Reported Effect Sizes Research Articles

The push-pull-mooring model of consumer service switching: a meta-analytical review to guide future research

PurposeFor nearly 2 decades, the push-pull-mooring (PPM) model has been used frequently by scholars to explain consumers’ service switching intention and behavior. However, heterogeneity and incomparability between PPM model studies are prevalent issues: The chosen predictor variables, their categorization, their measurement, reported effect sizes, and effect directions vary considerably. By addressing these issues, the present meta-analytical review enables future researchers applying the PPM model to identify relevant variables and use valid measurements.Design/methodology/approachBased on 148 empirical studies employing the PPM model, the variables used to predict consumers’ service switching intention and behavior, their frequency of use, their categorization into push, pull, and mooring factors, and their measurement are assessed. The effect sizes and directions of the relationships between these variables and consumers’ service switching intention and behavior are analyzed using meta-analytic structural equation modeling. Additionally, the predictive capacity of this model and the influence of moderators are assessed.FindingsAmong the 148 empirical studies, 382 different independent variables were used. The three most frequently used and distinctly categorized independent variables are dissatisfaction (push), alternative attractiveness (pull), and switching costs (mooring). Overall, 152 unique sources were cited to measure these variables and the dependent variables. Dissatisfaction and alternative attractiveness increase switching intention, which positively affects switching behavior, while switching costs decrease switching intention. The model explains 30% of the variance in switching intention and 31% of the variance in switching behavior.Originality/valueThis study provides the first meta-analytical review of the PPM model to guide future research systematically.

Haptic Technology: Exploring Its Underexplored Clinical Applications-A Systematic Review.

Haptic technology has transformed interactions between humans and both tangible and virtual environments. Despite its widespread adoption across various industries, the potential therapeutic applications of this technology have yet to be fully explored. A systematic review of randomized controlled trials (RCTs) and randomized crossover trials was conducted, utilizing databases such as PubMed, Embase, Cochrane Library, and Web of Science. This review included studies reporting clinical applications of haptic technology in rehabilitation, cognition, wellness, and mental health among adult subjects. This systematic review included 34 studies, of which 20 focused on clinical outcomes and 14 on learning clinical skills. The results showed that haptic devices, both robotic and non-robotic, enhance sensorimotor performance and motor function in rehabilitation settings, especially in post-stroke recovery, with reported effect sizes ranging from 0.2 to 0.7. The majority of the haptic technologies reported were integrated into robotic systems (40%). Haptic devices were also reported to improve clinical skills training by providing tactile feedback that enhances procedural performance and trainee self-efficacy. In fact, surgical simulations accounted for 79% of all the modalities used for medical training. This review underscores the potential yet underexplored applications of haptic technology in healthcare, including medical education, rehabilitation, cognition, and mental health. The key limitations of this review include heterogeneity across studies, small sample sizes, and a scarcity of comprehensive, long-term investigations. Therefore, future research should aim to validate these findings further and expand the applications of haptic technology to maximize its utility in the healthcare industry and clinical practice.

Review of Correlations Between Telomere Length and Metal Exposure Across Distinct Populations

Telomere length (TL) predicts the onset of replicative senescence, and its shortening is a limiter on the number of divisions individual somatic cells can perform. Metal-induced genotoxic events are discussed in Agency for Toxic Substances and Disease Registry’s (ATSDR) toxicological profiles. In vivo and in vitro toxicological studies suggest the correlation between toxic metals and TL. However, the correlation between TL and exposure to toxic metals in human populations is unclear despite decades of observational research. We conducted a literature search within the ATSDR toxicological profiles and PubMed database for peer-reviewed articles as of 04/2023 discussing TL and metal exposure in human populations. Through review of the 272 publications meeting these criteria, we identified 25 observational studies that considered the correlation between TL and exposure to some or all of six metals: cadmium (Cd), arsenic (As), nickel (Ni), selenium (Se), lead (Pb), and cesium (Cs). Because reported effect sizes were often not comparable across studies, we performed a sign test based on the reported significance for each metal–TL correlation. We found that Cd was consistently significantly correlated with shorter telomeres (p = 0.016). However, no consistent linear relationship was observed between TL and any of the other metals considered. Exploring this association can enhance our understanding of how metal exposure may influence TL dysfunction. Our findings suggest that Cd exposure contributes to shorter TL, which may affect the DNA damage response (DDR) resulting in numerous chronic health conditions. Further, we highlight inconsistencies in findings on the correlation between metal exposure and TL across different populations and exposure levels. This suggests that correlations between some metals and TL may vary across populations, and that correlations may change at different exposure levels. Also, our findings suggest the need for further research on the potential for nonlinear relationships and non-additive effects of co-exposure to multiple hazardous metals, which could explain the inconsistencies observed across studies. The inconsistent incidences of metal–TL correlations justify additional exploration into the complex interaction between metals and TL.

