| 1. |
- Al Nima, Ali, et al.
(författare)
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The ABC of happiness: Validation of the tridimensional model of subjective well-being (affect, cognition, and behavior) using Bifactor Polytomous Multidimensional Item Response Theory
- 2024
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Ingår i: Heliyon. - : CELL PRESS. - 2405-8440. ; 10:2
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Tidskriftsartikel (refereegranskat)abstract
- Background: Happiness is often conceptualized as subjective well-being, which comprises people's evaluations of emotional experiences (i.e., the affective dimension: positive and negative feelings and emotions) and judgements of a self-imposed ideal (i.e., the cognitive dimension: life satisfaction). Recent research has established these two dimensions as primary parts of a higher order factor. However, theoretical, conceptual, and empirical work suggest that people's evaluations of harmony in their life (i.e., the sense of balance and capacity to behave and adapt with both acceptance and flexibility to inter- and intrapersonal circumstances) constitutes a third dimension (i.e., the behavioral dimension). This tridemensional conceptualization of subjective well-being has recently been verified using Unidimensional Item Response Theory (UIRT) and Classical Test Theory (CTT). Here, we use a recently developed and more robust approach that combines these two methods (i.e., Multidimensional Item Response Theory, MIRT) to simultaneously address the complex interactions and multidimensionality behind how people feel, think, and behave in relation to happiness in their life. Method: A total of 435 participants (197 males and 238 females) with an age mean of 44.84 (sd = 13.36) responded to the Positive Affect Negative Affect Schedule (10 positive affect items, 10 negative affect items), the Satisfaction with Life Scale (five items), and the Harmony in life Scale (five items). We used Bifactor-Graded Response MIRT for the main analyses. Result: At the general level, each of the 30 items had a strong capacity to discriminate between respondents across all three dimensions of subjective well-being. The investigation of different parameters (e.g., marginal slopes, ECV, IECV) strongly reflected the multidimensionality of subjective well-being at the item, the scale, and the model level. Indeed, subjective well-being could explain 64 % of the common variance in the whole model. Moreover, most of the items measuring positive affect (8/10) and life satisfaction (4/5) and all the items measuring harmony in life (5/5) accounted for a larger amount of variance of subjective well-being compared to that of their respective individual dimensions. The negative affect items, however, measured its own individual concept to a lager extent rather than subjective well-being. Thus, suggesting that the experience of negative affect is a more independent dimension within the whole subjective well-being model. We also found that specific items (e.g., “Alert”, “Distressed”, “Irritable”, “I am satisfied with my life”) were the recurrent exceptions in our results. Last but not the least, experiencing high levels in one dimension seems to compensate for low levels in the others and vice versa. Conclusion: As expected, the three subjective well-being dimensions do not work separately. Interestingly, the order and magnitude of the effect by each dimension on subjective well-being mirror how people define happiness in their life: first as harmony, second as satisfaction, third as positive emotions, and fourth, albeit to a much lesser degree, as negative emotions. Ergo, we argue that subjective well-being functions as a complex biopsychosocial adaptive system mirroring our attitude towards life in these three dimensions (A: affective dimension; B: behavioral dimension; C: cognitive dimension). Ergo, researchers and practitioners need to take in to account all three to fully understand, measure, and promote people's experience of the happy life. Moreover, our results also suggest that negative affect, especially regarding high activation unpleasant emotions, need considerable changes and further analyses if it is going to be included as a construct within the affective dimension of a general subjective well-being factor.
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| 2. |
- Amato, Clara, et al.
(författare)
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LinkedIn Users' Identity Clusters in the Prediction of Affectivity and Regulatory Mode
- 2019
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Ingår i: 3rd Biennial International Convention of Psychological Science. Paris, France..
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- We used quantitative semantics to find clusters of words in LinkedIn users’ self-descriptions. Some of these identity clusters discriminated between LinkedIn users with high/low positive affect (social and messy vs. honest), high/low negative affect (social vs. flexible), high/low locomotion (social vs. flexible), and high/low assessment (analytical vs. happy).
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| 3. |
- Amato, Clara, et al.
(författare)
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Newly Graduated Nurses' Learning Work Climate, Health, Resilience, and Burnout Symptoms
- 2020
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Ingår i: 32nd Association for Psychological Science Annual Convention. Chicago, Illinois, USA.
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- The results provide an indication of important learning work climate factors associated to newly graduated nurses’ health, ability to cope successfully in adverse circumstances (i.e., resilience), and burnout symptoms. It is, however, plausible that there is an interconnection between personal vulnerability, learning climate, and health (Stoyanov & Cloninger, 2011).
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| 4. |
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| 5. |
- Amato, Clara, et al.
