Dataset Information

Risk-Based Decision Making: A Systematic Scoping Review of Animal Models and a Pilot Study on the Effects of Sleep Deprivation in Rats.

ABSTRACT: Animals, including humans, frequently make decisions involving risk or uncertainty. Different strategies in these decisions can be advantageous depending the circumstances. Short sleep duration seems to be associated with more risky decisions in humans. Animal models for risk-based decision making can increase mechanistic understanding, but very little data is available concerning the effects of sleep. We combined primary- and meta-research to explore the relationship between sleep and risk-based decision making in animals. Our first objective was to create an overview of the available animal models for risky decision making. We performed a systematic scoping review. Our searches in Pubmed and Psychinfo retrieved 712 references, of which 235 were included. Animal models for risk-based decision making have been described for rodents, non-human primates, birds, pigs and honey-bees. We discuss task designs and model validity. Our second objective was to apply this knowledge and perform a pilot study on the effect of sleep deprivation. We trained and tested male Wistar rats on a probability discounting task; a "safe" lever always resulted in 1 reward, a "risky" lever resulted in 4 or no rewards. Rats adapted their preferences to variations in reward probabilities (p < 0.001), but 12 h of sleep deprivation during the light phase did not clearly alter risk preference (p = 0.21).

SUBMITTER: Leenaars CHC

PROVIDER: S-EPMC7838799 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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Risk-Based Decision Making: A Systematic Scoping Review of Animal Models and a Pilot Study on the Effects of Sleep Deprivation in Rats.

Leenaars Cathalijn H C CHC Van der Mierden Stevie S Joosten Ruud N J M A RNJMA Van der Weide Marnix A MA Schirris Mischa M Dematteis Maurice M Meijboom Franck L B FLB Feenstra Matthijs G P MGP Bleich André A

Clocks & sleep 20210120 1

Animals, including humans, frequently make decisions involving risk or uncertainty. Different strategies in these decisions can be advantageous depending the circumstances. Short sleep duration seems to be associated with more risky decisions in humans. Animal models for risk-based decision making can increase mechanistic understanding, but very little data is available concerning the effects of sleep. We combined primary- and meta-research to explore the relationship between sleep and risk-base ...[more]

PMID: 33498259

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Project description:Sleep deprivation is highly prevalent in the modern world, possibly reaching epidemic proportions. While multiple theories regarding the roles of sleep exist (inactivity, energy conservation, restoration, brain plasticity and antioxidant), multiple unknowns still remain regarding the proposed antioxidant roles of sleep. The existing experimental evidence is often contradicting, with studies pointing both toward and against the presence of oxidative stress after sleep deprivation. The main goals of this review were to analyze the existing experimental data regarding the relationship between sleep deprivation and oxidative stress, to attempt to further clarify multiple aspects surrounding this relationship and to identify current knowledge gaps. Systematic searches were conducted in three major online databases for experimental studies performed on rat models with oxidative stress measurements, published between 2015 and 2022. A total of 54 studies were included in the review. Most results seem to point to changes in oxidative stress parameters after sleep deprivation, further suggesting an antioxidant role of sleep. Alterations in these parameters were observed in both paradoxical and total sleep deprivation protocols and in multiple rat strains. Furthermore, the effects of sleep deprivation seem to extend beyond the central nervous system, affecting multiple other body sites in the periphery. Sleep recovery seems to be characterized by an increased variability, with the presence of both normalizations in some parameters and long-lasting changes after sleep deprivation. Surprisingly, most studies revealed the presence of a stress response following sleep deprivation. However, the origin and the impact of the stress response during sleep deprivation remain somewhat unclear. While a definitive exclusion of the influence of the sleep deprivation protocol on the stress response is not possible, the available data seem to suggest that the observed stress response may be determined by sleep deprivation itself as opposed to the experimental conditions. Due to this fact, the observed oxidative changes could be attributed directly to sleep deprivation.

Project description:BackgroundDecision thresholds play important role in medical decision-making. Individual decision-making differences may be attributable to differences in subjective judgments or cognitive processes that are captured through the decision thresholds. This systematic scoping review sought to characterize the literature on non-expected utility decision thresholds in medical decision-making by identifying commonly used theoretical paradigms and contextual and subjective factors that inform decision thresholds.MethodsA structured search designed around three concepts-individual decision-maker, decision threshold, and medical decision-was conducted in MEDLINE (Ovid) and Scopus databases from inception to July 2023. ProQuest (Dissertations and Theses) database was searched to August 2023. The protocol, developed a priori, was registered on Open Science Framework and PRISMA-ScR guidelines were followed for reporting on this study. Titles and abstracts of 1,618 articles and the full texts for the 228 included articles were reviewed by two independent reviewers. 95 articles were included in the analysis. A single reviewer used a pilot-tested data collection tool to extract study and author characteristics, article type, objectives, theoretical paradigm, contextual or subjective factors, decision-maker, and type of medical decision.ResultsOf the 95 included articles, 68 identified a theoretical paradigm in their approach to decision thresholds. The most common paradigms included regret theory, hybrid theory, and dual processing theory. Contextual and subjective factors that influence decision thresholds were identified in 44 articles.ConclusionsOur scoping review is the first to systematically characterizes the available literature on decision thresholds within medical decision-making. This study offers an important characterization of the literature through the identification of the theoretical paradigms for non-expected utility decision thresholds. Moreover, this study provides insight into the various contextual and subjective factors that have been documented within the literature to influence decision thresholds, as well as these factors juxtapose theoretical paradigms.

