Source code is a form of human communication, albeit one where the information shared between the programmers reading and writing the code is constrained by the requirement that the code executes correctly. Programming languages are more syntactically constrained than natural languages, but they are also very expressive, allowing a great many different ways to express even very simple computations. Still, code written by developers is highly predictable, and many programming tools have taken advantage of this phenomenon, relying on language model (...) surprisal as a guiding mechanism. While surprisal has been validated as a measure of cognitive load in natural language, its relation to human cognitive processes in code is still poorly understood. In this paper, we explore the relationship between surprisal and programmer preference at a small granularity—do programmers prefer more predictable expressions in code? Using meaning‐preserving transformations, we produce equivalent alternatives to developer‐written code expressions and run a corpus study on Java and Python projects. In general, language models rate the code expressions developers choose to write as more predictable than these transformed alternatives. Then, we perform two human subject studies asking participants to choose between two equivalent snippets of Java code with different surprisal scores (one original and transformed). We find that programmers do prefer more predictable variants, and that stronger language models like the transformer align more often and more consistently with these preferences. (shrink)

In their contribution ‘Ethics of the algorithmic prediction of goal of care preferences’1 Ferrario et al elaborate a from theory to practice contribution concerning the realisation of artificial intelligence (AI)-based patient preference prediction (PPP) systems. Such systems are intended to help find the treatment that the patient would have chosen in clinical situations—especially in the intensive care or emergency units—where the patient is no longer capable of making that decision herself. The authors identify several challenges that complicate (...) their effective development, application and evaluation—and offer solutions to them. One of these issues is the question of who should ultimately use said systems. While it is undisputed that clinicians should use these AI systems for their decision-making process, there is an ongoing debate about whether next of kin should use them as well. The authors advocate that ‘’access should be provided to both clinicians and loved ones with due explanations and as desired’. We will disagree with this assessment and explain in our commentary why it is important that surrogates provide their own assessments with as little external (AI) influence as possible. Why do next of kin actually participate in the process of preference finding and treatment decision-making? A key reason is that clinicians usually …. (shrink)

In our recent article ‘The Ethics of the Algorithmic Prediction of Goal of Care Preferences: From Theory to Practice’1, we aimed to ignite a critical discussion on why and how to design artificial intelligence (AI) systems assisting clinicians and next-of-kin by predicting goal of care preferences for incapacitated patients. Here, we would like to thank the commentators for their valuable responses to our work. We identified three core themes in their commentaries: (1) the risks of AI paternalism, (2) worries (...) about attacks to our humanity stemming from the use of AI and (3) the possibility of designing AI systems for more relevant use cases than the one we consider in our work. We shall focus on these themes, leaving aside some other interesting suggestions, given the limited space available for our response. Diaz Milian and Bhattacharyya discuss the risks of AI paternalism highlighting how the use of an AI to predict goal of care preferences may incentivise clinicians and surrogates to shift the burden of decision making to the machine.2 In particular, ‘[i]f the AI-generated response is given priority above the other agents’2 and the AI makes decisions autonomously, then ‘AI paternalism’ would emerge.2 Against this possibility, the authors suggest four safeguards to be implemented in the AI life-cycle.2 These are procedures that may improve the trustworthiness of the AI and human control over it.3 We agree that it is important …. (shrink)

The use of machine learning, or “artificial intelligence” (AI) in medicine is widespread and growing. In this paper, I focus on a specific proposed clinical application of AI: using models to predict incapacitated patients’ treatment preferences. Drawing on results from machine learning, I argue this proposal faces a special moral problem. Machine learning researchers owe us assurance on this front before experimental research can proceed. In my conclusion I connect this concern to broader issues in AI safety.

