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Mobile communication technologies can provide citizens access to information that is tailored to their specific circumstances. Such technologies may therefore increase citizens’ ability to vote in line with their interests and hold politicians accountable. In a large-scale randomized controlled trial in Uganda (n = 16,083), we investigated whether citizens who receive private, timely, and individualized text messages by mobile phone about public services in their community punished or rewarded incumbents in local elections in line with the information. Respondents claimed to find the messages valuable and there is evidence that they briefly updated their beliefs based on the messages; however, the treatment did not cause increased votes for incumbents where public services were better than expected nor decreased votes where public services were worse than anticipated. The considerable knowledge gaps among citizens identified in this study indicate potential for communication technologies to effectively share civic information. Yet the findings imply that when the attribution of public service outcomes is difficult, even individualized information is unlikely to affect voting behavior.

This research examines the association between cross-cultural travelers’ well-being and the discrepancy between expected and experienced adaptation, in a longitudinal study of intercultural exchange students (N = 1762; Mage = 17 years; 70 % female). Specifically, two competing hypotheses were tested. Whereas the accuracy hypothesis suggests that unmet expectations lead to poorer outcomes, the directional hypothesis proposes that the outcome of unmet expectations will depend on whether expectations are overmet or undermet. Both sojourners’ adaptation expectations (pre-travel) and adaptation experiences (during the sojourn) were measured alongside general well-being. Controlling for baseline, well-being during the sojourn was regressed on the direction (undermet or overmet) and the magnitude (extent of discrepancy) of the adaptation expectation-experience discrepancies. These analyses were conducted across time (at entry or 5 months into the sojourn), different types of adaptation (psychological and sociocultural adaptation), and different measures of well-being (stress and satisfaction with life). Across analyses, results indicate that the direction of mismatch appears to matter little for small mismatches. However, for larger mismatches a positive effect emerged for sojourner well-being when the experience was better than expected, but a negative effect when the experience was worse than expected. Overall, the results support a directional hypothesis.

The present review investigates factors that predict three processes that lead to persistence versus change of expectations after confrontation with expectation violations, based on the ViolEx (Violated Expectation) Model (Gollwitzer, Thorwart, & Meissner, 2018) and related models. We address four groups of predictors: a) characteristics of the expectation, b) characteristics of the expectation-violating event(s), c) broader situational characteristics, and d) personality characteristics. The bulk of studies conducted in this area looked at expectation change in the direction of the experienced violation (accommodation) as their central dependent variable. The strongest empirical support was found for accommodation being less likely and minimizing of the potential impact of the discrepant information (immunization) being more likely to occur a) after the reality turns out to be worse rather than better than expected, b) if disconfirming events are more ambiguous, and c) if depressed rather than healthy people are confronted with better-than-expected events. Given the high heterogeneity between studies on assessed predictors, we recommend a more comprehensive and unifying approach that tests the relative impact and the interplay of the whole range of predictors across paradigms.

Low patient recruitment into diabetes prevention programs is a challenge. The primary aim of this study was to demonstrate that an increased recruitment rate can be achieved by communicating personalized risk of progression to type 2 diabetes, estimating risk reduction with weight loss, and offering program choice. Secondary aims included program participation rate, weight loss, and short-term decreased diabetes risk.In this single-arm study, persons with prediabetes from 3 primary care sites received a letter that communicated their personalized risk of progression to diabetes within 3-years, estimated risk reduction with 5, 10, 15 % weight loss, reported in pounds, and offered a choice of 5 free, 6-month, programs. A one-sided test was used to compare the recruitment rate against the maximum expected rate of (10 %).Recruitment response rate was 25.3 % (81/328, 95 % CI=[20.0 %, 29.4 %]) which was significantly higher than expected (p0.0001). Overall, 65 % of participants completed75 % of contacts. BMI, HbA1c, and diabetes risk (all p0.0001) improved at 6 months; BMI (p0.0001) and HbA1c (p0.05) improved at 12 months.Recruitment response rate was better than expected.Communicating personalized risk and reduction estimates with a choice of programs resulted in favorable outcomes, sustained at 1-year.

Within a conversation, individuals balance competing objectives, such as the motive to gather information and the motive to create a favorable impression. Across five experimental studies (N = 1427), we show that individuals avoid asking sensitive questions because they believe that asking sensitive questions will make their conversational partners uncomfortable and cause them to form negative perceptions. We introduce the Communication Motives and Expectations Model and we demonstrate that the aversion to asking sensitive questions is often misguided. Question askers systematically overestimate the impression management and interpersonal costs of asking sensitive questions. In conversations with friends and with strangers and in both face-to-face and computer-mediated conversations, respondents formed similarly favorable impressions of conversational partners who asked sensitive questions (e.g., “How much is your salary?”) as they did of conversational partners who asked non-sensitive questions (e.g., “How do you get to work?”). We assert that individuals make a potentially costly mistake when they avoid asking sensitive questions, as they overestimate the interpersonal costs of asking sensitive questions.

