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When planning abundance surveys, the impact of search intensity on the quality of the density estimates is rarely considered. We constructed a time-budget modeling framework for abundance surveys using principles from optimal foraging theory. We link search intensity to the number of sample units surveyed, searcher detection probability, the number of detections made, and the precision of the estimated population density. This framework allowed us to determine how a searcher should behave to produce optimized density estimates. Using data collected from quadrat and removal surveys of zebra mussels (Dreissena polymorpha) in central Minnesota, we applied this framework to evaluate potential improvements. We found that by tuning searcher behavior, density estimates from removal surveys of zebra mussels could be improved by up to 60% in some cases, without changing the overall survey time. Our framework also predicts a critical population density where the best survey method switches from removal surveys at low densities to quadrat surveys at high densities, consistent with past empirical work. In addition, we provide simulation tools to apply this form of analysis to a number of other commonly used survey designs. Our results provide insights into how to improve the performance of many survey methods in high-density environments by either tuning searcher behavior or decoupling the estimation of population density and detection probability.
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Can foreign conflicts affect attitudes in nonbelligerent countries? A large literature studies the effects of conflicts and wars on countries that are directly involved, without considering the potential consequences for other nonbelligerent countries that might nevertheless be threatened. To address this question, we examine how the Russian invasion of Ukraine affected 12 economic and political attitudes using survey data covering eight European countries. We use a natural experiment whereby the timing of the invasion overlapped with the fieldwork of a cross-national individual-level survey in these eight countries. We find that the war increased support for democracy, redistribution, support for Europe, and immigration, while it reduced authoritarian attitudes. Our findings highlight the impact of foreign conflicts on a wide range of attitudes in countries that are externally threatened, but neither directly involved militarily, nor necessarily very close to the conflict.
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BACKGROUND: The Population Assessment of Tobacco and Health (PATH) provides annual prevalence data on youth use of electronic nicotine delivery systems (ENDS). However, trends may be complicated by COVID-related changes in survey mode (self-completed vs. telephone interview) across 2019-2021. METHODS: Trends in past 30-day (P30D) ENDS use over PATH waves 5 (2019; 100 % self-completed), 5.5 (2020; 100 % telephone interview), and 6 (2021; 33.5 % self-completed, 66.5 % telephone interview) were examined among continuing youth, overall and within survey mode. Further analyses examined the nature of these changes by examining 1) potential response biases in social contexts of nicotine use, and 2) sources of ENDS over time. RESULTS: Telephone interviewees were less likely to report ENDS use (4.6 % vs. 8.6 % for self-completers), and more likely to report social disapproval of nicotine use, suggesting a reporting bias in telephone interviews. Survey-mode-naïve analyses suggested a large decline in P30D ENDS use prevalence between 2019-20 (10.2-4.6 %) followed by an apparent uptick in 2021 (5.9 %); however, comparing like-to-like survey modes showed a more modest decline (10.2 % in 2019; 8.6 % in 2021; self-completed) with no change between 2020 and 2021 (4.6 % in both; telephone interviews). Analyses suggested that the mode effects were partly, but not wholly, related to social desirability effects. DISCUSSION: Changes in PATH survey mode introduced artifacts into ENDS use prevalence, possibly due in part to social desirability bias suppressing reporting in telephone interviews, rather than a true uptick. It is essential to account for survey mode in PATH surveys.
