The psychology and policy of overcoming economic inequality.

Recent arguments claim that behavioral science has focused - to its detriment - on the individual over the system when construing behavioral interventions. In this commentary, we argue that tackling economic inequality using both framings in tandem is invaluable. By studying individuals who have overcome inequality, "positive deviants," and the system limitations they navigate, we offer potentially greater policy solutions.

Dimensionality assessment in bifactor structures with multiple general factors: A network psychometrics approach.

The accuracy of factor retention methods for structures with one or more general factors, like the ones typically encountered in fields like intelligence, personality, and psychopathology, has often been overlooked in dimensionality research. To address this issue, we compared the performance of several factor retention methods in this context, including a network psychometrics approach developed in this study. For estimating the number of group factors, these methods were the Kaiser criterion, empirical Kaiser criterion, parallel analysis with principal components (PAPCA) or principal axis, and exploratory graph analysis with Louvain clustering (EGALV). We then estimated the number of general factors using the factor scores of the first-order solution suggested by the best two methods, yielding a "second-order" version of PAPCA (PAPCA-FS) and EGALV (EGALV-FS). Additionally, we examined the direct multilevel solution provided by EGALV. All the methods were evaluated in an extensive simulation manipulating nine variables of interest, including population error. The results indicated that EGALV and PAPCA displayed the best overall performance in retrieving the true number of group factors, the former being more sensitive to high cross-loadings, and the latter to weak group factors and small samples. Regarding the estimation of the number of general factors, both PAPCA-FS and EGALV-FS showed a close to perfect accuracy across all the conditions, while EGALV was inaccurate. The methods based on EGA were robust to the conditions most likely to be encountered in practice. Therefore, we highlight the particular usefulness of EGALV (group factors) and EGALV-FS (general factors) for assessing bifactor structures with multiple general factors. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

The persistence of cognitive biases in financial decisions across economic groups.

While economic inequality continues to rise within countries, efforts to address it have been largely ineffective, particularly those involving behavioral approaches. It is often implied but not tested that choice patterns among low-income individuals may be a factor impeding behavioral interventions aimed at improving upward economic mobility. To test this, we assessed rates of ten cognitive biases across nearly 5000 participants from 27 countries. Our analyses were primarily focused on 1458 individuals that were either low-income adults or individuals who grew up in disadvantaged households but had above-average financial well-being as adults, known as positive deviants. Using discrete and complex models, we find evidence of no differences within or between groups or countries. We therefore conclude that choices impeded by cognitive biases alone cannot explain why some individuals do not experience upward economic mobility. Policies must combine both behavioral and structural interventions to improve financial well-being across populations.

Exploratory Bi-factor Analysis with Multiple General Factors.

Exploratory bi-factor analysis (EBFA) is a very popular approach to estimate models where specific factors are concomitant to a single, general dimension. However, the models typically encountered in fields like personality, intelligence, and psychopathology involve more than one general factor. To address this circumstance, we developed an algorithm (GSLiD) based on partially specified targets to perform exploratory bi-factor analysis with multiple general factors (EBFA-MGF). In EBFA-MGF, researchers do not need to conduct independent bi-factor analyses anymore because several bi-factor models are estimated simultaneously in an exploratory manner, guarding against biased estimates and model misspecification errors due to unexpected cross-loadings and factor correlations. The results from an exhaustive Monte Carlo simulation manipulating nine variables of interest suggested that GSLiD outperforms the Schmid-Leiman approximation and is robust to challenging conditions involving cross-loadings and pure items of the general factors. Thereby, we supply an R package (bifactor) to make EBFA-MGF readily available for substantive research. Finally, we use GSLiD to assess the hierarchical structure of a reduced version of the Personality Inventory for DSM-5 Short Form (PID-5-SF).

A silent burden: How negative experiences with public toilets impact quality of life and life satisfaction.

