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PubMedDate not supplied

Heuristics reasoning in diagnostic judgment.

Heuristics inquiry is an exciting new approach to understanding diagnostic reasoning. Heuristics are short-cut mental strategies that streamline information. Although heuristics allow for faster processing of information than analytic methods, they can lead to errors because not all information is considered. This article describes three heuristics particularly relevant to diagnostic reasoning: accessibility, similarity, and anchoring and adjustment. Specific factors thought to influence heuristic reasoning are reviewed and analyzed. Last, interventions to be tested for both practice and education are presented.

Clinical Competence↗
PubMed2005

Moral heuristics.

With respect to questions of fact, people use heuristics--mental short-cuts, or rules of thumb, that generally work well, but that also lead to systematic errors. People use moral heuristics too--moral short-cuts, or rules of thumb, that lead to mistaken and even absurd moral judgments. These judgments are highly relevant not only to morality, but to law and politics as well. examples are given from a number of domains, including risk regulation, punishment, reproduction and sexuality, and the act/omission distinction. in all of these contexts, rapid, intuitive judgments make a great deal of sense, but sometimes produce moral mistakes that are replicated in law and policy. One implication is that moral assessments ought not to be made by appealing to intuitions about exotic cases and problems; those intuitions are particularly unlikely to be reliable. Another implication is that some deeply held moral judgments are unsound if they are products of moral heuristics. The idea of error-prone heuristics is especially controversial in the moral domain, where agreement on the correct answer may be hard to elicit; but in many contexts, heuristics are at work and they do real damage. Moral framing effects, including those in the context of obligations to future generations, are also discussed.

Decision Making↗
PubMedDate not supplied

Quantitative prediction of logk of peptides in high-performance liquid chromatography based on molecular descriptors by using the heuristic method and support vector machine.

A new method support vector machine (SVM) and the heuristic method (HM) were used to develop the nonlinear and linear models between the capacity factor (logk) and seven molecular descriptors of 75 peptides for the first time. The molecular descriptors representing the structural features of the compounds only included the constitutional and topological descriptors, which can be obtained easily without optimizing the structure of the molecule. The seven molecular descriptors selected by the heuristic method in CODESSA were used as inputs for SVM. The results obtained by SVM were compared with those obtained by the heuristic method. The prediction result of the SVM model is better than that of heuristic method. For the test set, a predictive correlation coefficient R = 0.9801 and root-mean-square error of 0.1523 were obtained. The prediction results are in very good agreement with the experimental values. But the linear model of the heuristic method is easier to understand and ready to use for a chemist. This paper provided a new and effective method for predicting the chromatography retention of peptides and some insight into the structural features which are related to the capacity factor of peptides.

Artificial Intelligence↗
PubMed2002

The use of heuristics during route planning by expert and novice orienteers.

Expert orienteers have reported using two heuristics when planning routes to points in the environment that must be located, known as 'controls'. These heuristics constitute attending to the start first and subsequently planning forward to a given control, and attending to the control first and planning backwards to the start. The aim of this study was to establish which heuristic experts use predominantly and whether novices' use of these heuristics differs from that of experts. Two methods for tracing attention were used while 20 expert and 20 novice orienteers planned routes in the laboratory. The results were used to infer the use of heuristics. The orienteers were also interviewed about planning. We found that, when planning, experts generally attend to the control first and novices to the start first. There was also some evidence that novices work forwards from the start to the control and that experts work backwards from the control to the start. From the interviews, it would appear that experts regard the location of the control as the crux of the problem and prioritize this area during planning. These results have implications for an understanding of expertise and problem-solving in sport.

Adult↗
PubMed2007

A greedy heuristic using adjoint functions for the optimization of seed and needle configurations in prostate seed implant.

We continue our work on the development of an efficient treatment-planning algorithm for prostate seed implants by incorporation of an automated seed and needle configuration routine. The treatment-planning algorithm is based on region of interest (ROI) adjoint functions and a greedy heuristic. As defined in this work, the adjoint function of an ROI is the sensitivity of the average dose in the ROI to a unit-strength brachytherapy source at any seed position. The greedy heuristic uses a ratio of target and critical structure adjoint functions to rank seed positions according to their ability to irradiate the target ROI while sparing critical structure ROIs. Because seed positions are ranked in advance and because the greedy heuristic does not modify previously selected seed positions, the greedy heuristic constructs a complete seed configuration quickly. Isodose surface constraints determine the search space and the needle constraint limits the number of needles. This study additionally includes a methodology that scans possible combinations of these constraint values automatically. This automated selection scheme saves the user the effort of manually searching constraint values. With this method, clinically acceptable treatment plans are obtained in less than 2 min. For comparison, the branch-and-bound method used to solve a mixed integer-programming model took close to 2.5 h to arrive at a feasible solution. Both methods achieved good treatment plans, but the speedup provided by the greedy heuristic was a factor of approximately 100. This attribute makes this algorithm suitable for intra-operative real-time treatment planning.

