Measuring migration motives with open-ended survey data: Methodological and conceptual issues.
Ontology highlight
ABSTRACT:
SUBMITTER: Gillespie BJ
PROVIDER: S-EPMC8459254 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Objectification occurs when a person is perceived and/or treated like an object. With the present work, we overview the available measures of objectification and present a series of studies aimed at investigating the validity of the task of inverted body recognition proposed by Bernard and colleagues (2012), which might potentially be a useful cognitive measure of objectification. We conducted three studies. Study 1 (N = 101) is a direct replication of Bernard et al.'s study: participants were presented with the same photos of sexualized male and female targets used in the original research. Study 2a (N = 100) is a conceptual replication: we used different images of scantily dressed male and female models. Finally, in Study 2b (N = 100), we investigated a boundary condition by presenting to participants photos of the same models as in Study 2a, but fully dressed and non-sexualized. Using mixed-effects models for completely-crossed classified data structures, we investigated the relationship between the inversion effect and the stimulus' asymmetry, sexualization and attractiveness, and the perceivers' self-objectification, sexism, and automatic woman-human association. Study 1 replicated the original results, showing a stronger inversion effect for male photos. However, no difference between male and female stimuli emerged in either Study 2a or 2b. Moreover, the impact of the other variables on the inversion effect was highly unstable across the studies. These aspects together indicate that the inversion effect depends on the specific set of stimuli and limits the generalizability of results collected using this method.
| S-EPMC7031944 | biostudies-literature
Project description:The COVID-19 pandemic is an unprecedented public health crisis with broad social and economic consequences. We conducted four surveys between April and August 2020 using the graph-based open-ended survey (GOS) framework, and investigated the most pressing concerns and issues for the general public in Japan. The GOS framework is a hybrid of the two traditional survey frameworks that allows respondents to post their opinions in a free-format style, which can subsequently serve as one of the choice items for other respondents, just as in a multiple-choice survey. As a result, this framework generates an opinion graph that relates opinions and respondents. We can also construct annotated opinion graphs to achieve a higher resolution. By clustering the annotated opinion graphs, we revealed the characteristic evolution of the response patterns as well as the interconnectedness and multi-faceted nature of opinions. Substantively, our notable finding is that "social pressure," not "infection risk," was one of the major concerns of our respondents. Social pressure refers to criticism and discrimination that they anticipate receiving from others should they contract COVID-19. It is possible that the collectivist nature of Japanese culture coupled with the government's policy of relying on personal responsibility to combat COVID-19 explains some of the above findings, as the latter has led to the emergence of vigilantes. The presence of mutual surveillance can contribute to growing skepticism toward others as well as fear of ostracism, which may have negative consequences at both the societal and individual levels.
| S-EPMC8362959 | biostudies-literature
Project description:Much of the existing research on biological mechanisms underlying the stress experience has focused largely on moment-to-moment stress, rather than on chronic stress, an arguably more powerful predictor of long-term outcomes. Recent methodological innovations have paved the way for new lines of research on chronic stress, with promising implications for developmental researchers and for those who study health and adversity. In particular, there are increasing studies that have focused on chronic stress assessments by relying on cortisol derived from hair and nails as a biomarker for chronic stress. In this paper, we provide an overview of their use, describe how hair and nail cortisol ought to be conceptualized differently across the lifespan, how developmental factors may impact its interpretation, and the circumstances under which its use may be more methodologically sensible. The purpose of this review is to provoke further discussion and encourage careful research designs that utilize hair and nail cortisol for understanding the effects of chronic stress exposure from the early developmental period, across adverse contexts, and in association with psychological and physical health outcomes.
| S-EPMC6628692 | biostudies-literature
Project description:BackgroundThe analysis presented in this paper examines the multi-year capacity of the Medicare Current Beneficiary Survey (MCBS).MethodsWe systematically reviewed the literature for methodological approaches in research using multiple years of the MCBS and categorized the studies by study design, use of survey sampling weights, and variance adjustments. We then replicated the approaches in an empirical demonstration using functional status (activities of daily living (ADL) and 2005-2007 MCBS data.ResultsIn the systematic review, we identified 22 pooled, 17 repeated cross-sectional, and 17 longitudinal studies. Less than half of these studies explicitly described the weighting approach or variance estimation. In the empirical demonstration, we showed that different study designs and weighting approaches will yield statistically different estimates.ConclusionThere is a variety of methodological approaches when using multiple years of the MCBS, and some of them provide biased results. Research needs to improve in describing the methods and preferred approaches for using these complex data.