The Association Between Traumatic Brain Injury and the Risk of Cognitive Decline: An Umbrella Systematic Review and Meta-Analysis.

There is currently increasing interest in the implication of traumatic brain injury (TBI) as a potential risk factor for long-term neurodegenerative conditions, such as dementia and Alzheimer's disease (AD). In this context, we performed a systematic review and meta-analysis to evaluate the association between TBI and the risk of dementia. A systematic search was performed across multiple electronic databases, including PubMed, Embase, and Cochrane Library, to identify relevant meta-analyses and cohort studies. Studies were included if they reported effect sizes (odds ratios [ORs] or relative risks [RRs]) for the association between TBI, its severity, and the risk of dementia or AD. Meta-analyses were performed using random-effects models to account for heterogeneity, and sensitivity analyses were conducted. A total of six studies were included in the analysis. The pooled results showed that TBI significantly increases the risk of dementia, with an overall odds ratio of 1.81 (95% CI: 1.53-2.14). Mild TBI was associated with a modest increase in dementia risk (OR = 1.96, 95% CI: 1.70-2.26), while moderate-to-severe TBI showed a stronger association (OR = 1.95, 95% CI: 1.55-2.45). In contrast, the association between TBI and AD was less consistent, with the pooled OR for AD being 1.18 (at 95% CI: 1.11-1.25) for mild TBI; however, in several studies, no significant association was observed (OR = 1.02, 95% CI: 0.91-1.15). The results also indicated substantial heterogeneity across studies, particularly in relation to AD outcomes. The findings from this umbrella meta-analysis confirm that TBI is a significant risk factor for dementia, with more severe TBIs conferring a higher risk. While mild TBIs also increase the risk of dementia, the effect is more pronounced in moderate-to-severe injuries. The evidence linking TBI to AD is less robust, with inconsistent findings across studies. Clinicians should consider long-term cognitive screening and management for individuals with a history of TBI, particularly those with moderate-to-severe injuries.

Consolidating the evidence on the effectiveness of strategies to promote vegetable intake in priority settings: An overview of systematic reviews.

Effective interventions to increase vegetable intake are urgently needed. This systematic rapid review aimed to summarise the effectiveness of interventions targeting increased vegetable intakes across diverse settings. The review was guided by the conduct of rapid reviews from the Cochrane Handbook. The literature was searched in February 2024 across PubMed, Web of Science and Cochrane Central for systematic review articles published since 2014. The Risk of Bias In Systematic Reviews tool was used and characteristics of reviews synthesised narratively with intervention effectiveness results were summarised. A total of 20 systematic reviews met the eligibility criteria. Most targeted school-based settings (n = 7) or community/home-based settings (n = 4). Early childhood education and workplaces had one review each, with none in retail, secondary or tertiary education, food service, food relief or aged care. The mean change in vegetable consumption was +0.12 serves per day, with increases of up to +0.42 serves reported (range -0.09 to +0.42). By setting, the largest increases were reported for interventions in school settings (+0.42 serves/day), followed by home (+0.38 serves/day). Almost half the studies reporting effect sizes suggested no effect on intake (46%), 41% suggested a small effect and 13% suggested a medium effect. Greater effect sizes were achieved in interventions implemented across multiple settings. Review findings indicate that the average increase in vegetable intake following interventions is about one-eighth of a serve but up to almost half a serve in some settings. An increase of this magnitude could have a substantial population impact, particularly in population groups with persistently low intakes.

Pesticides and prostate cancer incidence and mortality: An environment-wide association study.