Algorithms↗
PubMedDate not supplied

The application of the heuristic-systematic processing model to treatment decision making about prostate cancer.

The study investigated the utility of the Heuristic-Systematic Processing Model as a framework for the investigation of patient decision making. A total of 111 men recently diagnosed with localized prostate cancer were assessed using Verbal Protocol Analysis and self-report measures. Study variables included men's use of nonsystematic and systematic information processing, desire for involvement in decision making, and the individual differences of health locus of control, tolerance of ambiguity, and decision-related uncertainty. Most men (68%) preferred that decision making be shared equally between them and their doctor. Men's use of the expert opinion heuristic was related to men's verbal reports of decisional uncertainty and having a positive orientation to their doctor and medical care; a desire for greater involvement in decision making was predicted by a high internal locus of health control. Trends were observed for systematic information processing to increase when the heuristic strategy used was negatively affect laden and when men were uncertain about the probabilities for cure and side effects. There was a trend for decreased systematic processing when the expert opinion heuristic was used. Findings were consistent with the Heuristic-Systematic Processing Model and suggest that this model has utility for future research in applied decision making about health.

Adult↗
PubMed1980

Algorithmic and heuristic processing of information by the nervous system.

Starting from the fact that the nervous system must discover the information it needs, the author describes the way it decodes the received message. The logical circuits of the nervous system, submitting the received signals to a process by means of which information brought is discovered step by step, participates in decoding the message. The received signals, as information, can be algorithmically or heuristically processed. Algorithmic processing is done according to precise rules, which must be fulfilled step by step. By algorithmic processing, one develops somatic and vegetative reflexes as blood pressure, heart frequency or water metabolism control. When it does not dispose of precise rules of information processing or when algorithmic processing needs a very long time, the nervous system must use heuristic processing. This is the feature that differentiates the human brain from the electronic computer that can work only according to some extremely precise rules. The human brain can work according to less precise rules because it can resort to trial and error operations, and because it works according to a form of logic. Working with superior order signals which represent the class of all inferior type signals from which they begin, the human brain need not perform all the operations that it would have to perform by superior type of signals. Therefore the brain tries to submit the received signals to intensive as possible superization. All informational processing, and especially heuristical processing, is accompanied by a certain affective color and the brain cannot operate without it. Emotions, passions and sentiments usually complete the lack of precision of the heuristical programmes. Finally, the author shows that informational and especially heuristical processes study can contribute to a better understanding of the transition from neurological to psychological activity.

Cybernetics↗
PubMed2006

Heuristic evaluation of a Web-based Educational Resource for low literacy NICU parents.

"Web-based Educational Resources for the NICU Parent," an educational website for low literacy families, was developed and implemented as prototype web pages using Macromedia Dreamweaver MX. Research has shown that evaluating a website before its implementation can reduce usability errors and improve the overall interface design. As an initial assessment of the website's interface, a heuristic evaluation was conducted with a sample of three usability experts. The usability experts reviewed the website with typical case scenario and completed an evaluation form covering ten usability heuristics. The task was completed in approximately one and a half hours; 82 heuristic violations were reported. The heuristic violations noted on the evaluation forms and the experts' verbalizations captured by a usability testing tool (Morae) were content analyzed and categorized based on the potential design solutions to be implemented: function, design and layout, content, and navigation. Approximately 88% of the violations were resolved by implementing these solutions. The study findings suggest that the heuristic evaluation was an efficient and inexpensive method for evaluating the low literacy interface of the "Web-based Educational Resources for the NICU Parent."

Comprehension↗
PubMed1985

Differential diagnosis and the competing-hypotheses heuristic. A practical approach to judgment under uncertainty and Bayesian probability.

Evaluating the same diagnostic information across the plausible competing diagnoses is a practical strategy (ie, heuristic) to guide decision making in the face of uncertainty. The prevalence of use of this competing-hypotheses heuristic by 89 first-year house officers was examined in three simulated patient cases. Results indicated that only a minority (24%) of the house officers selected optimal diagnostic information consistent with this Bayesian heuristic across all three cases. Almost all (97%) of the house officers selecting optimal diagnostic information were able to identify the most probable diagnosis specified by Bayes' theorem, while only a chance number (53%) of house officers selecting nonoptimal information were able to identify the most probable diagnosis. The competing-hypotheses heuristic is discussed within the context of diagnostic problem-solving models derived from the literature on medical decision making and clinicopathological conference case records. It is suggested that the heuristic, which does not necessitate any mathematical calculations, may be useful as a complement to clinical judgment.

