Academic literature on the topic 'Diagnostic Expectations'

We present the case for the centrality of overreaction in expectations for addressing important challenges in finance and macroeconomics. First, non-rational expectations by market participants can be measured and modeled in ways that address some of the key challenges posed by the rational expectations revolution, most importantly the idea that economic agents are forward-looking. Second, belief overreaction can account for many long-standing empirical puzzles in macro and finance, which emphasize the extreme volatility and boom-bust dynamics of key time series, such as stock prices, credit, and investment. Third, overreaction relies on psychology and is disciplined by survey data on expectations. This suggests that relaxing the assumption of rational expectations is a promising strategy, helps theory and evidence go together, and promises a unified view of a great deal of data.

We study the rationality of individual and consensus forecasts of macroeconomic and financial variables using the methodology of Coibion and Gorodnichenko (2015), who examine predictability of forecast errors from forecast revisions. We find that individual forecasters typically overreact to news, while consensus forecasts under-react relative to full-information rational expectations. We reconcile these findings within a diagnostic expectations version of a dispersed information learning model. Structural estimation indicates that departures from Bayesian updating in the form of diagnostic overreaction capture important variation in forecast biases across different series, yielding a belief distortion parameter similar to estimates obtained in other settings. (JEL C53, D83, D84, E13, E17, E27, E47)

In healthcare service, the customer feedback is often incomplete unless the unexpressed expectations are captured at the right time. These latent feelings and opinions are the ‘hidden expectations’ which are the quality indicators of the service offered. This short communication paper describes a couple of techniques for elicitation of hidden expectations of customers in the context of healthcare services. As an illustration, the paper depicts the application of these techniques for identification and prioritization of hidden expectations at a diagnostic center. Any organization in healthcare service sector could employ these techniques quickly and conveniently to improve quality of service thereby enhancing customer satisfaction. Keywords: Elicitation, Customer satisfaction, Hidden expectation, MoSCoW, Healthcare.

Purpose – Guidelines stating maximum waiting times fail to take cancer patients’ expectations into account. Therefore, the purpose of this paper is to assess patients’ expectations and experiences with their waiting time at a fast-track clinic. Design/methodology/approach – Patients were selected using a purposeful sampling strategy and were interviewed four times: before the visit; one day after; two weeks after the visit; and one week after starting treatment. Interviews were audiotaped and independently coded by two researchers. Findings – All patients (n=9) preferred a short waiting time before the first visit; they feared that their disease would spread and believed that cancer warrants priority treatment. Six patients experienced the waiting time as short, one had no expectations and two felt they waited longer than expected; three patients changed this evaluation during the study. Six patients received treatment – four preferred to wait before treatment and two wanted to start treatment immediately. Reasons to wait included putting one’s affairs in order, or needing to adjust to the diagnosis. Practical implications – Cancer patients prefer a short waiting time before the first visit but have different expectations and needs regarding waiting time before treatment. Ideally, their expectations are managed by their treating physician to match waiting time reality. Originality/value – This is the first study to assess cancer patients’ waiting time experiences and how these experiences change over time. This study paves the way for establishing a framework to better assess patient satisfaction with oncology care waiting time. An important aspect, is managing patients’ expectations.

Abstract Introduction. General practitioner (GP) plays an important role in the health care system as he is the first person that a patient turns to with his health related problem. The crucial role of the primary health care system is to control risk factors contributing to civilization diseases such as cancer, diabetes or cardiovascular diseases. Aim. The aim of the research was the assessment of the selected aspects of patients’ satisfaction with a GP’s care. Conducted study provided answers to questions about the level of patient’s satisfaction, his expectations and needs in the field of doctor’s care within the primary health care system. Material and methods. Diagnostic poll was used as a method to study public opinion. The poll was based on the research technique in the form of the original questionnaire consisting of 23 closed-ended questions. Study group consisted of 99 primary health care patients from lubelskie voivodship. Results. The majority of the studied group assessed the quality of general practitioners’ services both in cities and rural areas as high. Respondents declared their satisfaction with the availability of diagnostic tests (73%), quality of information about health condition and treatment provided by the doctor (80%), information about how the medicine should be taken and about further treatment (65%) and respect for privacy and dignity (82%). Minority of the researched group was dissatisfied with the quality of general practitioner’s services mainly because of the limited access to diagnostic tests (27%), low quality of information provided by the doctor about method of taking medicine (35%), short time of the doctor’s visit (38%), suggested method of treatment (36%), disrespect for privacy and dignity of a patient (18%) and limited access to medical documentation (24%). Conclusions. There is a need to implement actions that will increase patients’ satisfaction with the medical services provided by general practitioners, especially in the following fields: length of the doctor’s visit, quality of information provided by the doctor, improvement in the patient – doctor relation, full access to medical documentation and promotion of health by doctors.

OBJECTIVE Patients undergoing spine surgery generally have high expectations for improvement postoperatively. Little is known about how these expectations are affected by the diagnosis. The purpose of this study was to examine whether preoperative expectations differ based on diagnostic pathoanatomical patterns in elective spine surgery patients. METHODS Patients with common degenerative cervical/lumbar pathology (lumbar/cervical stenosis, lumbar spondylolisthesis, and cervical/lumbar disc herniation) who had given their consent for surgery were analyzed using the Canadian Spine Outcomes and Research Network (CSORN). Patients reported the changes they expected to experience postoperatively in relation to 7 separate items using a modified version of the North American Spine Society spine questionnaire. Patients were also asked about the most important item that would make them consider the surgery a success. Sociodemographic, lifestyle, and clinical variables were also collected. RESULTS There were 3868 eligible patients identified within the network for analysis. Patients with lumbar disc herniation had higher expectations for relief of leg pain compared with stenosis and lumbar degenerative spondylolisthesis cohorts within the univariate analysis. Cervical stenosis (myelopathy) patients were more likely to rank general physical capacity as their most important expectation from spine surgery. The multinomial regression analysis showed that cervical myelopathy patients have lower expectations for relief of arm or neck pain from surgery (OR 0.54, 0.34–0.88; p < 0.05). Patient factors, including age, symptoms (pain, disability, depression), work status, and lifestyle factors, were significantly associated with expectation, whereas the diagnoses were not. CONCLUSIONS Patients with degenerative spinal conditions consenting for spine surgery have high expectations for improvement in all realms of their daily lives. With the exception of patients with cervical myelopathy, patient symptoms rather than diagnoses had a more substantial impact on the dimensions in which patients expected to improve or their most important expected change. Determination of patient expectation should be individualized and not biased by pathoanatomical diagnosis.

Abstract. This work examines different conceptions of land surface model benchmarking and the importance of internationally standardized evaluation experiments that specify data sets, variables, metrics and model resolutions. It additionally demonstrates how essential the definition of a priori expectations of model performance can be, based on the complexity of a model and the amount of information being provided to it, and gives an example of how these expectations might be quantified. Finally, the Protocol for the Analysis of Land Surface models (PALS) is introduced – a free, online land surface model benchmarking application that is structured to meet both of these goals.

This study explores the expectations and experiences of newly qualified diagnostic radiographers during their transition into practice. This is a short, but important period in a professional’s career as he or she adjusts from being supervised to becoming an autonomous practitioner. It is during this period that they enhance their competence and confidence. This was a longitudinal study using interpretative phenomenological analysis methodology. Data was gathered from four students who participated in a focus group. This informed semi structured interviews with a further eight students who were interviewed prior to starting work and three times over the following twelve months. All the participants had undertaken a BSc (Hons) Diagnostic Radiography at the same higher education institution. Four main themes were generated from the data; experience, fitting in, identity and supporting the transition. A high proportion of clinical education, balanced with theoretical input had developed the participants to be autonomous, reflective practitioners. However, they did find it difficult when required to take responsibility for, and assess students. During the transition process their awareness of departmental culture increased as did their professional identity. The participants wanted tailored support and found that they could ask any colleagues for advice and support and found peer support useful. An excellent practice of organised scaffolding support was identified which can be adapted for use in different areas. This helped the participants build experience and confidence. This study brings to light the experiences of newly qualified diagnostic radiographers. The findings are open to theoretical generalizability and raise issues that may be used by academic staff in the preparation of students and managers who support newly qualified staff members. These include considering how to train and educate student radiographers in supervisory skills, how to build confidence in areas where it is difficult to gain clinical experience, and facilitating peer support in imaging departments.

