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Infection Control Sp Group

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Roman Gomez
Roman Gomez

Expression Des Sentiments Pdf Free [VERIFIED]

Learning to talk about feelings in Spanish is important. No one is feliz all the time. Children (and adults) need to be able to freely express their emotions and feelings. These activities teach the vocabulary for emotions in Spanish and help learners make connections between feelings and situations.

Expression Des Sentiments Pdf Free

Before you read on, we thought you might like to download our three Emotional Intelligence Exercises for free. These science-based exercises will not only enhance your ability to understand and work with your emotions but will also give you the tools to foster the emotional intelligence of your clients, students or employees.

This is the communicative function of how we express what we are experiencing (facial expressions, hand gestures, body movements, etc.). So it is extremely important on the inter-individual level, as well as that of the individual.

While the components of the emotions we feel are present in all individuals, the intensity and expression of these emotions differ from one person to another. There are also social factors like gender, culture, and race, that influence why people may feel emotions differently despite similar situations.

Sexual objectification is a pervasive phenomenon, in which the negative consequences impact the everyday lives of women. When a woman is objectified, she is considered only for her appearance and bodily functions, often seen as an instrument without regard for her personality and dignity (Fredrickson & Roberts, 1997). Studies on sexual objectification and its consequences are numerous and cover multiple areas of research ranging from its clinical ramifications to the study of mind perception and its cognitive and neural underpinnings. Even though the research on sexual objectification has been growing steadily in the last decade, no standardized and pretested pictorial stimuli have been made freely available. The current article contains the normative data of a rich set of objectified and non-objectified female stimuli that should allow researchers to improve the experimental control in their experiments, facilitate comparisons across studies, and facilitate exact replications of their results. Moreover, the current database includes pictures of different models expressing a variety of emotions allowing the research on sexual objectification to expand and widen its link to related fields of research.

Regarding the emotions, each model expressed anger, happiness, and sadness with a low and high intensity, allowing the current database to be used for creating morphed images that gradually go from a neutral face to the expression of a full-blown emotion. Moreover, the presence of pictures in which the target expresses a specific emotion with low intensity allows for the creation of ambiguous stimuli which might be interesting to test certain hypotheses (see Discussion).

We tested whether this database could effectively manipulate both the perceived objectification of the female target and the emotion she expressed by asking participants to judge and rate each picture. To verify the correct recognition of the expressed emotions, all the pictures were evaluated on the basis of the six basic emotions (anger, disgust, sadness, fear, happiness, and surprise). In addition, also the neutrality of the facial expression was judged for each picture. Therefore, we expected the pictures expressing an emotion with high intensity to be rated as expressing that specific emotion (i.e., anger, sadness, or happiness) more than the other basic emotions, while the low-intensity emotional expressions were expected to be evaluated as more ambiguous.

H1: We aimed to present a picture dataset that could manipulate different emotional expressions; therefore we expected all three emotions (i.e., anger, sadness, and happiness) to be recognized coherently. Moreover, we expected the high-intensity emotional expressions to be recognized more correctly, while the low-intensity emotional expressions were expected to be evaluated more ambiguously.

We first selected one image of each model in each condition displaying a neutral facial expression with the head and body of the person in a straight position. Afterwards, we proceeded by selecting the emotional expression images focusing on the quality and clarity of the emotional expression. All the image files were then edited using Adobe Photoshop. We modified the pictures by removing facial and body moles, earrings, and facial piercings. We also resized the pictures. The original dimensions of the photos were 5456 pixels (wide) 3632 pixels (high). To standardize the size of the photo, we created an invisible 5171 pixels (wide) 3320 pixels (high) rectangle in which we created two lines: the first one was a vertical line at the middle of the rectangle, while the second one was the first horizontal line of the thirds grid. The rectangle was applied over the pictures such that the center of the rectangle met the chin while the point where the two lines intersected corresponded to the nose of the person. Finally, images were equated for color temperature by setting a white point near the face of each model. In this way, a total of 280 pictures were created showing one of seven facial expressions [Neutral (NE), Anger low-intensity (AN1), Anger high-intensity (AN2), Sadness low-intensity (SA1), Sadness high-intensity (SA2), Happiness low-intensity (HA1), Happiness high-intensity (HA2)], either fully- (non-objectified condition) or scarcely dressed (objectified condition), with their hair tight into a tail or loose (see Figs. 1 and 2 for stimuli example).