Public toilets are a critical public health issue with a significant negative impact on people's lives. Unfortunately, the effect of negative experiences caused by public toilets on people's quality of life and life satisfaction is unknown. In this study, participants (n = 550) were asked to fill in a scale-based survey about their negative experiences with public toilets, quality of life, and life satisfaction. We found that people with toilet-dependent illnesses (36% of the sample) reported more negative experiences with public toilets than their counterparts. These negative experiences are also related to lower scores in some areas of participants' quality of life, such as their environmental, psychological, and physical health and life satisfaction, even after controlling for relevant socio-economic variables. Additionally, toilet-dependent individuals had particularly negative experiences in terms of life satisfaction and physical health than non-toilet-dependent people. We conclude that the impoverishment of quality of life linked to public toilets as an environmental inadequacy is traceable, estimable, and meaningful. This association is not only negative for ordinary people, but it is significantly negative for people with toilet-dependent illnesses. These results highlight that public toilets are essential to ensure collective well-being, particularly when considering those affected by their presence or lack thereof.

Negative experiences with public bathrooms and chronic illness-related shame.

INTRODUCTION: The use of public bathrooms is a challenge for everyone, but especially for those who are affected by a bathroom-dependent condition. Being dependent on bathrooms is linked with different negative emotions. One of them is a clinically relevant emotion: shame associated with the chronic condition. MATERIALS AND METHODS: In a cross-sectional survey study (n = 193) of people who suffer a bathroom-dependent condition we asked about health conditions, well-being, and shame related to chronic condition outcomes. RESULTS: We show a link between negative public bathroom experiences, and diminished well-being and feelings of shame related to chronic illness. We found that this relationship between negative experiences with public bathrooms and shame is not specific to the different conditions. CONCLUSION: We conclude that the negative experiences which people with different gastrointestinal illnesses face is an environmental stressor associated with more embarrassment as a result of the condition suffered.

Exploring COVID-19 research credibility among Spanish scientists.

Amidst a worldwide vaccination campaign, trust in science plays a significant role when addressing the COVID-19 pandemic. Given current concerns regarding research standards, we were interested in how Spanish scholars perceived COVID-19 research and the extent to which questionable research practices and potentially problematic academic incentives are commonplace. We asked researchers to evaluate the expected quality of their COVID-19 projects and other peers' research and compared these assessments with those from scholars not involved in COVID-19 research. We investigated self-admitting and estimated rates of questionable research practices and attitudes towards current research status. Responses from 131 researchers suggested that COVID-19 evaluations followed partisan lines, with scholars being more pessimistic about others' colleagues' research than their own. Additionally,researchers not involved in COVID-19 projects were more negative than their participating peers. These differences were particularly notable for areas such as the expected theoretical foundations or overall quality of the research, among others. Most Spanish scholars expected questionable research practices and inadequate incentives to be widespread. In these two aspects, researchers tended to agree regardless of their involvement in COVID-19 research. We provide specific recommendations for improving future meta-science studies, such as redefining QRPs as inadequate research practices (IRP). This change could help avoid key controversies regarding QRPs' definition while highlighting their detrimental impact. Lastly, we join previous calls to improve transparency and academic career incentives as a cornerstone for generating trust in science. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12144-022-02797-6.

Registered report: How open do you want your science? An international investigation into knowledge and attitudes of psychology students.

The use of Open Science practices is often proposed as a way to improve research practice, especially in psychology. Open Science can increase transparency and therefore reduce questionable research practices, making research more accessible to students, scholars, policy makers, and the public. However, little is known about how widespread Open Science practices are taught and how students are educated about these practices. In addition, it remains unknown how informing students about Open Science actually impacts their understanding and adoption of such practices. This registered report proposes the validation of a questionnaire. The aim is to survey how much psychology students know about Open Science and to assess whether knowledge of and exposure to Open Science in general-be it through university curricula or social media-influences attitudes towards the concept and intentions to implement relevant practices.

The general fault in our fault lines.