Rid and Wendler propose the development of a Patient Preference Predictor (PPP), an actuarial model for predicting incapacitated patient’s life-sustaining treatment preferences across a wide range of end-of-life scenarios. An actuarial approach to end-of-life decision making has enormous potential, but transferring the logic of actuarial prediction to end-of-life decision making raises several conceptual complexities and logistical problems that need further consideration. Actuarial models have proven effective in targeted prediction tasks, but no evidence supports their effectiveness in the (...) kind of broad spectrum prediction task that is the proposed goal of the PPP. We argue that a more focused approach, targeting specific medical conditions and generating treatment predictions based on the preferences of individuals with actual disease experience, is both more firmly grounded in past research and is a more prudent initial strategy for exploring the efficacy of actuarial prediction in end-of-life decision making. (shrink)

Experimental studies have suggested that variables such as aptness or conventionality are predictors of people’s preference for expressing a particular topic–vehicle pair as either a metaphor or a simile. In the present study, we investigated if such variables would also be predictive within a more naturalistic context, where other variables, such as the intention to include an explanation, may also influence people’s decision. Specifically, we investigated the production of metaphor and simile expressions on the Internet via the Google search (...) engine and checked for accompanying explanations, as well as the properties they expressed, to examine whether ratings such as aptness, conventionality, as well as participants’ own stated preference or the intention to produce an explanation, would predict which topic–vehicle pairs appeared more often as metaphor. We found that participants’ stated preference predicted metaphor dominance on the Internet, and that apt topic–vehicles occurred more often as metaphors. The explanations collected, however, occurred 82% of the time after similes, and familiar expressions were the most explained. Finally, comparing the properties expressed in these explanations to normed property lists, we found that simile explanations typically expressed a novel conception of the topic–vehicle relationship. Therefore, we found that Internet posters use metaphors to convey an apt relationship, as found in previous laboratory studies, but prefer using a simile frame when they want to express a relationship that readers will find novel. (shrink)

Artificial intelligence (AI) systems are quickly gaining ground in healthcare and clinical decision-making. However, it is still unclear in what way AI can or should support decision-making that is based on incapacitated patients’ values and goals of care, which often requires input from clinicians and loved ones. Although the use of algorithms to predict patients’ most likely preferred treatment has been discussed in the medical ethics literature, no example has been realised in clinical practice. This is due, arguably, to the (...) lack of a structured approach to the epistemological, ethical and pragmatic challenges arising from the design and use of such algorithms. The present paper offers a new perspective on the problem by suggesting that preference predicting AIs be viewed as sociotechnical systems with distinctive life-cycles. We explore how both known and novel challenges map onto the different stages of development, highlighting interdisciplinary strategies for their resolution. (shrink)

The accuracy of proxies when they interpret advance directives or apply substituted decision-making criteria has been called into question. It therefore became important to know if the Andalusian Advance Directive Form (AADF) can help to increase the accuracy of proxies' predictions. The aim of this research was to compare the effect of the AADF on the accuracy of proxies' predictions about patients' preferences with that gained from informative and deliberative sessions about end-of-life decision making. A total of 171 pairs of (...) patients and their proxies were randomized to three groups. The control group's answers to the Life Sustaining Preferences Questionnaire (LSPQ) were compared with their proxies' answers to the same questionnaire. In one intervention group, the patients had already completed the AADF and given it to their proxies, who used it to guide their own answers to the LSPQ. In the second intervention (discussion) group, both patients and proxies attended two educative sessions guided by trained nurses and later filled in the LSPQ. Comparisons of accuracy and other variables showed a strong association with the discussion group. The findings show that promoting communication between patients and their proxies improves the accuracy of proxies' predictions much more than isolated use of the AADF form. (shrink)

In this paper, we analyse higher-order risky choices by the representative cumulative prospect theory (CPT) decision maker from three alternative reference points. These are the status quo, average payout and maxmin. The choice tasks we consider in our analysis include binary risks, and are the ones employed in the experimental literature on higher order risk preferences. We demonstrate that the choices made by the representative subject depend on the reference point. If the reference point is the status quo and the (...) lottery choices exhibit symmetric risk, we demonstrate that there is no third order reflection effect of lottery choices but there is a fourth order reflection effect. When the average payout is the reference point, we demonstrate that any third or fourth order lottery choice is possible dependent upon the lottery payoffs. However, under the assumption of maxmin reference point, the risky choices are prudent and temperate. In addition to these results, our analysis reveals that the representative CPT subject can choose combinations of second with third and fourth order risky options that differ from those in other major models of decision under risk. We contrast our theoretical predictions with the empirical results reported in the literature on higher order risk preferences and are able to reconcile some conflicting experimental evidence. (shrink)