Nowadays, behavioral economics has lured the attention of an increasing number of economists. This is due to the recent financial crisis of 2007-09 that forced economists to realize that psychological biases could modifiy rational equilibria since, on avarage, arbitrageurs are not always able to bring back the economy to the rational path. Taking into account limits of arbitrage and limits in cognitive capacities, an economy can be vulnerable to the sensitiveness of agents to new information. If this sensitiveness is of a certain size, such that arbitrageurs behavior is negligible, then sensitive agents (also called local thinkers in the following essays) can enter into the formation of an equilibrium modifying its dynamics.

This multiple-case study examines the explicit and implicit assumptions of six veteran calculus instructors from three types of educational institutions, comparing and contrasting their views on the iteration of conceptual understanding and procedural fluency of pre-calculus topics. There were three components to the research data recording process. The first component was a written survey, the second component was a “think-aloud” activity of the instructors analyzing the results of a function diagnostic instrument administered to a calculus class, and for the third component, the instructors responded to two quotations. As a result of this activity, themes were found between and among instructors at the three types of educational institutions related to their expectations of their incoming students' prior knowledge of pre-calculus topics related to functions. Differences between instructors of the three types of educational institutions included two identifiable areas: (1) the teachers' expectations of their incoming students and (2) the methods for planning instruction. In spite of these differences, the veteran instructors were in agreement with other studies' findings that an iterative approach to conceptual understanding and procedural fluency are necessary for student understanding of pre-calculus concepts.
Ph.D.
Doctorate
Dean's Office, Education
Education and Human Performance
Education; Math Education

Women may present with slightly more subtle symptoms and could be more likely to only be diagnosed with Autism Spectrum Disorder (ASD) during adulthood, which may have implications for the way in which they view themselves, and for potential relationships. This dissertation explores the experience of intimate relationships of women who have been diagnosed with ASD in adulthood. Semi-structured interviews were used to interview eight participants. The data was transcribed and analysed using the Interpretative Phenomenological Analysis (IPA) method.

The medical laboratory science (MLS) profession is in need for published molecular diagnostics competency-based standards and curriculum. To assess their expectations of new MLS graduates, professionals performing and supervising performance of clinical molecular assays were surveyed to rate the importance of relevant cognitive and psychomotor learning objectives. A modified, asynchronous, iterative online Delphi process was utilized for assessment of consensus on the importance of the objectives. The survey was delivered through online REDCap application. Program directors of 221 MLS programs accredited by the National Accrediting Agency for Clinical Laboratory Science (NAACLS) were asked to forward the first Delphi survey to target participants at their affiliated clinical sites. Ninety-four experts submitted complete surveys, including 88 who provided email addresses, indicating agreement to participate in future Delphi rounds. Most of the participants were certified by ASCP or NCA (81.9%), had over 10 years of laboratory experience (76.6%), and worked in a hospital setting (43.6%). The reliability of the surveys, assessed using Cronbach’s alpha, was 0.96 and 0.97. In the second survey, the objectives assigned low importance by the majority were removed; and others, assigned high importance were expanded. Respondents were given the opportunity to confirm or change their opinion on the objectives after reviewing quantitative results and narrative comments collected in the preceding survey. Upon completion of the Delphi process, 25 essential items were identified as necessary for inclusion in the entry-level MLS curriculum. These concepts and objectives focused on basic molecular biology principles and general molecular laboratory operations, including practical knowledge of techniques designed to maintain specimen integrity and intense theoretical background of the polymerase chain reaction, as well as comprehension of the principles of laboratory assays designed for pathogens most commonly tested for using molecular methods. In this study, the investigator also provided information on the preferred number of contact hours devoted to each group of the identified essential items. The goal of creating the list of essential concepts and objectives was to share it with MLS educators, the NAACLS and the provider of MLS certification exam, the American Society for Clinical Pathology Board of Certification (ASCP-BOC), to contribute to the existing exam content guidelines.

Orientador: Filidor Edilfonso Vilca Labra
Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Matematica, Estatistica e Computação Cientifica
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Resumo: A classe de modelos Birnbaum-Saunders (BS) surgiu em problemas de fadiga dos materiais (que 'e um dano estrutural que ocorre quando um material é exposto a estresse e tensão). Nos últimos tempos, este modelo tem sido aplicado em áreas fora do contexto de fadiga dos materiais e engenharia, como por exemplo, em ciências da saúde, ambiental, florestal, demográficas, atuarial, financeira, entre outras. Tendo em vista que a distribuição BS tem a propriedade de descrever processos de degradação acumulativa. Neste trabalho, apresentamos um estudo do modelo BS baseado na distribuição skewnormal. Como subproduto consideramos o modelo de regressão linear log-Birnbaum-Saunders (log-BS). Para obter as estimativas de máxima verossimilhança usamos o algoritmo EM. Além disso, apresentamos um estudo de análise de influência global e local, através da metodologia de Zhu e Lee (2001) para dados incompletos. Ilustramos a metodologia proposta com dados encontrados na literatura.
Abstract: The class of models Birnbaum-Saunders (BS) appeared in problems of fatigue of materials (which is a structural damage that occurs when a material is exposed to stress and tension). Recently, this model has been applied in areas outside the context of fatigue of materials and engineering, for example in health sciences, environmental, forestry, demographic, actuarial, financial, among others. As the BS distribution has the property to describe cumulative degradation processes. In this work we present a study of the BS model based on Skew-normal distribution. As a byproduct consider the model of linear regression log-Birnbaum-Saunders (log-BS). To obtain estimates of maximum likelihood we use the EM algorithm. Furthermore, we present a study of the analysis of global and local influence, through the method of Zhu and Lee (2001) to incomplete data. Illustrate the proposed methodology with data found in literature.
Mestrado
Inferencia
Mestre em Estatística

