Expectation Bias Research Articles

Meaningful Activities and Recovery (MA&R): the effect of a novel rehabilitation intervention among persons with psychiatric disabilities on activity engagement\u2014study protocol for a randomized controlled trial

BackgroundEngagement in activities meaningful to the individual may support the process of recovery in those with mental illness. Persons with psychiatric disabilities may reduce their engagement in meaningful activities to various degrees with possible fluctuations over time. We hypothesized that activity engagement can be altered when opportunities and support are offered at an individual and a group peer-based level. Evidence is lacking regarding mental health interventions that enable engagement in meaningful activities, and powered effect studies are warranted.MethodsWe propose an 8-month combined individual and group peer-based intervention, Meaningful Activities and Recovery (MA&R), and a study protocol for a multicentre two-armed parallel randomized controlled trial (RCT). The trial investigates the effects of MA&R in community mental health centres in Copenhagen and municipality services in Denmark. The trial will comprise 128 participants with psychiatric disabilities who will be randomized to one of two groups: (1) MA&R in addition to standard mental healthcare or (2) standard mental healthcare alone. The primary outcome is self-reported activity engagement, measured by Profiles of Engagement in People with Severe Mental Illness. Secondary outcomes are recovery, functioning and quality of life. Data will be collected at baseline and at follow-up at the end of the intervention.DiscussionThis study adds new knowledge to a field with limited evidence, i.e. the clinical effectiveness of rehabilitation interventions among people with psychiatric disabilities, directly targeting activity engagement. The pragmatic design, regarding in- and exclusion criteria and settings, may allow assessment of the intervention’s effect under real-life conditions. The randomization, adequate power and fidelity monitoring allow testing of the intervention’s efficacy. The multicentre study design increases the potential for implementation in various mental health settings if the findings are positive. As the nature of the intervention does not permit blinding of the participants or staff, it may increase the risk of expectancy and performance bias. This must be considered when interpreting the findings.Trial registrationClinicalTrials.gov NCT03963245. Registered on 29 May 2019

Psychiatric Interventions in Virtual Reality: Why We Need an Ethical Framework.

Recent improvements in virtual reality (VR) allow for the representation of authentic environments and multiple users in a shared complex virtual world in real time. These advances have fostered clinical applications including in psychiatry. However, although VR is already used in clinical settings to help people with mental disorders (e.g., exposure therapy), the related ethical issues require greater attention. Based on a thematic literature search the authors identified five themes that raise ethical concerns related to the clinical use of VR: (1) reality and its representation, (2) autonomy, (3) privacy, (4) self-diagnosis and self-treatment, and (5) expectation bias. Reality and its representation is a theme that lies at the heart of VR, but is also of specific significance in a clinical context when perceptions of reality are concerned, for example, during psychosis. Closely associated is the autonomy of VR users. Although autonomy is a much-considered topic in biomedical ethics, it has not been sufficiently discussed when it comes to applications of VR in psychiatry. In this review, the authors address the different themes and recommend the development of an ethical framework for the clinical use of VR.

Unsupervised classification of single-molecule data with autoencoders and transfer learning

Datasets from single-molecule experiments often reflect a large variety of molecular behaviour. The exploration of such datasets can be challenging, especially if knowledge about the data is limited and a priori assumptions about expected data characteristics are to be avoided. Indeed, searching for pre-defined signal characteristics is sometimes useful, but it can also lead to information loss and the introduction of expectation bias. Here, we demonstrate how Transfer Learning-enhanced dimensionality reduction can be employed to identify and quantify hidden features in single-molecule charge transport data, in an unsupervised manner. Taking advantage of open-access neural networks trained on millions of seemingly unrelated image data, our results also show how Deep Learning methodologies can readily be employed, even if the amount of problem-specific, ‘own’ data is limited.