Project description:Study objectivesTo better understand the sometimes catastrophic effects of sleep loss on naturalistic decision making, we investigated effects of sleep deprivation on decision making in a reversal learning paradigm requiring acquisition and updating of information based on outcome feedback.DesignSubjects were randomized to a sleep deprivation or control condition, with performance testing at baseline, after 2 nights of total sleep deprivation (or rested control), and following 2 nights of recovery sleep. Subjects performed a decision task involving initial learning of go and no go response sets followed by unannounced reversal of contingencies, requiring use of outcome feedback for decisions. A working memory scanning task and psychomotor vigilance test were also administered.SettingSix consecutive days and nights in a controlled laboratory environment with continuous behavioral monitoring.SubjectsTwenty-six subjects (22-40 y of age; 10 women).InterventionsThirteen subjects were randomized to a 62-h total sleep deprivation condition; the others were controls.Measurements and resultsUnlike controls, sleep deprived subjects had difficulty with initial learning of go and no go stimuli sets and had profound impairment adapting to reversal. Skin conductance responses to outcome feedback were diminished, indicating blunted affective reactions to feedback accompanying sleep deprivation. Working memory scanning performance was not significantly affected by sleep deprivation. And although sleep deprived subjects showed expected attentional lapses, these could not account for impairments in reversal learning decision making.ConclusionsSleep deprivation is particularly problematic for decision making involving uncertainty and unexpected change. Blunted reactions to feedback while sleep deprived underlie failures to adapt to uncertainty and changing contingencies. Thus, an error may register, but with diminished effect because of reduced affective valence of the feedback or because the feedback is not cognitively bound with the choice. This has important implications for understanding and managing sleep loss-induced cognitive impairment in emergency response, disaster management, military operations, and other dynamic real-world settings with uncertain outcomes and imperfect information.

Project description:BackgroundCollective intelligence, facilitated by information technology or manual techniques, refers to the collective insight of groups working on a task and has the potential to generate more accurate information or decisions than individuals can make alone. This concept is gaining traction in healthcare and has potential in enhancing diagnostic accuracy. We aim to characterize the current state of research with respect to collective intelligence in medical decision-making and describe a framework for diverse studies in this topic.MethodsFor this systematic scoping review, we conducted a systematic search for published literature using PubMed, Embase, Web of Science, and CINAHL on August 8, 2017. We included studies that combined the insights of two or more medical experts to make decisions related to patient care. Studies that examined medical decisions such as diagnosis, treatment, and management in the context of an actual or theoretical patient case were included. We include studies of complex medical decision-making rather than identification of a visual finding, as in radiology or pathology. We differentiate between medical decisions, in which synthesis of multiple types of information is required over time, and studies of radiological scans or pathological specimens, in which objective identification of a visual finding is performed. Two reviewers performed article screening, data extraction, and final inclusion for analysis.ResultsOf 3303 original articles, 15 were included. Each study examined the medical decisions of two or more individuals; however, studies were heterogeneous in their methods and outcomes. We present a framework to characterize these diverse studies, and future investigations, based on how they operationalize collective intelligence for medical decision-making: 1) how the initial decision task was completed (group vs. individual), 2) how opinions were synthesized (information technology vs. manual vs. in-person), and 3) the availability of collective intelligence to participants.DiscussionCollective intelligence in medical decision-making is gaining popularity to advance medical decision-making and holds promise to improve patient outcomes. However, heterogeneous methods and outcomes make it difficult to assess the utility of collective intelligence approaches across settings and studies. A better understanding of collective intelligence and its applications to medicine may improve medical decision-making.