Background This study introduces an empirical approach for studying the role of prudence in physician treatment of end-of-life (EOL) decision making.Methods A mixed-methods analysis of transcripts from 88 simulated patient encounters in a multicenter study on EOL decision making. Physicians in internal medicine, emergency medicine, and critical care medicine were asked to evaluate a decompensating, end-stage cancer patient. Transcripts of the encounters were coded for actor, action, and content to capture the concept of Aristotelian prudence, and then quantitatively and qualitatively (...) analyzed to identify actions associated with preference-concordant treatment.Results Focusing on codes that describe characteristics of physician-patient interaction, the code for physicians restating patient preferences was associated with avoiding intubation. Multiple codes were associated with secondary measures of preference-concordant treatment.Conclusions Prudent actions can be identified empirically, and research focused on the virtue of prudence may provide a new avenue for assessment and training in EOL care. (shrink)

Philosophers working on time-biases assume that people are hedonically biased toward the future. A hedonically future-biased agent prefers pleasurable experiences to be future instead of past, and painful experiences to be past instead of future. Philosophers further predict that this bias is strong enough to apply to unequal payoffs: people often prefer less pleasurable future experiences to more pleasurable past ones, and more painful past experiences to less painful future ones. In addition, philosophers have predicted that future-bias is restricted to (...) first-person preferences, and that people’s third-person preferences are time-neutral. Philosophers disagree vigorously about the normative status of these preferences—i.e., they disagree about whether first-person future-bias is rationally permissible. Time-neutralists, for example, have appealed to the predicted asymmetry between first- and third-person preferences to argue for the rational impermissibility of future-bias. We empirically tested these predictions, and found that while people do prefer more past pain to less future pain, they do not prefer less future pleasure to more past pleasure. This was so in both first and third-person conditions. This suggests that future-bias is typically non-absolute, and is more easily outweighed in the case of positive events. We connect this result to the normative debate over future-bias. (shrink)

Leveraging a massive dataset of over 400 million potential matches between single heterosexuals on a leading mobile dating application we were able to identify numerous characteristics of effective matching. Effective matching is defined as the exchange of contact information with the intent to meet in person. The characteristics of effective match include alignment of psychological traits (i.e. extroversion), physical traits (i.e. height), personal choices (i.e., the relationship type they desired), and shared experiences. For nearly all characteristics, the more similar the (...) individuals were the higher the likelihood of them finding each other desirable and opting to meet in person. The only exception was introversion, where introverts rarely had an effective match with other introverts. Additionally, we investigated the preliminary stages of the choice process. We looked at the consistency between the choice of men/women, the time it took users to make these binary choices and the tendency of yes/no decisions. We used a biologically-inspired choice model to estimate the time allotted to a decision and could predict the decision and response time with nearly 60% accuracy. Given that people make their initial selection within no more than 11 seconds and ultimately converge to a partner who shares numerous attributes with them, we suggest that users are less selective in their early preferences and gradually converge to clusters with high degree of similarity in characteristics during their conversation. (shrink)

This book is about preferences, principally as they figure in economics. It also explores their uses in everyday language and action, how they are understood in psychology and how they figure in philosophical reflection on action and morality. The book clarifies and for the most part defends the way in which economists invoke preferences to explain, predict and assess behavior and outcomes. Hausman argues, however, that the predictions and explanations economists offer rely on theories of preference formation that are (...) in need of further development, and he criticizes attempts to define welfare in terms of preferences and to define preferences in terms of choices or self-interest. The analysis clarifies the relations between rational choice theory and philosophical accounts of human action. The book also assembles the materials out of which models of preference formation and modification can be constructed, and it comments on how reason and emotion shape preferences. (shrink)

The ways in which the decisions we make for others differ from the ones we make for ourselves has received much attention in the literature, although less is known about their relationship to our p...

