A model of naturalistic decision making in preference tests.
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ABSTRACT:
SUBMITTER: Ksander J
PROVIDER: S-EPMC8491944 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Ever-increasing evidence suggests that substance use disorder is mediated by decision-making processes, and as such, providing nondrug alternatives can shift maladaptive preferences away from drug reinforcers, such as cocaine. Of note, a recent hypothesis suggests that preference for cocaine is simply a byproduct of cocaine intake, such that the 'direct' effects of cocaine weaken the impact of non-drug alternatives while measuring choice. Conversely, existing quantitative theories of decision-making suggest preference is determined by various dimensions of concurrent reinforcers that in turn determine the relative value of available alternatives. Toward teasing apart the conflicting theories above, we developed a novel drug-choice procedure to control for reinforcer frequency and magnitude (two reinforcer dimensions well known to influence preference) that consequently controls for overall cocaine intake. As predicted by quantitative choice theory, results suggest that cocaine intake and preference are dissociable while measuring choice, with reinforcer frequency and magnitude having independent influence on the relative value of choice alternatives. Furthermore, we demonstrate that the choice procedure is sensitive to various manipulations known to alter cocaine reinforcement, all while keeping cocaine intake constant. Finally, the results point to the process of economic substitution as an important avenue of future neurobehavioral investigation toward the improvement of behavioral and pharmacological therapies for substance use disorders. Overall, the proposed choice procedure will allow for improved isolation of the neurobehavioral processes that mediate drug-associated decision-making in future studies.
| S-EPMC7716654 | biostudies-literature
Project description:BackgroundShared decision-making is the gold standard for good clinical practice, and thus, psychometric instruments have been established to assess patients' generic preference for participation (e.g., the Autonomy Preference Index, API). However, patients' preferences may vary depending on the specific disease and with respect to the specific decision context. With a modified preference index (API-Uro), we assessed patients' specific participation preference in preference-sensitive decisions pertaining to urological cancer treatments and compared this with their generic participation preference.MethodsIn Study 1, we recruited (N = 469) urological outpatients (43.1% urooncological) at a large university hospital. Participation preference was assessed with generic measures (API and API case vignettes) and with the disease-specific API-Uro (urooncological case vignettes describing medical decisions of variable difficulty). A polychoric exploratory factor analysis was used to establish factorial validity and reduce items. In Study 2, we collected data from N = 204 bladder cancer patients in a multicenter study to validate the factorial structure with confirmatory factor analysis. Differences between the participation preference for different decision contexts were analyzed.ResultsStudy 1: Scores on the specific urooncological case vignettes (API-Uro) correlated with the generic measure (r = .44) but also provided incremental information. Among the disease-specific vignettes of the API-Uro, there were two factors with good internal consistency (α ≥ .8): treatment versus diagnostic decisions. Patients desired more participation for treatment decisions (77.8%) than for diagnostic decisions (22%), χ2(1) = 245.1, p ≤ .001. Study 2: Replicated the correlation of the API-Uro with the API (r = .39) and its factorial structure (SRMR = .08; CFI = .974). Bladder cancer patients also desired more participation for treatment decisions (57.4%) than for diagnostic decisions (13.3%), χ²(1) =84, p ≤ .001.ConclusionsThe desire to participate varies between treatment versus diagnostic decisions among urological patients. This underscores the importance of assessing participation preference for specific contexts. Overall, the new API-Uro has good psychometric properties and is well suited to assess patients' preferences. In routine care, measures of participation preference for specific decision contexts may provide incremental, allowing clinicians to better address their patients' individual needs.
| S-EPMC10324222 | biostudies-literature
Project description:ObjectiveTo investigate women's preferred approach to prenatal genetic testing decision making and assess concordance between preference and experience.MethodsWe conducted a secondary analysis of data from two randomized trials conducted between 2007-2012. Survey items assessed participants' preferred approach to decision making and whether they experienced a preference-concordant decision process. Logistic regression estimated relationships between patient characteristics and these outcomes.Results56% of women preferred autonomous decision making, 39% preferred shared decision making, and 5% preferred a provider-driven approach. Only 57% experienced preference-concordant decision making. On bivariate analysis, black women, Spanish-speaking Latinas and women with less education were less likely to experience this outcome than white, more educated women. Numeracy and preferring a provider-driven approach fully mediated observed disparities in preference-concordant decision making for most participants, except for Spanish-speaking Latinas, who were still less likely to have experienced this outcome after accounting for these factors.ConclusionNumeracy, preference for provider-driven decision processes, and language barriers were key drivers of disparities in preference-concordant decision making.Practice implicationsGiven the values-sensitive and quantitative nature of prenatal testing decisions, nuanced counseling and interventions to address language barriers, numeracy gaps, and decision-making preferences are needed to tailor counseling to patient's backgrounds and desires.