Les réseaux de télécommunication doivent être fiables et robustes pour garantir la haute disponibilité des services. Les opérateurs cherchent actuellement à automatiser autant que possible les opérations complexes de gestion des réseaux, telles que le diagnostic de pannes.Dans cette thèse nous nous sommes intéressés au diagnostic automatique de pannes dans les réseaux d'accès optiques de l'opérateur Orange. L'outil de diagnostic utilisé jusqu'à présent, nommé DELC, est un système expert à base de règles de décision. Ce système est performant mais difficile à maintenir en raison, en particulier, du très grand volume d'informations à analyser. Il est également impossible de disposer d'une règle pour chaque configuration possible de panne, de sorte que certaines pannes ne sont actuellement pas diagnostiquées.Dans cette thèse nous avons proposé une nouvelle approche. Dans notre approche, le diagnostic des causes racines des anomalies et alarmes observées s'appuie sur une modélisation probabiliste, de type réseau bayésien, des relations de dépendance entre les différentes alarmes, compteurs, pannes intermédiaires et causes racines au niveau des différents équipements de réseau. Ce modèle probabiliste a été conçu de manière modulaire, de façon à pouvoir évoluer en cas de modification de l'architecture physique du réseau.Le diagnostic des causes racines des anomalies est effectué par inférence, dans le réseau bayésien, de l'état des noeuds non observés au vu des observations (compteurs, alarmes intermédiaires, etc...) récoltées sur le réseau de l'opérateur. La structure du réseau bayésien, ainsi que l'ordre de grandeur des paramètres probabilistes de ce modèle, ont été déterminés en intégrant dans le modèle les connaissances des experts spécialistes du diagnostic sur ce segment de réseau. L'analyse de milliers de cas de diagnostic de pannes a ensuite permis de calibrer finement les paramètres probabilistes du modèle grâce à un algorithme EM (Expectation Maximization).Les performances de l'outil développé, nommé PANDA, ont été évaluées sur deux mois de diagnostic de panne dans le réseau GPON-FTTH d'Orange en juillet-août 2015. Dans la plupart des cas, le nouveau système, PANDA, et le système en production, DELC, font un diagnostic identique. Cependant un certain nombre de cas sont non diagnostiqués par DELC mais ils sont correctement diagnostiqués par PANDA. Les cas pour lesquels les deux systèmes émettent des diagnostics différents ont été évalués manuellement, ce qui a permis de démontrer dans chacun de ces cas la pertinence des décisions prises par PANDA
Telecommunication networks must be reliable and robust to ensure high availability of services. Operators are currently searching to automate as much as possible, complex network management operations such as fault diagnosis.In this thesis we are focused on self-diagnosis of failures in the optical access networks of the operator Orange. The diagnostic tool used up to now, called DELC, is an expert system based on decision rules. This system is efficient but difficult to maintain due in particular to the very large volume of information to analyze. It is also impossible to have a rule for each possible fault configuration, so that some faults are currently not diagnosed.We proposed in this thesis a new approach. In our approach, the diagnosis of the root causes of malfunctions and alarms is based on a Bayesian network probabilistic model of dependency relationships between the different alarms, counters, intermediate faults and root causes at the level of the various network component. This probabilistic model has been designed in a modular way, so as to be able to evolve in case of modification of the physical architecture of the network. Self-diagnosis of the root causes of malfunctions and alarms is made by inference in the Bayesian network model of the state of the nodes not observed in view of observations (counters, alarms, etc.) collected on the operator's network. The structure of the Bayesian network, as well as the order of magnitude of the probabilistic parameters of this model, were determined by integrating in the model the expert knowledge of the diagnostic experts on this segment of the network. The analysis of thousands of cases of fault diagnosis allowed to fine-tune the probabilistic parameters of the model thanks to an Expectation Maximization algorithm. The performance of the developed probabilistic tool, named PANDA, was evaluated over two months of fault diagnosis in Orange's GPON-FTTH network in July-August 2015. In most cases, the new system, PANDA, and the system in production, DELC, make an identical diagnosis. However, a number of cases are not diagnosed by DELC but are correctly diagnosed by PANDA. The cases for which self-diagnosis results of the two systems are different were evaluated manually, which made it possible to demonstrate in each of these cases the relevance of the decisions taken by PANDA

This thesis examines how psychosocial factors influence the report of persistent symptoms after mild traumatic brain injury. Using quasi-experimental methods, the research program demonstrates how factors unrelated to trauma-induced physiological brain damage can contribute to persistent symptoms after a mild traumatic brain injury. The results of this thesis highlight the possibility that outcome from mild traumatic brain injury could be improved by targeting psychosocial factors.

Orientadores: Filidor E. Vilca Labra, Victor Hugo Lachos Davila
Tese (doutorado) - Universidade Estadual de Campinas, Instituto de Matematica, Estatistica e Computação Cientifica
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Resumo: Neste trabalho, estudamos alguns aspectos de estimação e diagnóstico de influência local (Cook, 1986) em modelos lineares, especificamente no modelo de regressão linear, no modelo linear misto e no modelo de Grubbs sob a classe de distribuições assimétricas misturas de escala skew-normal (SMSN) (Branco & Dey, 2001). Esta família de distribuições tem como membros particulares as versões simétrica e assimétrica das distribuições t-Student, slash e normal contaminada, todas com caudas mais pesadas que a distribuição normal, A estimação dos parâmetros será via o algoritmo EM (Dempster et al, 1977) e a análise de diagnóstico será baseada na técnica de dados aumentados que usa a esperança condicional da função log-verossimilhança dos dados aumentados (função-Q) proveniente do algoritmo EM, como proposta por Zhu & Lee (2001) e Lee & Xu (2004). Assim, pretendemos contribuir positivamente para desenvolvimento da área dos modelos lineares, estendendo alguns resultados encontrados na literatura, por exemplo, Pinheiro et al (2001), Arellano-Valle et aí (2005), Osório (2006), Montenegro et al (2009a), Montenegro et al (2009b), Osório et al (2009), Lachos et aí (2010), entre outros.
Abstract: In this work, we study some aspects of the estimation and the diagnostics based on the local influence (Cook, 1986) in linear models under the class of scale mixtures of the skew-normal (SMSN) distribution, as proposed by Branco & Dey (2001). Specifically, we consider the linear regression model, the linear mixed model and the Grubbs' measurement error model. The SMSN class of distributions provides a useful generalization of the normal and the skew-normal distributions since it covers both the asymmetric and heavy-tailed distributions such as the skew-t, the skew-slash, the skew-contaminated normal, among others. The local influence analysis will be based on the conditional expectation of the complete-data log-likelihood function (function-Q) from the EM algorithm (Dempster et al, 1977) ), as proposed by Zhu & Lee (2001) and Lee & Xu (2004). We believe that the results of our work have contributed positively to the development of this area of linear models, since we have extended some results from the works of Pinheiro et al. (2001), Arellano-Valle et al. (2005), Osorio (2006), Montenegro et al. (2009a), Montenegro et al. (2009b), Osorio et al. (2009), Lachos et al. (2010), among others.
Doutorado
Método Estatístico
Doutor em Estatística

This chapter will summarize contemporary models and methods used for the assessment of adaptive behavior functioning in children and adolescents. This chapter will also emphasize how to best use such assessment information for diagnostic and eligibility purposes and in developing interventions and support plans. We will review the use of traditional, norm-referenced adaptive behavior assessment tools as well as what will be referred to as “supplemental methods,” including the direct observation of adaptive skill functioning. The assessment of adaptive behavior with respect to developmental expectations, cultural expectations, systems of care, and legislation will also be discussed. Lastly, case studies will be presented to illustrate the usefulness of these methods in assessing individuals and planning effective interventions and services.

This chapter will summarize contemporary models and methods used for the assessment of adaptive behavior functioning in children and adolescents. This chapter will also emphasize how to best use such assessment information for diagnostic and eligibility purposes and in developing interventions and support plans. We will review the use of traditional, norm-referenced adaptive behavior assessment tools as well as what will be referred to as “supplemental methods,” including the direct observation of adaptive skill functioning. The assessment of adaptive behavior with respect to developmental expectations, cultural expectations, systems of care, and legislation will also be discussed. Lastly, case studies will be presented to illustrate the usefulness of these methods in assessing individuals and planning effective interventions and services.

The proportion of children who are deaf or hard of hearing and also have other medical, neurodevelopmental, behavioral, or psychosocial conditions is increasing. Prevalence estimates run as high as 50% to 70%. The shifting complexity challenges not only the learners but also the teachers, administrators, and policymakers responsible for the education of deaf students. Documentation of diagnostic profiles contributes to understanding the learning profile of deaf students with concomitant conditions. This may also inform policy decisions, programmatic design, calibration of parental expectations, and implementation of effective teaching strategies. Through illustrative case examples, this chapter explores the principles of differential diagnosis and the implications of various conditions. Topics covered include genetic syndromes, vestibular dysfunction, intrauterine viral infection with associated congenital hearing loss, autism spectrum disorder, reactive attachment disorder, complex medical histories resulting in severe neurologic compromise, intellectual disabilities, cerebral palsy, and nonsyndromic genetic conditions.

This chapter on obtaining an assessment begins by considering why, when, and where to obtain an assessment. Sources of referrals can be from child services (transition referral), primary care, other specialist colleagues, and occasionally other agencies such as social care, education (e.g. higher and further education), and the criminal justice system. Assessment services may be limited to performing a basic diagnostic function or may have access to more sophisticated needs assessment methods. A reasoned case for referral needs to be considered and developed. Alternative ways of meeting needs such as short-term problem-solving should also be considered. Information required for a referral for an assessment, whether brief or lengthy, is important. Pre-assessment tests and their evaluation should be considered. Experiences and expectations of the process of referral are also covered.