What makes a human voice agreeable is a matter of scientific discussion. Whereas prosody was shown to play a role regarding “male-female” attraction, the impact of frequency modulations in “non-sexual”, notably commercial, contexts has attracted little attention. Another point unaddressed in the literature is auditory sensitivity to short-term frequency modulations as current studies focus more on sentence. Thirty French female operators were recorded over the phone. All “bonjour” greeting words were classified in terms of frequency modulation linearity and orientation at (...) the syllable and word levels. Then, the different voices were played back to students and seniors who had to rate each voice according to their degree of agreeableness. Listeners preferred non-monotonous voices. Differences between age-classes were greater than between sex-classes. Results suggest that short-term frequency changes are important for auditory evaluation of voice agreeableness. This study opens new research perspectives concerning the importance of prosody during consumer-seller interactions. (shrink)

There is broad anthropological interest in understanding how people define “insiders” and “outsiders” and how this shapes their attitudes and behaviors toward others. As such, a suite of hypotheses has been proposed to account for the varying degrees of in-group preference between individuals and societies. We test three hypotheses related to material insecurity, pathogen stress, and views of gender equality among cross-sectional and longitudinal samples of young people in Ethiopia to explore stability and change in their preferences for coethnic (...) spouses. We show that food insecurity is associated with a greater likelihood of intolerant mate preferences. We also find that young people who hold more gender equitable attitudes tended to hold more tolerant mate preferences. Finally, we find no support for the hypothesis that expected pathogen exposure is associated with intolerant mate preferences. Our results most strongly support a material insecurity hypothesis of in-group bias, which assumes that uncertainty over meeting basic needs leads people to favor those in their in-group. As such, our findings join a small but growing group of studies that highlight the importance of material insecurity for understanding tolerance, xenophobia, in-group bias, and favoritism. (shrink)

In general, the technical apparatus of decision theory is well developed. It has loads of theorems, and they can be proved from axioms. Many of the theorems are interesting, and useful both from a philosophical and a practical perspective. But decision theory does not have a well agreed upon interpretation. Its technical terms, in particular, ‘utility’ and ‘preference’ do not have a single clear and uncontroversial meaning. How to interpret these terms depends, of course, on what purposes in pursuit (...) of which one wants to put decision theory to use. One might want to use it as a model of economic decision-making, in order to predict the behavior of corporations or of the stock market. In that case, it might be useful to interpret the technical term ‘utility’ as meaning money profit. Decision theory would then be an empirical theory. I want to look into the question of what ‘utility’ could mean, if we want decision theory to function as a theory of practical rationality. I want to know whether it makes good sense to think of practical rationality as fully or even partly accounted for by decision theory. I shall lay my cards on the table: I hope it does make good sense to think of it that way. For, I think, if Humeans are right about practical rationality, then decision theory must play a very large part in their account. And I think Humeanism has very strong attractions. (shrink)

The finding that women are attracted to men older than themselves whereas men are attracted to relatively younger women has been explained by social psychologists in terms of economic exchange rooted in traditional sex-role norms. An alternative evolutionary model suggests that males and females follow different reproductive strategies, and predicts a more complex relationship between gender and age preferences. In particular, males' preferences for relatively younger females should be minimal during early mating years, but should become more pronounced as the (...) male gets older. Young females are expected to prefer somewhat older males during their early years and to change less as they age. We briefly review relevant theory and present results of six studies testing this prediction. Study 1 finds support for this gender-differentiated prediction in age preferences expressed in personal advertisements. Study 2 supports the prediction with marriage statistics from two U.S. cities. Study 3 examines the cross-generational robustness of the phenomenon, and finds the same pattern in marriage statistics from 1923. Study 4 replicates Study 1 using matrimonial advertisements from two European countries, and from India. Study 5 finds a consistent pattern in marriages recorded from 1913 through 1939 on a small island in the Philippines. Study 6 reveals the same pattern in singles advertisements placed by financially successful American women and men. We consider the limitations of previous normative and evolutionary explanations of age preferences and discuss the advantages of expanding previous models to include the life history perspective. (shrink)

: In this paper I argue that belief in the greater confirmatory value of prediction over accommodation can best be understood as a function of the practice rather than the logic of science. Attempts to account for this asymmetry within the logic of science have revealed no non-arbitrary way to address the problem of underdetermination as it applies to prediction and thus have failed to account for the preference for prediction over accommodation on logical grounds. Instead, (...) I propose a model that not only justifies and explains this preference, but allows for a richer taxonomy of the types of evidential confirmation that are employed in scientific reasoning. (shrink)

