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Control over sampling boosts numerical evidence processing in human decisions from experience.

ABSTRACT: When acquiring information about choice alternatives, decision makers may have varying levels of control over which and how much information they sample before making a choice. How does control over information acquisition affect the quality of sample-based decisions? Here, combining variants of a numerical sampling task with neural recordings, we show that control over when to stop sampling can enhance (i) behavioral choice accuracy, (ii) the build-up of parietal decision signals, and (iii) the encoding of numerical sample information in multivariate electroencephalogram patterns. None of these effects were observed when participants could only control which alternatives to sample, but not when to stop sampling. Furthermore, levels of control had no effect on early sensory signals or on the extent to which sample information leaked from memory. The results indicate that freedom to stop sampling can amplify decisional evidence processing from the outset of information acquisition and lead to more accurate choices.

SUBMITTER: Appelhoff S

PROVIDER: S-EPMC9758588 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature

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Control over sampling boosts numerical evidence processing in human decisions from experience.

Appelhoff Stefan S Hertwig Ralph R Spitzer Bernhard B

Cerebral cortex (New York, N.Y. : 1991) 20221201 1

When acquiring information about choice alternatives, decision makers may have varying levels of control over which and how much information they sample before making a choice. How does control over information acquisition affect the quality of sample-based decisions? Here, combining variants of a numerical sampling task with neural recordings, we show that control over when to stop sampling can enhance (i) behavioral choice accuracy, (ii) the build-up of parietal decision signals, and (iii) the ...[more]

PMID: 35266973

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Project description:BackgroundThe experience sampling method (ESM) is an intensive longitudinal research method. Participants complete questionnaires at multiple times about their current or very recent state. The design of ESM studies is complex. People with psychosis have been shown to be less adherent to ESM study protocols than the general population. It is not known how to design studies that increase adherence to study protocols. A lack of typology makes it is hard for researchers to decide how to collect data in a way that allows for methodological rigour, quality of reporting, and the ability to synthesise findings. The aims of this systematic review were to characterise the design choices made in ESM studies monitoring the daily lives of people with psychosis, and to synthesise evidence relating the data completeness to different design choices.MethodsA systematic review was conducted of published literature on studies using ESM with people with psychosis. Studies were included if they used digital technology for data collection and reported the completeness of the data set. The constant comparative method was used to identify design decisions, using inductive identification of design decisions with simultaneous comparison of design decisions observed. Weighted regression was used to identify design decisions that predicted data completeness. The review was pre-registered (PROSPERO CRD42019125545).ResultsThirty-eight studies were included. A typology of design choices used in ESM studies was developed, which comprised three superordinate categories of design choice: Study context, ESM approach and ESM implementation. Design decisions that predict data completeness include type of ESM protocol used, length of time participants are enrolled in the study, and if there is contact with the research team during data collection.ConclusionsThis review identified a range of design decisions used in studies using ESM in the context of psychosis. Design decisions that influence data completeness were identified. Findings will help the design and reporting of future ESM studies. Results are presented with the focus on psychosis, but the findings can be applied across different mental health populations.

Dataset Information

Control over sampling boosts numerical evidence processing in human decisions from experience.

Publications

Control over sampling boosts numerical evidence processing in human decisions from experience.

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