Bias in Primary School Teachers’ Expectations of Students? A Study of General and Specific Bias Towards SES, Ethnicity and Gender

Based on teachers' knowledge base of students, teacher expectations of students' (future) abilities and potential are shaped, in which bias may occur. This study investigates data on multiple attributes of 535 sixth-grade Flemish students to find out (1) whether teacher expectations of students' cognitive and non-cognitive attributes, of teacher-student relationships, and of parental involvement in education are biased, and (2) whether teachers differ in their expectation bias towards SES, ethnicity, and gender. By means of correlation analysis, in which we compared teacher expectations with multiple measured student attributes (i.e., their achievement test scores and self-assessments), the results showed statistically significant, positive correlations for all the attributes included, indicating an overall correspondence between teacher expectations and students' measured attributes. At the same time, using an indicator of teacher expectation bias by subtracting the students' measured attributes from the corresponding teacher expectations, this study highlighted an expectation bias in terms of over- and underestimation by teachers, especially with respect to teachers' expectations of students cognitive attributes and parental involvement in education. Also, a specific bias in teacher expectations towards SES and gender was found.

Cultural conceptions of Women's labor pain and labor pain management: A mixed-method analysis.

We assess American cultural beliefs about labor pain and labor pain management, including stereotypical and disparate beliefs about labor pain of women from different racial groups. Understanding cultural beliefs about labor pain is critical as these beliefs influence experience, interpretation, and treatment of labor pain. We used an online survey with quantitative and qualitative questions about American labor pain beliefs. Participants were recruited and compensated using TurkPrime's Panels during the first week in August 2017 and the last week in May 2018. The completion rate was 76.86 percent (n=214). After screening using quality control items, the final sample included 200 respondents. Qualitative results indicate that 56.5 percent (n=113) of respondents have an accurate understanding of nociceptive/sensory drivers of labor pain, and 55.8 percent (n=63) of those respondents focused on the second stage of labor. However, only two respondents (1%) mentioned non-sensory (i.e., psychological) causes of labor pain - reflecting a lack of cultural knowledge of the biopsychosocial nature of pain. Categorical responses indicate almost all respondents (95%; n=190) believe women have a right to labor pain relief, and the majority believe labor pain has value (68%; n=136) and should be treated medically (87%; n=174). Quantitative results document stereotypical beliefs that women of color experience less labor pain than white women. Belief that there is value in experiencing labor pain and that pain should not be treated medically were both associated with greater racial disparities in beliefs about labor pain severity. Beliefs were not related to respondent sociodemographic identity, suggesting they are American cultural constructs. Future consideration of the influence of dominant American cultural beliefs about labor pain - including misunderstanding of the nature of labor pain and racial bias in expectations of labor pain - on individuals, norms, and structures is expected to improve quality of patient care.

Operating Cash Flows and Earnings Target Revision

We examine the extent to which current operating cash flows are incorporated in future earnings targets in executive compensation. Using target and actual compensation earnings per share (EPS) disclosed in proxy statements for large U.S. public companies, we find that revision of the following year’s EPS target is unrelated to current operating cash flows. Because of the positive association of operating cash flows with future earnings incremental to current earnings, failing to incorporate operating cash flows in target revision results in more achievable earnings targets for firms with higher operating cash flows. Interestingly, we find that the positive relationship between target achievability and operating cash flows is attributable to both expectation bias related to operating cash flows and contractual considerations designed to reward CEOs who deliver greater cash flows and to limit activities that sacrifice cash flows.

Validity aspects of behavioural measures to assess cows’ responsiveness towards humans

