Positive and Negative Affect Schedule (PANAS): psychometric properties of the online Spanish version in a clinical sample with emotional disorders

Díaz-García, Amanda; González‐Robles, Arturo; Mor, Sonia; Mira, Adriana; Quero, Soledad; García‐Palacios, Azucena; Baños, Rosa; Botella, Cristina

doi:10.1186/s12888-020-2472-1

Cited by 132 publications

(98 citation statements)

References 69 publications

(76 reference statements)

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“…A higher score indicates higher frequency and/or intensity of positive and negative emotions, while a lower score shows less frequency and/or intensity of the emotions experienced as positive or negative. Both the original validation ( Watson et al, 1988 ) and the Spanish validation ( Díaz et al, 2020 ) showed two clearly differentiated factors (PA and NA) and good psychometric properties. In the current study, the inventory has shown a Cronbach’s alpha of 0.826.…”

Section: Methodsmentioning

confidence: 96%

COVID-19 and Emotional Variables in a Sample of Chileans

Gonzalez-Tovar

Hernández-Rodríguez

2021

Front. Psychol.

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IntroductionDuring the Coronavirus (COVID-19) pandemic, a set of daily stressors are being experienced, all this affects people’s mental health, leading them to have a set of emotional disturbances. Little is known about how people’s age can influence their emotional well-being in the face of prolonged stress generate by the pandemic.ObjectiveTo clarify the presence of emotional aspects such as emotional expressiveness and the frequency of positive and negative affections in people with different age in times of crisis.MethodsThe final sample included 297 Chileans between 22 and 68 years old (M = 38.51, SD = 13.85), recruited through an online survey with the appropriate written informed consent. The study was carried out when the pandemic was spreading in Chile.ResultsThe findings revealed age differences in emotional expressivity and the type of affections experienced. The expression of emotions was more affected by negative affections, the age and the gender of the people. While the avoidance of this emotional expression, by age and affections both positive and negative. Age was a significant predictor of emotional expressiveness.DiscussionFindings suggests that the associations between both variables, varied according to the age group of the people. Furthermore, this finding proposes that although older people are facing the persistent and serious threat of COVID-19, they show better emotional functioning. Which would help to better understand the interaction of both positive and negative life experiences in times of crisis.

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Section: Methodsmentioning

confidence: 96%

COVID-19 and Emotional Variables in a Sample of Chileans

Gonzalez-Tovar

Hernández-Rodríguez

2021

Front. Psychol.

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“…A FFECTS are observed dynamic reactions caused by change in our emotions and are directly linked to our mental and physical health [1]. Specifically, the positive affects (PA) and negative affect (NA) give physicians valuable information about mood and anxiety disorders [1]. PA and NA are commonly measured using a self-report questionnaire known as the Positive and Negative Affect Schedule (PANAS) [2].…”

Section: Introductionmentioning

confidence: 99%

Multi-Modal Physiological Data Fusion for Affect Estimation Using Deep Learning

Hssayeni

Ghoraani

2021

IEEE Access

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Automated momentary estimation of positive and negative affects (PA and NA), the basic sense of feeling, can play an essential role in detecting the early signs of mood disorders. Physiological wearable sensors and machine learning have a potential to make such automated and continuous measurements. However, the physiological signals' features that are associated with the subject-reported PA or NA may not be known. In this work, we use data-driven feature extraction based on deep learning to investigate the application of raw physiological signals for estimating PA and NA. Specifically, we propose two multimodal data fusion methods with deep Convolutional Neural Networks. We use the proposed architecture to estimate PA and NA and also classify baseline, stress, and amusement emotions. The training and evaluation of the methods are performed using four physiological and one chest motion signal modalities collected using a chest sensing unit from 15 subjects. Overall, our proposed model performed better than traditional machine learning on hand-crafted features. Utilizing only two modalities, our proposed model estimated PA with a correlation of 0.69 (p<0.05) vs. 0.59 (p<0.05) with traditional machine learning. These correlations were 0.79 (p<0.05) vs. 0.73 (p<0.05) for NA estimation. The best emotion classification was achieved by the traditional method with 79% F1-score and 80% accuracy when all the four physiological modalities are used. This is while with only two modalities, the deep learning achieved 78% F1-score and 79% accuracy.

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“…Affect is regarded as psychological states that refers to personal evaluative feeling for objective things (Diaz-Garcia et al 2020 ). There were two independent dimensions, including positive affect and negative affect (Garcia 2012 ).…”

Section: Introductionmentioning

confidence: 99%

Positive and negative affect of university and college students during COVID-19 outbreak: a network-based survey

Wang

Jing

Han

et al. 2020

Int J Public Health

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Objectives To understand the status of positive affect (PA) and negative affect (NA) on university and college students, and to explore the determinants during the COVID-19 outbreak. Methods Our data were from network-based survey, and 17,876 participants completed the questionnaire. t test, one-way ANOVA and multiple linear regression model were performed using PANAS (Positive and Negative Affect Schedule) score as the dependent variable. Results Of 17,876 participants, the mean score of PA was 25.5 ± 7.3, while NA was 19.1 ± 7.1. Multiple linear regression models showed that there are some common determinants of PA and NA, such as education, health literacy on communicable diseases, satisfaction with measures for epidemic prevention and control, risk of infection, impact of the outbreak on daily life, sleep duration and frequency of hand washing in the past 2 weeks. Besides, whether the student is a medical major and whether outing in the past 2 weeks were specific determinants of PA, and frequency of masks wearing was specific determinant of NA. Conclusions The outbreak of COVID-19 is detrimental to university and college students' affect. During the outbreak response, we should strengthen the guidance and regulation for negative affect and pay attention to improving the positive affect of university and college students.

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Positive and Negative Affect Schedule (PANAS): psychometric properties of the online Spanish version in a clinical sample with emotional disorders

Cited by 132 publications

References 69 publications

COVID-19 and Emotional Variables in a Sample of Chileans

COVID-19 and Emotional Variables in a Sample of Chileans

Multi-Modal Physiological Data Fusion for Affect Estimation Using Deep Learning

Positive and negative affect of university and college students during COVID-19 outbreak: a network-based survey

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