Why do people expend resources to vote in large-number situations where the probability of their affecting the outcome is close to zero? In a recent article, Geoffrey Brennan and Loren Lomasky argue provocatively that Adam Smith's The Theory of Moral Sentiments not only predicts such behavior, but further predicts that people “frequently” vote for outcomes that cost them more than they would individually be willing to pay. In other words, in the relevant environment, they claim that individuals will systematically express (...) false preferences for costly outcomes they “really” do not want. I submit that a fair reading of TMS in fact provides no basis for their view; if anything, TMS suggests the opposite. (shrink)

The models of internal self-control that have recently been proposed by behavioral economists do not depict motivational interaction that occurs while temptation is present. Those models that include willpower at all either envision a faculty with a motivation (“strength”) different from the motives that are weighed in the marketplace of choice, or rely on incompatible goals among diverse brain centers. Both assumptions are questionable, but these models’ biggest problem is that they do not let resolutions withstand re-examination while being challenged (...) by impulsive alternatives. The economists’ models all attempt to make a single equilibrium preference predictable from a person’s prior incentives. This was the original purpose of these models’ hyperboloid (“β–δ”) delay discount functions, which have been widely justified by the assumption that a person’s intertemporal inconsistency (impulsiveness) can be accounted for by the arousal of appetite for visceral rewards. Although arousal is clearly a factor in some cases of intertemporal inconsistency, it cannot be blamed for others, and furthermore does not necessarily imply hyperboloid discounting. The inadequacy of β–δ functions is particularly evident in models of internal self-control. I have reviewed several of these models, and have argued for a return to pure hyperbolic discount function as originally proposed, the relatively high tails of which can motivate a recursive process of self-prediction and thereby the formation of self-enforcing intertemporal contracts. Such a process does not require a separately motivated faculty of will, or incompatible goals among brain centers; but it also does not permit the prediction of unique preferences from prior incentives. (shrink)

Neuromarketing has gained attention to bridge the gap between conventional marketing studies and electroencephalography -based brain-computer interface research. It determines what customers actually want through preference prediction. The performance of EEG-based preference detection systems depends on a suitable selection of feature extraction techniques and machine learning algorithms. In this study, We examined preference detection of neuromarketing dataset using different feature combinations of EEG indices and different algorithms for feature extraction and classification. For EEG feature extraction, we (...) employed discrete wavelet transform and power spectral density, which were utilized to measure the EEG-based preference indices that enhance the accuracy of preference detection. Moreover, we compared deep learning with other traditional classifiers, such as k-nearest neighbor, support vector machine, and random forest. We also studied the effect of preference indicators on the performance of classification algorithms. Through rigorous offline analysis, we investigated the computational intelligence for preference detection and classification. The performance of the proposed deep neural network outperforms KNN and SVM in accuracy, precision, and recall; however, RF achieved results similar to those of the DNN for the same dataset. (shrink)

When making substituted judgments for incapacitated patients, surrogates often struggle to guess what the patient would want if they had capacity. Surrogates may also agonize over having the (sole) responsibility of making such a determination. To address such concerns, a Patient Preference Predictor (PPP) has been proposed that would use an algorithm to infer the treatment preferences of individual patients from population-level data about the known preferences of people with similar demographic characteristics. However, critics have suggested that even if (...) such a PPP were more accurate, on average, than human surrogates in identifying patient preferences, the proposed algorithm would nevertheless fail to respect the patient’s (former) autonomy since it draws on the ‘wrong’ kind of data: namely, data that are not specific to the individual patient and which therefore may not reflect their actual values, or their reasons for having the preferences they do. Taking such criticisms on board, we here propose a new approach: the Personalized Patient Preference Predictor (P4). The P4 is based on recent advances in machine learning, which allow technologies including large language models to be more cheaply and efficiently ‘fine-tuned’ on person-specific data. The P4, unlike the PPP, would be able to infer an individual patient’s preferences from material (e.g., prior treatment decisions) that is in fact specific to them. Thus, we argue, in addition to being potentially more accurate at the individual level than the previously proposed PPP, the predictions of a P4 would also more directly reflect each patient’s own reasons and values. In this article, we review recent discoveries in artificial intelligence research that suggest a P4 is technically feasible, and argue that, if it is developed and appropriately deployed, it should assuage some of the main autonomy-based concerns of critics of the original PPP. We then consider various objections to our proposal and offer some tentative replies. (shrink)