| S-EPMC4006385 | biostudies-literature
Project description:BackgroundIn the context of ever-growing health expenditure and limited resources, economic evaluations aid in making evidence-informed policy decisions. Cost-utility analysis (CUA) is often used, and CUA data synthesis is also desirable, but methodological issues are challenged. Hence, we aim to provide a step-by-step process to prepare the CUA data for meta-analysis.MethodsData harmonisation methods were constructed specifically considering CUA methodology, including inconsistent reports, economic parameters, heterogeneity (i.e., country's income, time horizon, perspective, modelling approaches, currency, willingness to pay). An incremental net benefit (INB) and its variance were estimated and pooled across studies using a basic meta-analysis by COMER.ResultsFive scenarios show how to obtain INB and variance with various reported data: Study reports the mean and variance (Scenario 1) or 95% confidence interval (Scenario 2) of ΔC, ΔE, and ICER for INB/variance calculations. Scenario 3: ΔC, ΔE, and variances are available, but not for the ICER; a Monte Carlo was used to simulate ΔC and ΔE data, variance and covariance can be then estimated leading INB calculation. Scenario-4: Only the CE plane was available, ΔC and ΔE data can be extracted; means of ΔC, ΔE, and variance/covariance can be estimated accordingly, leading to INB/variance estimates. Scenario-5: Only mean cost/outcomes and ICER are available but not for variance and the CE-plane. A variance INB can be borrowed from other studies which are similar characteristics, including country income, ICERs, intervention-comparator, time period, country region, and model type and inputs (i.e., discounting, time horizon).ConclusionOut data harmonisation and meta-analytic methods should be useful for researchers for the synthesis of economic evidence to aid policymakers in decision making.
| S-EPMC8845252 | biostudies-literature
Project description:The primary method by which social scientists describe public opinion about science and technology is to present frequencies from fixed response survey questions and to use multivariate statistical models to predict where different groups stand with regard to perceptions of risk and benefit. Such an approach requires measures of individual preference which can be aligned numerically in an ordinal or, preferably, a continuous manner along an underlying evaluative dimension - generally the standard 5- or 7-point attitude question. The key concern motivating the present paper is that, due to the low salience and "difficult" nature of science for members of the general public, it may not be sensible to require respondents to choose from amongst a small and predefined set of evaluative response categories. Here, we pursue a different methodological approach: the analysis of textual responses to "open-ended" questions, in which respondents are asked to state, in their own words, what they understand by the term "DNA." To this textual data we apply the statistical clustering procedures encoded in the Alceste software package to detect and classify underlying discourse and narrative structures. We then examine the extent to which the classifications, thus derived, can aid our understanding of how the public develop and use "everyday" images of, and talk about, biomedicine to structure their evaluations of emerging technologies.
| S-EPMC4400270 | biostudies-other
Project description:Sample size determination for open-ended questions or qualitative interviews relies primarily on custom and finding the point where little new information is obtained (thematic saturation). Here, we propose and test a refined definition of saturation as obtaining the most salient items in a set of qualitative interviews (where items can be material things or concepts, depending on the topic of study) rather than attempting to obtain all the items. Salient items have higher prevalence and are more culturally important. To do this, we explore saturation, salience, sample size, and domain size in 28 sets of interviews in which respondents were asked to list all the things they could think of in one of 18 topical domains. The domains-like kinds of fruits (highly bounded) and things that mothers do (unbounded)-varied greatly in size. The datasets comprise 20-99 interviews each (1,147 total interviews). When saturation was defined as the point where less than one new item per person would be expected, the median sample size for reaching saturation was 75 (range = 15-194). Thematic saturation was, as expected, related to domain size. It was also related to the amount of information contributed by each respondent but, unexpectedly, was reached more quickly when respondents contributed less information. In contrast, a greater amount of information per person increased the retrieval of salient items. Even small samples (n = 10) produced 95% of the most salient ideas with exhaustive listing, but only 53% of those items were captured with limited responses per person (three). For most domains, item salience appeared to be a more useful concept for thinking about sample size adequacy than finding the point of thematic saturation. Thus, we advance the concept of saturation in salience and emphasize probing to increase the amount of information collected per respondent to increase sample efficiency.