This paper empirically compares the use of straightforward verses more complex methods to estimate public goods game data. Five different estimation methods were compared holding the dependent and explanatory variables constant. The models were evaluated using a large out-of-sample cross-country public goods game data set. The ordered probit and tobit random-effects models yielded lower p values compared to more straightforward models: ordinary least squares, fixed and random effects. However, the more complex models also had a greater predictive bias. The straightforward models performed better than expected. Despite their limitations, they produced unbiased predictions for both the in-sample and out-of-sample data.

Objective: To evaluate the characteristics and prognosis of hospitalized geriatric COVID-19-positive patients during the first 30 days of the Swiss confinement period. Design: A retrospective case series analyzing the characteristics and disease evolution for 81 patients admitted to the geriatric COVID-19-positive ward during a 30-day period from March 24 to April 22, 2020. Setting and participants: Any COVID-19-positive patients who was admitted to one of four geriatric hospital sites who were >65 years old and did not desire intubation. Methods: Data collection on patients admitted throughout the study period, as well as chart review for those discharged within the 30-day period to ensure that information was complete.

Many youth may make progress while accessing residential mental health treatment, though their outcomes post-discharge are varied. While some youth continue to struggle in the post-discharge enviro...

Contains fulltext : 251338.pdf (Publisher’s version ) (Open Access) Resilience is a dynamic process depicted by better than expected levels of functioning in response to significant adversity. This can be assessed statistically, by taking the residuals from a model of psychological functioning regressed onto negative life events. We report the first study to investigate multiple cognitive factors in relation to this depiction of resilient functioning. Life events, internalizing symptoms, and a range of cognitive risk and protective factors were assessed in a large sample of adolescents (N = 504) across three waves spaced 12-18 months apart. Adolescents who displayed fewer symptoms than expected, relative to negative life events, were considered more resilient. Adolescents who displayed more symptoms than expected, relative to negative life events, were considered less resilient. All cognitive factors were associated with resilient functioning to differing degrees. These included memory bias, interpretation bias, worry, rumination, self-esteem, and self-reported trait resilience. Regression models showed that memory bias was a key factor explaining unique variance in prospective resilient functioning. In a subsequent cross-lagged panel model, memory bias and resilient functioning were reinforcing mechanisms across time points, supporting cognitive models of emotional resilience. This study adds to the literature, by highlighting key cognitive mechanisms as potential intervention targets.

In modern coexistence theory, species coexistence can either arise via stabilizing mechanisms that increase niche differences or equalizing mechanisms that reduce fitness differences. Having a common currency for interpreting these mechanisms is essential for synthesizing knowledge across different studies and systems. Several methods for quantifying niche and fitness differences exist, but it remains unknown to what extent these methods agree on the reasons why species coexist. Here, we apply four common methods to quantify niche and fitness differences to one simulated and two empirical data sets. We ask if different methods result in different insights into what drives species coexistence. We find that different methods disagree on the effects of resource supply rates (simulated data), and of plant traits or phylogenetic distance (empirical data), on niche and fitness differences. More specifically, these methods often do not agree better than expected by chance. We argue for (1) a better understanding of what connects and sets apart different methods, and (2) the simultaneous application of multiple methods to enhance a more complete insight into why species coexist.

Since the outbreak of Coronavirus disease in December 2019, information specific to pregnancy remains limited and controversial. Based on data from previous reports, it has been noticed that contrary to prior pandemics such as SARS, MERS and H1N1 and although pregnancy is usually considered as a condition of high susceptibility to viral infections, new SARS-CoV2 infection seems to have a more benign clinical course when affecting pregnant women. We speculate that during pregnancy the physiological "silencing" of the Th1 pro-inflammatory response may blunt the cytokines storm which is thought to play a key-role in the pathogenesis of the severe complications of Covid-19.

Abstract. We analyzed grade level and sex differences for changes in expectations and coping with expectation violations, based on the ViolEx model. A sample of 114 third to sixth graders (male, n = 44, 38.6 %; female, n = 70, 61.4 %) reported their expected achievement in trials with no feedback, worse-than-expected achievement feedback, and better-than-expected feedback. Expectations improved across the no-feedback and better-than-expected feedback trials, and deteriorated across worse-than-expected trials. While expectation change did not vary by grade level or sex, reported coping with expectation violation did vary, and pupils of younger years reported higher attempts to fulfill their expectations (assimilative behavior). Immunization against worse-than-expected feedback was associated with higher expectations in the negative-feedback condition, but protective effects of immunization were lost with an increasing number of expectation violations. In addition, higher willingness to reduce one’s expectations (accommodation) inhibited the update of expectations after receiving better-than-expected feedback. Conclusions for future research are drawn.

