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Support of EU Climate Policies in Germany
No full textUsing a representative online survey from Germany, we will examine how hypothetical vignettes in which we introduce respondents to different climate policies of the European Union (EU) causally affect their support for these climate policies, their perceived behavior regarding these climate policies , and their perceived norms regarding these climate policies
Factors that impacted the inpatient experience in the context of the COVID-19 pandemic, perspective of quality and patient safety: a scoping review protocol
No full textThis scoping review is being conducted to identify the factors that impacted the hospitalized patient experience in the context of the COVID-19 pandemic from the perspective of quality and patient safety, as well as to identify gaps in knowledge and propose future studies
Impacts of Plant-Based Protein Consumption on Kidney Function and Mineral Bone Disorder (MBD) Outcomes in Stage 3-5 CKD Patients: A Systematic Review
No full textThe global prevalence of chronic kidney disease (CKD) is ~697.5 million people, including ~37 million adults in the United States.[1,2] CKD is characterized by the progressive loss of kidney function and leads to poor health outcomes including anemia, a weakened immune system, edema, loss of appetite, and decreased quality of life.[3] Further, as kidney function declines, CKD patients experience metabolic alterations including disturbances in calcium and phosphorus metabolism, resulting in a disorder known as CKD-mineral bone disorder (CKD-MBD).[4,5] CKD-MBD can lead to increased risk of cardiovascular disease and bone fracture.[6,7] Thus, nutrition therapy is a mainstay in managing these metabolic alterations. This requires patients with stage 3-5 CKD (moderate severity) to follow a protein and phosphorus restricted diet to preserve renal function and mitigate associated comorbidities . However, while dietary protein restriction slows renal decline by reducing nitrogenous waste products and lowering intraglomerular pressure, less is known about the influence of protein source (i.e., plant vs animal) on disease outcomes in these patients.[8] Plant proteins are growing in popularity amongst consumers and may have benefits for CKD patients because the bioavailability of phosphorus from plant sources is lower than from animal sources.[9-11] This has led researchers to hypothesize that shifting to dietary plant protein sources may mitigate metabolic abnormalities exhibited in CKD-MBD. However, current evidence for recommendation of dietary plant-based protein sources is lacking. Thus, the aim of this systematic review is to evaluate the available evidence for the effect of dietary plant-based protein on kidney function and CKD-MBD outcomes in stage 3-5 CKD patients
Belief change in response to evidence: Predictors and persistence over time (Study 3)
No full textResearch Questions: Does belief change in response to empirical evidence persist over time? What variables predict belief change in response to empirical evidence?
Study Overview/Design: This study has two primary aims. First, it serves as a conceptual replication of the previous studies on a different stimulus study topic (video games and aggression). Second, this study extends the previous studies by examining whether people show more belief change in response to stronger vs. weaker evidence, and whether those with a stronger understanding of science are more sensitive to the strength of the evidence when updating their beliefs in response to new evidence.
In Study 3, participants will read about a real study examining the relationship between playing video games and aggressive behavior. Participants will be randomly assigned to read evidence suggesting that playing video games is related to higher levels of aggression or not. In addition to the direction of the findings, the strength of the evidence will be manipulated. In the stronger evidence condition, participants will read the results from a recent meta-analysis, containing correlational and experimental evidence from over 100 studies on violent video games and aggression. In the weaker evidence condition, participants will read the results from a single, more dated, correlational study, examining the relationship between playing video games (in general, not just violent ones) and aggression.
Thus, participants will be randomly assigned to read one of four studies on video games and aggression: a single (correlational) study showing positive results (Fling, 1992), a single (correlational) study showing null results (van Shie et al., 1997), a meta-analysis (containing correlational and experimental evidence) showing positive results (Anderson et al., 2010), or a meta-analysis (containing correlational and experimental evidence) showing null results (Ferguson, 2015). Beliefs will be measured before and after the presentation of the evidence, along with at a follow-up 24 hours later. Possible individual difference variables associated with belief change in response to empirical evidence will be measured.
In this design, the primary factors of interest are the stimulus study findings (positive vs. null), the strength of the evidence (stronger vs. weaker), and time of belief assessment (T1, T2, T3).
Procedure:
Participants will be recruited from Amazon’s Mechanical Turk for a two-part study.
Session 1. Participants will first report their position on violent video games (1=strongly oppose, 7=strongly support; position T1), belief about how playing violent video games relates to levels of aggression (1=much lower, 7=much higher; correlational belief T1), belief about how playing violent video games affects levels of aggression (1=strongly decreases, 7=strongly increases; causal belief T1), and the certainty of their (causal) belief (1=very uncertain, 7=very certain; certainty T1). Participants will also answer a few distractor questions and complete a scale assessing their current emotions (including two exploratory items, uninterested and intrigued, not included in Study 2).