| S-EPMC6421100 | biostudies-literature
Project description:OBJECTIVE:Implementing treat-to-target (TTT) strategies requires that patients with rheumatoid arthritis (RA) and their rheumatologists decide on how best to escalate care when indicated. The objective of this study was to develop preference phenotypes to facilitate shared decision-making at the point of care for patients failing methotrexate monotherapy. METHODS:We developed a conjoint analysis survey to measure the preferences of patient with RA for triple therapy, biologics and Janus kinase (JAK) inhibitors. The survey included seven attributes: administration, onset, bothersome side effects, serious infection, very rare side effects, amount of information and cost. Each choice set (n=12) included three hypothetical profiles. Preference phenotypes were identified by applying latent class analysis to the conjoint data. RESULTS:1273 participants completed the survey. A five-group solution was chosen based on progressively lower values of the Akaike and Bayesian information criteria. Members of the largest group (group 3: 38.4%) were most strongly impacted by the cost of the medication. The next largest group (group 1: 25.8%) was most strongly influenced by the risk of bothersome side effects. Members of group 2 (11.2%) were also risk averse, but were most concerned with the risk of very rare side effects. Group 4 (6.6%) strongly preferred oral over parenteral medications. Members of group 5 (18.0%) were most strongly and equally influenced by onset of action and the risk of serious infections. CONCLUSIONS:Treatment preferences of patients with RA can be measured and represented by distinct phenotypes. Our results underscore the variability in patients' values and the importance of using a shared decision-making approach to implement TTT.
| S-EPMC5898982 | biostudies-literature
Project description:In daily life, people often make consecutive decisions before the ultimate goal is reached (i.e., sequential decision-making). However, this kind of decision-making has been largely overlooked in the literature. The current study investigated whether behavioral preference would change during sequential decisions, and the neural processes underlying the potential changes. For this purpose, we revised the classic balloon analogue risk task and recorded the electroencephalograph (EEG) signals associated with each step of decision-making. Independent component analysis performed on EEG data revealed that four EEG components elicited by periodic feedback in the current step predicted participants' decisions (gamble vs. no gamble) in the next step. In order of time sequence, these components were: bilateral occipital alpha rhythm, bilateral frontal theta rhythm, middle frontal theta rhythm, and bilateral sensorimotor mu rhythm. According to the information flows between these EEG oscillations, we proposed a brain model that describes the temporal dynamics of sequential decision-making. Finally, we found that the tendency to gamble (as well as the power intensity of bilateral frontal theta rhythms) was sensitive to the individual level of trait anxiety in certain steps, which may help understand the role of emotion in decision-making.
| S-EPMC6866314 | biostudies-literature
Project description:We investigated the neural correlates of subjective valuations during a task involving risky choices about lotteries. Because expected value was held constant across all lotteries, decisions were influenced by subjective preferences, which manifest behaviorally as risk-seeking or risk-averse attitudes. To isolate structures encoding risk preference during choice, we probed for areas showing increased activation as a function of selected risk-level. Such response patterns were obtained in anterior (ACC) and posterior cingulate cortex (PCC), superior frontal gyrus, caudate nucleus, and substantia nigra. Behavioral results revealed the presence of risk-averse and risk-neutral individuals. In parallel, brain signals revealed modulation of activity by risk attitude during choice. Correlations between risk-seeking attitudes and neural activity during risky choice were obtained in superior and inferior frontal gyri, medial and lateral orbitofrontal cortex, and parahippocampal gyrus, while correlations with risk-averse attitudes were found in the caudate. The dynamics of neural responses relevant to each stage of the task (decision, anticipation, outcome) were investigated via timeseries and conjunction analyses. Though the networks engaged in each of the task stages were mostly distinct, regions within ACC, PCC and caudate were consistently activated during each decision-making phase. These results demonstrate (1) that subjective assessments of risk, as well as individual attitudes toward risk, play a significant role in modulating activity within brain regions recruited during decision-making, and (2) that ACC, PCC and caudate are relevant during each phase of a decision-making task requiring subjective valuations, strengthening the role of these regions in self-referential subjective valuations during choice.