Bayes Theorem↗
PubMed2003

Heuristic charge assignment for deconvolution of electrospray ionization mass spectra.

We propose a new algorithm for deconvolution of electrospray ionization mass spectra based on direct assignment of charge to the measured signal at each mass-to-charge ratio (m/z). We investigate two heuristics for charge assignment: the entropy-based heuristic is adapted from a deconvolution algorithm by Reinhold and Reinhold;10 the multiplicative-correlation heuristic is adapted from the multiplicative-correlation deconvolution algorithm of Hagen and Monnig.6 The entropy-based heuristic is insensitive to overestimates of z(max), the maximum ion charge. We test the deconvolution algorithm on two single-component samples: the measured spectrum of human beta-endorphin has two prominent and one very weak line whereas myoglobin has a well-developed quasi-gaussian envelope of 17 peaks. In both cases, the deconvolution algorithm gives a clean deconvoluted spectrum with one dominant peak and very few artefacts. The relative heights of the peaks due to the parent molecules in the deconvoluted spectrum of a mixture of two peptides, which are expected to ionize with equal efficiency, give an accurate measure of their relative concentration in the sample.

Algorithms↗
PubMed1998

The list heuristic for studying personality correlates of food choice behaviour: a review and results from two samples.

Over the past half century, a methodology has been used to investigate predictors of eating behaviour which involves the use of a list of foods, with subjects answering some preference question(s) about each food. For each person, the number of foods which elicit a particular response, usually of rejection, is used as a psychometric measure of their eating behaviour. We refer to this as the list heuristic. There has been great variability in the exact design used and comparing across studies is difficult. We tackle this issue by comparing "sublists" within one study. Previous list heuristic studies have found a link between behaviour and both anxiety and sensation seeking. Food choice behaviours can also be studied through psychometric questionnaires of more traditional design. Such studies have produced similar results and suggest a distinction between neophobia and general "pickiness". The list heuristic is used here in two studies. Our results are notably different, finding no relationships with anxiety and only weak relationships with sensation seeking. Further, results concerning food neophobia measures (list heuristic and questionnaire) suggest problems in differentiating food neophobia from more general food rejection behavior.

Adolescent↗
PubMed1999

The probability heuristics model of syllogistic reasoning.

A probability heuristic model (PHM) for syllogistic reasoning is proposed. An informational ordering over quantified statements suggests simple probability based heuristics for syllogistic reasoning. The most important is the "min-heuristic": choose the type of the least informative premise as the type of the conclusion. The rationality of this heuristic is confirmed by an analysis of the probabilistic validity of syllogistic reasoning which treats logical inference as a limiting case of probabilistic inference. A meta-analysis of past experiments reveals close fits with PHM. PHM also compares favorably with alternative accounts, including mental logics, mental models, and deduction as verbal reasoning. Crucially, PHM extends naturally to generalized quantifiers, such as Most and Few, which have not been characterized logically and are, consequently, beyond the scope of current mental logic and mental model theories. Two experiments confirm the novel predictions of PHM when generalized quantifiers are used in syllogistic arguments. PHM suggests that syllogistic reasoning performance may be determined by simple but rational informational strategies justified by probability theory rather than by logic.

Algorithms↗
PubMed1991

Heuristic determination of quantitative data for knowledge acquisition in medicine.

Knowledge acquisition for medical knowledge bases can be aided by programs that suggest possible values for portions of the data. The paper presents an experiment which was used in designing a heuristic to help the process of knowledge acquisition. The heuristic helps to determine numerical data from stylized literature excerpts in the context of knowledge acquisition for the QMR medical knowledge base. Quantitative suggestions from the heuristics are shown to agree substantially with the data incorporated in the final version of the knowledge base. The experiment shows the potential of knowledge base specific heuristics in simplifying the task of knowledge base creation.

Artificial Intelligence↗
PubMed2006

Reasoning under uncertainty: heuristic judgments in patients with persecutory delusions or depression.

OBJECTIVE: The substantial literature examining social reasoning in people with delusions has, to date, neglected the commonest form of decision making in daily life. We address this imbalance by reporting here the findings of the first study to explore heuristic reasoning in people with persecutory delusions. METHOD: People with active or remitted paranoid delusions, depressed and healthy adults performed two novel heuristic reasoning tasks that varied in emotional valence. RESULTS: The findings indicated that people with persecutory delusions displayed biases during heuristic reasoning that were most obvious when reasoning about threatening and positive material. Clear similarities existed between the currently paranoid group and the depressed group in terms of their reasoning about the likelihood of events happening to them, with both groups tending to believe that pleasant things would not happen to them. However, only the currently paranoid group showed an increased tendency to view other people as threatening. CONCLUSION: This study has initiated the exploration of heuristic reasoning in paranoia and depression. The findings have therapeutic utility and future work could focus on the differentiation of paranoia and depression at a cognitive level.