Next, participants will be presented with a summary of a study examining whether or not playing video games relates to aggressive behavior. Participants will be randomly assigned to one of four conditions, in which the study provides weaker or stronger evidence indicating that playing video games is a risk factor for aggression or not. In each condition, the evidence presented is summarized from a real study, so there is no deception.
Following the study summary, participants will evaluate the study in a closed (2 items, 7-point scales; “How well was the study conducted?” and “How convincing was this study?”, which will be averaged) and open-ended manner (i.e., “Do you think the study you just read supports the argument that playing violent video games [is or is not] a risk factor for aggression? Why?”). Then, participants will again report their emotions, position on violent video games (position T2), belief about how playing violent video games relates to levels of aggression (correlational belief T2), belief about how playing violent video games affects levels of aggression (causal belief T2), and the certainty of their (causal) belief (certainty T2). They will also be asked to recall the study findings (included as an attention check).
In the second part of Session 1, participants will complete several individual difference measures predicted to be associated with belief change: social desirability (Crowne & Marlowe, 1960), perceptions of scientific (un)certainty, a measure of commitment to one’s beliefs about violent video games and aggression, scientific reasoning ability (Drummond & Fischhoff, 2017), intellectual humility (Leary et al., 2014), and objectivism (Leary et al., 1986). Intellectual humility and objectivism were added in Study 3 as two additional variables that may be linked to belief change. Actively open-minded thinking was removed in Study 3 as it assesses attitudes toward open-minded thinking, rather than open-minded thinking directly, and was not related to belief change in the previous studies. The individual difference measures will be presented in randomized order, with the exception of the scientific reasoning scale, which will be presented last (due to the difference in its formatting).
At the end of Session 1, participants will answer several demographic questions. In addition to the questions from the previous studies, this section will contain questions about educational background, parent/guardian status, whether participants allow or would allow their children to play video games (in general) and violent video games, how frequently the participants play video games themselves, and the types of video games they play (violent, somewhat violent, nonviolent). Participants will be paid 0.50 for completing Session 2.
Copies of the Qualtrics surveys for each session (with exact question wording) are available on OSF.
Power Analysis: For a 2 (research findings: positive vs. null) x 2 (evidence strength: stronger vs. weaker) x 3 (time: T1, T2, T3) mixed-model ANOVA, a sample size of N=160 is necessary to obtain small-medium effects (f=0.15) at power of .95, alpha=.05. The power was set high (.95) to ensure the quality of the replication (Funder et al., 2014). Because a factor was added from Study 2 (which included a sample of ~N=300 participants) to Study 3, a higher initial sample of N=400 was targeted for Session 1.
Planned Analyses:
Exclusions. The main analyses will be performed with and without those who fail the attention check. Any discrepancies in the findings based on whether participants are excluded will be reported. If no discrepancies exist, all participants will be retained in the results reported.
Manipulation Check. To test whether participants perceive the evidence from the meta-analysis to be stronger than the evidence from the single study, a 2 (evidence strength: stronger vs. weaker) x 2 (research findings: positive vs. null) ANOVA will be performed on study evaluations. A main effect of evidence strength is expected, such that participants perceive the evidence from the meta-analysis to be higher in quality than the evidence from the single study. A possible main effect for research findings (with participants perceiving a study with positive results to be higher in quality than a study with null results) and evidence strength x research findings interaction will be examined, although such differences were not intended to be manipulated.
Belief and Position Change. 2x2x3 mixed-model ANOVAs, with research findings and evidence strength as between-subjects factors and time of belief/position assessment as a within-subjects factor, will be performed to examine whether participants change their beliefs (or position) in response to each study, maintain this shift 24 hours after the presentation of evidence, and change their beliefs more in response to stronger vs. weaker evidence. Although the primary test of the hypothesis is the analysis for beliefs, position will also be examined as it has shown change in previous studies, though to a lesser degree (Anglin, 2019).
If the three-way research findings x evidence strength x time of assessment interactions are significant, simple effects analyses will be performed on evidence strength to test whether the two-way research findings x time of assessment interactions vary based on the strength of the evidence. Significant two-way research findings x time of assessment interactions will be analyzed as in the previous studies by performing two sets of planned contrasts: one comparing T1 to each time point (T1 vs. T2, T1 vs. T3) and one comparing each subsequent time point (T1 vs. T2, T2 vs. T3). To control for multiple comparisons, the significance level for all planned contrasts will be set to p < .01.