Prostate cancer is the most common cancer among men in the United States, yet modifiable risk factors remain elusive. In this study, the authors investigated the potential role of agricultural pesticide exposure in prostate cancer incidence and mortality. For this environment-wide association study (EWAS), linear regression was used to analyze county-level associations between the annual use of 295 distinct pesticides (measured in kg per county) and prostate cancer incidence and mortality rates in the contiguous United States. Data were analyzed in two cohorts: 1997-2001 pesticide use with 2011-2015 outcomes (discovery) and 2002-2006 use with 2016-2020 outcomes (replication). The reported effect sizes highlight how a 1-standard-deviation increase in log-transformed pesticide use (kg per county) corresponds to changes in incidence. Analyses were adjusted for county-level demographics, agricultural data, and multiple testing. Twenty-two pesticides showed consistent, direct associations with prostate cancer incidence across both cohorts. Of these, four pesticides were also associated with prostate cancer mortality. In the replication cohort, each 1-standard-deviation increase in log-transformed pesticide use corresponded to incidence increases per 100,000 individuals (trifluralin, 6.56 [95% confidence interval (CI), 5.04-8.07]; cloransulam-methyl, 6.18 [95% CI, 4.06-8.31]; diflufenzopyr, 3.20 [95% CI, 1.09-5.31]; and thiamethoxam, 2.82 [95% CI, 1.14-4.50]). Limitations included ecological study design, potential unmeasured confounding, and lack of individual-level exposure data. The results of this study suggest a potential link between certain pesticides and increased prostate cancer incidence and mortality. These findings warrant further investigation of these specific pesticides to confirm their role in prostate cancer risk and to develop potential public health interventions.

Estimating the impact on patient safety of enabling the digital transfer of patients’ prescription information in the English NHS

ObjectivesTo estimate the number and burden of medication errors associated with prescription information transfer within the National Health Service (NHS) in England and the impact of implementing an interoperable prescription...

Doing Mindfulness-Oriented Recovery Enhancement (MORE) With MORE: A Systematic Search and Review of MORE for Opioid Misuse

There is evidence that Mindfulness-Oriented Recovery Enhancement (MORE) can be an effective intervention for individuals with chronic pain who are misusing opioids. A recent meta-analysis reported effect sizes ranging from small to moderate in the reduction of addictive behavior, craving, opioid dosage, pain, and psychiatric symptoms with subjects who had chronic pain and opioid misuse. However, there are no studies objectively evaluating the research methodology behind these studies. This study used a “systematic search and review” approach, to objectively evaluate the research methodology in opioid-related MORE studies. A comprehensive search was conducted encompassing four databases and the references from the retrieved articles. Seventy-five articles were identified, of which 12 met the review criteria. Among the 12 articles, data were extracted related to the studies’ methodological rigor using evaluation scores by three raters. The results support high levels of statistical conclusion validity. Suggestions are offered addressing both clinical and research implications including examining client populations that may benefit most from MORE, investigating the most suitable settings for MORE, and the need for more large-scale randomized controlled trials.

The association between road traffic accidents and visual functions: A systematic review and meta-analysis.

Poor visual functions have been reported to be related to the occurrence of road traffic accidents. To review the association between visual function and road traffic accidents (RTAs) from published relevant empirical studies. Worldwide. A random effects (RE) model meta-analysis was conducted using STATA 18. Statistical tests conducted include meta-summary statistics, RE meta-analysis (forest plot), meta-regression (relationship between mean age and effect sizes), funnel plots, Egger's and Begg's tests for publication bias and small study effects. A total of 17 relevant studies, which were either cross-sectional or observational by design, were included in the meta-analysis. Reported effect sizes were within computed confidence intervals (CI) at 95%. The computedQtest of homogeneity was 61.94. The overall mean effect size of 1.43 (95% CI of 0.985-1.883) was statistically significant at a 5% level (Z= 6.26;p 0.001). TheI-squared = 62.17% (p= 0.00) confirmed moderate heterogeneity and theQ-value of 61.94 (p= 0.00) rejected the null hypothesis that the effect size was the same in all the studies. The funnel plot showed that the remaining majority of 13 studies were within the funnel plot on the right-hand side of the line of no effect. These results provide evidence of associations between visual functions and RTAs, and highlight the need for targeted interventions and further research to address the challenges associated with impaired visual functions and road safety.Contributions:The study contributes to the understanding of the implications of visual functions for road safety.