Several low-and-middle-income countries (LMICs) have responded to COVID-19 much better than expected, despite little help from high-income nations. LMICs can learn from the COVID-19 experience and re-imagine healthcare delivery. Using Bangladesh and India as examples, we explain how COVID-19 investments and systems can be leveraged to fight endemic infectious diseases.

National audience; Political accountability may be constrained by the reach and relevance of information campaigns in developing democracies and—upon receiving information—voters' ability and will to hold politicians accountable. To illuminate voter‐level constraints and information relevance absent dissemination constraints, we conducted a field experiment around Senegal's 2017 parliamentary elections to examine the core theoretical steps linking receiving different types of incumbent performance information to electoral and nonelectoral accountability. Voters immediately processed information as Bayesians, found temporally benchmarked local performance outcomes particularly informative, and updated their beliefs for at least a month. Learning that incumbents generally performed better than expected, voters durably requested greater politician contact after elections while incumbent vote choice increased among likely voters and voters prioritizing local projects when appraising incumbents. In contrast, information about incumbent duties did not systematically influence beliefs or accountability. These findings suggest voters were able and mostly willing to use relevant information to hold politicians to account.

There seems to be a widespread view that foreign lorry drivers’ lack of competence on Norwegian roads, especially related to winter driving, is a significant safety problem. It has, however, been suggested that foreign heavy goods vehicle (HGV) drivers perform better than expected on Norwegian winter roads, as they feel less safe than Norwegian drivers, and adapt by driving slower and more carefully. The aim of the present paper is twofold. First, we examine whether foreign HGV drivers in Norway actually have poorer competence on, training for, experience with and equipment for winter driving than Norwegian HGV drivers. Second, we discuss whether the expected negative effect of these safety challenges is mitigated, as foreign HGV drivers adapt their behaviours. We use four data sources to shed light on the aims: (1) interviews, (2) roadside inspections, (3) small-scale survey and (4) towing incidents. Our data support the hypothesis about behavioural adaptation, indicating that foreign HGV drivers experience winter driving as more difficult or unsafe, as they have supposedly less suitable vehicles and equipment, less experience, training and competence for winter driving. They are therefore more likely to get stuck while driving uphill on winter roads, supposedly as they drive more carefully and slower than Norwegian HGV drivers. Norwegian HGV drivers feel safer and more confident while driving on winter roads, because of their equipment and their experience.

© 2020 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/), Acute stress is ubiquitous in everyday life, but the extent to which acute stress affects how people learn from the outcomes of their choices is still poorly understood. Here, we investigate how acute stress impacts reward and punishment learning in men using a reinforcement-learning task. Sixty-two male participants performed the task whilst under stress and control conditions. We observed that acute stress impaired participants' choice performance towards monetary gains, but not losses. To unravel the mechanism(s) underlying such impairment, we fitted a reinforcement-learning model to participants' trial-by-trial choices. Computational modeling indicated that under acute stress participants learned more slowly from positive prediction errors - when the outcomes were better than expected - consistent with stress-induced dopamine disruptions. Such mechanistic understanding of how acute stress impairs reward learning is particularly important given the pervasiveness of stress in our daily life and the impact that stress can have on our wellbeing and mental health., This work was supported by grants from the Portuguese Foundation for Science and Technology (FCT) to A. Seara-Cardoso [PTDC/MHC-PCN/2296/2014, co-financed by FEDER through COMPETE2020 under the PT2020 Partnership Agreement (POCI-01-0145-FEDER-016747)] and to A. Mesquita (IF/00750/2015). J. Carvalheiro was supported by a FCT PhD fellowship (PD/BD/128467/2017). This study was conducted at the Psychology Research Centre (PSI/01662), School of Psychology, University of Minho, supported by FCT and the Portuguese Ministry of Science, Technology and Higher Education (UID/PSI/01662/2019), through national funds (PIDDAC).

Expectancies of cancer patients regarding their physical activity before they took part in a behavior change intervention were compared with their experiences during the intervention period. A total of 66 cancer patients completed either a randomly assigned 4-week physical activity or a stress-management counseling intervention. On average, participants had positive expectancies toward physical activity. Outcome expectancies predicted outcomes (e.g. physical activity) at a 10-week follow-up. Outcome realization (discrepancy between expectancies and experiences) further increased explained variance in self-efficacy and physical activity enjoyment. In conclusion, not only initial outcome expectancies but also their realizations seem to be important for subsequent behavior and cognitions.