Hypotheses. Based on the results of Anglin (2019) and the previous studies, an interaction between research findings and time of assessment is expected, with participants shifting their beliefs in response to the evidence presented and maintaining this shift 24 hours later. A three-way research findings x evidence strength x time of assessment interaction is also expected, such that the interaction between research findings and time of assessment will be stronger in the stronger vs. weaker evidence condition. This pattern would suggest that participants shift their beliefs more when the evidence bearing on a question is strong and clear.
Note: Some participants in the single, correlational study condition may not shift their beliefs about whether playing violent video games increases aggression in response to the evidence because the study is not experimental. As in Study 2, an additional belief question was included at each time point to assess participants’ (correlational) belief about the association between playing violent video games and aggression. This question will be examined in an exploratory fashion, as it is unknown how strongly correlated responses to the correlational and causal belief questions will be.
Belief and position change based on the (in)consistency of the evidence with prior views. Beliefs at T1 will be recoded so that higher scores indicate a stronger belief in the direction of the evidence presented, and belief change scores will be calculated (from T1 to T2 and T1 to T3) so that higher scores indicate more belief change in the direction of the evidence. Then, regression analyses will be performed, with the recoded belief at T1, research findings, and their interaction as predictors of belief change, to examine whether participants exhibit more or less belief and position change based on the consistency of the evidence with their initial belief (or position). The interaction of belief consistency with evidence strength will also be tested as an exploratory analysis.
Hypotheses. Based on the findings of Study 1, participants are expected to show the most belief and position change when the evidence conflicts with their prior views (presumably because these individuals have more room with which to move).
Study evaluation ratings. A regression analysis will be performed, with belief at T1, research findings, and their interactions as predictors, to examine whether participants evaluate the evidence more favorably when it is more consistent (vs. inconsistent) with their beliefs. The interaction of belief consistency with evidence strength will also be tested as an exploratory analysis.
Hypotheses. An interaction between belief at T1 and research findings is expected, such that participants will evaluate each study more favorably when it is more consistent with their initial belief.
Open-ended evaluations. Participants’ open-ended evaluations will be examined in an exploratory fashion.
Predictors of belief change. If the items from each individual difference measure have good internal consistency (i.e., α ≥ .70) and all items load ≥ .40 on a single factor, they will be averaged to create a composite measures. If not, items with low item-total correlations will be dropped and/or multiple factors (as determined by a factor analysis) will be examined separately. If the two belief items correlate strongly (i.e., r > .70), they will be averaged; otherwise, they will be analyzed separately.
A series of regression analyses will be performed to examine predictors of belief change in response to the evidence (from T1 to T2 and T1 to T3). An analysis will be performed for each individual difference measure (study evaluations, social desirability, positive and negative emotion at T1 and T2, scientific reasoning, belief commitment, perceptions of scientific uncertainty, intellectual humility, objectivism, and education), with the individual difference measure, evidence strength, and their interaction entered as predictors of belief change.
Hypotheses. Based on the findings from the previous studies, study evaluations are predicted to correlate positively, and perceptions of scientific uncertainty and scientific reasoning negatively, with belief change for the causal item. Based on evidence suggesting that individuals higher in intellectual humility are open to new evidence (McDiarmid et al., 2021) and opposing viewpoints (Bowes et al., in press; Porter & Schumann, 2017), we also expect that intellectual humility will positively correlate with belief change. Intellectual humility may also interact with belief consistency, such that those lower in intellectual humility show more belief change in response to belief-consistent vs. inconsistent evidence whereas those higher in intellectual humility show belief change irrespective of the consistency of the evidence with their initial beliefs.
In addition, interactions are expected between evidence strength and the individual difference measures associated with understanding of science/critical reasoning (i.e., scientific reasoning, perceptions of scientific uncertainty, and education), such that those with a stronger understanding of science will be more sensitive to the strength of the evidence in updating their beliefs. Evidence strength may also interact with intellectual humility, as Leary et al. (2014) found that those high in intellectual humility were more sensitive to argument strength in evaluating evidence than those low in intellectual humility.
Thus, those greater scientific reasoning, perceptions of scientific uncertainty, education, and intellectual humility are expected to change their beliefs more in response to strong vs. weak evidence, whereas those lower in these individual difference variables are expected to discriminate less between the two types of evidence, showing less discrepancy in belief change between conditions.