Project description:ObjectivesTo (1) provide an up-to-date overview of shared decision making (SDM)-models, (2) give insight in the prominence of components present in SDM-models, (3) describe who is identified as responsible within the components (patient, healthcare professional, both, none), (4) show the occurrence of SDM-components over time, and (5) present an SDM-map to identify SDM-components seen as key, per healthcare setting.DesignSystematic review.Eligibility criteriaPeer-reviewed articles in English presenting a new or adapted model of SDM.Information sourcesAcademic Search Premier, Cochrane, Embase, Emcare, PsycINFO, PubMed, and Web of Science were systematically searched for articles published up to and including September 2, 2019.ResultsForty articles were included, each describing a unique SDM-model. Twelve models were generic, the others were specific to a healthcare setting. Fourteen were based on empirical data, 26 primarily on analytical thinking. Fifty-three different elements were identified and clustered into 24 components. Overall, Describe treatment options was the most prominent component across models. Components present in >50% of models were: Make the decision (75%), Patient preferences (65%), Tailor information (65%), Deliberate (58%), Create choice awareness (55%), and Learn about the patient (53%). In the majority of the models (27/40), both healthcare professional and patient were identified as actors. Over time, Describe treatment options and Make the decision are the two components which are present in most models in any time period. Create choice awareness stood out for being present in a markedly larger proportion of models over time.ConclusionsThis review provides an up-to-date overview of SDM-models, showing that SDM-models quite consistently share some components but that a unified view on what SDM is, is still lacking. Clarity about what SDM constitutes is essential though for implementation, assessment, and research purposes. A map is offered to identify SDM-components seen as key.Trial registrationPROSPERO registration CRD42015019740.

Project description:ObjectivesCognitive and other biases can influence the quality of healthcare decision making. While substantial research has explored how biases can lead to diagnostic or other errors in medicine, fewer studies have examined how they impact the decision making of other healthcare professionals. This scoping review aimed to identify and synthesise a broad range of research investigating whether decisions made by allied health professionals are influenced by cognitive, affective or other biases.Materials and methodsA systematic literature search was conducted in five electronic databases. Title, abstract and full text screening was undertaken in duplicate, using prespecified eligibility criteria designed to identify studies attempting to demonstrate the presence of bias when allied healthcare professionals make decisions. A narrative synthesis was undertaken, focussing on the type of allied health profession, type of decision, and type of bias reported within the included studies.ResultsThe search strategy identified 149 studies. Of these, 119 studies came from the field of psychology, with substantially fewer from social work, physical and occupational therapy, speech pathology, audiology and genetic counselling. Diagnostic and assessment decisions were the most common decision types, with fewer studies assessing treatment, prognostic or other clinical decisions. Studies investigated the presence of over 30 cognitive, affective and other decision making biases, including stereotyping biases, anchoring, and confirmation bias. Overall, 77% of the studies reported at least one outcome that represented the presence of a bias.ConclusionThis scoping review provides an overview of studies investigating whether decisions made by allied health professionals are influenced by cognitive, affective or other biases. Biases have the potential to seriously impact the quality, consistency and accuracy of decision making in allied health practice. The findings highlight a need for further research particularly in professional disciplines outside of psychology, using methods that reflect real life healthcare decision making.

Project description:This scoping review identifies and describes the methods used to prioritize diseases for resource allocation across disease control, surveillance, and research and the methods used generally in decision-making on animal health policy. Three electronic databases (Medline/PubMed, Embase, and CAB Abstracts) were searched for articles from 2000 to 2021. Searches identified 6, 395 articles after de-duplication, with an additional 64 articles added manually. A total of 6, 460 articles were imported to online document review management software (sysrev.com) for screening. Based on inclusion and exclusion criteria, 532 articles passed the first screening, and after a second round of screening, 336 articles were recommended for full review. A total of 40 articles were removed after data extraction. Another 11 articles were added, having been obtained from cross-citations of already identified articles, providing a total of 307 articles to be considered in the scoping review. The results show that the main methods used for disease prioritization were based on economic analysis, multi-criteria evaluation, risk assessment, simple ranking, spatial risk mapping, and simulation modeling. Disease prioritization was performed to aid in decision-making related to various categories: (1) disease control, prevention, or eradication strategies, (2) general organizational strategy, (3) identification of high-risk areas or populations, (4) assessment of risk of disease introduction or occurrence, (5) disease surveillance, and (6) research priority setting. Of the articles included in data extraction, 50.5% had a national focus, 12.3% were local, 11.9% were regional, 6.5% were sub-national, and 3.9% were global. In 15.2% of the articles, the geographic focus was not specified. The scoping review revealed the lack of comprehensive, integrated, and mutually compatible approaches to disease prioritization and decision support tools for animal health. We recommend that future studies should focus on creating comprehensive and harmonized frameworks describing methods for disease prioritization and decision-making tools in animal health.

Dataset Information

Risk-Based Decision Making: A Systematic Scoping Review of Animal Models and a Pilot Study on the Effects of Sleep Deprivation in Rats.

Publications

Risk-Based Decision Making: A Systematic Scoping Review of Animal Models and a Pilot Study on the Effects of Sleep Deprivation in Rats.

Similar Datasets

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