We studied the determinants of consumer satisfaction with mobile phones on the basis of their perceived product attribute performance, and the disconfirmation of product attribute expectations. Disconfirmation refers to the discrepancy between the prior expectation about the performance of a product’s attributes, and its perceives realizations after purchase. Evaluability theory assumes that the perceived attribute performance has a larger effect on consumer satisfaction for easy-to-evaluate than for difficult-to-evaluate attributes, after product acquisition. Furthermore, we used predictions of the asymmetric evaluations of gains (product performs better than expected) and losses (product performs worse than expected) from prospect theory, in combination with evaluability theory. We studied how evaluability influences the effects of the asymmetric evaluations of both positive and negative disconfirmation of product attribute expectations on consumer satisfaction. Our empirical study included 3099 participants of Amazon Mechanical Turk. We found that negative attribute disconfirmation had a larger effect on satisfaction than positive attribute disconfirmation, which is in line with loss aversion theory. Although the perceived product attribute performance positively influenced satisfaction, we found little support for the effects of perceived attribute performance being influenced by attribute evaluability. However, our findings indicated that negative attribute disconfirmation influenced satisfaction to a greater extent for relatively difficult-to-evaluate attributes than for relatively easy-to-evaluate attributes. We discuss both theoretical and managerial implications of our findings.

The focus of this working paper is on how secondary schools can optimise young people’s preparation for adult employment at a time of extreme labour market turbulence. By reviewing academic analysis of national longitudinal datasets, it is possible to identify indicators of comparative adult success. How teenagers (i) think about their futures in work and what they do to (ii) explore and (iii) experience workplaces within and outside of schools is consistently associated with better than expected employment outcomes in adulthood. Data-driven career guidance will take such indicators into account within delivery. Analysis of the Programme for International Student Assessment (PISA) 2018 illustrates substantial variation in the extent of such career readiness between and within countries. Variation in career readiness is particularly associated with disadvantage. More effective education systems will ensure schools systematically address inequalities in teenage access to information and support in preparing for working life.

Intraoperative anesthetic technique directly impacts immediate postoperative recovery, yet there are few opportunities for anesthesiologists to receive feedback and no easily available benchmarks, making it difficult to reflect on one's own practice. This initial implementation study used retrospective data from 5,712 ambulatory surgery cases with healthy adult patients undergoing general anesthesia in 2018 at a large tertiary care academic center. It examines variation in practice among anesthesiologists for eight surgical specialties. Scorecards assessing intraoperative and postoperative opioids, antiemetics, nonopioid analgesics, regional blocks, recovery time, and severe postoperative pain compared with peers were given to anesthesiologists with prefeedback and postfeedback surveys assessing their attitudes toward feedback. Before receiving their scorecard, 71% of providers predicted their performance was average, and 29% predicted their performance was above average. After receiving their scorecards, 42% rated their quality of recovery as worse than expected, 42% rated it as expected, and 16% rated it as better than expected. Thirteen percent disagreed, 44% were neutral, and 44% agreed that this feedback will change their practice. Implementing a scorecard of patient-centered measures that shows where an anesthesiologist stands in the distribution of their peers was well-received, provides a benchmark, and has the potential to change practice.

Nowadays those who make replicate measurements of physicochemical properties usually employ spreadsheets or handheld devices to perform averaging and other statistical operations. Using the determination of a partition ratio as an exemplary procedure, and employing statistical simulation, we examine errors that can arise by unthinking reliance on “clicking”. Alternative, more soundly based, procedures are advocated. A serendipitous result is that the logarithm of a partition ratio behaves statistically much better than expected.

Analysing the behaviour of student performance in classroom education is an active area in educational research. Early prediction of student performance may be helpful for both teacher and the student. However, the influencing factors of the student performance need to be identified first to build up such early prediction model. The existing data mining literature on student performance primarily focuses on student-related factors, though it may be influenced by many external factors also. Superior teaching acts as a catalyst which improves the knowledge dissemination process from teacher to the student. It also motivates the student to put more effort on the study. However, the research question, how the performance or grade correlates with teaching, is still relevant in present days. In this work, we propose a quantifiable measure of improvement with respect to the expected performance of a student. Furthermore, this study analyses the impact of teaching on performance improvement in theoretical courses of classroom-based education. It explores nearly 0.2 million academic records collected from an online system of an academic institute of national importance in India. The association mining approach has been adopted here and the result shows that confidence of both non-negative and positive improvements increase with superior teaching. This result indeed establishes the fact that teaching has a positive impact on student performance. To be more specific, the growing confidence of non-negative and positive improvements indicate that superior teaching facilitates more students to obtain either expected or better than expected grade.