An overview of the replicability, generalizability and practical relevance of eyewitness testimony research in the Journal of Criminal Psychology

Purpose Before psychological research is used for policy reforms and recommendations, it is important to evaluate its replicability, generalizability and practical relevance. This paper aims to examine these three criteria for published articles in the Journal of Criminal Psychology. Design/methodology/approach Through a literature search for published articles in the Journal of Criminal Psychology related to the topics of the special issue Contemporary Developments in the Retrieval and Evaluation of Witness Testimony: Towards making research more applicable to investigations, this paper identified 158 eligible articles. For each article, this paper extracted variables related to the type of article, reported p-values, type of sample and stimuli, power analyses and conducted analyses and how effect sizes were used and interpreted. This paper analyzed these variables descriptively and conducted a z-curve analysis. Findings In terms of generalizability, the articles examined populations of interest (e.g. offenders, prisoners) and there was no sole reliance on Western, Educated, Industrial, Rich and Democratic samples. However, for replicability, there were currently no replication studies or published Registered Reports and the z-curve analysis indicated a low expected replication rate. Moreover, when examining practical relevance, almost no power analyses were conducted and when they were conducted, they were not reproducible or did not use meaningful effect sizes. Finally, although the majority of studies reported effect sizes, they were oftentimes not interpreted. Originality/value The present study sheds light on the potential societal impact of published articles in the Journal of Criminal Psychology.

Glucagon-Like Peptide-1 Receptor Agonists and Major Adverse Cardiovascular Events in Patients With and Without Diabetes: A Meta-Analysis of Randomized-Controlled Trials.

Glucagon-like peptide-1 receptor agonists (GLP-1 RAs) have shown encouraging results regarding cardiovascular outcomes mainly in patients with diabetes. In the present study, we compared the efficacy of GLP-1 RAs in cardiovascular events between patients with and without diabetes. After finding eligible studies assessing the impact of GLP-1 RAs on cardiovascular events in patients with and without diabetes using a systematic search, we performed a meta-analysis on randomized-controlled trials (RCTs) comparing cardiovascular outcomes between patients taking GLP-1 RAs and placebo stratified by the presence or absence of diabetes. Relative risk (RR) and its 95% confidence interval (CI) were set as the reporting effect size using the random-effects model. A total of 24 RCTs (50 033 with GLP-1 RAs and 44 514 with placebo) were included. Patients on GLP-1 RAs had lower risk of major adverse cardiovascular events (MACE) (RR 0.87, 95% CI0.82-0.93), cardiovascular death (RR 0.88, 95% CI0.82-0.94), myocardial infarction (MI) (RR 0.87, 95% CI0.77-0.97), stroke (RR 0.86, 95% CI0.80-0.92), and hospitalization for heart failure (RR 0.90, 95% CI0.83-0.98). Both subgroups were shown to be effective in terms of MACE and mortality. Nondiabetic patients had decreased risk of hospitalization for heart failure and MI, whereas the diabetic subgroup had marginally nonsignificant efficacy. The findings of this meta-analysis indicated that patients who are overweight/obese but do not have diabetes have a comparable reduction in the risk of adverse cardiovascular events as those with diabetes. These results need to be confirmed further by large-scale randomized trials in the future.

Determination of sample size for various study designs in medical research: A practical primer.

Formulating a research question and selecting an appropriate study design for answering that question are crucial initial steps in the research process. The population, intervention, control group, and outcomes measures (PICO time and setting [TS]) framework provides a practical guide in this regard, which stands for population, intervention, control, outcome, type of research question, and study design. The various study designs have their own merits and demerits, and implementing the methodology meticulously requires knowledge of all of these. Similarly, different methods of sample size calculation are warranted based on the most appropriate study design and outcome variables of interest. Sometimes, a post hoc power analysis can be performed after the sample size calculation, to check whether the study was adequately powered or not. There are multiple validated free software tools for sample size calculation, including Open-Epi, R, StatCalc, etc. The practice by most researchers of reporting significant P values is to be replaced by reporting effect sizes, as the latter is a much better estimate of the strength of association. This review provides a comprehensive, ready reckoner for busy family physicians to quickly identify the appropriate study design for answering any applied research questions in their minds and estimating the sample size required for the same.

Durga: an R package for effect size estimation and visualization.

Statistical analysis and data visualization are integral parts of science communication. One of the major issues in current data analysis practice is an overdependency on-and misuse of-p-values. Researchers have been advocating for the estimation and reporting of effect sizes for quantitative research to enhance the clarity and effectiveness of data analysis. Reporting effect sizes in scientific publications has until now been mainly limited to numeric tables, even though effect size plotting is a more effective means of communicating results. We have developed the Durga R package for estimating and plotting effect sizes for paired and unpaired group comparisons. Durga allows users to estimate unstandardized and standardized effect sizes and bootstrapped confidence intervals of the effect sizes. The central functionality of Durga is to combine effect size visualizations with traditional plotting methods. Durga is a powerful statistical and data visualization package that is easy to use, providing the flexibility to estimate effect sizes of paired and unpaired data using different statistical methods. Durga provides a plethora of options for plotting effect size, which allows users to plot data in the most informative and aesthetic way. Here, we introduce the package and its various functions. We further describe a workflow for estimating and plotting effect sizes using example data sets.