Subject(s)
Electronic Nicotine Delivery Systems , Vaping , Humans , Electronic Nicotine Delivery Systems/statistics & numerical data , Adolescent , Male , Female , Vaping/epidemiology , United States/epidemiology , Young Adult , COVID-19/epidemiology , Prevalence , Self Report , Child , Surveys and QuestionnairesABSTRACT
Increasingly, large, nationally representative health and behavioral surveys conducted under a multistage stratified sampling scheme collect high dimensional data with correlation structured along some domain (eg, wearable sensor data measured continuously and correlated over time, imaging data with spatiotemporal correlation) with the goal of associating these data with health outcomes. Analysis of this sort requires novel methodologic work at the intersection of survey statistics and functional data analysis. Here, we address this crucial gap in the literature by proposing an estimation and inferential framework for generalizable scalar-on-function regression models for data collected under a complex survey design. We propose to: (1) estimate functional regression coefficients using weighted score equations; and (2) perform inference using novel functional balanced repeated replication and survey-weighted bootstrap for multistage survey designs. This is the first frequentist study to discuss the estimation of scalar-on-function regression models in the context of complex survey studies and to assess the validity of various inferential techniques based on re-sampling methods via a comprehensive simulation study. We implement our methods to predict mortality using diurnal activity profiles measured via wearable accelerometers using the National Health and Nutrition Examination Survey 2003-2006 data. The proposed computationally efficient methods are implemented in R software package surveySoFR.
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Quantifying the cost-effectiveness of alternative sampling methods is crucial for efficient biodiversity monitoring and detection of population trends. In this study, we compared the cost-effectiveness of three novel sampling methods for detecting changes in koala (Phascolarctos cinereus) occupancy: thermal drones, passive acoustic recorders and camera trapping. Specifically, we fitted single-season occupancy-detection models to data recorded from 46 sites in eight bioregions of New South Wales, Australia, between 2018 and 2022. We explored the effect of weather variables on daily detection probability for each method and, using these estimates, calculated the statistical power to detect 30%, 50% and 80% declines in koala occupancy. We calculated power for different combinations of sites (1-200) and repeat surveys (2-40) and developed a cost model that found the cheapest survey design that achieved 80% power to detect change. On average, detectability of koalas was highest with one 24-h period of acoustic surveys (0.32, 95% CI's: 0.26, 0.39) compared to a 25-ha flight of drone surveys (0.28, 95% 0.15, 0.48) or a 24-h period of camera trapping consisting of six cameras (0.019, 95% CI's: 0.014, 0.025). We found a negative quadratic relationship between detection probability and air temperature for all three methods. Our power and cost analysis suggested that 148 sites surveyed with acoustic recorders deployed for 14 days would be the cheapest method to sufficiently detect a 30% decline in occupancy with 80% power. We recommend passive acoustic recorders as the most efficient sampling method for monitoring koala occupancy compared to cameras or drones. Further comparative studies are needed to compare the relative effectiveness of these methods and others when the monitoring objective is to detect change in koala abundance over time.
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Despite widespread engagement in contemplative religious practices, comparatively little research has been conducted on their potential effects on well-being. Furthermore, few studies have focused on how an explicitly religious framing may impact the outcomes of such practices. In this online randomized controlled trial (N = 702), we tested the well-being effects of a contemplative prayer practice called Centering Prayer on self-identifying Christians. We compared 1) presenting the practice with an explicitly religious framing (experimental condition), 2) presenting the practice without an explicitly religious framing (active control), and 3) presenting simple instructions to reflect on the day, without any instructions regarding a meditation-like practice (passive control). After randomization into one of these three conditions, participants were asked to complete their assigned practice daily for 28 days. We hypothesized that the religious framing version of the practice would increase well-being over the active and passive control conditions. Well-being was assessed at three follow-up time points: one day, one week, and one month after the practice period. We found no group differences between the conditions on our primary outcome measure of well-being at one-week post-intervention. Each group increased in well-being from baseline to follow-up. We found significant group differences on acute measures of spiritual experience, the Mystical Experience Questionnaire (MEQ-30) and Daily Spiritual Experience Questionnaire (DSES). These results suggest that a religious framing may not enhance well-being effects but may alter spiritual outcomes related to contemplative practices.