Purpose The purpose of this paper is to examine analyst followings of firms starting from one year prior to their filing for Chapter 11 and as the firms progress through bankruptcy proceedings with a focus on firms receiving “Hold” or better recommendations. The authors attempt to answer questions such as what the common characteristics of the firms receiving stronger than expected recommendations one year prior to filing for bankruptcy reorganization or while in bankruptcy are, and how the market reacts to the issuance of stronger ratings for those firms. Design/methodology/approach The authors design various regressions and apply them to a total of 2,754 sell-side analyst recommendations and 325 firms that are either approaching bankruptcy filing or in the process of reorganizing. In each analysis, the authors control for several firm and performance characteristics. Findings The authors find that the probability of securing stronger ratings is higher for small firms and for those followed by a greater number of analysts than for large firms and firms followed by fewer analysts. The market becomes more skeptical of optimistic evaluations closer to the date of bankruptcy filing (perhaps reflecting some anticipation) and reacts more positively to rating upgrades issued during bankruptcy protection than to the upgrades issued before the bankruptcy filing. Research limitations/implications The conclusions are based on the analysis of analyst recommendations issued shortly before Chapter 11 filings and during bankruptcy proceedings. The conclusions could be strengthened by further analysis of firms’ post-bankruptcy recovery and performance and examination of analyst recommendations issued for the firms after they emerge from Chapter 11.. Practical implications Analyst security ratings that are more positive than expected are perhaps the result of superior expertise and access to private information. During bankruptcy proceedings, when information disclosure is limited, investors could greatly benefit from reports issued by security analysts. Originality/value This study contributes to the literature in a number of ways. First, the authors contribute to the literature on the analyst ratings of firms in distress by considering the period between bankruptcy filing and emergence, while the existing literature provides analysis of pre-bankruptcy recommendations and forecasts. Second, the authors focus on better than expected ratings rather than all types of ratings as the firms approach bankruptcy filings and proceed through reorganization. Finally, they evaluate how investors react to stronger than expected analyst ratings.

We conducted two experiments to study people’s prior expectations and actual perceptions of automated and human-written news. We found that, first, participants expected more from human-written news in terms of readability and quality; but not in terms of credibility. Second, participants’ expectations of quality were rarely met. Third, when participants saw only one article, differences in the perception of automated and human-written articles were small. However, when presented with two articles at once, participants preferred human-written news for readability but automated news for credibility. These results contest previous claims according to which expectation adjustment explains differences in perceptions of human-written and automated news.

The effects of data uncertainty on real-time decision-making can be reduced by predicting data revisions to US GDP growth. We show that survey forecasts efficiently predict the revision implicit in the second estimate of GDP growth, but that forecasting models incorporating monthly economic indicators and daily equity returns provide superior forecasts of the data revision implied by the release of the third estimate. We use forecasting models to measure the impact of surprises in GDP announcements on equity markets, and to analyse the effects of anticipated future revisions on announcement-day returns. We show that the publication of better than expected third-release GDP figures provides a boost to equity markets, and if future upward revisions are expected, the effects are enhanced during recessions\ud

Although the global economy is forecasted to shrink by 4.4 percent in 2020 (IMF 2020), the Egyptian economy is proving resilient to the immense human and financial costs caused by the global COVID-19 pandemic. This resilience is mainly explained by the successful implementation of the economic reform program since 2016 that provided more fiscal space to withstand the adverse impact of the COVID-19 crisis. However, that Egypt’s economy is holding up is also due to the rapid response and proactive measures to limit the impact of the virus that were implemented by the Egyptian Government since March 2020 (MPED 2020). These enabled the country to avoid a full lockdown policy (Figure 1). While Egypt posted negative economic growth rates from April to June 2020 at the height of the crisis, overall economic growth was still positive at 3.6 percent for fiscal year (FY) 2019/20. This estimate is only slightly lower than the initial projection of the impact of the pandemic on Egypt’s economy of an annual economic growth equal to 3.8 percent, as estimated by staff of the International Food Policy Research Institute (IFPRI) and the Ministry of Planning and Economic Development (MPED) (Breisinger et al. 2020). The deviation between the early and final estimate can be mainly explained by the lower than expected growth rates in the manufacturing and health services sectors and the better than expected performance of the trade and transport sectors.

Background/Study Context: Older adults show a greater response to feedback whilst learning than younger adults. To date this has only been shown for receiving veridical feedback, but there is evidence that suggests that receiving false positive feedback may further enhance learning. We tested the hypothesis that receiving false positive feedback, being told you are preforming better than expected, would be more advantageous for older than younger adults when learning an inhibitory-action task. Methods: 42 younger and 34 older adults trained to improve their inhibition and response times on the Simon task. They completed 18 training blocks and a retention test two weeks after training. Participants received either false positive feedback or veridical feedback on their performance at the end of each training session and the start of the next session. Those in the false positive feedback group were told they were performing faster than expected. Results: Both older and younger adults improved their inhibition and response times but receiving false positive feedback did not significantly change their rate of learning on these outcomes. However, false positive feedback did impact on accuracy levels with those receiving this type of feedback making fewer errors. Older adults were slower but more accurate than younger adults, but contrary to our hypothesis they did not benefit more from false positive feedback than younger adults. Conclusion: This first direct comparison of the effects of false positive feedback on older and younger adults showed that the positive impact of false positive feedback does not decline with age. We also demonstrated that feedback given about one aspect of a skill (in this case speed) may in fact influence another aspect of the skill (in this case accuracy). This suggests that false positive feedback could be used as a motivational tool to enhance cognitive-motor learning in older adults, but care needs to be taken when using this, as the feedback may not affect the element of the skill at which it is targeted.