Adult↗
PubMed1999

Heuristic-systematic information processing and risk judgment.

The heuristic-systematic information processing model (HSM) holds that individuals will use one or both of these modes of information processing when attempting to evaluate information in order to arrive at a judgment. Systematic processing is defined by effortful scrutiny and comparison of information, whereas heuristic processing is defined by the use of cues to arrive more easily at a judgment. Antecedents to the two processing modes include information sufficiency, motivation, and self-efficacy. Structural equation modeling is used to examine competing configuration of this model and to evaluate the model as appropriate for predicting risk judgment. The model also is evaluated across three groups that vary with respect to their level of concern. These analyses are executed within a case study involving an epidemiological investigation of a suspected cancer cluster. The analysis confirms the HSM's theoretically proposed structure and shows it to be a useful vehicle for evaluating risk judgment. In the overall analysis, antecedent variables generally function as specified by theory. Systematic processing is predicted by greater motivation. Heuristic processing is predicted by information sufficiency. Self-efficacy is a significant predictor of both processing modes. And heuristic processing is shown to be associated with judgment of less risk. However, when the analysis is contrasted across three groups (those concerned about cancer, not concerned and uncertain) it is shown that the model is significantly more robust for the uncertain group. This finding may have implications for the use of the HSM in risk research specifically, and in field research generally.

Analysis of Variance↗
PubMed2005

How forgetting aids heuristic inference.

Some theorists, ranging from W. James (1890) to contemporary psychologists, have argued that forgetting is the key to proper functioning of memory. The authors elaborate on the notion of beneficial forgetting by proposing that loss of information aids inference heuristics that exploit mnemonic information. To this end, the authors bring together 2 research programs that take an ecological approach to studying cognition. Specifically, they implement fast and frugal heuristics within the ACT-R cognitive architecture. Simulations of the recognition heuristic, which relies on systematic failures of recognition to infer which of 2 objects scores higher on a criterion value, demonstrate that forgetting can boost accuracy by increasing the chances that only 1 object is recognized. Simulations of the fluency heuristic, which arrives at the same inference on the basis of the speed with which objects are recognized, indicate that forgetting aids the discrimination between the objects' recognition speeds.

Cognition↗
PubMed2006

The priority heuristic: making choices without trade-offs.

Bernoulli's framework of expected utility serves as a model for various psychological processes, including motivation, moral sense, attitudes, and decision making. To account for evidence at variance with expected utility, the authors generalize the framework of fast and frugal heuristics from inferences to preferences. The priority heuristic predicts (a) the Allais paradox, (b) risk aversion for gains if probabilities are high, (c) risk seeking for gains if probabilities are low (e.g., lottery tickets), (d) risk aversion for losses if probabilities are low (e.g., buying insurance), (e) risk seeking for losses if probabilities are high, (f) the certainty effect, (g) the possibility effect, and (h) intransitivities. The authors test how accurately the heuristic predicts people's choices, compared with previously proposed heuristics and 3 modifications of expected utility theory: security-potential/aspiration theory, transfer-of-attention-exchange model, and cumulative prospect theory.

Attention↗
PubMed2006

On the psychology of the recognition heuristic: retrieval primacy as a key determinant of its use.

The recognition heuristic is a prime example of a boundedly rational mind tool that rests on an evolved capacity, recognition, and exploits environmental structures. When originally proposed, it was conjectured that no other probabilistic cue reverses the recognition-based inference (D. G. Goldstein & G. Gigerenzer, 2002). More recent studies challenged this view and gave rise to the argument that recognition enters inferences just like any other probabilistic cue. By linking research on the heuristic with research on recognition memory, the authors argue that the retrieval of recognition information is not tantamount to the retrieval of other probabilistic cues. Specifically, the retrieval of subjective recognition precedes that of an objective probabilistic cue and occurs at little to no cognitive cost. This retrieval primacy gives rise to 2 predictions, both of which have been empirically supported: Inferences in line with the recognition heuristic (a) are made faster than inferences inconsistent with it and (b) are more prevalent under time pressure. Suspension of the heuristic, in contrast, requires additional time, and direct knowledge of the criterion variable, if available, can trigger such suspension.

Adult↗