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Christianity , Stress, Psychological , Humans , Female , Male , Adult , Stress, Psychological/psychology , Middle Aged , Meditation/methods , Meditation/psychology , Religion and Psychology , Young AdultABSTRACT
The objective of this study is to explore the influence of self-commitment on career crafting, examining the mediating role of career adaptability and the moderating effect of job autonomy within the context of career construction theory. This research aims to deepens our understanding of the key mechanisms that underpin successful career development, providing valuable insights for both individuals and organizations to enhance career success and adaptability. Utilizing a two-wave survey methodology, we collected data from 363 full-time employees across various industries in the United States. Hierarchical regression analysis and the PROCESS Macro were employed to test the proposed hypotheses. Our findings reveal that self-commitment significantly enhances career crafting through career adaptability. Additionally, job autonomy was found to influence both the direct relationship between self-commitment and career adaptability, and the indirect relationship between self-commitment and career crafting. This study highlights the pathways linking self-commitment to career crafting, underscoring the importance of career adaptability as a developmental tool facilitated by job autonomy. We recommend that individuals commit to their personal growth to enhance their career adaptability and actively shape their careers. Meanwhile, organizations should focus on promoting job autonomy to foster career development, benefiting both employees and the broader organizational ecosystem.
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Professional Autonomy , Humans , Female , Male , Adult , Career Choice , Career Mobility , United States , Employment/psychology , Middle Aged , Surveys and QuestionnairesABSTRACT
This article is part of a series of articles in the Journal of the Academy of Nutrition and Dietetics exploring the importance of research design, epidemiological methods, and statistical analysis as applied to nutrition and dietetics research. The purpose of this ongoing statistical portfolio is to assist registered dietitian nutritionists and nutrition and dietetic technicians, registered with interpreting nutrition research and applying scientific principles to produce high-quality data analysis. A survey is a systematic method for collecting reportable information on a topic of interest. Developing, adapting, and conducting survey research is a complex process; its aim is to collect accurate and useful data for the intended purpose and context. This article, which accompanies a companion article on electronic survey research, is an overview of survey methodology for data collection and analysis in nutrition and dietetics research. Its purpose is to highlight the general principles and components of survey development and survey administration that would maximize the validity of the data obtained. The goal is to provide a practical guide on the design and implementation of a survey as a method for data collection. Supporting figures are provided for use in direct application by practitioners and students.
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OBJECTIVE: Measuring attitudes of farmers to safe farming practices using quantitative causal relationship approaches is central to improving understanding of (un)safe practices. This knowledge is important in the development of effective farm safety interventions. However, the accuracy of quantitative attitudinal studies in explaining farmers' decision-making faces a potential measurement challenge, i.e. a high level of optimism bias. In this paper, we present research that develops and tests farm safety attitudinal questions that are framed around "real-life" farming practices with the objective of reducing optimism bias. METHODS: We apply construal level theory (CLT) to support the design of vignettes that reflect common risk scenarios faced by farmers. Applying qualitative analysis of 274 fatal farm incidents that occurred in Ireland between 2004 and 2018 we identify the occupational behaviors (what farmers do), social (who are farmers), spatial (where farming takes place), and temporal (when farming happens) dimensions of risks resulting in most deaths. The results informed subsequent co-design activities with farm safety experts and farm advisors to develop "real-life" scenarios, attitudinal questions, and response options. The questionnaire was piloted and subsequently implemented to collect data from a sample of 381 farmers with either tractors or livestock. The results of the survey were compared to previous attitudinal research on farmer's attitudes to safety in Ireland to establish if there was as follows: i) increased variance in the responses, and ii) a statistically significant difference in the attitudes of respondents compared to the results reported in previous studies. RESULTS: The findings established that when farmers were provided with real-life scenarios, their responses were less optimistic and more varied, i.e. there was a greater range of responses, compared to previous studies. CONCLUSION: Applying CTL to the development of attitudinal survey instruments anchors attitudinal questions within farming specific occupational, social, spatial, and temporal contexts. The use of vignettes that draw on real-life scenarios offers the potential for improved design of surveys that seek to understand farmer/worker practices. The results suggest that this approach can improve the measurement of attitudes to farm safety.