People are seen as resilient when they respond better than expected in the face of adversity. The aim of the article is to provide a description of the risks the unemployed day labourers waiting at a street corner in Cape Town experience daily and the resilience they display. An ethnographic approach was used to gather data. The results show that day labourers experience difficulties related to insufficient and irregular income to care for those dependent on them, friction between local and foreign day labourers, and uncertain working conditions. Hope of obtaining employment to look after their families and caring individuals and groups enhance their resilience.

We study the impact of secure survey designs ensuring plausible deniability on information transmission in organizations. We are interested in settings in which fear of retaliation makes potential informants reluctant to reveal the truth. Theory predicts that: (i) popular randomized-response designs fail to induce informative reports, because they are strategically equivalent to non-secure direct-elicitation designs; (ii) hard-garbling designs that exogenously distort survey responses improve information transmission; and (iii) unbiased estimates of the impact of survey design on information transmission can be obtained in equilibrium. Laboratory experiments qualify these predictions. While hard-garbling does improve information transmission over direct-elicitation, other predictions fail: randomized response performs much better than expected; and false accusations lead to a small but persistent bias in treatment effect estimates. We show that these deviations from equilibrium can be accounted for in an off-the-shelf model of boundedly rational play, and that this model of play makes specific predictions over the bias of treatment effect estimators. Additional experiments reveal that play converges to equilibrium if players can (socially) learn from cross-sectional data. These results suggest that randomized response cannot be used systematically in organizational settings, whereas hard garbling improves survey quality even under long-run equilibrium conditions.

What’s the long term outlook after covid? And what’s the prognosis for health systems and staff struggling with covid pressures, waiting lists, and stretched resources? Most people make a good recovery, but the wide range of covid related illness and organ damage weave a complex prognostic picture. Of patients discharged from hospital, more than one in 10 will die within six months, writes Emily Fraser (doi:10.1136/bmj.n1565).1 Some patients with lung damage will have persisting respiratory symptoms, but for those who were previously fit and without other complications the outlook is good, with functional recovery better than expected from the radiological evidence. Up to 376 000 people in the UK have reported ongoing …

This empirical study analyzed data from 638 teachers and 11,800 students in low-socioeconomic status (SES) urban schools (and schools with urban characteristics) exploring associations of school, teacher, teaching, and professional development characteristics toward student performance on the revised Advanced Placement (AP) Biology and AP Chemistry examinations. The analyses indicated that districts per-student funding allocations, the days of instruction, teachers’ knowledge and experience, and some aspects of teachers’ professional development participation were significantly associated with student performance on AP science examinations that was better than predicted by students’ Preliminary Scholastic Aptitude Test (PSAT) scores.

Humans update their beliefs upon feedback and, accordingly, modify their behaviors to adapt to the complex, changing social environment. However, people tend to incorporate desirable (better than expected) feedback into their beliefs but to discount undesirable (worse than expected) feedback. Such optimistic updating has evolved as an advantageous mechanism for social adaptation. Here, we examine the role of oxytocin (OT)-an evolutionary ancient neuropeptide pivotal for social adaptation-in belief updating upon desirable and undesirable feedback in three studies (n = 320). Using a double-blind, placebo-controlled between-subjects design, we show that intranasally administered OT (IN-OT) augments optimistic belief updating by facilitating updates of desirable feedback but impairing updates of undesirable feedback. The IN-OT-induced impairment in belief updating upon undesirable feedback is more salient in individuals with high, rather than with low, depression or anxiety traits. IN-OT selectively enhances learning rate (the strength of association between estimation error and subsequent update) of desirable feedback. IN-OT also increases participants' confidence in their estimates after receiving desirable but not undesirable feedback, and the OT effect on confidence updating upon desirable feedback mediates the effect of IN-OT on optimistic belief updating. Our findings reveal distinct functional roles of OT in updating the first-order estimation and second-order confidence judgment in response to desirable and undesirable feedback, suggesting a molecular substrate for optimistic belief updating.

In the present study, the assumption was tested that expectancy-incongruent feedback in conjunction with explicit self-affirmation directs attention away from the task and to the self. As a result, performance should decrease in resource-sensitive text/picture comprehension tasks as compared to resource-insensitive tasks. Three hundred and thirty-seven fifth graders first completed either easy or difficult text/picture comprehension tasks and then rated their learning outcome. After that, they received bogus feedback that had been congruent or incongruent with their expectations. In addition, half of the participants were given the opportunity for self-affirmation before they completed additional easy or difficult text/picture tasks. As predicted, feedback better than expected or worse than expected impaired performance in the resource-sensitive tasks but only in the self-affirmation condition. The results are discussed with regard to central assumptions of the feedback intervention theory (Kluger and DeNisi, Psychological Bulletin, 119: 254–284, 1996) and practical implications for the provision of feedback.