Pervading global narratives suggest that political polarization is increasing, yet the accuracy of such group meta-perceptions has been drawn into question. A recent US study suggests that these beliefs are inaccurate and drive polarized beliefs about out-groups. However, it also found that informing people of inaccuracies reduces those negative beliefs. In this work, we explore whether these results generalize to other countries. To achieve this, we replicate two of the original experiments with 10,207 participants across 26 countries. We focus on local group divisions, which we refer to as fault lines. We find broad generalizability for both inaccurate meta-perceptions and reduced negative motive attribution through a simple disclosure intervention. We conclude that inaccurate and negative group meta-perceptions are exhibited in myriad contexts and that informing individuals of their misperceptions can yield positive benefits for intergroup relations. Such generalizability highlights a robust phenomenon with implications for political discourse worldwide.

On Omega Hierarchical Estimation: A Comparison of Exploratory Bi-Factor Analysis Algorithms.

As general factor modeling continues to grow in popularity, researchers have become interested in assessing how reliable general factor scores are. Even though omega hierarchical estimation has been suggested as a useful tool in this context, little is known about how to approximate it using modern bi-factor exploratory factor analysis methods. This study is the first to compare how omega hierarchical estimates were recovered by six alternative algorithms: Bi-quartimin, bi-geomin, Schmid-Leiman (SL), empirical iterative empirical target rotation based on an initial SL solution (SLiD), direct SL (DSL), and direct bi-factor (DBF). The algorithms were tested in three Monte-Carlo simulations including bi-factor and second-order structures and presenting complexities such as cross-loadings or pure indicators of the general factor and structures without a general factor. Results showed that SLiD provided the best approximation to omega hierarchical under most conditions. Overall, neither SL, bi-quartimin, nor bi-geomin produced an overall satisfactory recovery of omega hierarchical. Lastly, the performance of DSL and DBF depended upon the average discrepancy between the loadings of the general and the group factors. The re-analysis of eight classical datasets further illustrated how algorithm selection could influence judgments regarding omega hierarchical.

Bi-factor Exploratory Structural Equation Modeling Done Right: Using the SLiDapp Application.

BACKGROUND: Due to its flexibility and statistical properties, bi-factor Exploratory Structural Equation Modeling (bi-factor ESEM) has become an often-recommended tool in psychometrics. Unfortunately, most recent methods for approximating these structures, such as the SLiD algorithm, are not available in the leading software for performing ESEM (i.e., Mplus). To resolve this issue, we present a novel, user-friendly Shiny application for integrating the SLiD algorithm in bi-factor ESEM estimation in Mplus. Thus, a two-stage framework for conducting SLiD-based bi-factor ESEM in Mplus was developed. METHOD: This approach was presented in a step-by-step guide for applied researchers, showing the utility of the developed SLiDApp application. Using data from the Open-Source Psychometrics Project (N = 2495), we conducted a bi-factor ESEM exploration of the Generic Conspiracist Beliefs Scale. We studied whether bi-factor modelling was appropriate and if both general and group factors were related to each personality trait. RESULTS: The application of the SLiD algorithm provided unique information regarding this factor structure and its ESEM structural parameters. CONCLUSIONS: The results illustrated the usefulness and validity of SLiD-based bi-factor ESEM, and how the proposed Shiny app could make it eaiser for applied researchers to use these methods.

The Development of a Public Bathroom Perception Scale.

Public bathrooms are sensible locations in which individuals confront an intimate environment outside the comfort of their own home. The assessment of public bathrooms is especially problematic for people whose illnesses make them more prone to needing this service. Unfortunately, there is a lack in the evaluation of the elements that are relevant to the user's perspective. For that reason, we propose a new scale to assess these elements of evaluation of public bathrooms. We developed a scale of 14 items and three domains: privacy, ease of use and cleanliness. We tested the factor validity of this three-factor solution (n = 654) on a sample of healthy individuals and 155 respondents with a bowel illness or other affection that reported to be bathroom-dependent. We found that bathroom-dependent people value more privacy and cleanliness more than their healthy counterparts. We additionally found a gender effect on the scale: female participants scored higher in every domain. This study provides the first scale to assess value concerning public bathrooms and to highlight the relevance of different bathrooms' aspects to users.