Different measures reflecting the cows’ behavioural responses towards humans are used for the assessment of the human–animal relationship (HAR). Besides the established avoidance distance (AD), different handling tests, such as the tolerance to tactile interaction (TTI), release behaviour after restraint (RB), and qualitative behaviour assessment (QBA) during a human–animal interaction are used. However, uncertainties still exist regarding the measures’ validity, vulnerability to confounders or risks of observer bias. These aspects are addressed in the current study. AD, TTI, RB, and QBA were investigated on a research farm regarding (1) their relationships with an expected HAR improvement due to rewarding human-animal contact (here: manual provision of concentrate), (2) potential confounding effects of lactation status (before/after calving), (3) or an expectedly aversive event of claw trimming, and (4) the occurrence of expectation bias. Concerning objectives 1–3, different samples of cows (n = 13–29 out of 102 in total) were assessed repeatedly and differences in behaviour before and after manual concentrate provision, calving, and claw trimming were analysed using paired Wilcoxon tests; for the latter blinded videos were used. For objective 4, both for non-blinded live and blinded video assessments it was tested separately, whether assessments before and after claw trimming differed. After a 6-days period of manual concentrate provision, cows had lower ADs (p = 0.013, n = 27), responded less fearfully in TTI (p = 0.045, n = 27) and QBA (p = 0.026, n = 14), and by tendency in RB (p = 0.052, n = 27), supporting the measures´ construct validity, i.e. that all of them reflect changes in the relationship to humans after the cows experienced rewarding routine interactions. Neither blinded assessments before and one day after claw trimming (p = 0.489–1.0, n = 29), nor assessments before and after calving (p = 0.244–1.0, n = 13) differed significantly, suggesting that single routine procedures and physiological changes around calving do not confound assessments. Numerically, in non-blinded QBA after claw trimming cows were assessed less fearful than in blinded, possibly because the observer tried to avoid bias. Nevertheless, non-blinded live assessments did not yield any significant differences between HAR measures before and after claw trimming (paired Wilcoxon: p = 0.151–1.0, n = 15–29).

Sensorimotor Expectations Bias Motor Resonance during Observation of Object Lifting: The Causal Role of pSTS.

Transcranial magnetic stimulation studies have highlighted that corticospinal excitability is increased during observation of object lifting, an effect termed "motor resonance." This facilitation is driven by movement features indicative of object weight, such as object size or observed movement kinematics. Here, we investigated in 35 humans (23 females) how motor resonance is altered when the observer's weight expectations, based on visual information, do not match the actual object weight as revealed by the observed movement kinematics. Our results highlight that motor resonance is not robustly driven by object weight but easily masked by a suppressive mechanism reflecting the correctness of weight expectations. Subsequently, we investigated in 24 humans (14 females) whether this suppressive mechanism was driven by higher-order cortical areas. For this, we induced "virtual lesions" to either the posterior superior temporal sulcus (pSTS) or dorsolateral prefrontal cortex (DLPFC) before having participants perform the task. Importantly, virtual lesion of pSTS eradicated this suppressive mechanism and restored object weight-driven motor resonance. In addition, DLPFC virtual lesion eradicated any modulation of motor resonance. This indicates that motor resonance is heavily mediated by top-down inputs from both pSTS and DLPFC. Together, these findings shed new light on the theorized cortical network driving motor resonance. That is, our findings highlight that motor resonance is not only driven by the putative human mirror neuron network consisting of the primary motor and premotor cortices as well as the anterior intraparietal sulcus, but also by top-down input from pSTS and DLPFC.SIGNIFICANCE STATEMENT Observation of object lifting activates the observer's motor system in a weight-specific fashion: Corticospinal excitability is larger when observing lifts of heavy objects compared with light ones. Interestingly, here we demonstrate that this weight-driven modulation of corticospinal excitability is easily suppressed by the observer's expectations about object weight and that this suppression is mediated by the posterior superior temporal sulcus. Thus, our findings show that modulation of corticospinal excitability during observed object lifting is not robust but easily altered by top-down cognitive processes. Finally, our results also indicate how cortical inputs, originating remotely from motor pathways and processing action observation, overlap with bottom-up motor resonance effects.

Quantifying similarity for spectra with a large number of overlapping transitions: Examples from soft X-ray spectroscopy

Theoretical simulations are frequently used to assign electronic and geometric structure from spectral fingerprints. However, such assignments are prone to expectation bias. Bias can be reduced by using numerical measures of the similarity between calculated and experimental spectra. However, the commonly used point-wise comparisons cannot handle larger deviations in peak position. Here a weighted cross-correlation function is used to evaluate similarity scores for soft X-ray spectra of first-row transition metals. These spectra consist of hundreds of overlapping resonances, which makes spectral decomposition difficult. They are also challenging to model, leading to significant errors in both peak position and intensity. It is first shown how the choice of weight-function width can be related to the modeling errors. The method is then applied to evaluate the sensitivity of multiconfigurational wavefunction and charge-transfer multiplet simulations to model choices. The approach makes it possible to assess the reliability of assignments from spectral fingerprinting.