In this paper I propose minimal criteria for a successful theory of the mechanisms of motivation, and argue that extant philosophical accounts fail to meet them. Further, I argue that a predictive processing framework gives us the theoretical power to meet these criteria, and thus ought to be preferred over existing theories. The argument proceeds as follows—motivational mental states are generally understood as mental states with the power to initiate, guide, and control action, though few existing theories of motivation explicitly (...) detail how they are meant to explain these functions. I survey two contemporary theories of motivational mental states, due to Wayne Wu and Bence Nanay, and argue that they fail to satisfactorily explain one or more of these functions. Nevertheless, I argue that together, they are capable of giving a strong account of the control function, which competing theories ought to preserve. I then go on to argue that what I call the ‘predictive theory’ of motivational mental states, which makes use of the notion of active inference, is able to explain all three of the key functions and preserves the central insights of Wu and Nanay on control. It thus represents a significant step forward in the contemporary debate. (shrink)

The accommodation of evidence has been argued to be associated with several methodological problems that should prompt evaluators to lower their confidence in the accommodative theory. Accommodators may overfit their model to data (Hitchcock and Sober, Br J Philos Sci 55(1):1–34, 2004. https://doi.org/10.1093/bjps/55.1.1), hunt for (spurious) associations between variables (Mayo, Error and the growth of experimental knowledge. University of Chicago Press, Chicago, 1996, pp 294–318), or ‘fudge’ their theory in the effort to accommodate a particular datum (Lipton, Inference to the (...) best explanation. Routledge, London, 2004, pp. 164–183). The converse of accommodation, novel prediction, has been offered as a solution. If theorists novelly predict empirical results rather than accommodate those results, the potential risks of accommodation are avoided, and the theory warrants greater confidence. This paper evaluates if the problems of accommodation justify a preference for novel prediction over accommodation for evaluators of a scientific theory. I argue that there is currently insufficient evidence to conclude that the problems of accommodation result in a predictivist advantage in theory confirmation. Taking into consideration the disadvantages of novel prediction and the advantages of accommodation, the impact of further evidential factors, and recent scientific evidence about the consequences of novel prediction and accommodation, novel prediction and accommodation appear roughly on a par, or accommodation is even superior in the current context. (shrink)

This paper presents a comparison of social kinship (patrilineage) and biological kinship (genetic relatedness) in predicting cooperative relationships in two different economic contexts in the fishing and whaling village of Lamalera, Indonesia. A previous analysis (Alvard, Human Nature 14:129–163, 2003) of boat crew affiliation data collected in the village in 1999 found that social kinship (patrilineage) was a better predictor of crew affiliation than was genetic kinship. A replication of this analysis using similar data collected in 2006 finds the same (...) pattern: lineage is a better predictor than genetic kinship of crew affiliation, and the two together explain little additional variance over that explained by lineage alone. However, an analogous test on food-sharing relationships finds the opposite pattern: biological kinship is a better predictor of food-sharing relationships than is social kinship. The difference between these two cooperative contexts is interpreted in terms of kin preferences that shape partner choice, and the relative autonomy with which individuals can seek to satisfy those preferences. Drawing on stable matching theory, it is suggested that unilineal descent may serve as a stable compromise among multiple individuals’ incongruent partner preferences, with patriliny favored over matriliny in the crew-formation context because it leads to higher mean degrees of relatedness among male cooperators. In the context of food-sharing, kin preferences can be pursued relatively autonomously, without the necessity of coordinating preferences with those of other households through the institution of lineage. (shrink)

Patient preference predictors aim to solve the moral problem of making treatment decisions on behalf of incapacitated patients. This commentary on a case of an unrepresented patient at the end of life considers 3 related problems of such predictors: the problem of restricting the scope of inputs to the models (the “scope” problem), the problem of weighing inputs against one another (the “weight” problem), and the problem of multiple reasonable solutions to the scope and weight problems (the “multiple reasonable (...) models” problem). Each of these problems poses challenges to reliably implementing patient preference predictors in important, high-stakes health care decision making. This commentary also suggests a way forward. (shrink)