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This article presents the results of an adaptive design experiment in the recruitment of households and individuals for a two-stage national probability web or mail mixed-mode survey, the American Family Health Study (AFHS). In the screening stage, we based the adaptive design's subgroup differentiation on Esri Tapestry segmentation. We used tailored invitation materials for a subsample where a high proportion of the population was Hispanic and added a paper questionnaire to the initial mailing for a subsample with rural and older families. In the main-survey stage, the adaptive design targeted the households where a member other than the screening respondent was selected for the survey. The adaptations included emailing and/or texting, an additional prepaid incentive, and seeking screening respondents' help to remind the selected individuals. The main research questions are (i) whether the adaptive design improved survey production outcomes and (ii) whether combining adaptive design and postsurvey weighting adjustments improved survey estimates compared to performing postsurvey adjustments alone. Unfortunately, the adaptive designs did not improve the survey production outcomes. We found that the weighted AFHS estimates closely resemble those of a benchmark national face-to-face survey, the National Survey of Family Growth, although the adaptive design did not additionally change survey estimates beyond the weighting adjustments. Nonetheless, our experiment yields useful insights about the implementation of adaptive design in a self-administered mail-recruit web or mail survey. We were able to identify subgroups with potentially lower response rates and distinctive characteristics, but it was challenging to develop effective protocol adaptations for these subgroups under the constraints of the two primary survey modes and the operational budget of the AFHS. In addition, for self-administered within-household selection, it was difficult to obtain contact information from, reach, and recruit selected household members that did not respond to the screening interview.
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Community reaction to refugees and asylum-seekers is often gauged by attitude surveys that are not designed to overcome built-in bias. Questionnaires that do not account for context and background consequently yield results that misrepresent community attitudes and offer predictably negative responses to immigrant groups. Such surveys can alter public perception, fuel anti-refugee sentiment, and affect policy simply because of how they are constructed. This model survey among humanitarian aid-workers from nine Greek non-governmental organizations uses specific techniques designed to overcome these challenges by applying sample familiarity, non-inflammatory hypothesis-testing, educational question stems, intentional ordering of questions, and direct questioning rather than surrogate measures like statistical approximation. Respondents working in the refugee crisis in Greece demonstrate how empathy, education, and exposure to refugees serve to overcome the harmful stereotypes of outsiders as contributors to crime, terror, and social burden.
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Recognizing the value of experiential education in social/behavioral science research training, we designed and offered a simulation of a survey research project for doctoral students in education. Through three phases of the project, from instrument design through scale investigation and quantitative analyses, students are developed as researchers in a realistic and authentic way. In this paper, we highlight the advantages, challenges, and outcomes from applying simulation methods within graduate research methods courses, with a specific focus on survey methodology and quantitative skill development.
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BACKGROUND: POCD is a common complication among patients who underwent coronary artery bypass graft (CABG), it is linked to loss of independence and reduced quality of life. AIMS AND OBJECTIVES: To examine the association between postoperative cognitive dysfunction (POCD), postoperative delirium (POD) and interleukin-6 (IL-6). DESIGN: A prospective cohort study. METHODS: Patients who underwent elective isolated CABG were enrolled. POCD was assessed by a set of cognitive function tools. Delirium was assessed using the CAM-ICU. The logistic regression analyses were used to identify the predictive value of POD or IL-6 on POCD. The path analysis was used to analyse the relationship among POD, IL-6 and POCD. RESULTS: A total of 212 patients were enrolled, with 25.0% of patients developing POD and 32.5% developing POCD. The multiple logistic regression analysis revealed that patients with POD had a four-fold increased hazard of POCD (OR = 3.655), and patients with IL-6 ≥ 830.50 pg/mL at the 6th hours after surgery had a 5-fold increased risk of experiencing POCD (OR = 5.042). However, the mediation effect of POD between IL-6 and POCD was not statistically significant (ß = 0.059, p = .392). CONCLUSIONS: POD and IL-6 at the 6th hour after surgery (≥830.50 pg/mL) are two potent predictors for POCD, while POD did not play a mediation effect between IL-6 and POCD. RELEVANCE TO CLINICAL PRACTICE: Early identification of risk factors (e.g., delirium assessment and testing for serum IL-6 levels) by clinical nurses for POCD may contribute to the clinical practice for the targeted prevention nursing strategies.
