Oscar Kjell

Sustainable Well-Being: A Potential Synergy Between Sustainability and Well-Being Research

This article outlines a potential synergy between sustainability and well-being research. Currently aims within well-being and sustainability research focus on increasing well-being. First, sustainability is defined and important concepts within it highlighted, that is, aims, interdependencies, constraints, values and balanced adaptive processes. It is suggested that positioning well-being more clearly within the sustainability framework can enhance the role of sustainability; for example, in terms of aims and monitoring progress. In turn, the sustainability framework outlined, guides the second part of the article, illustrating how it can reciprocally enhance well-being research. That is, comprehensive empirical, evolutionary, cross-cultural, and self-conceptual evidence illustrate individuals’ interdependencies with other people and nature. Despite this, contemporary hedonic and eudaimonic well-being approaches and accompanying measures are demonstrated to be isolating; investigating well-being individualistically and in a decontextualized manner. This is in line with the individualistic and independent values of Western cultures. Therefore, it is suggested that employing the sustainability framework emphasizing interdependencies within well-being research can be beneficial; perhaps even resulting in an all-inclusive increase in well-being. Limitations are also raised and future research directions suggested. The author concludes that both sustainability and well-being research can benefit from the synergy toward sustainable well-being.

The affective profiles, psychological well-being, and harmony: environmental mastery and self-acceptance predict the sense of a harmonious life

Background. An important outcome from the debate on whether wellness equals happiness, is the need of research focusing on how psychological well-being might influence humans’ ability to adapt to the changing environment and live in harmony. To get a detailed picture of the influence of positive and negative affect, the current study employed the affective profiles model in which individuals are categorised into groups based on either high positive and low negative affect (self-fulfilling); high positive and high negative affect (high affective); low positive and low negative affect (low affective); and high negative and low positive affect (self-destructive). The aims were to (1) investigate differences between affective profiles in psychological well-being and harmony and (2) how psychological well-being and its dimensions relate to harmony within the four affective profiles. Method. 500 participants (mean age = 34.14 years, SD. = ±12.75 years; 187 males and 313 females) were recruited online and required to answer three self-report measures: The Positive Affect and Negative Affect Schedule; The Scales of Psychological Well-Being (short version) and The Harmony in Life Scale. We conducted a Multivariate Analysis of Variance where the affective profiles and gender were the independent factors and psychological well-being composite score, its six dimensions as well as the harmony in life score were the dependent factors. In addition, we conducted four multi-group (i.e., the four affective profiles) moderation analyses with the psychological well-being dimensions as predictors and harmony in life as the dependent variables. Results. Individuals categorised as self-fulfilling, as compared to the other profiles, tended to score higher on the psychological well-being dimensions: positive relations, environmental mastery, self-acceptance, autonomy, personal growth, and purpose in life. In addition, 47% to 66% of the variance of the harmony in life was explained by the dimensions of psychological well-being within the four affective profiles. Specifically, harmony in life was significantly predicted by environmental mastery and self-acceptance across all affective profiles. However, for the low affective group high purpose in life predicted low levels of harmony in life. Conclusions. The results demonstrated that affective profiles systematically relate to psychological well-being and harmony in life. Notably, individuals categorised as self-fulfilling tended to report higher levels of both psychological well-being and harmony in life when compared with the other profiles. Meanwhile individuals in the self-destructive group reported the lowest levels of psychological well-being and harmony when compared with the three other profiles. It is proposed that self-acceptance and environmental acceptance might enable individuals to go from self-destructive to a self-fulfilling state that also involves harmony in life.

Iranian and Swedish adolescents: differences in personality traits and well-being

Introduction. This study addresses the need to further contextualize research on well-being (e.g., Kjell, 2011) in terms of cross-cultural aspects of personality traits among adolescents and by examining two different conceptualizations of well-being: subjective well-being (i.e., life satisfaction, positive and negative affect) and psychological well-being (i.e., positive relations with others, environmental mastery, self-acceptance, autonomy, personal growth, and life purpose). Methods. Iranian (N = 122, mean age 15.23 years) and Swedish (N = 109, mean age 16.69 years) adolescents were asked to fill out a Big Five personality test, as well as questionnaires assessing subjective well-being and psychological well-being. Results. Swedes reported higher subjective and psychological well-being, while Iranians reported higher degree of Agreeableness, Openness and Conscientiousness. Neuroticism and Extraversion did not differ between cultures. Neuroticism was related to well-being within both cultures. Openness was related to well-being only among Iranians, and Extraversion only among Swedes. A mediation analysis within the Swedish sample, the only sample meeting statistical criteria for mediation analysis to be conducted, demonstrated that psychological well-being mediated the relationship between Neuroticism and subjective well-being as well as between Extraversion and subjective well-being. Conclusions. Certain personality traits, such as Extraversion, Openness, and Conscientiousness, relate differently to well-being measures across cultures. Meanwhile, Neuroticism seems to relate similarly across cultures at least with regard to subjective well-being. Furthermore, the results give an indication on how psychological well-being might mediate the relationship between certain personality traits and subjective well-being. Overall, the complexity of the results illustrates the need for more research whilst supporting the importance of contextualizing well-being research.