Assessing omitted variables bias in intention-behavior linkages: Mitigation strategies and research implications

Omitting relevant variables in research models is a significant challenge in academic research involving non-experimental research methods. Omitted variables may bias the empirical findings and lead to erroneous conclusions about relationships between factors underlying information systems phenomena. Using data coded from 128 samples reported in 105 prior studies, this study applies meta-regression methods to quantify the extent to which omitted variables bias the reported effect sizes between behavioral intention and system use. Since a direct examination of omitted variables is not possible, this study quantifies four measures: independent variables common to both behavioral intention and system use, moderators for the relationship between behavioral intention and system use, moderators for relationships between other independent variables and system use, and control variables for system use. Meta-regression results show that the effect size for the relationship between behavioral intention and system use decreases when independent variables common to behavioral intention and system use or moderators for the relationship between behavioral intention and system use are included in research models. This implies that the non-inclusion of relevant variables distorts the effect size for the relationship between behavioral intention and system use resulting in a biased understanding of the relationships. It is crucial for research models to include relevant variables such that the omitted variables bias can be effectively handled. Several mitigation strategies and research implications are described.

Neuroticism and relationship quality: A meta-analytic review.

Regardless of participant age, length of relationship, country of origin, and numerous other factors, prior research has established a robust negative association between neuroticism and relationship quality. As so much has already been studied on the topic of neuroticism and relationship quality, this study explored the association between neuroticism and relationship quality using meta-analytic methodology, examined moderators, and outlined future studies for the field. After searching through databases and the references of included studies, 148 published studies were identified that reported an effect size between neuroticism and relationship quality. Reported effect sizes resulted in an overall aggregate correlation of r = -.238 and differentiated effect sizes for male actor and partner correlations, and female actor and partner correlations were similar. Results indicated that participant race, participant sexual orientation, and whether the effect sizes were taken from cross-sectional or longitudinal data did not moderate the relationship. However, the region of the world that the participants were from, the type of measurement tool used, participant age, and the length of time spent in a relationship were all significant moderators of our variables. We outline a model for how neuroticism operates through emotions, interpretations, and behaviors, which offers information for ways couples' practitioners could work to mitigate the association between neuroticism and relationship quality. Future directions for the field are delineated. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

An updated evidence synthesis on the Risk-Need-Responsivity (RNR) model: Umbrella review and commentary

PurposeTo conduct an umbrella review of Risk-Need-Responsivity (RNR) principles by synthesizing and appraising the consistency and quality of the underlying evidence base of RNR. MethodsFollowing PRISMA guidelines, we searched three bibliographic databases, the Cochrane Library, and grey literature from 2002 to 2022 for systematic reviews and meta-analysis on RNR principles. We summarized effect sizes, including as odds ratios and Area Under the Curve (AUC) statistic. We evaluated the quality of review evidence by examining risk of bias, excess statistical significance, between-study heterogeneity, and calculated prediction intervals for reported effect sizes. ResultsWe identified 26 unique meta-anlayses that examined RNR principles. These meta-analyses indicate inconsistent statistical support for the individual components of RNR. For the risk principle, there were links with recidivism (OR = 1.6, 95% CI [1.1, 2.3]). For the need principle, although there were associations between adherence to intervention programs and recidivism, risk assessment tools reflecting this principle had low predictive accuracy (AUCs 0.62–0.64). The general and specific responsivity principles received some support. However, the overall quality of the evidence was poor as indicated by potential authorship bias, lack of transparency, substandard primary research, limited subgroup analyses, and conflation of prediction with causality. ConclusionThe prevalent poor quality evidence and identified biases suggests that higher quality research is needed to determine whether current RNR claims of being evidence-based are justified.

How to Use and Report on p-values.