Aim A ‘good’ classification should provide information about the composition and abundance of the species within communities, if it serves as an informative surrogate for biodiversity. A natural way to formalize this is with a predictive model, where group membership (clusters) is the predictor, and multivariate species data (site by species matrix) is the response. In this study, we aimed to develop a predictive model-based framework for evaluating the predictive performance of alternative classifications of vegetation communities, and apply it to make objective and automated decisions about classification structure. Methods We used GLMs fit to multivariate species data to predict occurrence of individual species with site groupings. We used AIC to estimate predictive performance of alternative models to: (1) identify optimal partitioning of sites among multiple competing flexible-β clustering solutions; (2) identify species that contribute most to compositional differences between clusters (i.e. characteristic species); and (3) automatically merge clusters to maximize expected predictive performance using an iterative pruning approach. Using field data from southeastern Australia, and simulated data, we demonstrate our approach for common ecological data types (presence/absence, counts, cover–abundance scores, percentage cover). We supply all code and data required for these analyses. Results AIC was a useful metric for assessing competing classification solutions. Our method produced outputs that were simple to interpret and required few subjective choices to be made by the user, while performing similarly to the popular OptimClass assessment methodology. Characteristic species defined by predictive performance were consistent between data types, and had good general agreement with existing methods for defining characteristic species. Using model performance to iteratively refine clustering produced classifications with better than expected predictive performance compared to the dendrogram hierarchy, although the flexible-β hierarchy did a reasonable job of improving predictive performance. Conclusions Appropriately specified models are a natural way to maximize the predictive performance of a classification and its associated diagnostics. We show that a model-based assessment provides a clear decision framework based on data type, offering an objective pathway to make classification assessment decisions, as well as evaluate methodological choice and performance.

Recent visual masking studies that have measured visual awareness with graded subjective scales have often failed the show any evidence for unconscious visual processing in normal observers in a paradigm similar to that used in studies on blindsight patients. Without any reported awareness of the target, normal observers typically cannot discriminate target's features better than chance. The present study examined processing of color and orientation by measuring graded awareness and forced-choice discriminations for both features in each trial. When no awareness for either feature was reported, discrimination of each feature succeed better than expected by chance, even when the other feature was incorrectly discriminated in the same trial. However, the characteristics of the mask determined whether or not masked blindsight was observed. We conclude that when the processing channels are free from intra-channel interference, unbound or weakly bound features can guide behaviour without any reported awareness in normal observers.

This paper analyses whether jersey sponsorship has an effect on team performance at FIFA World Cup matches, taking team qualities into account. Team qualities are measured by the Elo-ratings of national soccer teams. We measure the performance of sponsors by comparing the Elo-ratings at the start and the end of World Cup tournaments. The Elo-ratings are used to calculate the expected probabilities of a win during knockout matches and to compare them with the actual outcomes. The results show that in the knockout stages of the World Cup tournaments, national teams sponsored by Adidas perform significantly better than expected, while teams sponsored by other companies, such as Puma or Nike, perform worse. The average advantage per knockout match for the Adidas teams is to raise the probability of winning by 10 percentage points.

Many decisions involve weighing immediate gratification against future consequences. In such intertemporal choices, people often choose smaller, immediate rewards over larger delayed rewards. It has been proposed that emotional responses to immediate rewards lead us to choose them at our long-term expense. Here we utilize an objective measure of emotional arousal – pupil dilation – to examine the role of emotion in these decisions. We show that emotional arousal responses, as well as choices, in intertemporal choice tasks are reference-dependent and reflect the decision-maker’s recent history of offers. Arousal increases when less predictable rewards are better than expected, whether those rewards are immediate or delayed. Furthermore, when immediate rewards are less predictable than delayed rewards, participants tend to be patient. When delayed rewards are less predictable, immediate rewards are preferred. Our findings suggest that we can encourage people to be more patient by changing the context in which intertemporal choices are made.

The loss of manufacturing jobs in the United States has been widely noted in the popular press as well as in public policy debate. We examine several of the most prominently made assertions about manufacturing decline and its consequences for deindustrializing metropolitan areas and find not all of them supported by the data. In particular, we find that, given their industrial structure some of these areas performed better than expected, that long-term economic distress was not inevitable, that manufacturing remains an important component in many metropolitan area economies, and that much of the growth in the service sector is based upon or complementary to the existence of manufacturing. We also find that low growth in these deindustrialized areas was due more to these regions losing their market share of individual industries to other U.S. regions than it was to the areas having an adverse industrial structure, that economies that were more diversified in 1980 did not have greater employment growth from 1980-2011 than those that were less diverse, and that declines in manufacturing did result in a movement of jobs from relatively high-wage to relatively low-wage industries and thus a decline in earnings per jobs.