The final chapter summarizes the benefits of clinician support for students and families who experience academic challenges and learning problems. A review of issues covered in this volume includes the definition of learning disability, challenges in understanding differences between school and external evaluations, differences in terminology, and the lack of congruence between parental expectations for schools and what schools may actually (and appropriately) offer. Recommendations for clinicians include the importance of obtaining a thorough academic history and consideration of school performance as a critical piece of the diagnostic and treatment picture. The impact of related disorders, such as ADHD and executive function deficits, is discussed. Clinicians are advised to become familiar with school-based legal requirements, evaluations, and identification procedures for the benefit of students and their parents.

This chapter summarizes career counseling with diverse, and often marginalized, adult populations and reviews career development and adjustment theories and their application to practice. Diagnostic schemes for vocational problems and expectations for career counseling are reviewed in the context of client characteristics. Career counseling criteria, outcomes, and process components are discussed along with an overview of the integration of career and personal counseling. The section on current trends focuses on the use of career intervention with the unemployed, domestic violence survivors, ex-offenders, people with mental illness, immigrant and migrant populations, military veterans, individuals with physical disabilities, older adults transititoning to retirement, and adults in educational settings. Strength based and relational interventions, executive and career coaching, therapeutic assessment, behavioral intervention technologies, and the expanding role of career counseling in workplace and corporate settings also are summarized.

People with disorders of intellectual development (DID) have a diversity of abilities and consequent support needs. Adjustment difficulties give rise to mental distress and behavioural concerns when expectations are more than can be managed in the absence of needed supports. People with DID also experience a disturbing range of negative life events, trauma, and adversity, all of which can trigger adjustment disorder. Unless such stressors are identified, the individual with DID may be diagnosed with more serious psychiatric disorder, and the opportunity to remove the stressor and offer psychological treatment that both minimizes the emotional impact of the stressor and enhances coping (best practice) is lost. Chronic adjustment disorder, other serious psychiatric disorders, and challenging behaviours may develop and be perceived as treatment resistant (as long as the stressor remains). These diagnostic and treatment issues, in the context of the lives of people with DID, are explored in this chapter.

Percutaneous transluminal coronary angioplasty (PTCA) transformed the cardiac catheter from a diagnostic tool into a treatment tool. The technology involved a special catheter fitted with a balloon near its tip that could be blown up to expand a narrowed coronary artery segment. For patients with angina, the procedure was an attractive alternative to coronary bypass surgery. Mayo cardiologists were among the first to adopt angioplasty and to call for controlled clinical trials to compare it to bypass surgery. Initially, cardiologists (who already performed coronary angiography) learned to perform PTCA informally. After attending one or more live demonstration courses, many began to perform angioplasty in their local hospitals. The philosophy in many contexts was “see one, do one.” By the mid-1980s, however, more rigorous training expectations were elaborated. Heart specialists who performed PTCA were described as “interventional cardiologists,” a phrase that acknowledged that this catheter-based treatment had immediate effects.

Adjustment disorder is a psychiatric diagnosis that has undergone numerous iterations within the Diagnostic and Statistical Manual of Mental Disorders and is characterized by an immediate or almost immediate maladaptive or pathologic psychological response to a stressor. When the stressor is removed, there is the expectation that the patient returns to his or her previous level of functioning. This chapter provides an overview of its historical development, diagnostic criteria, potential controversies, epidemiology, neurobiology, comorbidities, and other differential diagnostic and treatment considerations such as ruling out depression and using assessment instruments. The chapter closes with the presentation of a case illustrating application of the criteria and clinical characteristics of adjustment disorder.The views expressed in this chapter are those of the authors and do not reflect the official policy of the Department of Army/Navy/Force, Department of Defense, or U.S. Government. The identification of specific products or scientific instrumentation is considered an integral part of the scientific endeavor and does not constitute endorsement or implied endorsement on the part of the author, DoD, or any component agency.

This chapter discusses key components of cardiovascular physiology applicable to clinical practice in the field of anaesthesiology. From theory development to ground-breaking innovations, the history of cardiac and vascular anatomy, as well as physiology, is presented. Utilizing knowledge of structure and function, parameters created have allowed adequate patient clinical assessment and guided interventions. A review of concepts reveals the impact of multiple physiological variables on a patient’s haemodynamic state and the need for more accurate and efficient measurements. In particular, it is noted that a more reliable index of ventricular contractility is the end-systolic elastance rather than the ejection fraction. Constant direct preload assessment has not yet been achieved but continues to be determined through surrogate variables, and continuous cardiac output monitoring for oxygen delivery, although advancing, has limitations. Considering the effect of compound factors perioperatively, especially heart failure, modifies the goals and interventions of anaesthetists to achieve improved outcomes. Therefore, medical management prior to surgery and complete assessment through history, physical examination, and diagnostic tests are a priority. This chapter also details the expectations following volume expansion to augment haemodynamics during surgery, the concept of functional haemodynamic monitoring, and limitations to the parameters applied in assessing fluid responsiveness. Challenging the accuracy of conventional indices to predict volume status led to the use of goal-directed therapy, reducing morbidity and minimizing length of hospital stay. The mainstay of this chapter is to reinforce the relevance of advances in haemodynamic monitoring and homeostasis optimization by anaesthetists during surgery, using fundamental concepts of cardiovascular physiology.

AbstractLaboratory medicine in the healthcare system has recently been recognized as a fundamental service in the clinical decision-making process. Therefore, the notion of patient safety in laboratory medicine must be recognized as the assurance that harm to patients will be avoided, safe care outcomes will be enhanced through error prevention, and the total testing process (TTP) will be continuously improved.Although the goal for patient safety is zero errors, and although laboratory professionals have made numerous efforts to reduce errors in the last few decades, current research into laboratory-related diagnostic errors highlights that: (a) errors occur at every step of the TTP, mainly affecting phases at clinical interfaces; (b) despite the improvement strategies adopted, analytical quality remains a challenge; (c) errors are linked not only to clinical chemistry tests, but also to new, increasingly complex diagnostic testing.Medical laboratories must therefore implement effective quality assurance tools to identify and prevent errors in order to guarantee the reliability of laboratory information. Accreditation in compliance with the International Standard ISO 15189 represents the first step, establishing processes with excellence requirements and greater expectations of staff competency. Another important step in preventing errors and ensuring patient safety is the development of specific educational and training programs addressed to all professionals involved in the process, in which both technical and administrative skills are integrated. A wide variety of information is provided by a robust quality management system and consensus-approved Quality Indicators (QI) that identify undesirable events, evaluate the risk to the patient, and call for corrective and preventive actions. However, the effectiveness of the system depends on the careful analysis of data collected and on staff awareness of the importance of laboratory medicine to the healthcare process. The main task of the new generation of laboratory professionals should be to gain experience in “clinical laboratory stewardship.” In order to safeguard patients, laboratory professionals must assist clinicians in selecting the right test for the right patient at the right time and facilitate the interpretation of laboratory information.

AbstractTechnological innovations in healthcare, perhaps now more than ever, are posing decisive opportunities for improvements in diagnostics, treatment, and overall quality of life. The use of artificial intelligence and big data processing, in particular, stands to revolutionize healthcare systems as we once knew them. But what effect do these technologies have on human agency and moral responsibility in healthcare? How can patients, practitioners, and the general public best respond to potential obscurities in responsibility? In this paper, I investigate the social and ethical challenges arising with newfound medical technologies, specifically the ways in which artificially intelligent systems may be threatening moral responsibility in the delivery of healthcare. I argue that if our ability to locate responsibility becomes threatened, we are left with a difficult choice of trade-offs. In short, it might seem that we should exercise extreme caution or even restraint in our use of state-of-the-art systems, but thereby lose out on such benefits as improved quality of care. Alternatively, we could embrace novel healthcare technologies but in doing so we might need to loosen our commitment to locating moral responsibility when patients come to harm; for even if harms are fewer – say, as a result of data-driven diagnostics – it may be unclear who or what is responsible when things go wrong. What is clear, at least, is that the shift toward artificial intelligence and big data calls for significant revisions in expectations on how, if at all, we might locate notions of responsibility in emerging models of healthcare.

