Retrieval-constrained valuation: Toward prediction of open-ended decisions.
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ABSTRACT:
SUBMITTER: Zhang Z
PROVIDER: S-EPMC8157967 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundChanging population demographics and technology developments have resulted in growing interest in the potential of consumer-facing digital health. In the United Kingdom, a £37 million (US $49 million) national digital health program delivering assisted living lifestyles at scale (dallas) aimed to deploy such technologies at scale. However, little is known about how consumers value such digital health opportunities.ObjectiveThis study explored consumers' perspectives on the potential value of digital health technologies, particularly mobile health (mHealth), to promote well-being by examining their willingness-to-pay (WTP) for such health solutions.MethodsA contingent valuation study involving a UK-wide survey that asked participants to report open-ended absolute and marginal WTP or willingness-to-accept for the gain or loss of a hypothetical mHealth app, Healthy Connections.ResultsA UK-representative cohort (n=1697) and a dallas-like (representative of dallas intervention communities) cohort (n=305) were surveyed. Positive absolute and marginal WTP valuations of the app were identified across both cohorts (absolute WTP: UK-representative cohort £196 or US $258 and dallas-like cohort £162 or US $214; marginal WTP: UK-representative cohort £160 or US $211 and dallas-like cohort £151 or US $199). Among both cohorts, there was a high prevalence of zeros for both the absolute WTP (UK-representative cohort: 467/1697, 27.52% and dallas-like cohort: 95/305, 31.15%) and marginal WTP (UK-representative cohort: 487/1697, 28.70% and dallas-like cohort: 99/305, 32.5%). In both cohorts, better general health, previous amount spent on health apps (UK-representative cohort 0.64, 95% CI 0.27 to 1.01; dallas-like cohort: 1.27, 95% CI 0.32 to 2.23), and age had a significant (P>.00) association with WTP (UK-representative cohort: -0.1, 95% CI -0.02 to -0.01; dallas-like cohort: -0.02, 95% CI -0.03 to -0.01), with younger participants willing to pay more for the app. In the UK-representative cohort, as expected, higher WTP was positively associated with income up to £30,000 or US $39,642 (0.21, 95% CI 0.14 to 0.4) and increased spending on existing phone and internet services (0.52, 95% CI 0.30 to 0.74). The amount spent on existing health apps was shown to be a positive indicator of WTP across cohorts, although the effect was marginal (UK-representative cohort 0.01, 95% CI 0.01 to 0.01; dallas-like cohort 0.01, 95% CI 0.01 to 0.02).ConclusionsThis study demonstrates that consumers value mHealth solutions that promote well-being, social connectivity, and health care control, but it is not universally embraced. For mHealth to achieve its potential, apps need to be tailored to user accessibility and health needs, and more understanding of what hinders frequent users of digital technologies and those with long-term conditions is required. This novel application of WTP in a digital health context demonstrates an economic argument for investing in upskilling the population to promote access and expedite uptake and utilization of such digital health and well-being apps.
| S-EPMC6354197 | biostudies-literature
Project description:Individual traits and reactions to ambiguity differ and are conceptualized in terms of an individual's attitudes toward ambiguity or ambiguity tolerance. The development of natural language processing technology has made it possible to measure mental states and reactions through open-ended questions, rather than predefined numerical rating scales, which have traditionally been the dominant method in psychological research. This study presented three ambiguity-related situations and responses collected online from 591 participants in an open-ended format. After the analysis with bidirectional encoder representations from transformers, correlations were calculated using scores from the numerical evaluation by conventional questionnaire, and a significant moderate positive correlation was found. Therefore, this study found that attitudes toward ambiguity can be measured using an open-ended response method of reporting everyday life states. It is a novel methodology that can be expanded to other scales in psychology and can potentially be used in educational and clinical situations where participants can be asked to respond with minimal burden.