Neural correlates of negative expectancy and impaired social feedback processing in social anxiety.

Social anxiety has been associated with abnormalities in cognitive processing in the literature, manifesting as various cognitive biases. To what extent these biases interrupt social interactions remains largely unclear. This study used the Social Judgment Paradigm that could separate the expectation and experience stages of social feedback processing. Event-related potentials (ERPs) in these two stages were recorded to detect the effect of social anxiety that might not be reflected by behavioral data. Participants were divided into two groups according to their social anxiety level. Participants in the high social anxiety (HSA) group were more likely to predict that they would be socially rejected by peers than did their low social anxiety (LSA) counterparts (i.e. the control group). Compared to the ERP data of the LSA group, the HSA group showed: (a) a larger P1 component to social cues (peer faces) prior to social feedback presentation, possibly indicating an attention bias; (b) a difference in feedback-related negativity amplitude between unexpected social acceptance and unexpected social rejection, possibly indicating an expectancy bias; and (c) a diminished sensitivity of the P3 amplitude to social feedback valence (be accepted/be rejected), possibly indicating an experience bias. These results could help understand the cognitive mechanisms that comprise and maintain social anxiety.

The developing predictive brain: How implicit temporal expectancy induced by local and global prediction shapes action preparation across development.

Human behavior is continuously shaped not just as a function of explicitly responding to external world events but also by internal biases implicitly driven by the capacity to extract statistics from complex sensory patterns. Two possible sources of predictability engaged to generate and update temporal expectancy are the implicit extraction of either local or global statistical contingencies in the events' temporal structure. In the context of action preparation the local prediction has been reported to be stable from the age of 6. However, there is no evidence about how the ability to extract and use global statistical patterns to establish temporal expectancy changes across development. Here we used a new, child-friendly reaction time task purposely designed to investigate how local (within-trial expectancy bias) and global (between-block expectancy bias) prediction interplay to generate temporal expectancy and consequently shape action preparation in young (5- to 6-year-old), middle-aged (7- to 8-year-old) and old (9- to 10-year-old) typically developing children. We found that while local temporal prediction showed stable developmental trajectories, the ability to use a global rule to action preparation in terms of both accuracy and speed becomes stable after the age of seven. These findings are discussed by adopting a neuroconstructivist-inspired theoretical account, according to which the developmental constraints on learning from hierarchically nested levels of sensory complexity may constitute a necessary prerequisite for mastering complex domains.

Effect of heuristic anchoring and adjustment, and optimism bias, in stock market forecasts

Stock market forecasting is an important and challenging process that influences investment decisions. This paper presents an experimental design that aims to measure the influence of the anchoring and adjustment heuristic and optimism bias in these forecasts. The study was conducted using information from the S&P MILA Pacific Alliance Select financial index; this was presented to 670 students from the cities of Concepción (Chile), Cali (Colombia), and Lima (Peru). Data was collected and presented through an instrument that asked participants to make a forecast judgment of the said financial index, based on the presented graphics, representing a year, a month, a week, and the last closing value of the index. Thus, it was possible to measure the influence of the anchor and adjustment heuristic in order to establish whether the presence of an initial value affected the financial forecast. Similarly, the study sought to determine whether the judgment issued was biased toward an optimistic or pessimistic position, thereby proving the presence of an error or expectation bias, known as optimism bias. The results were analyzed using the least squares method, and the data panel confirmed that the anchoring and adjustment heuristic influences the forecast of the financial index used in the study. Similarly, the presence of optimism bias in the cognitive process of forecasting in finance was inferred.

Sex and gender impacts on the behavioural presentation and recognition of autism.