Using Language and Affective Profiles to Investigate Differences between Individuals

The affective profiles model (i.e., four possible profiles based on the combination of people’s high/low positive/ negative affect) has led to a great number of studies on individual differences during the past ten years. Nevertheless, only a handful of these studies have investigated actual behavior. Here we put forward two ways for analyzing online behavior (i.e., Facebook status updates) using data published elsewhere. We used the affective profiles model as the framework to investigate individual differences in the words people use when they write on Facebook and the semantic content of their status updates. We suggest that the use of computerized methods to quantify and analyze text need to be used in order to move the affective profiles model into the era of big text data.

Semantic measures: Using natural language processing to measure, differentiate, and describe psychological constructs.

Abstract Psychological constructs, such as emotions, thoughts, and attitudes are often measured by asking individuals to reply to questions using closed-ended numerical rating scales. However, when asking people about their state of mind in a natural context (“How are you?”), we receive open-ended answers using words (“Fine and happy!”) and not closed-ended answers using numbers (“7”) or categories (“A lot”). Nevertheless, to date it has been difficult to objectively quantify responses to open-ended questions. We develop an approach using open-ended questions in which the responses are analyzed using natural language processing (Latent Semantic Analyses). This approach of using open-ended, semantic questions is compared with traditional rating scales in nine studies (N = 92–854), including two different study paradigms. The first paradigm requires participants to describe psychological aspects of external stimuli (facial expressions) and the second paradigm involves asking participants to report their subjective well-being and mental health problems. The results demonstrate that the approach using semantic questions yields good statistical properties with competitive, or higher, validity and reliability compared with corresponding numerical rating scales. As these semantic measures are based on natural language and measure, differentiate, and describe psychological constructs, they have the potential of complementing and extending traditional rating scales.

Exploring the impact of positive and negative emotions on cooperative behaviour in a Prisoner’s Dilemma Game

Objective. To explore the influences of discrete positive and negative emotions on cooperation in the context of a social dilemma game. Design. Two controlled studies were undertaken. In Study 1, 69 participants were randomly assigned to an essay emotion manipulation task designed to induce either guilt, joy or no strong emotion. In Study 2, 95 participants were randomly assigned to one of the same three tasks, and the impact of emotional condition on cooperation was explored using a repeated Prisoner’s Dilemma Game. Results. Study 1 established that the manipulation task was successful in inducing the specified emotions. The analysis from Study 2 revealed no significant main effects for emotions, in contrast to previous research. However, there was a significant effect for participants’ pre-existing tendency to cooperate (social value orientation; SVO). Conclusion. Methodological explanations for the result are explored, including the possible impact of trial-and-error strategies, different cooperation games and endogenous vs exogenous emotions.

A Collective Picture of What Makes People Happy: Words Representing Social Relationships, not Money, are Recurrent with the Word ‘Happiness’

The Internet allows people to freely navigate through news and use that information to reinforce or support their own beliefs in, for example, different social networks. In this chapter we suggest that the representation of current predominant views in the news can be seen as collective expressions within a society. Seeing that the notion of what makes individuals happy has been of increasing interest in recent decades, we analyze the word happiness in online news. We first present research on the co-occurrence of the word happiness with other words in online newspapers. Among other findings, words representing people (e.g., “mom”, “grandmother”, “you”/”me”, “us”/”them”) often appear with the word happiness. Words like “iPhone”, “millions” and “Google” on the other hand, almost never appear with the word for happiness. Secondly, using words with predefined sets of psycholinguistic characteristics (i.e., word-norms measuring social relationships, money, and material things) we further examine differences between sets of articles including the word happiness (“happy” dataset) and a random set (“neutral” dataset) of articles not including this word. The results revealed that the “happy” dataset was significantly related to social relationships word-norm, while the “neutral” dataset was related to the money word-norm. However, the “happy” dataset was also related to the material things word-norm. In sum, there is a relatively coherent understanding among members of a society concerning what makes us happy: relationship, not money; meanwhile there is a more complex relationship when it comes to material things. The semantic method used here, which is particularly suitable for analyzing big data, seems to be able to quantify collective ideas in online news that might be expressed through different social networks.