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Project description:Sample size determination for open-ended questions or qualitative interviews relies primarily on custom and finding the point where little new information is obtained (thematic saturation). Here, we propose and test a refined definition of saturation as obtaining the most salient items in a set of qualitative interviews (where items can be material things or concepts, depending on the topic of study) rather than attempting to obtain all the items. Salient items have higher prevalence and are more culturally important. To do this, we explore saturation, salience, sample size, and domain size in 28 sets of interviews in which respondents were asked to list all the things they could think of in one of 18 topical domains. The domains-like kinds of fruits (highly bounded) and things that mothers do (unbounded)-varied greatly in size. The datasets comprise 20-99 interviews each (1,147 total interviews). When saturation was defined as the point where less than one new item per person would be expected, the median sample size for reaching saturation was 75 (range = 15-194). Thematic saturation was, as expected, related to domain size. It was also related to the amount of information contributed by each respondent but, unexpectedly, was reached more quickly when respondents contributed less information. In contrast, a greater amount of information per person increased the retrieval of salient items. Even small samples (n = 10) produced 95% of the most salient ideas with exhaustive listing, but only 53% of those items were captured with limited responses per person (three). For most domains, item salience appeared to be a more useful concept for thinking about sample size adequacy than finding the point of thematic saturation. Thus, we advance the concept of saturation in salience and emphasize probing to increase the amount of information collected per respondent to increase sample efficiency.
| S-EPMC6010234 | biostudies-literature
Project description:As more sequencing data accumulate and novel puzzling genetic regulations are discovered, the need for accurate automated modeling of RNA structure increases. RNA structure modeling from chemical probing experiments has made tremendous progress, however accurately predicting large RNA structures is still challenging for several reasons: RNA are inherently flexible and often adopt many energetically similar structures, which are not reliably distinguished by the available, incomplete thermodynamic model. Moreover, computationally, the problem is aggravated by the relevance of pseudoknots and non-canonical base pairs, which are hardly predicted efficiently. To identify nucleotides involved in pseudoknots and non-canonical interactions, we scrutinized the SHAPE reactivity of each nucleotide of the 188 nt long lariat-capping ribozyme under multiple conditions. Reactivities analyzed in the light of the X-ray structure were shown to report accurately the nucleotide status. Those that seemed paradoxical were rationalized by the nucleotide behavior along molecular dynamic simulations. We show that valuable information on intricate interactions can be deduced from probing with different reagents, and in the presence or absence of Mg2+. Furthermore, probing at increasing temperature was remarkably efficient at pointing to non-canonical interactions and pseudoknot pairings. The possibilities of following such strategies to inform structure modeling software are discussed.
| S-EPMC8628965 | biostudies-literature
Project description:A major problem for evolutionary theory is understanding the so-called open-ended nature of evolutionary change, from its definition to its origins. Open-ended evolution (OEE) refers to the unbounded increase in complexity that seems to characterize evolution on multiple scales. This property seems to be a characteristic feature of biological and technological evolution and is strongly tied to the generative potential associated with combinatorics, which allows the system to grow and expand their available state spaces. Interestingly, many complex systems presumably displaying OEE, from language to proteins, share a common statistical property: the presence of Zipf's Law. Given an inventory of basic items (such as words or protein domains) required to build more complex structures (sentences or proteins) Zipf's Law tells us that most of these elements are rare whereas a few of them are extremely common. Using algorithmic information theory, in this paper we provide a fundamental definition for open-endedness, which can be understood as postulates. Its statistical counterpart, based on standard Shannon information theory, has the structure of a variational problem which is shown to lead to Zipf's Law as the expected consequence of an evolutionary process displaying OEE. We further explore the problem of information conservation through an OEE process and we conclude that statistical information (standard Shannon information) is not conserved, resulting in the paradoxical situation in which the increase of information content has the effect of erasing itself. We prove that this paradox is solved if we consider non-statistical forms of information. This last result implies that standard information theory may not be a suitable theoretical framework to explore the persistence and increase of the information content in OEE systems.
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Project description:Objective:This study investigates the effectiveness of open-ended psychotherapy in a large, naturalistic, and diverse patient cohort using rigorous and multifaceted assessments. Method:Patients (N = 370) in open-ended psychotherapy completed an extensive set of self-report measures and diagnostic interviews, including long-term follow-up in order to assess stability of outcomes. About half of the patients qualified for a personality disorder at the onset of treatment. Treatments were open-ended, and on average therapists provided substantially larger treatment doses than common in the literature. Results:A substantial majority recovered from their respective Axis I (58%) and/or Axis II (55%) disorders during treatment. Patients also experienced large positive changes in self-report measures of overall psychiatric symptoms and moderate positive changes in self-reported interpersonal problems, while very few (< 3%) demonstrated negative development. The patients maintained their diagnostic and self-assessed changes at a two-and-a-half-year follow-up. In contrast, self-reported occupational functioning showed minimal improvement throughout the treatment and follow-up phase. Conclusion:A naturalistic patient cohort undergoing open-ended psychotherapy demonstrates substantial and stable improvements.
