Discuss social factors that influence people or groups to conform to the actions of others.
Instructions
According to the World Health Organization (WHO), in 2019, a new strain of the coronavirus disease was discovered. Also known as COVID-19, this strain of the virus had previously not been identified in humans. A worldwide pandemic ensued as the virus quickly spread across the globe, impacting countless lives, including many individuals in the United States.
In an effort to contain the virus, numerous countries’ leaders encouraged social distancing, which is an infection control strategy aimed to help lessen the spread of a contagious disease. This directive was given by leaders in the United States as well. Two schools of thought emerged. In fact, many people were skeptical about the authenticity of this pandemic due to perplexing and often conflicting messages that were received across social media and news outlets. Therefore, numerous Americans assumed business as usual and maintained their daily living and social rituals. On the other hand, scores of others quickly retreated to their homes, embracing the warning provided by some of the nation’s top infectious disease experts.
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Order Paper NowThis assignment provides you with an opportunity to analyze a real-world, peer-reviewed, psychology journal article that contains research examining the social psychology aspects of motivation and emotion. You will then demonstrate your understanding of the article by relating the research and conclusions contained therein to current events.
Begin by visiting the CSU Online Library to locate and choose a journal article in which motivation and emotion are viewed under the lens of social psychology. The article must be peer-reviewed and should be no older than 7 years.
NOTE: You are not required to locate an article about COVID-19; instead, you must find a peer-reviewed journal article concerning research that specifically examines motivation and emotion. You will then be critiquing the article and framing the research and conclusions presented in the article in the context of how they can be applied to behavior and social psychology during such an event as the COVID-19 pandemic.
A good place to start your search is the PsycARTICLES database or the Academic Search Ultimate database. You can access these databases from the Databases box on the library homepage.
For assistance in locating your article, you may find the following tutorial How to Find Journal Articles helpful. Additionally, you may find this tutorial How to Search in PsycARTICLES useful.
Once you have chosen your article about motivation, emotion, and social psychology, you will write an article critique that addresses the following elements.
Explain the research methodology that was used in the study.
Discuss social factors that influence people or groups to conform to the actions of others.
Indicate how behaviors and motivation are impacted by the presence of others. (How does this apply to COVID-19?)
Indicate the structures of the brain that are involved in emotion and motivation. (How could a person’s emotions related to fear drive their behaviors during this pandemic?)
Examine the article’s generalizability to various areas of psychology.
Why would some people choose to follow the orders to avoid social contact and others allow desire for human interaction to be their driving force?
In addition, your article critique should clearly identify the article’s premise and present an insightful and thorough analysis with strong arguments and evidence. You should present your own informed and substantiated opinion on the article’s content and its relation to social psychology during the COVID-19 pandemic. You should use the textbook as your second source to support your analysis and to supplement any information that is not contained in the journal article.
Your article critique must be a minimum of three pages in length, not including the title and reference pages. All sources used must be properly cited. Your article critique, including all references, must be formatted in APA
How Does the Emotional Experience Evolve? Feeling Generation as Evidence Accumulation
Ella Givon, Ayelet Itzhak-Raz, Anat Karmon-Presser, Gal Danieli, and Nachshon Meiran Ben-Gurion University of the Negev
How do people answer the question “How do you feel?” In the present work, participants were given 2 tasks in each trial. They first indicated whether a picture made them feel pleasant (or was supposed to be felt as pleasant, in another group), and then made gender decisions regarding faces. Evidence accumulation modeling showed that (a) reporting genuine feeling is qualitatively different from reporting the supposed feeling; (b) reporting one’s feeling is remarkably similar to gender decisions; and (c) evidence regarding negative feelings accumulates more quickly than in positive feelings. These results support the assumption that when asked, participants report genuine as opposed to supposed feelings and strengthen the analogy between feeling reports and perceptual decisions.
Keywords: emotional feelings, evidence-accumulation modeling, valence
You drive to work, expecting a very important meeting you planned months ahead, and suddenly realizing that the cars ahead of you are slowing down into what initially seems like a heavy traffic jam that would certainly make you miss the meeting. Your heart pounds heavily and you start thinking that it would be a disaster if this meeting would be missed. Your partner calls and asks if you feel good and you immediately reply “not at all.”
In the current work, we aimed to understand how this report of feeling emerges. In other words, we asked how people become aware (conscious) of their emotional experience. We did so by extending previous work from our lab (Karmon-Presser, Sheppes, & Meiran, 2018). In that work, the authors continued theoretical suggestions (James, 1884; Sokolov & Boucsein, 2000; Thagard & Aubie, 2008) which draw an analogy between feeling generation and perceptual decision. Karmon-Presser, Sheppes, and Meiran (2018) extended these suggestions by testing whether a well- established model of perceptual decisions, signal-detection theory (SDT; Macmillan & Creelman, 2004) is an appropriate model for emotional-feeling reports. According to this theorizing, evidence regarding emotion is noisy and (conscious-reportable) feelings emerge once the evidence is sufficiently strong and crosses a decision boundary. However, Karmon-Presser et al. (2018) used SDT, and this model does not take into account the time domain,
namely the time taken to complete the perceptual decision and the rate by which emotional evidence accumulates. We reasoned that if feeling reports truly resemble perceptual decisions, this analogy between emotional feeling and perception should also be reflected in the temporal domain.
Evidence accumulation models (EAMs; Ratcliff & Smith, 2004; Teodorescu & Usher, 2013) fill this gap by explaining how per- ceptual decisions unfold in time. The core assumption of EAMs is that the representation of stimuli is inherently noisy, such that in order to make a decision, one must repeatedly sample evidence regarding the stimulus. A perceptual decision is made once suffi- cient evidence has accumulated. EAMs explain both accuracy and the precise shape of the reaction time (RT) distributions for correct and incorrect answers and as such are considerably more con- strained than SDT. In the following sections, we review literature related to the main areas which are dealt with in this work includ- ing the emotional subjective experience and EAMs.