There is increasing realisation that human health status in adulthood depends critically upon environmental conditions pertaining around the time of conception and during pregnancy. Poor maternal diet or adverse environmental conditions around the periconception period somehow induces the resultant embryo to adapt predictively in order to survive this level of stress for the whole of its life. However, if there is a mismatch between expectation and reality, where the conditions during later life are better than expected, things go wrong and the adult suffers a range of illnesses, including diabetes, heart disease, hypertension and stroke. Understanding the molecular signals that direct the early embryo to adopt appropriate adaptations to suit its future life would be extremely valuable. However, although it appears to be an ideal task for proteomic applications, there are technical, ethical and practical limitations to what can be achieved with the current framework of proteomic technology. Here, we review what has been achieved to date, explain some of the experimental problems and suggest some strategies for taking this field forward.

Rule learning comes in many forms, here we investigate a modified version of Separate and Conquer (SAC) learning to see if it improves the predictive performance of the induced predictive models. Our modified version of SAC has a hyperparameter which is used to specify the amount of examples that should not be removed from the induction. This selection is done at random and as a consequence the SAC algorithm will produce more and diverse rules, given the hyperparameter setting. The modified algorithm has been implemented in both an unordered single rule set setting as well as in an ensemble rule set setting. Both of these settings have been evaluated empirically on a number of datasets. The results show that in the single rule set setting, the modified version significantly improves the predictive performance, at the cost of more rules, which was expected. In the ensemble setting the combined method of bagging and the modified SAC algorithm did not perform as good as expected, while using only the modified SAC algorithm in ensemble setting performed better than expected.

Suppose you have one unit of stock, currently worth 1, which you must sell before time $T$. The Optional Sampling Theorem tells us that whatever stopping time we choose to sell, the expected discounted value we get when we sell will be 1. Suppose however that we are able to see $a$ units of time into the future, and base our stopping rule on that; we should be able to do better than expected value 1. But how much better can we do? And how would we exploit the additional information? The optimal solution to this problem will never be found, but in this paper we establish remarkably close bounds on the value of the problem, and we derive a fairly simple exercise rule that manages to extract most of the value of foresight., 19 pages

BACKGROUND AND OBJECTIVE: Like their adult counterparts, pediatric hospitals are increasingly at risk for financial penalties based on readmissions. Limited information is available on how the composition of a hospital’s patient population affects performance on this metric and hence affects reimbursement for hospitals providing pediatric care. We sought to determine whether applying different readmission metrics differentially affects hospital performance based on the characteristics of patients a hospital serves. METHODS: We performed a cross-sectional analysis of 64 children’s hospitals from the Children’s Hospital Association Case Mix Comparative Database 2012 and 2013. We calculated 30-day observed-to-expected readmission ratios by using both all-cause (AC) and Potentially Preventable Readmissions (PPR) metrics. We examined the association between observed-to-expected rates and hospital characteristics by using multivariable linear regression. RESULTS: We examined a total of 1 416 716 hospitalizations. The mean AC 30-day readmission rate was 11.3% (range 4.3%–19.6%); the mean PPR rate was 4.9% (range 2.9%–6.9%). The average 30-day AC observed-to-expected ratio was 0.96 (range 0.63–1.23), compared with 0.95 (range 0.65–1.23) for PPR; 59% of hospitals performed better than expected on both measures. Hospitals with higher volumes, lower percentages of infants, and higher percentage of patients with low income performed worse than expected on PPR. CONCLUSIONS: High-volume hospitals, those that serve fewer infants, and those with a high percentage of patients from low-income neighborhoods have higher than expected PPR rates and are at higher risk of reimbursement penalties.

Reinforcement learning models make use of reward prediction errors (RPEs), the difference between an expected and obtained reward. There is evidence that the brain computes RPEs, but an outstanding question is whether positive RPEs (“better than expected”) and negative RPEs (“worse than expected”) are represented in a single integrated system. An electrophysiological component, feedback related negativity, has been claimed to encode an RPE but its relative sensitivity to the utility of positive and negative RPEs remains unclear. This study explored the question by varying the utility of positive and negative RPEs in a design that controlled for other closely related properties of feedback and could distinguish utility from salience. It revealed a mediofrontal sensitivity to utility, for positive RPEs at 275–310 ms and for negative RPEs at 310–390 ms. These effects were preceded and succeeded by a response consistent with an unsigned prediction error, or “salience” coding.

Learning Analytics (LA) has been identified as one of the top technology trends in higher education today (Johnson et al., 2013). LA is based on the idea that datasets generated through normal admi...

There are many ways the plan could go wrong, but initially it has worked better than expected. If this positive course continues there will be far-reaching benefits.