Driver eye movements in relation to unfamiliar traffic signs: An eye tracking study.

Traffic signs are an integral part of the traffic control plan and they provide road users with necessary information on the upcoming situation. This paper aims to examine the level of understanding of traffic sign imagery used in different countries and to track participants' eye movement when they encounter unfamiliar signs. Tobii eye tracking glasses were used to track gaze differences between familiar and unfamiliar traffic signs. Our findings show that sign characteristics (such as the amount of information on the sign) and the observer's knowledge of the sign meaning have a significant impact on eye behaviour. Signs containing more information (loaded with more content) and unfamiliar to the participant systematically produced the longest overall and average fixations and gazing duration. Given that longer gaze time for unfamiliar traffic signs presents a potential traffic hazard, we evaluated the need for standardization of traffic signs.

Global mental health: an improved measure of well-being in multiple languages.

BACKGROUND: An increasing number of international organisations and national governments have committed to well-being promotion. Unfortunately, important questions regarding how to assess well-being are still unresolved, making policy implementation and evaluation difficult. METHODS: This research expanded on Huppert and So's (Soc Indic Res. 110, 837-861 2013) multidimensional subjective well-being framework by investigating the replicability of the model in two non-European regions (South America, represented by Brazil and Colombia, and Eastern Africa, represented by Uganda), and the United Kingdom. Additionally, previous limitations of the framework were also addressed. ESS Round Six items were crucially improved in terms of temporal and response scale consistency. Bayesian approximate measurement invariance was applied on a sample of 381 young adult participants to test for consistency across countries. RESULTS: The Huppert & So (Soc Indic Res. 110, 837-861 2013) model was found to fairly replicate across non-European regions, where meaningful differences in well-being patterns across regions were observed. Additionally, estimated well-being was related with other well-being measures (Five Ways): Learn and Connect were the strongest predictors of general well-being, with Take Notice and Give being associated with specific aspects of it. CONCLUSIONS: Based on this narrow sample of young adults, it appears the ten-item measure proposed by Huppert & So (Soc Indic Res. 110, 837-861 2013) is useful for assessing population mental health outside of Europe. This is only an initial attempt to assess qualities, so further testing should be done before applying at scale for identifying policy opportunities to address well-being of populations.

Well-being is more than happiness and life satisfaction: a multidimensional analysis of 21 countries.

BACKGROUND: Recent trends on measurement of well-being have elevated the scientific standards and rigor associated with approaches for national and international comparisons of well-being. One major theme in this has been the shift toward multidimensional approaches over reliance on traditional metrics such as single measures (e.g. happiness, life satisfaction) or economic proxies (e.g. GDP). METHODS: To produce a cohesive, multidimensional measure of well-being useful for providing meaningful insights for policy, we use data from 2006 and 2012 from the European Social Survey (ESS) to analyze well-being for 21 countries, involving approximately 40,000 individuals for each year. We refer collectively to the items used in the survey as multidimensional psychological well-being (MPWB). RESULTS: The ten dimensions assessed are used to compute a single value standardized to the population, which supports broad assessment and comparison. It also increases the possibility of exploring individual dimensions of well-being useful for targeting interventions. Insights demonstrate what may be masked when limiting to single dimensions, which can create a failure to identify levers for policy interventions. CONCLUSIONS: We conclude that both the composite score and individual dimensions from this approach constitute valuable levels of analyses for exploring appropriate policies to protect and improve well-being.

A Psychometric Review and Conceptual Replication Study of the Five Facets Mindfulness Questionnaire Latent Structure.