Feeling: The Conscious Emotional Subjective Experience
Following past research (e.g., Scherer, 1987), some emotion researchers define emotion by their components. Among the com- ponents of emotions are autonomic changes, facial and bodily expressions, thought and action tendencies, and cognitive apprais- als. A highly important component of emotion is the associated conscious experience—the feeling. Here we specifically focus on the awareness of the emotion, for example, being aware of the fact that I feel bad, as reflected in feeling reports.
One cannot overestimate the importance of conscious emotional feelings: Feelings indicate personal relevance (Ekman & David- son, 1994), guide decision making (Clore, Gasper, & Garvin, 2001), and help in understanding the experience of others (Lambie & Marcel, 2002). Additionally, feeling is strongly related to emo- tion regulation, considering that one’s ability to choose optimally which emotion regulation strategy to use is highly depended on one’s ability to recognize her own emotion (Barrett, Gross, Chris-
This article was published Online First March 7, 2019. Ella Givon, Ayelet Itzhak-Raz, Anat Karmon-Presser, Gal Danieli, and
Nachshon Meiran, Department of Psychology and Zlotowski Center for Neuroscience, Ben-Gurion University of the Negev.
This research was supported by a research grant from the Israel Science Foundation (381/15). We thank Assaf Kron and Oxana Itekes for providing the instructions used in Itkes et al. (2017), and Maya Weismann for her help in data collection.
Correspondence concerning this article should be addressed to Ella Givon, Department of Psychology and Zlotowski Center for Neurosci- ence, Ben-Gurion University of the Negev, Beer-Sheva, Israel. E-mail: ellasharon123@gmail.com
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Emotion © 2019 American Psychological Association 2020, Vol. 20, No. 2, 271–285 1528-3542/20/$12.00 http://dx.doi.org/10.1037/emo0000537
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tensen, & Benvenuto, 2001). The ability to feel varies among people. Evidence for individual differences in the ability to feel can be found in research concerning feeling-related constructs such as emotional awareness (Lane & Schwartz, 1987), emotion differentiation (Barrett et al., 2001), and affective clarity (Lisch- etzke, Cuccodoro, Gauger, Todeschini, & Eid, 2005).
In the current work, we follow the dimensional approach and focus on the valence dimension (e.g., Barrett, 2006; Kron, Gold- stein, Lee, Gardhouse, & Anderson, 2013). Nevertheless, we ac- knowledge the fact that this approach has been criticized (e.g., Zachar & Ellis, 2012), and thus adopt it only as a starting point. Additionally, while using established norms of valence from the Nencki Affective Picture System (NAPS) database (Marchewka, Żurawski, Jednorǒg, & Grabowska, 2014), we compared negative and positive valence as being part of a bipolar scale (Feldman Barrett & Russell, 1998). While our norms are driven from a bipolar scale, our procedure involves a yes/no report and, as such, does not require a full commitment to the bipolar approach. Nev- ertheless, we acknowledge the fact that the choice to use a bipolar scale is also controversial (e.g., Cacioppo & Berntson, 1994). Lastly, since the construct of the emotional experience is charac- terized by heated debates such as the aforementioned ones, we decided to use what seems to be the simplest components of feeling (i.e., valence).
Evidence Accumulation Models (EAMs)
EAMs, whose roots are already half a century old, have become popular in recent years (Bogacz, Brown, Moehlis, Holmes, & Cohen, 2006; Bogacz, Usher, Zhang, & McClelland, 2007; Brown & Heathcote, 2008; Ratcliff & Rouder, 1998; Ratcliff & Smith, 2004; Stone, 1960; Usher & McClelland, 2001; van Ravenzwaaij, Mulder, Tuerlinckx, & Wagenmakers, 2012). These models, as- suming that the evidence for decisions is noisy, can thus be viewed as an extension of SDT. However, in contrast to SDT, EAMs take into account the time domain. EAMs do so by using accuracy and RT data to uncover psychological processes that underlie decision making. All EAMs share a fundamental principle of sequential sampling of evidence regarding choice alternatives. This sampling resolves the noise-related uncertainty through averaging external and internal evidence over time, until the amount of evidence favoring a given choice reaches a threshold. This noise reduction and reliability increase is analogous to how reliability of a psy- chological test score increases when the number of test items increases. In this regard, pieces of evidence can be viewed as test items. EAMs may be viewed as a robot that has controllers (parameters) that specify its behavior. This robot generates re- sponses and RTs for those responses. When “fitting” an EAM, we essentially “play with” the controllers until its responses and RTs closely resembles the data of responses and RTs from actual participants. When resemblance is sufficiently high, we conclude that actual participants probably process the task in the same way that the robot does. This is sometimes referred as “reverse engi- neering.”
Among the various EAMs, we chose to use the linear ballistic accumulator model (LBA; Brown & Heathcote, 2008) in the current study (the reasons for choosing this specific model are discussed in the following section). As we view it (see Sternberg & Backus, 2015), all EAMs, including the LBA, treat RT as
combined of three processing stages: an early processing stage in which low-level features are extracted, a decision stage, and a motor preparation stage in which the decision leads to the pro- gramming of the motor response (see Figure 1a). The core of the model is the elaborated description of the decision stage (see further elaboration below). To get its gist, we will use a sink-filling contest metaphor1 (see Figure 1b) according to which there are two sinks, each being filled with water at a constant rate by a faucet. The decision is based on a race between the sinks in which the sink to become full first is winning. This race begins when there is already water in the sinks.