Examples of stimuli. These first four pictures depict a model with neutral expression in the four different combinations of objectification and hairstyle conditions available in the picture dataset (first line: non-objectified; second line: objectified; first column: hair tight into a tail; second column: hair loose)

Four different versions of the questionnaire were created in order to make sure that each participant was presented with all ten models and that all four conditions appeared in each version. Specifically, in each version, every single model expressed all of the possible emotions (neutral, sad-high, sad-low, happy-high, happy-low, anger-high, and anger-low), but in only one of the possible combinations between dress and hairstyle (e.g., in version 1, model 1 appeared with her hair tight into a tail and in bikini, in version 2 the same model was presented with her hair tight into a tail and fully dressed, in version 3 with her hair loose and in bikini, and in version 4 with her hair loose and fully dressed). The combinations between dress and hairstyle changed in each version across models. As such, in each questionnaire, a total of 70 pictures were presented that included all ten models each showing all the facial expressions.

In order to verify whether the emotional expressions on average were correctly identified by participants, a repeated measures ANOVA was conducted in a 7 (Judgement: Neutral expression, Angry, Disgust, Fear, Happiness, Sadness, Surprise) X 2 (Objectification: Objectified, Non-Objectified) X 2 (Hair: Loose, Tight into a tail ) X2 (Gender: Women, Men) experimental design, with the Judgment as within-participants factor and the Objectification, Hair and Gender as between-participants factors. This analysis was conducted for each of the seven emotion expressions separately (i.e., neutral, low-, and high anger, sadness and happiness).

The main effect of Judgment, F(1.94, 139.86) = 107.74, p ηp2 = .599, was qualified by a significant two-way interaction with Gender, F(1.94, 139.86) = 3.49, p = .034, ηp2 = .046. Even though both men and women judged the models portrayed with a low-anger expression as angrier than all other emotions (ps ps > .99), men showed this effect more strongly than women did. Specifically, while disgust was not significantly distinguished from anger by both genders, women showed a slightly stronger tendency to distinguish anger from neutrality (p = .15; MAnger = 3.94, SDAnger = .15; MNeutral = 3.12, SDNeutral = .16), while men did not (p > .99; MAnger = 3.72, SDAnger = .15; MNeutral = 3.49, SDNeutral = .16).

Again, the main effect of Judgment, F(2.47, 177.50) = 363.88, p ηp2 = .835, was qualified by a significant interaction with Gender, F(2.47, 177.50) = 9.15, p ηp2 = .113. Pairwise comparisons showed that women successfully labeled the Anger expression (ratings for anger higher than all other ratings, ps ps M = 4.51, SD = .14), except for Disgust (p > .27; M = 4.21, SD = .08).

The significant main effect of Judgment, F(1.66, 119.51) = 102.91, p ηp2 = .588, was qualified by a significant interaction with Objectification, F(1.66, 119.51) = 4.59, p = .017, ηp2 = .060, showing that models with sad-low expressions in the Objectified condition were properly judged as more intensely sad than all other emotions (all ps M = 3.96, SD = .20) did not differ from the ratings of neutrality (p > .99; M = 3.68, SD = .18).

Finally, the main effect of Judgment, F(2.23, 160.51) = 363.51, p ηp2 = .835, showed that photos depicting a neutral expression were properly perceived as expressing a more neutral face compared to all other emotions, all ps F(2.23, 160.51) = 4.21, p = .013, ηp2 = .055, (MObjectified = 3.21, SDObjectified = .16; MNon-objectified = 3.41, SDNon-objectified = .16).


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