The use of the p-value in quantitative research, particularly its threshold of "P < 0.05" for determining "statistical significance," has long been a cornerstone of statistical analysis in research. However, this standard has been increasingly scrutinized for its potential to mislead findings, especially when the practical significance, the number of comparisons, or the suitability of statistical tests are not properly considered. In response to controversy around use of p-values, the American Statistical Association published a statement in 2016 that challenged the research community to abandon the term "statistically significant". This stance has been echoed by leading scientific journals to urge a significant reduction or complete elimination in the reliance on p-values when reporting results. To provide guidance to researchers in health professions education, this paper provides a succinct overview of the ongoing debate regarding the use of p-values and the definition of p-values. It reflects on the controversy by highlighting the common pitfalls associated with p-value interpretation and usage, such as misinterpretation, overemphasis, and false dichotomization between "significant" and "non-significant" results. This paper also outlines specific recommendations for the effective use of p-values in statistical reporting including the importance of reporting effect sizes, confidence intervals, the null hypothesis, and conducting sensitivity analyses for appropriate interpretation. These considerations aim to guide researchers toward a more nuanced and informative use of p-values.

Multiply by 37 (or Divide by 0.027): A Surprisingly Accurate Rule of Thumb for Converting Effect Sizes From Standard Deviations to Percentile Points

Educational researchers often report effect sizes in standard deviation units (SD), but SD effects are hard to interpret. Effects are easier to interpret in percentile points, but converting SDs to percentile points involves a calculation that is not transparent to educational stakeholders. We show that if the outcome variable is normally distributed, we can approximate the percentile-point effect simply by multiplying the SD effect by 37 (or, equivalently, dividing the SD effect by 0.027). For students in the middle three-fifths of a normal distribution, this rule of thumb is always accurate to within 1.6 percentile points for effect sizes of up to 0.8 SD. Two examples show that the rule can be just as accurate for empirical effects from real studies. Applying the rule to empirical benchmarks, we find that the least effective third of educational interventions raise scores by 0 to 2 percentile points; the middle third raise scores by 2 to 7 percentile points; and the most effective third raise scores by more than 7 percentile points.

Targeted Therapy Following Metastasectomy for Metastatic Renal Cell Carcinoma: A Systematic Review and Meta-analysis

Purpose: The aim of this study was to assess the effects of tyrosine kinase inhibitors (TKIs) following metastasectomy in patients with metastatic renal cell carcinoma (mRCC).Materials and Methods: A systematic search of multiple electronic databases was conducted. The inclusion criteria encompassed randomized clinical trials evaluating the use of TKIs after metastasectomy in mRCC patients. Study outcomes were relapse-free survival (RFS)/disease-free survival (DFS), overall survival (OS), and adverse events of TKIs.Results: Two studies with 197 randomized participants that compared TKIs following metastasectomy versus metastasectomy alone were identified. According to these studies, TKIs following metastasectomy may result in little to no difference in RFS/DFS (hazard ratio [HR], 1.01; 95% confidence interval [CI], 0.65–1.57; I&lt;sup&gt;2&lt;/sup&gt;=29%; low-certainty evidence). TKIs after metastasectomy may slightly increase OS, but the CI crossed the line of no effect (HR, 0.80; 95% CI, 0.06–9.87; I&lt;sup&gt;2&lt;/sup&gt;=86%; low-certainty evidence). TKIs after metastasectomy likely resulted in a large increase in adverse events (risk ratio, 2.76; 95% CI: 1.65–4.62; I&lt;sup&gt;2&lt;/sup&gt;=not applicable; moderatecertainty evidence).Conclusions: TKIs following metastasectomy did not improve RFS/DFS, but slightly improved OS. It is likely that TKIs following metastasectomy increase adverse events compared to surgery only. The certainty of evidence ranged from moderate (signaling confidence that the reported effect size is likely close to the true effect) to low (indicating that the true effect may be substantially different from the effect estimate). The findings of this study should help to inform future guidelines and clinical decision-making at the point of care.

Spatial location does not consistently constrain perceptual learning in speech

Recent research showed selectivity of perceptual learning in speech to linguistic variables and non-linguistic variables. With regard to the latter Keetels et al. (2016) reported that perceptual learning for one spatial location does not fully generalize to another. This spatial selectivity has been suggested to indicate that learning may target non-linguistic representations. We test whether spatial selectivity is a general property of perceptual learning or whether it is related to specific design choices, such as using a single nonword throughout the study. Therefore, we aimed to replicate spatial selectivity with a paradigm that makes use of a larger set of word and nonword stimuli. However, in three experiments, one in-person and two web-based, no effect of spatial selectivity was observed. A Bayesian analysis suggests that the null hypothesis is better supported by the data than the alternative hypothesis based on the previously reported effect size. Repercussions for the debate about pre-lexical representations in speech processing are discussed.