AbstractPoland’s experience of road safety work is relatively short. In the early 1990s road deaths soared to a staggering 8000 a year. A diagnosis found that Poland’s lack of systemic road safety action was to blame for those figures. In response, the state set up road safety bodies and commissioned road safety programs. In 2005, Poland followed the example of Sweden and adopted Vision Zero as a far-reaching concept of changes in road safety. The work that followed helped to improve the situation and reach less than 3000 fatalities in 2015. Despite that, for years Poland has been notorious for its road accident deaths, which are some of the highest in the EU. Poland has had its share of both successes and failures. The results of road safety policies are still below the expectations and many problems have not been solved. Road accidents are not considered a major problem. As a consequence, they are low on political agendas and the institutions remain ineffective due to a sense of collective responsibility for road safety problems. Achieving Vision Zero will require many changes, learning from past mistakes, taking advantage of the experience of the best performing countries, and, above all, taking effective and efficient actions with their systematic monitoring.This chapter is a summary of the last 30 years of road safety work in Poland. It presents a diagnosis of Poland’s problems, an assessment of the policies so far, and the likelihood of achieving the assumptions of Vision Zero in the future. Building on this, recommendations are given on the next steps Poland should take to improve its road safety.

AbstractPoland’s experience of road safety work is relatively short. In the early 1990s road deaths soared to a staggering 8000 a year. A diagnosis found that Poland’s lack of systemic road safety action was to blame for those figures. In response, the state set up road safety bodies and commissioned road safety programs. In 2005, Poland followed the example of Sweden and adopted Vision Zero as a far-reaching concept of changes in road safety. The work that followed helped to improve the situation and reach less than 3000 fatalities in 2015. Despite that, for years Poland has been notorious for its road accident deaths, which are some of the highest in the EU. Poland has had its share of both successes and failures. The results of road safety policies are still below the expectations and many problems have not been solved. Road accidents are not considered a major problem. As a consequence, they are low on political agendas and the institutions remain ineffective due to a sense of collective responsibility for road safety problems. Achieving Vision Zero will require many changes, learning from past mistakes, taking advantage of the experience of the best performing countries, and, above all, taking effective and efficient actions with their systematic monitoring.This chapter is a summary of the last 30 years of road safety work in Poland. It presents a diagnosis of Poland’s problems, an assessment of the policies so far, and the likelihood of achieving the assumptions of Vision Zero in the future. Building on this, recommendations are given on the next steps Poland should take to improve its road safety.

With advances in information and communication technology, students can be educated from anywhere at any time at their own pace. Students of the 21st century have different learning expectations. These expectations require the design of smart learning environments to ensure more effective and adaptive learning. This chapter essays an introduction to a new educational tool developed on the Moodle platform by The University of the South Pacific to bridge gaps in mathematics knowledge and skills as students' transit from secondary to tertiary education. The tool, known as the Online Mathematics Diagnostic Tool (OMDT), is an intelligent system which provides online tests and automates personalized remediation. This chapter will include the reasons why this diagnostic tool has been developed for the Pacific region students aspiring for tertiary education. It will also discuss why the tool is considered as a smart learning environment (SLE) and how it ensures effective learning of mathematics.

This research paper mainly deals with expectation and perception of service quality of select Indian Banks i.e. SBI and HDFC on the customer satisfaction. The research survey was based on IS-QUAL dimensions (Ray & Ghosh,2014) a diagnostic model developed in 2014, which measures service quality and internet service quality in terms of customer expectations and perceptions of banking services. This present research tends to evaluate the overall idea of expected and perceived services of the two banks. This study is a cross-sectional survey that employed the use of pre-structured questionnaire to collect primary data from a sample of 120 respondents through personal contact, field survey and email. Collected data have been analyzed through SPSS 21 software by different statistical tools like Reliability test for judgment of internal consistency of collected data and paired t- test.

The satisfaction of students of the Engineering and Physics Faculty of High Technologies of USU with the quality of online learning during the pandemic was studied. The criteria and indicators of satisfaction with online learning are determined based on the implementation of expectations from online learning and the social and professional adaptation of students to online conditions. The diagnostic tools included a questionnaire to identify the implementation of students ' expectations from online learning and a methodology for its processing. The level of adaptation was measured by a seven-level scale of self-assessment of psychological comfort in online and offline classes. The results of the study showed a fairly high level of student satisfaction with the study of natural sciences and humanities online.

A diagnostic tool (computer program) has been developed by the US Navy to provide the operators of LM2500 gas turbines (which are used as main propulsion on 6 ship classes in the USN) and the supporting technical staff, an assessment of the performance of this engine and the calibration of the engine control system. Typically, USN LM2500s do not mechanically degrade to the point where they will physically not be capable of making the required power. Instead, drift or lack of calibration of the engine sensors or its signal conditioning, mechanical wear and drift in the engine fuel scheduling control will cause the engine, after a period of time, either to not meet its performance expectations or report a performance level that is different from the actual condition. This can cause the engine to fail to meet the performance expectations of the propulsion control system, whether it is a real problem or a reporting problem (due to sensor mis-calibration), and in the worst case can cause an engine failure. To address these issues a performance diagnostic tool was developed that allowed the troubleshooter to compare engine performance, as reported by engine sensors etc., against what should be expected from the engine. Based on any differences, the tool provides the investigator guidance on the most likely source for the problem. To make such a tool, required integrating engine steady state performance models, with knowledge of the engine control loops as well as engine sensor, signal conditioning accuracy and calibration requirements. At present the diagnostic tool is being used by Fleet Technical Support Center Pacific to diagnose engine and controls problems. The goal is to provide ship’s force with the capability to diagnose most of their own problems and to provide a history of a particular engine’s performance.

The idea of sustainable farming entails farming production management which allows for the efficient use of natural resources in order to achieve financial profit, while respecting the laws of nature and meeting expectations of society at the same time. The idea is interdisciplinary and incorporates many facets. The author analysed numerous methods of production technology which exert influence on the natural environment. The aim of the research was to evaluate if - and to what extent - agricultural production of the examined farms was sustainable. The empirical data was collected by means of the diagnostic interview technique. The poll was carried out between 2014 and 2017 among 155 respondents. The research showed that the majority of the polled farmers adhered to the sustainable farming production guidelines and tried to extend their knowledge of the subject matter.

Many first-year students are seen to struggle to build resilience in their first year of post-secondary education just like racing cars. The journey of the first year or incoming university students is explained with an analogy of racing cars mainly an analogy for student learning based on the performance of race cars. To improve retention and first year experience, higher education institutes try to build resilience in students, they expect students to participate in campus activities and interact with other students and teachers from different backgrounds. But what about students’ expectations of their institution and how often institutions emphasize these training and engagement opportunities to their incoming students? An online student readiness intervention program has been designed to understand expectations and investigate predictors that promote resilience. The student readiness resilience intervention program includes three phases, which begin with a diagnostic assessment to determine individuals acquired knowledge and skills. The next phase helps prepare students by addressing the learning gaps from the results of the online tests through virtual events. The final phase includes personalized learning with mentors’ mobile coaching with an aim to build resilience by creating lasting habits and capabilities to enable first year students to remain calm and focused. This study further reviews various theories to identify process, trends, differences, and gaps to describe and critically analyse student readiness and effects of intervention programs. It will also provide useful critique and recommendations to transition leaders and educators in relation to the student resilience.

