Coping with levels of explanation in the behavioral sciences

Boccignone, Giuseppe; Cordeschi, Roberto

doi:10.3389/fpsyg.2015.00213

Cited by 3 publications

(3 citation statements)

References 14 publications

(16 reference statements)

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“…These aspects can only be studied through the qualitative analysis of experiences communicated via language. The value of data obtained via autobiographical memory has recently received explicit recognition ( Harrison and Loui, 2014 ; Boccignone and Cordeschi, 2015 ; Buckley, 2015a ; Gardner et al, 2015 ; Morin et al, 2015 ). There have been far fewer field tests or methodological advances using these approaches, however, than for approaches based on technological observations and measurements.…”

Section: Introductionmentioning

confidence: 99%

Qualitative Analysis of Emotions: Fear and Thrill

Buckley

2016

Front. Psychol.

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People can speak, and this provides opportunities to analyze human emotions using perceived experiences communicated via language, as well as through measurement and imaging techniques that are also applicable to other higher animal species. Here I compare four qualitative methodological approaches to test if, and how, thrill depends on fear. I use eight high-risk, high-skill, real-life outdoor adventure recreation activities to provide the test circumstances. I present data from: >4000 person-days of participant observation; interviews with 40 expert practitioners; retrospective autoethnography of 50 critical incidents over 4 decades; and experimental autoethnography of 60 events. Results from different methods are congruent, but different approaches yield different insights. The principal findings are as follows. Individuals differ in their fear and thrill responses. The same individual may have different responses on different occasions. Fear boosts performance, but panic causes paralysis. Anxiety or apprehension prior to a risky action or event differs from fear experienced during the event itself. The intensity of pre-event fear generally increases with the immediacy of risk to life, and time to contemplate that risk. Fear must be faced, assessed and overcome in order to act. Thrill can occur either during or after a high-risk event. Thrill can occur without fear, and fear without thrill. Below a lower threshold of perceived risk, thrill can occur without fear. Between a lower and upper threshold, thrill increases with fear. Beyond the upper threshold, thrill vanishes but fear remains. This there is a sawtooth relation between fear and thrill. Perceived danger generates intense focus and awareness. Fear and other emotions can disappear during intense concentration and focus. Under high risk, the usual emotional sequence is fear before the action or event, then focus during the action or event, then thrill, relief, or triumph afterward. The emotionless state persists only during the most intense concentration. For events long enough to differentiate time within the events, fear and thrill can arise and fade in different fine-scale sequences.

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Section: Introductionmentioning

confidence: 99%

Qualitative Analysis of Emotions: Fear and Thrill

Buckley

2016

Front. Psychol.

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“…As noted above, medication may be a necessary but in many cases insufficient part of the control of positive symptoms. In addition, Guo et al (24) found that medication plus psychosocial support outperformed medication alone in early schizophrenia, though this result is confounded by the fact that treatment discontinuation rates were higher in the medication-only group. Perhaps the key point to be made is that, despite ACT and CSC teams varying in composition and services provided (17,20), none of them are limited to services that simply improve medication adherence.…”

Section: Introductionmentioning

confidence: 99%

“…Examining this question requires engaging in one of the most challenging exercises in behavioral science-integrating information across levels of explanation (Boccignone & Cordeschi, 2015), or attempting to understand how a change in social or psychological situation might affect neurobiology or vice versa. In attempting to integrate across these different levels of interpretation and analysis, it is helpful to have one common language-a set of concepts which can serve as the benchmarks for use in comparing pieces of information from different levels of inquiry.…”

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confidence: 99%

Computational Mechanism for the Effect of Psychosis Community Treatment: A Conceptual Review From Neurobiology to Social Interaction

et al. 2021

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The computational underpinnings of positive psychotic symptoms have recently received significant attention. Candidate mechanisms include some combination of maladaptive priors and reduced updating of these priors during perception. A potential benefit of models with such mechanisms is their ability to link multiple levels of explanation, from the neurobiological to the social, allowing us to provide an information processing-based account of how specific alterations in self-self and self-environment interactions result in the experience of positive symptoms. This is key to improving how we understand the experience of psychosis. Moreover, it points us toward more comprehensive avenues for therapeutic research by providing a putative mechanism that could allow for the generation of new treatments from first principles. In order to demonstrate this, our conceptual paper will discuss the application of the insights from previous computational models to an important and complex set of evidence-based clinical interventions with strong social elements, such as coordinated specialty care clinics (CSC) in early psychosis and assertive community treatment (ACT). These interventions may include but also go beyond psychopharmacology, providing, we argue, structure and predictability for patients experiencing psychosis. We develop the argument that this structure and predictability directly counteract the relatively low precision afforded to sensory information in psychosis, while also providing the patient more access to external cognitive resources in the form of providers and the structure of the programs themselves. We discuss how computational models explain the resulting reduction in symptoms, as well as the predictions these models make about potential responses of patients to modifications or to different variations of these interventions. We also link, via the framework of computational models, the patient's experiences and response to interventions to putative neurobiology.

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Roberto cordeschi. Biographical note and list of publications

Cilia¹

2016

Paradigmi

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Coping with levels of explanation in the behavioral sciences

Cited by 3 publications

References 14 publications

Qualitative Analysis of Emotions: Fear and Thrill

Qualitative Analysis of Emotions: Fear and Thrill

Computational Mechanism for the Effect of Psychosis Community Treatment: A Conceptual Review From Neurobiology to Social Interaction

Roberto cordeschi. Biographical note and list of publications

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