Possible differences in belief change based on whether the participants play violent video games and allow their children to play violent video games will be examined in an exploratory fashion
Gestural and verbal evidence of conceptual representation differences in blind and sighted individuals
No full textWe explore whether lack of visual experience alters how specific features of concepts are mapped onto gestural representations of concepts. To address this question, we examine whether congenitally blind people rely on different features of concepts in silent gestures compared to sighted individuals. Earlier studies focusing on depiction of individual concepts in silent gestures have suggested that visuospatial cues drive systematic patterns in silent gestures (e.g., Ortega & Ozyurek, 2020a, 2020b; van Nispen et al., 2017). Thus, a lack of visual experience may result in different gestural forms being selected for depiction of conceptual representations
“Latent State Trait Modelling of Executive Functions” (LST-EF Study)
No full textThe question being asked is to what extent variance in the executive functions of inhibition, updating, and shifting is due to state or trait influences. We wish to answer this question by applying latent state trait (LST) and latent growth-curve (LGC) modelling to dependent variables derived from widely used experimental tasks of the inhibition, updating, and shifting dimensions tasks in (N=250) healthy adults.
In addition, a secondary goal is to obtain information on the extent to which the number of trials in each task affects its reliability and stability. We also include two questionnaires assessing self-control and impulsivity, aiming to compare results from experimental tasks with commonly used self-report measures
Job Interview and Language
No full textThe aim of the study is to examine natural language use among female and male candidates for a leadership position. In particular, we are interested whether women and men differ in their use of agentic (AA) and communal (CW) expressions when presenting for a masculine or feminine framed leadership role
Does the language you speak shape the way you think about the world? Experiment 2, first replication
No full textThis study is a replication of Experiment 2 from Boroditsky et al. (2002). In this study, we are comparing how English-Indonesian bilinguals perceive actions based on grammatical tenses. English-Indonesian bilinguals were shown pictures representing action events for them to rate the similarity between pictures
How effective is contingent instruction? A replication study
No full textContingent Instruction is a key concept in contemporary educational policy development, is considered highly effective and currently widely promoted and implemented. It is advocated, for instance, by the Dutch government (e.g. Ministry of Education, Culture, and Science, 2011 and 2014), and the Educational Inspectorate regards it as an important normative standard: they yearly evaluate the extent to which teachers provide contingent instruction (e.g., Educational Inspectorate, 2019). And also internationally, student-centred education and personalized learning in which contingent instruction is a key aspect, are promoted (OECD, 2006; DfES, 2007). Therefore, it is surprising that the empirical evidence for the effectiveness of this famous and widely applied principle is scarce and weak (e.g., Van de Pol, Volman, & Beishuizen, 2010). Thus, more empirical evidence with more precise estimations of the effect is needed. In 1976, Wood, Bruner, and Ross laid the foundation of contingent instruction, using the classical notion of scaffolding. Scaffolding is instruction provided by an adult or teacher that is contingent upon the needs of a learner in the sense that more controlling support is provided when the learner’s understanding of the task at hand is low and less controlling support is provided when the learner demonstrates good understanding. The seminal study of Wood, Wood, and Middleton (1978), belonging to the top 2% of the most cited educational psychological studies of its era, was the first to experimentally test the effectiveness of the eminent principle of contingent instruction. Wood et al. found that 3-4 year old children who had received contingent instruction scored significantly better and worked more efficiently when working independently on a block-building task compared to children who had received various other, less-contingent, forms of instruction. Such block-building tasks address, amongst others, general problem solving skills, spatial skills and gross and fine motor skills (Hanline et al., 2001). Spatial skills strongly predict (future) Science, Technology, Mathematics, and Science (STEM) skills and training these skills with such block-building tasks results in improved concurrent and future performance on similar and different spatial tasks (Ramani et al., 2014; meta-analysis of Uttal et al., 2013). Furthermore, contingent instruction is a fundamental instructional principle that can be applied in a wide range of domains (e.g., math, science, social studies, reading, cf. review of Van de Pol et al., 2010). Given the lack of close replications and the small sample size of the 1978 study, a close replication is indispensable to verify whether the positive effect of contingent instruction really exists (Hüffmeier, Mazei, & Schultze, 2016). Replicating the original study will yield more certainty about the effect of this fundamental instructional principle. Of course, follow-up conceptual replications with older children and different domains will be needed to find more substantiation for policy regarding contingent instruction. Yet our close replication of Wood et al. (1978) is an important and necessary first step in accumulating evidence (also see Hüffmeier et al., 2016)
Sequential Pricing
No full textSellers and buyers think and behave differently during transactions, such that they price the same product differently. We are interested in how their marginal utility varies differently as the quantity of products or the quantity of a product attribute changes. And this effect holds for incentive compatible purchases