(författare)
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“Tell Me Who You Are" Latent Semantic Analysis for Analyzing Spontaneous Self-Presentations in Different Situations
- 2020
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Ingår i: Testing, Psychometrics, Methodology in Applied Psychology. - 1972-6325. ; 27:2, s. 153-170
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Tidskriftsartikel (refereegranskat)abstract
- The aim of the study was to analyze freely generated self-presentations through the natural language processing technique of Latent Semantic Analysis (LSA). Four hundred fifty-one participants (F = 360; M = 143) recruited from LinkedIn (a professional social network) were randomly assigned to generate 10 words to describe themselves to either an employer (recruitment-condition) or a friend (friendship- condition). The words’ frequency-rate and their semantic representation were compared between condi- tions and to the natural language (Google’s n-gram database). Self-presentations produced in the recruit- ment condition (vs. natural language) had significantly higher number of agentic words (e.g., problem- solver, responsible, able team-worker) and their contents were semantically closer to the concept of agency (i.e., competence, assertiveness, decisiveness) comparing to the friendship condition. Further- more, the valence of the self-presentations’ words was higher (i.e., with a more positive meaning) in the recruitment condition. Altogether, these findings are consistent with the literature on the “Big Two,” self- presentation, and impression management.
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| 6. |
- Andersson, Richard, et al.
(författare)
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Visually mediated valence effects in dialogue: an explorative study
- 2012
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Ingår i: Lund University Cognitive Studies. - 1101-8453. ; 151, s. 1-16
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- This is an exploratory study investigating potential effects of emotional valence in images and their influence on conversation in the presence of the images. We used latent-semantic analysis to generalize valence ratings of Swedish words to a corpus of spoken conversations. Each utterance in the conversation was given a valence rating, which represented how emotionally positive or emotionally negative the utterance was. We found no effects that indicate that valenced images have an effect on conversations. However, we find that valenced images in general, and positive images in particular, were considered more helpful by the participants who engaged in the conversations. Additionally, we find no results that interlocutors align over time in their use of valenced language.
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| 7. |
- Arvidsson, David, et al.
(författare)
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Changes in self and object representations following psychotherapy measured by a theory-free, computational, semantic space method
- 2011
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Ingår i: Psychotherapy Research. - : Informa UK Limited. - 1050-3307 .- 1468-4381. ; 21:4, s. 430-446
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Tidskriftsartikel (refereegranskat)abstract
- We propose a theory-neutral, computational and data-driven method for assessing changes in semantic content of object representations following long-term psychodynamic psychotherapy. Young adults in psychotherapy are compared with an age-matched, non-clinical sample at three time points. Verbatim transcripts of descriptions of the self and parents were quantified in a semantic space constructed by Latent Semantic Analysis. In the psychotherapy group, all representations changed from baseline to follow-up, whereas no comparable changes could be observed in the comparison group. The semantic space method supports the hypothesis that long-term psychodynamic psychotherapy contributes to sustained change of affective-cognitive schemas of self and others.
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| 8. |
- Asgharian, Hossein, et al.
(författare)
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Predicting Stock Price Volatility by Analyzing Semantic Content in Media.
- 2014
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Current models for predicting volatility do not incorporate information flow and are solely based on historical volatilities. We suggest a method to quantify the semantic content of words in news articles about a company and use this as a predictor of its stock volatility. The results show that future stock volatility is better predicted by our method than the conventional models. We also analyze the functional role of text in media either as a passive documentation of past information flow or as an active source for new information influencing future volatility. Our data suggest that semantic content may take both roles.
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| 9. |
- Bååth, Rasmus, et al.
(författare)
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Latent Semantic Analysis Discriminates Children with Developmental Language Disorder (DLD) from Children with Typical Language Development
- 2019
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Ingår i: Journal of Psycholinguistic Research. - : Springer Science and Business Media LLC. - 0090-6905 .- 1573-6555. ; 48:3, s. 683-697
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Tidskriftsartikel (refereegranskat)abstract
- Computer based analyses offer a possibility for objective methods to assess semantic-linguistic quality of narratives at the text level. The aim of the present study is to investigate whether a semantic language impairment index (SELIMI) based on latent semantic analysis (LSA) can discriminate between children with developmental language disorder (DLD) and children with typical language development. Spoken narratives from 54 children with DLD and 54 age matched controls with typical language development were summarized in a semantic representation generated using LSA. A statistical model was trained to discriminate between children with DLD and children with typical language development, given the semantic vector representing each individual child’s narrative. The results show that SELIMI could distinguish between children with DLD and children with typical language development significantly better than chance and thus has a potential to complement traditional analyses focussed on form or on the word level.
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