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Dietary assessments provide the snapshots of population-based dietary habits. Questions remain about how generalisable those snapshots are in national survey data, where certain subgroups are sampled disproportionately. We propose a Bayesian overfitted latent class model to derive dietary patterns, accounting for survey design and sampling variability. Compared to standard approaches, our model showed improved identifiability of the true population pattern and prevalence in simulation. We focus application of this model to identify the intake patterns of adults living at or below the 130% poverty income level. Five dietary patterns were identified and characterised by reproducible code/data made available to encourage further research.
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The standard approach for detecting and preventing bots from doing harm online involves CAPTCHAs. However, recent AI research, including our own in this manuscript, suggests that bots can complete many common CAPTCHAs with ease. The most effective methodology for identifying potential bots involves completing image-processing, causal-reasoning based, free-response questions that are hand coded by human analysts. However, this approach is labor intensive, slow, and inefficient. Moreover, with the advent of Generative AI such as GPT and Bard, it may soon be obsolete. Here, we develop and test various automated, bot-screening questions, grounded in psychological research, to serve as a proactive screen against bots. Utilizing hand coded free-response questions in the naturalistic domain of MTurkers recruited for a Qualtrics survey, we identify 18.9% of our sample to be potential bots, whereas Google's reCAPTCHA V3 identified only 1.7% to be potential bots. We then look at the performance of these potential bots on our novel bot-screeners, each of which has different strengths and weaknesses but all of which outperform CAPTCHAs.
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Artificial Intelligence , Humans , Computer SecurityABSTRACT
Purpose: Research and lived experience demonstrate that sexual orientation and gender identity (SOGI) can change over the life course; however, little empirical work exists to understand the prevalence of such changes. To address this gap, we used data from a large nationally representative panel of adults and adolescents to assess changes in self-reported SOGI over time and identify trends by sex assigned at birth, age, race and ethnicity, and survey mode. Methods: We reviewed SOGI data collected between 2014 and 2022 for a sample of 19,469 adults and 970 adolescents. Up to eight SOGI measurements per panelist were available over the nine-year period, collected through a combination of panel recruitment and demographic refresh surveys and topic-specific surveys. Results: Among adults older than 18 years, 4.1% reported a change in sexual orientation and 3.6% reported a change in gender identity. Among teens, who are developmentally more apt to change identity, 13.5% reported a change in sexual orientation and 9.3% reported a change in gender identity. Conclusions: Findings demonstrate that SOGI can change over time, particularly for adolescents, so it is important to re-ask SOGI questions to ensure current information. We recommend re-asking SOGI questions at least every three years of adults and every two years of adolescents. Potential undercounting of sexual and gender minority (SGM) respondents decreases visibility and our ability to understand health and economic disparities affecting these populations. Improvements in SOGI measurement can help advance data quality and, ultimately, evidence-based interventions in support of SGM communities that these data help to inform.
