Evidence for Decision-Making: The Importance of Systematic Data Collection as an Essential Component of Responsive Feedback.
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ABSTRACT:
SUBMITTER: McCloud RF
PROVIDER: S-EPMC10727464 | biostudies-literature | 2023 Dec
REPOSITORIES: biostudies-literature
Publications
Evidence for Decision-Making: The Importance of Systematic Data Collection as an Essential Component of Responsive Feedback.
McCloud Rachel F RF Bekalu Mesfin A MA Vaughan Tom T Maranta Lydia L Peck Eliz E Viswanath K K
Global health, science and practice 20231218 Suppl 2
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Project description:BackgroundIn 2011, the Ministry of Health in Malawi developed and institutionalized a resource-tracking process, known as resource mapping (RM), to collect information on planned funding flows across the health sector to support resource allocation and mobilization decisions. We analyze the RM process and tools and describe key uses of the data for health financing decision making to achieve universal health coverage (UHC).MethodsWe applied a case study approach, written as a collaboration between policy makers who have led the RM process in Malawi and the implementation team who have developed tools, collected data, and reported results over the period. It draws on our experiences in conducting RM in Malawi to document the RM process and data, key uses of data, implementation challenges, and lessons learned. We conducted a gray literature review to understand rounds of RM in which we did not participate. Finally, we conducted a search of published literature to situate our work in the international health resource-tracking literature.ResultsThe RM exercise in Malawi is iteratively designed around the needs of the end users and policy priorities of the government, which in turn drives institutionalization of the exercise. We describe 4 ways in which RM data has been used, including national and district planning and budgeting; prioritization and coordination of existing funds by estimating resource availability; mobilization of new resources by conducting financial gap analysis against costed national strategic plans; and generation of evidence to support the national response to the coronavirus disease 2019 pandemic.DiscussionTo achieve UHC goals in Malawi, RM has equipped the government and development partners with critical data used for resource mobilization and coordination decisions. Lessons learned from RM in Malawi may be applicable to other countries starting or refining their own health resource-tracking exercise.
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Project description:Study objectivesTo better understand the sometimes catastrophic effects of sleep loss on naturalistic decision making, we investigated effects of sleep deprivation on decision making in a reversal learning paradigm requiring acquisition and updating of information based on outcome feedback.DesignSubjects were randomized to a sleep deprivation or control condition, with performance testing at baseline, after 2 nights of total sleep deprivation (or rested control), and following 2 nights of recovery sleep. Subjects performed a decision task involving initial learning of go and no go response sets followed by unannounced reversal of contingencies, requiring use of outcome feedback for decisions. A working memory scanning task and psychomotor vigilance test were also administered.SettingSix consecutive days and nights in a controlled laboratory environment with continuous behavioral monitoring.SubjectsTwenty-six subjects (22-40 y of age; 10 women).InterventionsThirteen subjects were randomized to a 62-h total sleep deprivation condition; the others were controls.Measurements and resultsUnlike controls, sleep deprived subjects had difficulty with initial learning of go and no go stimuli sets and had profound impairment adapting to reversal. Skin conductance responses to outcome feedback were diminished, indicating blunted affective reactions to feedback accompanying sleep deprivation. Working memory scanning performance was not significantly affected by sleep deprivation. And although sleep deprived subjects showed expected attentional lapses, these could not account for impairments in reversal learning decision making.ConclusionsSleep deprivation is particularly problematic for decision making involving uncertainty and unexpected change. Blunted reactions to feedback while sleep deprived underlie failures to adapt to uncertainty and changing contingencies. Thus, an error may register, but with diminished effect because of reduced affective valence of the feedback or because the feedback is not cognitively bound with the choice. This has important implications for understanding and managing sleep loss-induced cognitive impairment in emergency response, disaster management, military operations, and other dynamic real-world settings with uncertain outcomes and imperfect information.
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Project description:Decision-making theories explain animal behaviour, including human behaviour, as a response to estimations about the environment. In the case of collective behaviour, they have given quantitative predictions of how animals follow the majority option. However, they have so far failed to explain that in some species and contexts social cohesion increases when conditions become more adverse (i.e. individuals choose the majority option with higher probability when the estimated quality of all available options decreases). We have found that this failure is due to modelling simplifications that aided analysis, like low levels of stochasticity or the assumption that only one choice is the correct one. We provide a more general but simple geometric framework to describe optimal or suboptimal decisions in collectives that gives insight into three different mechanisms behind this effect. The three mechanisms have in common that the private information acts as a gain factor to social information: a decrease in the privately estimated quality of all available options increases the impact of social information, even when social information itself remains unchanged. This increase in the importance of social information makes it more likely that agents will follow the majority option. We show that these results quantitatively explain collective behaviour in fish and experiments of social influence in humans.
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