PSY 120 Measuring the Mind After Covid 19 Essay

March 8, 2022
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PSY 120 Measuring the Mind After Covid 19 Essay

PSY 120 Measuring the Mind After Covid 19 Essay

Suppose you wanted to study the effects of COVID-19 on mood—which of the three methods (case study, naturalistic observation, or survey) might you select and why? What would be the goal?

1. Select a method

2. Develop a testable hypothesis

3. Explain how you would collect data. Who would you collect data from? How would you recruit people right now during the pandemic?

4. Why do you think your approach would be helplful to the understanding of the impacts of COVID-19 on mental health?

5. How do you keep a positive mood during this pandemic?

Knowing and measuring the psychosocial reactions of people to the coronavirus crisis could be useful for predicting citizen responsibility and psychological well-being in the general population. In this research, we present the COVID Reaction Scales (COVID-RS), a new tool that can measure and quantify the psychopathological reactions of the population to the COVID-19 crisis. The sample consisted of 667 subjects. Explorative and confirmative factor analyses were applied to examine the validity and reliability of the COVID-RS. Five dimensions were extracted that predicted 35.08% of the variance of the psychopathological reactions: (1) disorganized behaviors, (2) avoidant behaviors, (3) maladaptive information consumption, (4) herd behaviors and (5) loneliness. The results indicated that social quarantine induces and increases psychopathological reactions. However, emotional loneliness is reduced for each person with whom the respective subject lives during the quarantine. Finally, we can conclude that the COVID-RS has satisfactory validity and reliability. Measuring dysfunctional reactions to COVID-19 can enable the prediction of citizen responsibility.

PSY 120 Measuring the Mind After Covid 19 EssayCOVID Reaction Scales (COVID-RS)
This scale was developed by Álex Escolà-Gascón and aimed to measure the psychopathological reactions and the way each subject copes with the coronavirus crisis. It consists of 31 items expressed in the form of statements. The responses are scored according to the Likert model, which ranges from 0 (which means “completely disagree”) to 4 (which means “totally agree”). The items are grouped into five dimensions contrasted and validated in this report: (1) avoidant behaviors (AB); (2) disorganized behaviors (DB); (3) Maladaptive information consumption (MI); (4) Loneliness (LO); and (5) Herd behavior (HB). The development process of the items and the clinical contents that each scale evaluates are described in the procedures section (see Table 2). The reliability and validity of the COVID-RS were analyzed in this study.

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Development of COVID Reaction Scales (COVID-RS) Items
The items were written taking into account 4 sources of information: (1) the theories related to coping and attachment styles (see Ainsworth and Bowlby, 1991); (2) the statistical evidence describing the changes in information consumption during the COVID-19 crisis (e.g., Pulido et al., 2020b); (3) the loneliness model proposed by de Jong-Gierveld and Kamphuis (1985); and (4) the empirical evidence regarding the most common pathological behaviors during the first social quarantine (see Escolà-Gascón et al., 2020). Table 2 summarizes the clinical indicators of the COVID-RS to specify more clearly the relationship between each construct and item.

In total, 31 items were written in the form of statements or phrases. All of them were reviewed and approved by the research team of this report. Although coding the responses is the same for all items, the COVID-RS was designed to take into account two application contexts: The first 15 items were written to be answered in the current context, and from a more general perspective, they are written in the present tense. The rest of the items are written in the present perfect because they intend to integrate the psychological consequences and possible metric biases derived from the first mass confinement that was experienced in the European Union (e.g., Brooks et al., 2020). This study tests the validity and reliability of the 31 items of the COVID-RS.

Development of Sampling
The sample was obtained through the online application and distribution of the two questionnaires specified in the previous section. Google Forms was used to digitize the items and responses. The massive online application of the tests on social networks and WhatsApp began on July 22 and ended on August 04, 2020. The first raw data matrix obtained was cleaned and because 27 of the participants were minors, these cases were eliminated from the original matrix. There were no blank responses, and no missing values were identified. Once the matrix was refined, 667 final subjects remained, which are the responses analyzed in this report. All participants checked the acceptance box before responding to the scales.

PSY 120 Measuring the Mind After Covid 19 EssayEthics Statement
The Committee of Ethical Guarantees of Ramon Llull University, (Barcelona, Spain) reviewed, favorably evaluated, and approved this research. Likewise, the procedures of this study adhere to the Spanish Government Data Protection Act 15/1999 and the Declaration of Helsinki of 1975, revised in 2013.

Data Analysis
The data were processed with the JAMOVI open-access statistical program (see The Jamovi Project, 2020). First, an exploratory factor analysis (EFA) was applied. The factors were extracted by parallel analysis and the unweighted least squares method (see Reise et al., 2000). The Promax rotation was applied. From the solution obtained in the EFA, the structural equations were applied adjusting a confirmatory factor analysis (CFA) model. The parameters were estimated using the maximum likelihood method, and the respective fit indices provided by the AMOS program (an extension of SPSS 25 specialized in structural equations) were applied. According to Kline (2013) and Abad et al. (2015) the following adjustment indices and thresholds were used: root mean square error of approximation (RMSEA, threshold ≤0.05); adjusted goodness of fit index (AGFI, threshold ≥0.9); parsimony ratio (PRATIO, threshold ≥0.9); parsimony adjustment to the comparative fit index (PCFI, threshold ≥0.8); comparative fit index (CFI, threshold ≥0.95); Tucker-Lewis coefficient (TLI, threshold ≥0.95); and incremental fit index (IFI, threshold ≥0.95).

Given that this program allows obtaining the Bayes information criterion (BIC), Akaike information criterion (AIC) and consistent Akaike information criterion (CAIC) indices, which indicate the degree of misfit in the model, the Mismatch Reduction Ratio (MRR) was estimated following the deviance expression developed by Pardo and Ruiz (2015):

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