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Project description:Collective intelligence has emerged as a powerful mechanism to boost decision accuracy across many domains, such as geopolitical forecasting, investment, and medical diagnostics. However, collective intelligence has been mostly applied to relatively simple decision tasks (e.g., binary classifications). Applications in more open-ended tasks with a much larger problem space, such as emergency management or general medical diagnostics, are largely lacking, due to the challenge of integrating unstandardized inputs from different crowd members. Here, we present a fully automated approach for harnessing collective intelligence in the domain of general medical diagnostics. Our approach leverages semantic knowledge graphs, natural language processing, and the SNOMED CT medical ontology to overcome a major hurdle to collective intelligence in open-ended medical diagnostics, namely to identify the intended diagnosis from unstructured text. We tested our method on 1,333 medical cases diagnosed on a medical crowdsourcing platform: The Human Diagnosis Project. Each case was independently rated by ten diagnosticians. Comparing the diagnostic accuracy of single diagnosticians with the collective diagnosis of differently sized groups, we find that our method substantially increases diagnostic accuracy: While single diagnosticians achieved 46% accuracy, pooling the decisions of ten diagnosticians increased this to 76%. Improvements occurred across medical specialties, chief complaints, and diagnosticians' tenure levels. Our results show the life-saving potential of tapping into the collective intelligence of the global medical community to reduce diagnostic errors and increase patient safety.
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Project description:Are there large-scale trends in art history that surpass individual creativity or relatively short artistic movements? Many theories describe art history as a process similar to a change of fashions, while others suggest that art can be progressive - getting better, in some sense, over time. We approach this question anew with the theory of cumulative cultural evolution, which describes cultural accomplishments in terms of innovations that are maintained across generations and accumulated to support ever greater creative potential. In this paper, we empirically test the possibility for cumulative evolution in the techniques used to make an artistic product. Specifically, we measure the size and structure of the production crews in American films in 1910-2010 based on a dataset of 1000 popular films across the century. We find that film crews become exponentially more complex, with a growing set of core jobs, and more innovative in creating new jobs in filmmaking. Our study shows that art history can be cumulative, showing the progressive maintenance of innovative techniques, and thus providing an alternative to the widespread view of art history as a mere fluctuation of trends and fashions.
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Project description:By polling individual responses to hypothetical scenarios, valuation studies estimate population preferences toward health on a quality-adjusted life year (QALY) scale. The scenarios typically involve trade-offs in time (time trade-off (TTO)), risk (standard gamble (SG)), or number of persons affected (person trade-off (PTO)). This paper revisits the QALY assumptions and provides a coherent health econometric approach that unites TTO, SG, and PTO techniques under a common estimator. The proposed approach avoids the use of ratio statistics in QALY estimation and the common convention of arbitrarily changing trade-off responses. As an example, 34% of the TTO responses from the seminal Measurement and Valuation of Health study were changed in the original UK analysis, which led to substantially lower QALY estimates. As a general rule, if the original estimate is less than 0.5 QALYs, add 0.25 QALYs to get the new estimates.
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Project description:Creativity is progressively acknowledged as the main driver for progress in all sectors of humankind's activities: arts, science, technology, business, and social policies. Nowadays, many creative processes rely on many actors collectively contributing to an outcome. The same is true when groups of people collaborate in the solution of a complex problem. Despite the critical importance of collective actions in human endeavors, few works have tackled this topic extensively and quantitatively. Here we report about an experimental setting to single out some of the key determinants of efficient teams committed to an open-ended creative task. In this experiment, dynamically forming teams were challenged to create several artworks using LEGO bricks. The growth rate of the artworks, the dynamical network of social interactions, and the interaction patterns between the participants and the artworks were monitored in parallel. The experiment revealed that larger working teams are building at faster rates and that higher commitment leads to higher growth rates. Even more importantly, there exists an optimal number of weak ties in the social network of creators that maximizes the growth rate. Finally, the presence of influencers within the working team dramatically enhances the building efficiency. The generality of the approach makes it suitable for application in very different settings, both physical and online, whenever a creative collective outcome is required.
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