With increasing awareness of potential differences of autism presentation in nonmale versus male individuals, this review summarizes the rapidly evolving literature on sex and gender impacts on autism across nosology, behavioural presentation, developmental change and contextual recognition biases. Most studies have not differentiated sex versus gender impacts. Regarding behavioural presentation, measurement invariance across sex/gender was found in several standard measures. On this basis, diagnosed females overall showed lower restricted/repetitive behaviour/interests/activities (RRBI) than males, with small and variable effects depending on age, developmental level and kinds of RRBI. Differences insufficiently captured by standard measures may include autistic females displaying female-gender-typical narrow interests, higher social attention, linguistic abilities, motivation for friendship and more camouflaging than autistic males. Regarding developmental change, diagnosed young girls were more likely to have better cognitive development, less intense autistic symptoms and reduction of symptoms over time. Difficulties in adaptive functioning and social challenges, however, may emerge more for females in adolescence. Regarding diagnosis, general expectancy biases and gender-stereotypes may impede timely recognition of autism in females. Appreciating the multilevel sex and gender impacts on presentation, development, and diagnosis is key to sex-equitable and gender-equitable care for autistic individuals. A holistic approach to understanding the person in the contexts of sex and gender is essential for timely and accurate diagnosis and support.

Repeatability of flatfish reflex impairment assessments based on video recordings

Using measures of reflex impairment and injury to quantify an aquatic organism's vitality have gained popularity as survival predictors of discarded non-target fisheries catch. To evaluate the robustness of this method with respect to 'rater' subjectivity, we tested inter- and intra-rater repeatability and the role of 'expectation bias'. From video clips, multiple raters determined impairment levels of four reflexes of beam-trawled common sole (Solea solea) intended for discard. Raters had a range of technical experience, including veterinary students, practicing veterinarians, and fisheries scientists. Expectation bias was evaluated by first assessing a rater's assumption about the effect of air exposure on vitality, then comparing their reflex ratings of the same fish, once when the true air exposure duration was indicated and once when the time was exaggerated (by either 15 or 30 min). Inter-rater repeatability was assessed by having multiple raters evaluate those clips with true air exposure information; and intra- and inter-rater repeatability was determined by having individual raters evaluate a series of duplicated clips, all with true air exposure. Results indicate that inter- and intra-rater repeatability were high (intra-class correlation coefficients of 74% for both), and were not significantly affected by background type nor expectation bias related to assumed impact from prolonged air exposure. This suggests that reflex impairment as a metric for predicting fish survival is robust to involving multiple raters with diverse backgrounds. Bias is potentially more likely to be introduced through subjective reflexes than raters, given that consistency in scoring differed for some reflexes based on rater experience type. This study highlights the need to provide ample training for raters, and that no prior experience is needed to become a reliable rater. Moreover, before implementing reflexes in a vitality study, it is important to evaluate whether the determination of presence/absence is subjective.

Post hoc analysis of a randomised, placebo-controlled, active-reference 6-week study of brexpiprazole in acute schizophrenia.

We provide a closer look at the result of a randomised, placebo-controlled, active-reference (quetiapine XR), flexible-dose, 6-week study of brexpiprazole in schizophrenia, which did not meet its primary endpoint - change from baseline in Positive and Negative Syndrome Scale (PANSS) total score. We also investigate potential expectancy bias from the well-known side-effect profile of the active reference that could have affected the study outcome. Pre-specified sensitivity analyses of the primary end point were performed using analysis of covariance (ANCOVA) last observation carried forward (LOCF) and observed cases (OC). Post hoc analyses of change from baseline in PANSS total score were performed using the mixed model for repeated measures approach with treatment groups split by having typical adverse events with potential for functional unblinding, for example, somnolence, increase in weight, dizziness, dry mouth and sedation. Pre-specified sensitivity analyses showed separation from placebo for brexpiprazole at week 6: LOCF, ANCOVA: -4.3 [95% CI (-8.0, -0.5), p = 0.0254]. OC, ANCOVA: -3.9 [95% CI (-7.3, -0.5), p = 0.0260]. Patients treated with brexpiprazole experiencing typical adverse events with potential for functional unblinding before or at Week 2 had a least square (LS) mean PANSS change of -29.5 (improvement), with a difference in change from baseline to Week 6 in PANSS total score between brexpiprazole and placebo of -13.5 [95% CI (-23.1, -4.0), p = 0.0057], and those who did not had an LS mean change of -18.9 and a difference between brexpiprazole and placebo of -2.9 [95% CI (-7.2, 1.4), p = 0.1809]. Pre-specified sensitivity analyses showed separation from placebo for brexpiprazole at Week 6. A post hoc analysis suggested a potential confounding of efficacy rating towards symptom improvement in patients who experience known side effects of quetiapine XR.