| S-EPMC4353645 | biostudies-literature
Project description:As an important way to help express the preference relation between alternatives, distributed preference relation (DPR) can represent the preferred, non-preferred, indifferent, and uncertain degrees of one alternative over another simultaneously. DPR, however, is unavailable in some situations where a decision maker cannot provide the precise degrees of one alternative over another due to lack of knowledge, experience, and data. In this paper, to address this issue, we propose interval-valued DPR (IDPR) and present its properties of validity and normalization. Through constructing two optimization models, an IDPR matrix is transformed into a score matrix to facilitate the comparison between any two alternatives. The properties of the score matrix are analyzed. To guarantee the rationality of the comparisons between alternatives derived from the score matrix, the additive consistency of the score matrix is developed. In terms of these, IDPR is applied to model and solve multiple criteria group decision making (MCGDM) problem. Particularly, the relationship between the parameters for the consistency of the score matrix associated with each decision maker and those for the consistency of the score matrix associated with the group of decision makers is analyzed. A manager selection problem is investigated to demonstrate the application of IDPRs to MCGDM problems.
| S-EPMC5995369 | biostudies-literature
Project description:PurposeThis study examined the effects of an oncofertility education program on decisional conflict in nurses and patients with breast cancer.MethodsA cluster randomized controlled trial was conducted with 84 nurses of five breast care units. Three units were randomly selected from the five as the nurse experimental group. Nurses at the experimental group accepted the oncofertility education based on the naturalistic decision-making (NDM) model, while those at the control group accepted the other non-oncofertility education. We also collected data from female patients before and after the nurses' educational training, respectively. The decisional conflict was measured using the Chinese version of the decisional conflict scale.ResultsNurses in the experimental group had less decisional conflict after the oncofertility educational intervention than those in the control group. After the intervention, nurses with higher infertility knowledge scores had significantly lower decisional conflict. Single nurses had significantly higher decisional conflict than married nurses. A higher perceived barrier score was significantly associated with a higher decisional conflict score. Among patients with the same fertility intention scores, those in the experimental group had lower decisional conflict scores than those in the control group.ConclusionsOur work demonstrates that NDM-based oncofertility care education is feasible and acceptable to improve nurse and patient decisional conflict. Educational training based on the NDM model decreased the decisional conflict regarding oncofertility care.Trial registrationClinicaltrialsgov Identifier: NCT04600869.
| S-EPMC9283095 | biostudies-literature
Project description:Within decisions, perceived alternatives compete until one is preferred. Across decisions, the playing field on which these alternatives compete evolves to favor certain alternatives. Mouse cursor trajectories provide rich continuous information related to such cognitive processes during decision making. In three experiments, participants learned to choose symbols to earn points in a discrimination learning paradigm and the cursor trajectories of their responses were recorded. Decisions between two choices that earned equally high-point rewards exhibited far less competition than decisions between choices that earned equally low-point rewards. Using positional coordinates in the trajectories, it was possible to infer a potential field in which the choice locations occupied areas of minimal potential. These decision spaces evolved through the experiments, as participants learned which options to choose. This visualisation approach provides a potential framework for the analysis of local dynamics in decision-making that could help mitigate both theoretical disputes and disparate empirical results.
| S-EPMC3713532 | biostudies-other
Project description:BackgroundDual processing theory of human cognition postulates that reasoning and decision-making can be described as a function of both an intuitive, experiential, affective system (system I) and/or an analytical, deliberative (system II) processing system. To date no formal descriptive model of medical decision-making based on dual processing theory has been developed. Here we postulate such a model and apply it to a common clinical situation: whether treatment should be administered to the patient who may or may not have a disease.MethodsWe developed a mathematical model in which we linked a recently proposed descriptive psychological model of cognition with the threshold model of medical decision-making and show how this approach can be used to better understand decision-making at the bedside and explain the widespread variation in treatments observed in clinical practice.ResultsWe show that physician's beliefs about whether to treat at higher (lower) probability levels compared to the prescriptive therapeutic thresholds obtained via system II processing is moderated by system I and the ratio of benefit and harms as evaluated by both system I and II. Under some conditions, the system I decision maker's threshold may dramatically drop below the expected utility threshold derived by system II. This can explain the overtreatment often seen in the contemporary practice. The opposite can also occur as in the situations where empirical evidence is considered unreliable, or when cognitive processes of decision-makers are biased through recent experience: the threshold will increase relative to the normative threshold value derived via system II using expected utility threshold. This inclination for the higher diagnostic certainty may, in turn, explain undertreatment that is also documented in the current medical practice.ConclusionsWe have developed the first dual processing model of medical decision-making that has potential to enrich the current medical decision-making field, which is still to the large extent dominated by expected utility theory. The model also provides a platform for reconciling two groups of competing dual processing theories (parallel competitive with default-interventionalist theories).
| S-EPMC3471048 | biostudies-literature