Since its inception the gas turbine market has been driven by an emphasis on improved operating efficiency, greater megawatt output, with reduced environmental impact through technology advancement. The technology advances that have taken place include; higher firing temperatures and pressure ratios, improved cooling schemes with advanced metallurgy and coatings for hot gas path parts, consideration for tighter clearances, low emissions combustion systems, and fuels flexibility. Contemporaneously, there has been a commensurate focus on ensuring that the achievable levels of availability and reliability of these evolving product offerings would be optimized for various duty cycles, applications, and plant arrangements. In fact, as product evolution and advancement has taken place, there has been an expectation that availability and reliability performance would be consistent with the best achievable levels experienced by existing and more mature technologies. The purpose of this paper is to address the industry focus on availability and reliability (from EPRI to DOE), and to discuss the current and historical availability and reliability performance of gas turbines based on class; specifically “E” and “F” class. Additionally, this paper will also address the positive impact that “remote monitoring” has had; through the automation and computation of availability and reliability metrics. “Remote monitoring” has been introduced to provide an extra level of protection and diagnostic capability; providing an emphasis on performance, operability, and availability of the power generation equipment. The fact that “remote monitoring” has facilitated rapid data acquisition has had a positive impact on the calculation of availability and reliability metrics, making them more timely and accurate. This important point will also be discussed. With the permission of Mitsubishi Power Systems America (MPSA), specific data for the M501F fleet is presented. These comparisons will assist in establishing benchmarks for equipment performance based on duty cycle and other meaningful segmentations. Data available from SPS’s ORAP® (Operational Reliability Analysis Program) and other industry sources will be used to provide valid references for consideration.

Abstract An operator working in Indian western land reservoirs, planned to develop a low-permeability, high potential reservoir with hydraulic fracturing. In the pilot project, production behavior of the initial wells was below expectation. As a diagnostic procedure few of the wells were attempted with memory coiled tubing-assisted production logging to record production log data and identify the root cause behind poor performance. Apart from the horizontal trajectory, major challenges associated with this approach included the low flow rate (150-200bbl) and expectation of frac fluid inside the wellbore due to inadequate cleaning. As a result, all the attempts for effective diagnosis were inconclusive. Moreover, absence of critical input such as individual stage frac evaluation demanded attention in order to optimize completion quality (CQ) and conclude effective fracturing and completion strategy prior to full field development planning. Addressing the challenges and with an aim to provide the critical inputs required for reservoir characterization and production optimization, a multi-spinner production logging tool with new innovative spinner design and multi-electrical and optical sensors were proposed on cased-hole tractor in order to resolve the complex flow profiles associated with the low flow rates and horizontal well trajectory. The newly configured spinners with innovative spinner design material lowered the spinner threshold from 2ft/min to 1ft/min for multipass logging in lab tests. It also optimized the magnetic field distribution to ensure less accretion of debris on the spinner (causing spinners to clog) without compromising measurement accuracy. With well production being 200 bbl at the time of logging, the multi-spinner survey with innovative spinner design clearly resolved the dynamic changes across the borehole during multi bean data acquisition. Overcoming the major interpretation challenge of isolating the dynamic changes in the wellbore due to borehole trajectory and due to fracturing stage, individual stage frac flow contributions were evaluated. Stage frac productivity correlated very well with the frac operation parameters, reservoir quality and completion quality. Apart from individual contributions, key findings such as activation of few frac stages at high drawdown pressures, increasing gas contribution from toe to heel and resolving presence of leftover frac fluid in the well, exceeded the expectations set by the client in terms of the objectives vs. results. This success clearly demonstrated that knowledge of downhole dynamics for horizontal trajectory is vital. This is not limited only to address the individual well requirement, but an integrated approach would help to optimize future wells through better understanding of reservoir productivity vs frac operation and completion quality (CQ).

The use of elastic wave based Structural Health Monitoring has shown its usefulness in both characterizing and diagnosing composite structures. Techniques using elastic wave SHM are being developed to allow for improved efficiency and assurance in all stages of space structure development and deployment. These techniques utilize precise understanding of wave propagation characteristics to extract meaningful information regarding the health and validity of a component, assembly, or structure. However, many of these techniques focus on the diagnostic of traditional, isotropic materials, and questions remain as to the effect of the orthotropic properties of resin matrix composite material on the propagation of elastic waves. As the demands and expectations placed upon composite structures continue to expand in the space community, these questions must be addressed to allow the development of elastic wave based SHM techniques that will enable advancements in areas such as automated build validation and qualification, and in-situ characterization and evaluation of increasingly complex space structures. This study attempts to aid this development by examines the effect of cross ply, off-axis fiber orientation on the propagation characteristics of lamb waves. This is achieved by observing the result of symmetric and anti-symmetric wave propagation across materials in cases containing both off-axis and axially-aligned elements. In both cases the surface plies of the test specimen are axially aligned with the wave propagation direction. Using these results, the relative effect of core ply orientation on lamb wave propagation, and lamb wave sensitivity to bulk properties, or alternatively, the dominance of surface properties on propagation characteristics, can be seen, and this information can be used to aid in future research and application of lamb waves for interrogation of advanced, high-strain composite space structures. It was found that the core orientation caused significant variation in the S0 wave velocity, while yielding little influence on the A0 wave velocity.

The production of LDPE may require huge heavy-duty reciprocating compressors to withstand the loads, deriving from the operating pressures, to satisfy the growing needs of the market. Safety, Performance and Reliability are normal expectations and therefore need a thorough evaluation of the specific service. The machine selection is based on positive experience in similar applications and cylinder performance. The cylinders are special pressure vessels, whose design and construction have to consider the extreme internal pressures and the process gas. The design must foresee all possible failure modes of each component, to have safe and smooth operation, thanks to innovative methods of modeling and simulation, like FEM and CFD, important for the design of cylinder parts. Valves are simulated by mathematical models optimizing performance, to reach a correct mechanical behavior with minimum energy consumption and ensuring reliable operation. The available technological improvements are a starting point, resulting from the developments of manufacturers and long experience of End Users. The pulsation and vibration of the piping are usually investigated to keep the plant in operation without failures. Many cylinder components are exposed to pressures fluctuating between suction and discharge and therefore to high fatigue loads. To reach high endurance capabilities they have to be pre-compressed to keep them operating under compressive stresses whenever possible. Special materials, shrink fitting and auto-frettage procedures are usually required. The operation is the stage where all the parameters have to be kept under control and incipient problems have to be identified to minimize shut-downs and arrange various maintenance works. Automation, monitoring and diagnostic systems complete the efforts of operators to afford high safety levels, with increased availability and optimized maintenance interventions. The continuing development of technology will help to challenge performance and high capacity demand of future plants.

The production of LDPE may require huge power, heavy-duty reciprocating compressors, provided with opposite cylinders and special frames to withstand the loads, deriving from the operating pressures. In many new projects larger capacities and higher performance requirements, renew the challenge of engineers to handle the mechanical, thermodynamic, chemical-physical, process and operational aspects. Safety, performance, operation and reliability are usual expectations needing a thorough evaluation of the service and the machine selection is based on positive results in similar applications. Valve, packing and cylinder performance is noticeably influenced by the design, operation and maintenance activities. The cylinders are compound pressure vessels, excluded by design codes, but their design and construction have to consider the extreme internal pressures and the nature of the process gas. The ability to withstand the high fatigue stresses and the need to avoid any leakage of gas around the compressor area implies solutions to minimize such occurrences including abnormal operations and emergencies. The design must foresee all possible failure modes of each component, to have safe and smooth operation. Innovative methods of simulation and modeling, like FEA, CFD, and others, are very important tools for the design of cylinder components. Valves are simulated by mathematical models optimizing performance and ensuring reliable operation, to reach a correct mechanical behavior with minimum energy consumption. The available technological improvements are taken as a base, resulting from the R&D of manufacturers and long experience of End Users. Also the pulsation and related vibration of the piping have to be investigated to keep the plant in operation without hazard. The operation is the stage where all the parameters have to be kept under control and incipient problems have to be identified to minimize shut down and arrange various maintenance works. Automation systems, together with new monitoring and diagnostic systems, allow very high safety levels, availability and optimized maintenance interventions.