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Survey scores are often the basis for understanding how individuals grow psychologically and socio-emotionally. A known problem with many surveys is that the items are all "easy"-that is, individuals tend to use only the top one or two response categories on the Likert scale. Such an issue could be especially problematic, and lead to ceiling effects, when the same survey is administered repeatedly over time. In this study, we conduct simulation and empirical studies to (a) quantify the impact of these ceiling effects on growth estimates when using typical scoring approaches like sum scores and unidimensional item response theory (IRT) models and (b) examine whether approaches to survey design and scoring, including employing various longitudinal multidimensional IRT (MIRT) models, can mitigate any bias in growth estimates. We show that bias is substantial when using typical scoring approaches and that, while lengthening the survey helps somewhat, using a longitudinal MIRT model with plausible values scoring all but alleviates the issue. Results have implications for scoring surveys in growth studies going forward, as well as understanding how Likert item ceiling effects may be contributing to replication failures.
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Understanding how and why certain communities bear a disproportionate burden of disease is challenging due to the scarcity of data on these communities. Surveys provide a useful avenue for accessing hard-to-reach populations, as many surveys specifically oversample understudied and vulnerable populations. When survey data is used for analysis, it is important to account for the complex survey design that gave rise to the data, in order to avoid biased conclusions. The field of Bayesian survey statistics aims to account for such survey design while leveraging the advantages of Bayesian models, which can flexibly handle sparsity through borrowing of information and provide a coherent inferential framework to easily obtain variances for complex models and data types. For these reasons, Bayesian survey methods seem uniquely well-poised for health disparities research, where heterogeneity and sparsity are frequent considerations. This review discusses three main approaches found in the Bayesian survey methodology literature: 1) multilevel regression and post-stratification, 2) weighted pseudolikelihood-based methods, and 3) synthetic population generation. We discuss advantages and disadvantages of each approach, examine recent applications and extensions, and consider how these approaches may be leveraged to improve research in population health equity.
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AIM: To use co-design principles to design a nationwide maternity experiences survey and to distribute the survey through social media. DESIGN: A co-designed, cross sectional, and national online survey. METHODS: Using co-design principles from study design and throughout the research process a cross-sectional, online, national survey of Australian women's experiences of maternity care was designed. Four validated survey instruments were included in the survey design. RESULTS: An extensive social media strategy was utilized, which included paid advertising, resulting in 8804 surveys for analysis and 54,896 comments responding to open text questions. DISCUSSION: The inclusion of co-design principles contributed to a well-designed survey and consumer involvement in distribution and support of the online survey. The social media distribution strategy contributed to high participation rates with overall low marketing costs. CLINICAL RELEVANCE: Maternity services should be designed to provide woman-centered, individualized care. This survey was co-designed with maternity users and maternity organizations to explore women's recent experiences of maternity care in Australia. The outcomes of this study will highlight the factors that contribute to positive and negative experiences in maternity services. PATIENT OR PUBLIC CONTRIBUTION: As a co-designed study, there was consumer engagement from the design of the study, throughout the research process.
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Maternal Health Services , Social Media , Pregnancy , Female , Humans , Cross-Sectional Studies , Australia , Surveys and QuestionnairesABSTRACT
OBJECTIVE: We sought to understand the relative impact of fielding mode on response rate among public health alumni. METHODS: As part of the 2021 Career Trends Survey of alumni from the University of Minnesota School of Public Health, we designed a fielding mode experiment to ascertain whether a paper survey, a postcard with a custom survey link ("postcard push-to-web"), a mobile telephone call or text (mobile), or an email invitation would garner the highest response rates. Invitations were randomly assigned from available contact information. RESULTS: Of 8531 alumni invited, 1671 alumni (19.6%) completed the survey. Among the initial fielding modes, the paper survey had the highest response rate (28%), followed by mobile (19%), email (10%), and postcard push-to-web (10%). More robust recent engagement with alumni relations, paper survey invitation or mode switch, and recent graduation were all significantly associated with a higher likelihood of response. CONCLUSIONS: Paper and mobile invitations had the highest response rates to our survey among public health alumni. Findings from this fielding mode experiment are relevant to schools and programs of public health seeking to capture similar information among their alumni, especially given current trends in investment in the public health workforce.