, normally unknown. In particular, a wrong specification of the single unit model variances may lead to a serious loss of efficiency of estimates. For this reason, we have proposed some techniques for the estimation of model variances, which instead of being put equal to given a priori functions, can be estimated through historical data concerning past survey occasions. This approach is pragmatic and realistic, since quite always a time series of past observations is available, especially in a longitudinal survey context. Moreover, a simple post-stratification method has been proposed, in order to better define the models which can explain observed data. Finally, a comparative non parametric donor imputation procedure has been considered, which may be used separately or coupled with model assisted estimation. Usefulness of the techniques proposed has been tested through an empirical attempt, concerning the quarterly wholesale trade survey carried out by ISTAT (Italian National Statistical Institute) in the period 2005-2010. In this framework, the problem consists in minimizing magnitude of revisions, given by the differences between preliminary estimates (based on the sub-sample of quick respondents) and final estimates (which take into account late respondents as well). Main results show that model variances estimation through historical data leads to efficiency gains (lower average revisions) which cannot be neglected, and that model based prediction is normally more efficient than generalized regression estimation (which takes into account the sampling design randomness as well). Moreover, in many cases the mixed procedure (joint use of estimations of model unit variances through historical data, post-stratification and donor imputation) can improve precision of preliminary estimates even more. Keywords: Donor; Longitudinal Survey; Model; Non Response; Post-Stratification; Revision; Variance. 2010 Mathematics Subject Classification: 62D05

Improving Efficiency of Model Based Estimation in Longitudinal Surveys Through the Use of Historical Data

In this context, supposing a sampling survey framework and a model-based approach, the attention has been focused on the main features of the optimal prediction strategy for a population mean, which implies knowledge of some model parameters and functions, normally unknown. In particular, a wrong specification of the model individual variances may lead to a serious loss of efficiency of estimates. For this reason, we have proposed some techniques for the estimation of model variances, which instead of being put equal to given a priori functions, can be estimated through historical data concerning past survey occasions. A time series of past observations is almost always available, especially in a longitudinal survey context. Usefulness of the technique proposed has been tested through an empirical attempt, concerning the quarterly wholesale trade survey carried out by ISTAT (Italian National Statistical Institute) in the period 2005-2010. In this framework, the problem consists in minimising magnitude of revisions , given by the differences between preliminary estimates (based on the sub-sample of quick respondents) and final estimates (which take into account late respondents as well). Main results show that model variances estimation through historical data lead to efficiency gains which cannot be neglected. This outcome was confirmed by a further exercise, based on 1000 random replications of late responses.

Examining non-response bias in substance use research—Are late respondents proxies for non-respondents?

BackgroundNon-response is a major concern among substance use epidemiologists. When differences exist between respondents and non-respondents, survey estimates may be biased. Therefore, researchers have developed time-consuming strategies to convert non-respondents to respondents. The present study examines whether late respondents (converted former non-participants) differ from early respondents, non-consenters or silent refusers (consent givers but non-participants) in a cohort study, and whether non-response bias can be reduced by converting former non-respondents. Methods6099 French- and 5720 German-speaking Swiss 20-year-old males (more than 94% of the source population) completed a short questionnaire on substance use outcomes and socio-demographics, independent of any further participation in a cohort study. Early respondents were those participating in the cohort study after standard recruitment procedures. Late respondents were non-respondents that were converted through individual encouraging telephone contact. Early respondents, non-consenters and silent refusers were compared to late respondents using logistic regressions. Relative non-response biases for early respondents only, for respondents only (early and late) and for consenters (respondents and silent refusers) were also computed. ResultsLate respondents showed generally higher patterns of substance use than did early respondents, but lower patterns than did non-consenters and silent refusers. Converting initial non-respondents to respondents reduced the non-response bias, which might be further reduced if silent refusers were converted to respondents. ConclusionEfforts to convert refusers are effective in reducing non-response bias. However, converted late respondents cannot be seen as proxies of non-respondents, and are at best only indicative of existing response bias due to persistent non-respondents.

NON-RESPONSE BIAS IN A COMMUNITY SURVEY OF DRINKING, ALCOHOL-RELATED EXPERIENCES AND PUBLIC OPINION ON ALCOHOL POLICY

BackgroundThe continuing decline in response rates to household surveys is a concern for the health and social sciences as it increases the risk of selective non-response biasing the estimates of...

Non-response bias in a community survey of drinking, alcohol-related experiences and public opinion on alcohol policy

BackgroundThe continuing decline in response rates to household surveys is a concern for the health and social sciences as it increases the risk of selective non-response biasing the estimates of interest. MethodsWe analysed non-response bias in a postal survey measuring drinking behaviour, experience of harm and opinion on local government alcohol policies among residents in six New Zealand communities. The Continuum of Resistance model, which suggests that late respondents to a survey are most similar to non-respondents on the measures of interest, was used to guide our investigation. ResultsMen, younger people, those of Māori descent and those living in more deprived areas were less likely to respond to our survey than women, older people, those not of Māori descent and those living in comparatively affluent areas. Late respondents more closely resembled non-respondents demographically than early respondents. The prevalence of binge drinking and experience of assault was higher, and support for restrictive local government alcohol policies lower, among late respondents. Assuming the drinking behaviour and alcohol-related experiences of non-respondents were the same as those of late respondents, prevalence was under-estimated by 3.4% (relative difference: 13%) and 2.1% (relative difference: 21%) for monthly binge drinking and assault respectively. Policy support was not over-estimated. ConclusionThe findings add to a growing body of evidence suggesting that surveys under-estimate risk behaviour because of selective non-response and this bias increases as response rates fall. Notably, public opinion may not be subject to such misestimation.

The Effect of Low Survey Response Rates on Estimates of Alcohol Consumption in a General Population Survey

BackgroundResponse rates for surveys of alcohol use are declining for all modes of administration (postal, telephone, face-to-face). Low response rates may result in estimates that are biased by selective non-response. We examined non-response bias in the NZ GENACIS survey, a postal survey of a random electoral roll sample, with a response rate of 49.5% (n = 1924). Our aim was to estimate the magnitude of non-response bias in estimating the prevalence of current drinking and heavy episodic (binge) drinking.MethodsWe used the “continuum of resistance” model to guide the investigation. In this model the likelihood of response by sample members is related to the amount of effort required from the researchers to elicit a response. First, the demographic characteristics of respondents and non-respondents were compared. Second, respondents who returned their questionnaire before the first reminder (early), before the second reminder (intermediate) or after the second reminder (late) were compared by demographic characteristics, 12-month prevalence of drinking and prevalence of binge drinking.ResultsDemographic characteristics and prevalence of binge drinking were significantly different between late respondents and early/intermediate respondents, with the demographics of early and intermediate respondents being similar to people who refused to participate while late respondents were similar to all other non-respondents. Assuming non-respondents who did not actively refuse to participate had the same drinking patterns as late respondents, the prevalence of binge drinking amongst current drinkers was underestimated. Adjusting the prevalence of binge drinkers amongst current drinkers using population weights showed that this method of adjustment still resulted in an underestimate of the prevalence.ConclusionsThe findings suggest non-respondents who did not actively refuse to participate are likely to have similar or more extreme drinking behaviours than late respondents, and that surveys of health compromising behaviours such as alcohol use are likely to underestimate the prevalence of these behaviours.