| S-EPMC6010234 | biostudies-literature
Project description:BackgroundChanging population demographics and technology developments have resulted in growing interest in the potential of consumer-facing digital health. In the United Kingdom, a £37 million (US $49 million) national digital health program delivering assisted living lifestyles at scale (dallas) aimed to deploy such technologies at scale. However, little is known about how consumers value such digital health opportunities.ObjectiveThis study explored consumers' perspectives on the potential value of digital health technologies, particularly mobile health (mHealth), to promote well-being by examining their willingness-to-pay (WTP) for such health solutions.MethodsA contingent valuation study involving a UK-wide survey that asked participants to report open-ended absolute and marginal WTP or willingness-to-accept for the gain or loss of a hypothetical mHealth app, Healthy Connections.ResultsA UK-representative cohort (n=1697) and a dallas-like (representative of dallas intervention communities) cohort (n=305) were surveyed. Positive absolute and marginal WTP valuations of the app were identified across both cohorts (absolute WTP: UK-representative cohort £196 or US $258 and dallas-like cohort £162 or US $214; marginal WTP: UK-representative cohort £160 or US $211 and dallas-like cohort £151 or US $199). Among both cohorts, there was a high prevalence of zeros for both the absolute WTP (UK-representative cohort: 467/1697, 27.52% and dallas-like cohort: 95/305, 31.15%) and marginal WTP (UK-representative cohort: 487/1697, 28.70% and dallas-like cohort: 99/305, 32.5%). In both cohorts, better general health, previous amount spent on health apps (UK-representative cohort 0.64, 95% CI 0.27 to 1.01; dallas-like cohort: 1.27, 95% CI 0.32 to 2.23), and age had a significant (P>.00) association with WTP (UK-representative cohort: -0.1, 95% CI -0.02 to -0.01; dallas-like cohort: -0.02, 95% CI -0.03 to -0.01), with younger participants willing to pay more for the app. In the UK-representative cohort, as expected, higher WTP was positively associated with income up to £30,000 or US $39,642 (0.21, 95% CI 0.14 to 0.4) and increased spending on existing phone and internet services (0.52, 95% CI 0.30 to 0.74). The amount spent on existing health apps was shown to be a positive indicator of WTP across cohorts, although the effect was marginal (UK-representative cohort 0.01, 95% CI 0.01 to 0.01; dallas-like cohort 0.01, 95% CI 0.01 to 0.02).ConclusionsThis study demonstrates that consumers value mHealth solutions that promote well-being, social connectivity, and health care control, but it is not universally embraced. For mHealth to achieve its potential, apps need to be tailored to user accessibility and health needs, and more understanding of what hinders frequent users of digital technologies and those with long-term conditions is required. This novel application of WTP in a digital health context demonstrates an economic argument for investing in upskilling the population to promote access and expedite uptake and utilization of such digital health and well-being apps.
| S-EPMC6354197 | biostudies-literature
Project description:Consistent functional brain abnormalities in Parkinson's disease (PD) are difficult to pinpoint because differences from the normal state are often subtle. In this regard, the application of multivariate methods of analysis has been successful but not devoid of misinterpretation and controversy. The Scaled Subprofile Model (SSM), a principal components analysis (PCA)-based spatial covariance method, has yielded critical information regarding the characteristic abnormalities of functional brain organization that underlie PD and other neurodegenerative disorders. However, the relevance of disease-related spatial covariance patterns (metabolic brain networks) and the most effective methods for their derivation has been a subject of debate. We address these issues here and discuss the inherent advantages of proper application as well as the effects of the misapplication of this methodology. We show that ratio pre-normalization using the mean global metabolic rate (GMR) or regional values from a "reference" brain region (e.g. cerebellum) that may be required in univariate analytical approaches is obviated in SSM. We discuss deviations of the methodology that may yield erroneous or confounding factors.
| S-EPMC3020239 | biostudies-literature
Project description:For policy goal setting, efficacy evaluations, and the development of related programs for reducing sodium intake, it is essential to accurately identify the amount of sodium intake in South Korea and constantly monitor its trends. The present study aimed to identify the status of sodium intake in South Korea and to review the methods and their validity for estimating sodium intake in each country; through this, we aim to determine more accurate methods for determining sodium intake and to monitor the trend in sodium intake for Korean citizens in the future. Using 24-hour dietary recall data from the 2012 Korea National Health and Nutrition Examination Survey (KNHANES) to estimate daily sodium intake, the average daily sodium intake among Koreans was 4,546 mg (men, 5,212 mg; women, 3,868 mg). In addition to the nutrition survey that uses the 24-hour dietary recall method, sodium intake can also be calculated from the amount of sodium excreted in 24-hour urine, 8-hour overnight urine, and spot urine samples. Although KNHANES uses the 24-hour dietary recall method to estimate the sodium intake, the 24-hour dietary recall method has the disadvantage of not being able to accurately determine the amount of sodium intake owing to its unique characteristics of the research method and in the processing of data. Although measuring the amount of sodium excreted in 24-hour urine is known to be the most accurate method, because collecting 24-hour urine from the general population is difficult, using spot urine samples to estimate sodium intake has been suggested to be useful for examining the trend of sodium intake in the general population. Therefore, we planned to conduct a study for estimating of 24-hour sodium excretion from spot urine and 8-hour overnight urine samples and testing the validity among subsamples in the KNHANES. Based on this result, we will adopt the most appropriate urine collection method for estimating population sodium intake in South Korea.
| S-EPMC4371387 | biostudies-literature