The Five Facets Mindfulness Questionnaire (FFMQ) is a popular tool in mindfulness research. However, its psychometric qualities and its replicability have caused controversy. This study carried out a psychometric review and a conceptual replication of the FFMQ latent structure. The review showed that previous validation studies of the FFMQ used nonoptimal methods. In addition, this conceptual replication study tested the structure of the FFMQ using frequentist and Bayesian techniques. The original structure did not provide a good fit with both techniques, while the proposed alternative provided mixed results. We also found systematic fit improvements in both techniques when the Observe facet was excluded and method factors were included. With these findings, we conclude that the conceptual replication of the FFMQ's structure failed. Alternatively, we propose a new provisional FFMQ model with a set of recommendations regarding its application. Future research proposals on improving techniques and models toward mindfulness assessment are also presented and discussed.

Searching for G: A New Evaluation of SPM-LS Dimensionality.

There has been increased interest in assessing the quality and usefulness of short versions of the Raven's Progressive Matrices. A recent proposal, composed of the last twelve matrices of the Standard Progressive Matrices (SPM-LS), has been depicted as a valid measure of g. Nonetheless, the results provided in the initial validation questioned the assumption of essential unidimensionality for SPM-LS scores. We tested this hypothesis through two different statistical techniques. Firstly, we applied exploratory graph analysis to assess SPM-LS dimensionality. Secondly, exploratory bi-factor modelling was employed to understand the extent that potential specific factors represent significant sources of variance after a general factor has been considered. Results evidenced that if modelled appropriately, SPM-LS scores are essentially unidimensional, and that constitute a reliable measure of g. However, an additional specific factor was systematically identified for the last six items of the test. The implications of such findings for future work on the SPM-LS are discussed.

An evidence-based policy for improving choice in global health access through medical travel.

Global medical travel has had an increasing trend without a comprehensive, evidence-driven policy to ensure safe and effective practice. To identify key factors that influence medical travel, we conducted a series of studies culminating with a preference and decision-making component of over 500 prospective medical travelers from a number of countries. Results indicated that quality of care was the most critical factor in the decision, followed by lower costs of procedure and shorter waiting times. Lower costs were less of a factor if the procedure was more invasive, which also increased the importance of waiting time in the decision. The most desired destinations for care were in Europe (United Kingdom, Germany) and North America (United States). Building on these insights and previous literature, we present a model that implements applications from these factors and additional insights generated across the series of studies toward an effective policy framework.

Iteration of Partially Specified Target Matrices: Application to the Bi-Factor Case.

The current study proposes a new bi-factor rotation method, Schmid-Leiman with iterative target rotation (SLi), based on the iteration of partially specified target matrices and an initial target constructed from a Schmid-Leiman (SL) orthogonalization. SLi was expected to ameliorate some of the limitations of the previously presented SL bi-factor rotations, SL and SL with target rotation (SLt), when the factor structure either includes cross-loadings, near-zero loadings, or both. A Monte Carlo simulation was carried out to test the performance of SLi, SL, SLt, and the two analytic bi-factor rotations, bi-quartimin and bi-geomin. The results revealed that SLi accurately recovered the bi-factor structures across the majority of the conditions, and generally outperformed the other rotation methods. SLi provided the biggest improvements over SL and SLt when the bi-factor structures contained cross-loadings and pure indicators of the general factor. Additionally, SLi was superior to bi-quartimin and bi-geomin, which performed inconsistently across the types of factor structures evaluated. No method produced a good recovery of the bi-factor structures when small samples (N = 200) were combined with low factor loadings (0.30-0.50) in the specific factors. Thus, it is recommended that larger samples of at least 500 observations be obtained.

Multilevel Modeling and Policy Development: Guidelines and Applications to Medical Travel.

Medical travel has expanded rapidly in recent years, resulting in new markets and increased access to medical care. Whereas several studies investigated the motives of individuals seeking healthcare abroad, the conventional analytical approach is limited by substantial caveats. Classical techniques as found in the literature cannot provide sufficient insight due to the nested nature of data generated. The application of adequate analytical techniques, specifically multilevel modeling, is scarce to non-existent in the context of medical travel. This study introduces the guidelines for application of multilevel techniques in public health research by presenting an application of multilevel modeling in analyzing the decision-making patterns of potential medical travelers. Benefits and potential limitations are discussed.