Subjective Expectations, Social Security Benefits, and the Optimal Path to Retirement

Americans face the challenges of retirement with varying degrees of preparation. Evidence indicates that that many individuals may not be making the best possible choices with respect to their Social Security and retirement savings. We assess the subjective expectations of non-retirees and find that they have sizable biases and uncertainty about future retirement benefits. This uncertainty and the level of subjective expectations can affect workers’ wealth accumulation and retirement readiness. We build on these observations and combine unique survey data with a life-cycle optimization model to measure the role of Social Security literacy, subjective expectations about retirement benefits, and behavioral traits as determinants of life-cycle savings decisions and welfare. The goal of this project is to better understand the role of retirement expectations as determinants of savings decisions and retirement income. We forecast future benefits and measure the bias in expectations. We find heterogeneity in the direction of the expectation bias: Men and those with low levels of uncertainty about retirement benefits are less likely to overestimate their future retirement benefits, hence are more likely to save more and reach retirement better prepared. We find that these biases in subjective expectations translate into suboptimal asset accumulation and welfare losses.

Overreaction in Expectations: Evidence and Theory

We investigate biases in expectations across different settings through a large-scale randomized experiment where participants forecast stable stochastic processes. The experiment allows us to control forecasters’ information sets as well as the data generating process, so we can cleanly measure biases in beliefs. We find that forecasts display significant overreaction to the most recent observation. Moreover, overreaction is especially pronounced for less persistent processes and longer forecast horizons. We also find that commonly-used expectations models do not easily account for these variations in the degree of overreaction across different settings. To explain the observed patterns of overreaction, we develop a tractable model of expectations formation with costly information processing. Our model closely fits the empirical findings and generates additional predictions that we confirm in the data.

Man vs. Machine Learning: The Term Structure of Earnings Expectations and Conditional Biases

We introduce a real-time measure of conditional biases in firms' earnings forecasts. The measure is defined as the difference between analysts' expectations and a statistically optimal unbiased machine-learning benchmark. Analysts' conditional expectations are, on average, biased upwards, and the bias increases in the forecast horizon. These biases are associated with negative cross-sectional return predictability, and the short legs of many anomalies contain firms with excessively optimistic earnings. Further, managers of companies with the greatest upward-biased earnings forecasts are more likely to issue stocks. Commonly-used linear earnings models do not work out-of-sample and are inferior to those provided by analysts.

Computational Modeling of the Dynamics of Human Trust During Human–Machine Interactions

We developed an experiment to elicit human trust dynamics in human-machine interaction contexts and established a quantitative model of human trust behavior with respect to these contexts. The proposed model describes human trust level as a function of experience, cumulative trust, and expectation bias. We estimated the model parameters using human subject data collected from two experiments. Experiment 1 was designed to excite human trust dynamics using multiple transitions in trust level. Five hundred and eighty-one individuals participated in this experiment. Experiment 2 was an augmentation of Experiment 1 designed to study and incorporate the effects of misses and false alarms in the general model. Three hundred and thirty-three individuals participated in Experiment 2. Beyond considering the dynamics of human trust in automation, this model also characterizes the effects of demographic factors on human trust. In particular, our results show that the effects of national culture and gender on trust are significant. For example, U.S. participants showed a lower trust level and were more sensitive to misses as compared with Indian participants. The resulting trust model is intended for the development of autonomous systems that can respond to changes in human trust level in real time.

Why diversity and expectations matter

AbstractThis article was delivered in a session entitled Insights from a behavioral lens: why perceptions and diversity matter. In the article, I ask whether a diverse academic workforce is an asset to a University, and more generally to society, and conclude that it is. Although this conclusion is based on empirical data from US universities, the message is universal. Even when correcting for years of experience, rank, and nature of appointment and women's work‐life situation, there is still a negative expectation bias, whereby women and minority candidates are not expected to be as good as male researchers (a bias that also exists in the case of the appointment of female Chief Executive Officers). On the other hand, more women and minority appointments increase the productivity of women students.