The sharing economy offers great potential for companies to access resources in a more sustainable way, to create knowledge synergies or to save costs. This potential is particularly attractive to small and medium-sized enterprises (SMEs) as it provides access to scarce resources that otherwise are not affordable. However, sharing resources in B2B is not yet widespread. Therefore, in this project, which is supported by the Swiss federation, we aimed at promoting sharing between SMEs. To do so, we developed tools supporting different phases of sharing projects. This paper focuses on the initial phase of a sharing project where SMEs interested in sharing need to find partners. The tool we developed for that purpose supports partner matching. To develop the tool, we started with an extensive literature review to identify the factors that contribute to a successful sharing. This review revealed a total of about 40 success factors. From these, the most critical factors were selected through expert judgment and testing as described below. This resulted in a final set of 16 factors deemed important and demonstrated to be distinctive. Expert judgment to validate the success factors was conducted by the means of interviews (n=10) with representatives of Swiss SMEs interested in B2B sharing. Beside factor validation, results from the interviews showed that companies have a very heterogeneous understanding of what factors are important for a successful sharing. The importance assigned to the different success factors seemed to strongly depend on characteristics of the resource to be shared and on the importance of a particular resource to the individual SME's business. We concluded that consensus on the importance of success factors is not a prerequisite for successful sharing. Rather, it is important that the different objectives and associated expectations for sharing are not incompatible. Thus, the success factors can help identify potential areas of incompatibility and thus clarify where consensus needs to be found and where heterogeneous views will not have a negative impact on a successful partnership. To test the success factors, we operationalized and integrated them into a diagnostic tool that allows interested companies to self-assess and enables them to find potentially suitable sharing partners. This tool was tested by Swiss SMEs (n=10). Based on the tests, two version of the diagnostic tool were developed: A short version with five items that supports platform-based online matching, and a long version with 16 items that supports a more comprehensive negotiating process between partners willing to share resources. The two versions of the tool, the operationalized criteria as well as the tool application will be presented in the paper.

Gennaioli and Shleifer (GS) have proposed diagnostic expectations (DE) as an empirically-based approach to specifying participants’ expectations, which, like REH, can be applied in every model. Beyond its supposedly general applicability, GS’s formalization of DE implies that participants systematically and predictably overreact to news. Here, we present a formal argument that Kahneman and Tversky’s compelling empirical findings, and those of other behavioral economists, do not provide a basis for a general approach to specifying participants’ “predictable errors.” We also show that the overreaction of participants’ expectations is not a regularity, but rather an artifact of GS’s particular specification of DE.

We show that inflation expectations are heterogeneous and depend on past individual experiences. We propose a diagnostic expectations-augmented Kalman filter to represent consumers’ heterogeneous inflation expectations-formation process, where heterogeneity comes from an anchoring-to-the-past mechanism. We estimate the diagnosticity parameter that governs the inflation expectations-formation process and show that the model can replicate systematic differences in inflation expectations across cohorts in the US. We introduce this mechanism into a New Keynesian model and find that heterogeneous expectations anchor aggregate responses to the agents’ memory, making shocks more persistent. Central banks should be more active to prevent agents from remembering current shocks far into the future.

We develop a novel characterization of participants’ forecasts with a mixture of normal variables arising from a Markov component. Using this characterization, we formulate five behavioral specifications, including four implied by the diagnostic expectations approach, as well as three implied by REH, and derive several new predictions for Coibion and Gorodnichenko.s regression of forecast errors on forecast revisions. Predictions of all eight specifications are inconsistent with the observed instability of individual CG regressions’ coefficients, based on inflation forecasts from 24 professionals. Our findings suggest how to build on key insights of the REH and behavioral approaches in specifying individuals’ forecasts.