Substituted judgment assumes adequate knowledge of patient’s mind-set. However, surrogates’ prediction of individual healthcare decisions is often inadequate and may be based on shared background rather than patient-specific knowledge. It is not known whether surrogate’s prediction of patient’s integrative life-story narrative is better. Respondents in 90 family pairs rank-ordered 47 end-of-life statements as life-story narrative measure and completed instruments on decision-control preference and healthcare-outcomes acceptability as control measures, from respondent’s view and predicted pair’s view. They also scored (...) their confidence in surrogate’s decision-making and familiarity with pair’s healthcare-preferences. Life-story narratives’ prediction was examined by calculating correlation of statements’ ranking scores between respondent-personal and respondent-surrogate Q-sorts and between respondent-surrogate and pair-personal Q-sorts before and after controlling for correlation with respondent-personal scores, and by comparing percentages of respondent-surrogate Q-sorts co-loading with pair-personal vs. respondent-personal Q-sorts. Accuracy in predicting decision-control preference and healthcare-outcomes acceptability was determined by percent concordance. Results were compared among subgroups defined by intra-pair relationship, surrogate’s decision-making confidence, and healthcare-preferences familiarity. Mean age was 35.4 years, 69% were females, and 73 and 80% reported ≥ very good health and life-quality, respectively. Mean surrogate’s decision-making confidence score was 3.35 and 75% were ≥ familiar with pair’s healthcare-preferences. Mean projection, simulation, and adjusted-simulation correlations were 0.68, 0.42, and 0.26, respectively. Out of 180 respondent-surrogate Q-sorts, 24, 9, and 32% co-loaded with respondent-personal, pair-personal, or both Q-sorts, respectively. Accuracy in predicting decision-control preference and healthcare-outcomes acceptability was 47 and 52%, respectively. Surrogate’s decision-making confidence score correlated with adjusted-simulation’s correlation score. There were significant differences among the husband-wife, parent-child, and sibling-sibling subgroups in percentage of respondent-surrogate Q-sorts co-loading with pair-personal Q-sorts and percent agreement on healthcare-outcomes acceptability. Despite high self-reported surrogate’s decision-making confidence and healthcare-preferences familiarity, family surrogates are variably inadequate in simulating life-story narratives. Simulation accuracy may not follow the next-of-kin concept and is 38% based on shared background. (shrink)

Introduction: This study, the first of its kind in Iran, was to assess Iranian patients’ preferences for receiving information and participating in decision-making and to evaluate their satisfaction with how medical information is given to them and with their participation in decision-making at present. Method and materials: 299 of 312 eligible patients admitted to general internal medicine or surgery wards from May to December 2006 were interviewed according to a structured questionnaire. The questionnaire contained questions about patients’ preferences regarding four (...) domains of information and their participation in decision-making. Patients’ responses were measured on a visual analogue scale graded from 1 to 10. Results: The mean (SD) score for desire to receive information was 8.88 out of 10 (1.5) and for participation in medical decision-making was 7.75 out of 10 (3). The desire to receive information was greater in women than men (9.0 (1.5) vs 7.8 (1.4), p = 0.025). It was also correlated with their education (r = 0.2, p = 0.001) and their estimation of the severity of their own disease (r = 0.13, p = 0.027). The score for preference to participate in decision-making was higher in women than in men (7.95 (2.8) and 7.0 (3.2), respectively; β = 0.8, p = 0.022) and was negatively correlated with education (r = −0.14, p = 0.015). Discussion: This study shows that Iranian patients are highly interested in receiving information about their condition and participating in clinical decision-making. No predictive variable for such attitudes was found; therefore, the only way for the physician to recognise patients’ desire is to ask them explicitly. (shrink)

Three studies investigated implicit brand attitudes and their relation to explicit attitudes, prod- uct usage, and product differentiation. Implicit attitudes were measured using the Implicit As- sociation Test (IAT; Greenwald, McGhee, & Schwartz, 1998). Study 1 showed expected differ- ences in implicit attitudes between users of two leading yogurt brands, also revealing significant correlations between IAT-measured implicit attitudes and explicit attitudes. In Study 2, users of two fast food restaurants (McDonald’s and Milk Bar) showed implicit attitudi- nal preference for (...) their favorite restaurant. In Study 3, implicit attitudes of users of two soft drinks (Coca-Cola and Pepsi) predicted brand preference, product usage, and brand recognition in a blind taste test. A meta-analytic combination of the three studies showed that the use of IAT measures increased the prediction of behavior relative to explicit attitude measures alone. (shrink)