1.1 Macroeconomic summary Economic recovery has consistently outperformed the technical staff’s expectations following a steep decline in activity in the second quarter of 2020. At the same time, total and core inflation rates have fallen and remain at low levels, suggesting that a significant element of the reactivation of Colombia’s economy has been related to recovery in potential GDP. This would support the technical staff’s diagnosis of weak aggregate demand and ample excess capacity. The most recently available data on 2020 growth suggests a contraction in economic activity of 6.8%, lower than estimates from January’s Monetary Policy Report (-7.2%). High-frequency indicators suggest that economic performance was significantly more dynamic than expected in January, despite mobility restrictions and quarantine measures. This has also come amid declines in total and core inflation, the latter of which was below January projections if controlling for certain relative price changes. This suggests that the unexpected strength of recent growth contains elements of demand, and that excess capacity, while significant, could be lower than previously estimated. Nevertheless, uncertainty over the measurement of excess capacity continues to be unusually high and marked both by variations in the way different economic sectors and spending components have been affected by the pandemic, and by uneven price behavior. The size of excess capacity, and in particular the evolution of the pandemic in forthcoming quarters, constitute substantial risks to the macroeconomic forecast presented in this report. Despite the unexpected strength of the recovery, the technical staff continues to project ample excess capacity that is expected to remain on the forecast horizon, alongside core inflation that will likely remain below the target. Domestic demand remains below 2019 levels amid unusually significant uncertainty over the size of excess capacity in the economy. High national unemployment (14.6% for February 2021) reflects a loose labor market, while observed total and core inflation continue to be below 2%. Inflationary pressures from the exchange rate are expected to continue to be low, with relatively little pass-through on inflation. This would be compatible with a negative output gap. Excess productive capacity and the expectation of core inflation below the 3% target on the forecast horizon provide a basis for an expansive monetary policy posture. The technical staff’s assessment of certain shocks and their expected effects on the economy, as well as the presence of several sources of uncertainty and related assumptions about their potential macroeconomic impacts, remain a feature of this report. The coronavirus pandemic, in particular, continues to affect the public health environment, and the reopening of Colombia’s economy remains incomplete. The technical staff’s assessment is that the COVID-19 shock has affected both aggregate demand and supply, but that the impact on demand has been deeper and more persistent. Given this persistence, the central forecast accounts for a gradual tightening of the output gap in the absence of new waves of contagion, and as vaccination campaigns progress. The central forecast continues to include an expected increase of total and core inflation rates in the second quarter of 2021, alongside the lapse of the temporary price relief measures put in place in 2020. Additional COVID-19 outbreaks (of uncertain duration and intensity) represent a significant risk factor that could affect these projections. Additionally, the forecast continues to include an upward trend in sovereign risk premiums, reflected by higher levels of public debt that in the wake of the pandemic are likely to persist on the forecast horizon, even in the context of a fiscal adjustment. At the same time, the projection accounts for the shortterm effects on private domestic demand from a fiscal adjustment along the lines of the one currently being proposed by the national government. This would be compatible with a gradual recovery of private domestic demand in 2022. The size and characteristics of the fiscal adjustment that is ultimately implemented, as well as the corresponding market response, represent another source of forecast uncertainty. Newly available information offers evidence of the potential for significant changes to the macroeconomic scenario, though without altering the general diagnosis described above. The most recent data on inflation, growth, fiscal policy, and international financial conditions suggests a more dynamic economy than previously expected. However, a third wave of the pandemic has delayed the re-opening of Colombia’s economy and brought with it a deceleration in economic activity. Detailed descriptions of these considerations and subsequent changes to the macroeconomic forecast are presented below. The expected annual decline in GDP (-0.3%) in the first quarter of 2021 appears to have been less pronounced than projected in January (-4.8%). Partial closures in January to address a second wave of COVID-19 appear to have had a less significant negative impact on the economy than previously estimated. This is reflected in figures related to mobility, energy demand, industry and retail sales, foreign trade, commercial transactions from selected banks, and the national statistics agency’s (DANE) economic tracking indicator (ISE). Output is now expected to have declined annually in the first quarter by 0.3%. Private consumption likely continued to recover, registering levels somewhat above those from the previous year, while public consumption likely increased significantly. While a recovery in investment in both housing and in other buildings and structures is expected, overall investment levels in this case likely continued to be low, and gross fixed capital formation is expected to continue to show significant annual declines. Imports likely recovered to again outpace exports, though both are expected to register significant annual declines. Economic activity that outpaced projections, an increase in oil prices and other export products, and an expected increase in public spending this year account for the upward revision to the 2021 growth forecast (from 4.6% with a range between 2% and 6% in January, to 6.0% with a range between 3% and 7% in April). As a result, the output gap is expected to be smaller and to tighten more rapidly than projected in the previous report, though it is still expected to remain in negative territory on the forecast horizon. Wide forecast intervals reflect the fact that the future evolution of the COVID-19 pandemic remains a significant source of uncertainty on these projections. The delay in the recovery of economic activity as a result of the resurgence of COVID-19 in the first quarter appears to have been less significant than projected in the January report. The central forecast scenario expects this improved performance to continue in 2021 alongside increased consumer and business confidence. Low real interest rates and an active credit supply would also support this dynamic, and the overall conditions would be expected to spur a recovery in consumption and investment. Increased growth in public spending and public works based on the national government’s spending plan (Plan Financiero del Gobierno) are other factors to consider. Additionally, an expected recovery in global demand and higher projected prices for oil and coffee would further contribute to improved external revenues and would favor investment, in particular in the oil sector. Given the above, the technical staff’s 2021 growth forecast has been revised upward from 4.6% in January (range from 2% to 6%) to 6.0% in April (range from 3% to 7%). These projections account for the potential for the third wave of COVID-19 to have a larger and more persistent effect on the economy than the previous wave, while also supposing that there will not be any additional significant waves of the pandemic and that mobility restrictions will be relaxed as a result. Economic growth in 2022 is expected to be 3%, with a range between 1% and 5%. This figure would be lower than projected in the January report (3.6% with a range between 2% and 6%), due to a higher base of comparison given the upward revision to expected GDP in 2021. This forecast also takes into account the likely effects on private demand of a fiscal adjustment of the size currently being proposed by the national government, and which would come into effect in 2022. Excess in productive capacity is now expected to be lower than estimated in January but continues to be significant and affected by high levels of uncertainty, as reflected in the wide forecast intervals. The possibility of new waves of the virus (of uncertain intensity and duration) represents a significant downward risk to projected GDP growth, and is signaled by the lower limits of the ranges provided in this report. Inflation (1.51%) and inflation excluding food and regulated items (0.94%) declined in March compared to December, continuing below the 3% target. The decline in inflation in this period was below projections, explained in large part by unanticipated increases in the costs of certain foods (3.92%) and regulated items (1.52%). An increase in international food and shipping prices, increased foreign demand for beef, and specific upward pressures on perishable food supplies appear to explain a lower-than-expected deceleration in the consumer price index (CPI) for foods. An unexpected increase in regulated items prices came amid unanticipated increases in international fuel prices, on some utilities rates, and for regulated education prices. The decline in annual inflation excluding food and regulated items between December and March was in line with projections from January, though this included downward pressure from a significant reduction in telecommunications rates due to the imminent entry of a new operator. When controlling for the effects of this relative price change, inflation excluding food and regulated items exceeds levels forecast in the previous report. Within this indicator of core inflation, the CPI for goods (1.05%) accelerated due to a reversion of the effects of the VAT-free day in November, which was largely accounted for in February, and possibly by the transmission of a recent depreciation of the peso on domestic prices for certain items (electric and household appliances). For their part, services prices decelerated and showed the lowest rate of annual growth (0.89%) among the large consumer baskets in the CPI. Within the services basket, the annual change in rental prices continued to decline, while those services that continue to experience the most significant restrictions on returning to normal operations (tourism, cinemas, nightlife, etc.) continued to register significant price declines. As previously mentioned, telephone rates also fell significantly due to increased competition in the market. Total inflation is expected to continue to be affected by ample excesses in productive capacity for the remainder of 2021 and 2022, though less so than projected in January. As a result, convergence to the inflation target is now expected to be somewhat faster than estimated in the previous report, assuming the absence of significant additional outbreaks of COVID-19. The technical staff’s year-end inflation projections for 2021 and 2022 have increased, suggesting figures around 3% due largely to variation in food and regulated items prices. The projection for inflation excluding food and regulated items also increased, but remains below 3%. Price relief measures on indirect taxes implemented in 2020 are expected to lapse in the second quarter of 2021, generating a one-off effect on prices and temporarily affecting inflation excluding food and regulated items. However, indexation to low levels of past inflation, weak demand, and ample excess productive capacity are expected to keep core inflation below the target, near 2.3% at the end of 2021 (previously 2.1%). The reversion in 2021 of the effects of some price relief measures on utility rates from 2020 should lead to an increase in the CPI for regulated items in the second half of this year. Annual price changes are now expected to be higher than estimated in the January report due to an increased expected path for fuel prices and unanticipated increases in regulated education prices. The projection for the CPI for foods has increased compared to the previous report, taking into account certain factors that were not anticipated in January (a less favorable agricultural cycle, increased pressure from international prices, and transport costs). Given the above, year-end annual inflation for 2021 and 2022 is now expected to be 3% and 2.8%, respectively, which would be above projections from January (2.3% and 2,7%). For its part, expected inflation based on analyst surveys suggests year-end inflation in 2021 and 2022 of 2.8% and 3.1%, respectively. There remains significant uncertainty surrounding the inflation forecasts included in this report due to several factors: 1) the evolution of the pandemic; 2) the difficulty in evaluating the size and persistence of excess productive capacity; 3) the timing and manner in which price relief measures will lapse; and 4) the future behavior of food prices. Projected 2021 growth in foreign demand (4.4% to 5.2%) and the supposed average oil price (USD 53 to USD 61 per Brent benchmark barrel) were both revised upward. An increase in long-term international interest rates has been reflected in a depreciation of the peso and could result in relatively tighter external financial conditions for emerging market economies, including Colombia. Average growth among Colombia’s trade partners was greater than expected in the fourth quarter of 2020. This, together with a sizable fiscal stimulus approved in the United States and the onset of a massive global vaccination campaign, largely explains the projected increase in foreign demand growth in 2021. The resilience of the goods market in the face of global crisis and an expected normalization in international trade are additional factors. These considerations and the expected continuation of a gradual reduction of mobility restrictions abroad suggest that Colombia’s trade partners could grow on average by 5.2% in 2021 and around 3.4% in 2022. The improved prospects for global economic growth have led to an increase in current and expected oil prices. Production interruptions due to a heavy winter, reduced inventories, and increased supply restrictions instituted by producing countries have also contributed to the increase. Meanwhile, market forecasts and recent Federal Reserve pronouncements suggest that the benchmark interest rate in the U.S. will remain stable for the next two years. Nevertheless, a significant increase in public spending in the country has fostered expectations for greater growth and inflation, as well as increased uncertainty over the moment in which a normalization of monetary policy might begin. This has been reflected in an increase in long-term interest rates. In this context, emerging market economies in the region, including Colombia, have registered increases in sovereign risk premiums and long-term domestic interest rates, and a depreciation of local currencies against the dollar. Recent outbreaks of COVID-19 in several of these economies; limits on vaccine supply and the slow pace of immunization campaigns in some countries; a significant increase in public debt; and tensions between the United States and China, among other factors, all add to a high level of uncertainty surrounding interest rate spreads, external financing conditions, and the future performance of risk premiums. The impact that this environment could have on the exchange rate and on domestic financing conditions represent risks to the macroeconomic and monetary policy forecasts. Domestic financial conditions continue to favor recovery in economic activity. The transmission of reductions to the policy interest rate on credit rates has been significant. The banking portfolio continues to recover amid circumstances that have affected both the supply and demand for loans, and in which some credit risks have materialized. Preferential and ordinary commercial interest rates have fallen to a similar degree as the benchmark interest rate. As is generally the case, this transmission has come at a slower pace for consumer credit rates, and has been further delayed in the case of mortgage rates. Commercial credit levels stabilized above pre-pandemic levels in March, following an increase resulting from significant liquidity requirements for businesses in the second quarter of 2020. The consumer credit portfolio continued to recover and has now surpassed February 2020 levels, though overall growth in the portfolio remains low. At the same time, portfolio projections and default indicators have increased, and credit establishment earnings have come down. Despite this, credit disbursements continue to recover and solvency indicators remain well above regulatory minimums. 1.2 Monetary policy decision In its meetings in March and April the BDBR left the benchmark interest rate unchanged at 1.75%.