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Scholarly Publications
Source: Possell, P., Mitchell, A.M., Ronkainen, K., Kaplan, G.A., Kuahanen, J. (2015). Do depressive symptoms predict the incidence of myocardial infarction independent of hopelessness? Journal of Health Psychology, 20(1), 60-68. doi.10.1177/1359105313498109
A longitudinal study has found that hopelessness and depression are each predictors of coronary heart disease (CHD). When adjusted for level of depression, hopelessness was an independent predictor of CHD. However, when adjusted for level of hopelessness, depression was not an independent predictor of CHD.
This study was the first of its kind to explore depression and hopelessness as individual predictors as long as 18 years out.
Hopelessness occurs often in severe depression, but it is not recognized as a symptom of depression in the Diagnostic and Statistical Manual of Mental Disorders. Hopelessness, therefore, might be distinct from depression in its associations with CHD.
Researchers suggested future studies to investigate whether reducing hopelessness, compared with reducing depressive symptoms, would lead to fewer incidents of heart attack.
Coronary heart disease including heart attack is the leading cause of death worldwide. The World Health Organization predicts that by 2030, depression and CHD will rank globally as two of the three most disabling conditions, surpassed only by HIV/AIDS.
Citation: Quoidbach, J., Mikolajczak, M., & Gross, J.J. (2015, January 26). Positive interventions: An emotion regulation perspective. Psychological Bulletin. Advance online publication.
Researchers find that regulating one’s responses (emotion regulation) to life events increases happiness.
Learning to control emotions before, during and after a positive event can increase short-term and long-term happiness. Researchers reviewed scientific literature that included 157 positive emotion interventions. Results showed that there are several strategies that can effectively increases happiness. These strategies include selecting a situation, deploying attention, engaging in cognitive change and expressing a response. Doing so has a variety of benefits, such as helping people choose and modify situations where positive emotions are likely to occur, helping people appreciate their good fortune, and helping people foster positive emotions like joy and gratitude. Researchers focused on empirical evidence for 25 positive interventions. They found strong evidence in support of 13 of them, including mindfulness-based therapies, applications of character strengths, acts of kindness, and the gratitude visit.
To increase positive emotions in the short term, interventions that help people focus their attention, realize good fortune, and express positive feeling states like enjoyment had strong empirical backing. To increase positive emotions in the long term, two strategies had strong support: choosing or modifying a situation while an event unfolds, and focusing attention before, during and after an event.
Findings could benefit research aimed at matching emotion regulation strategies and a person’s natural inclinations, leading to more tailor-made interventions.
Citation: Dodds, P.S., Clark, E.M., Desu, S., Frank, M.R., Reagan, A.J., Williams, J.R. . . Danforth, C.M. (2015). Human language reveals a universal positivity bias. Proceedings of the National Academy of Sciences, 112(8), 2389-2394. doi/10.1073/pnas.1411678112
Data-driven analysis of billions of words confirms a universal bias in favor of happy words.
Big Data methods applied to sources as varied as Korean Twitter feeds and Russian literature suggest that positive social interaction is built into human language. This so-called “Pollyanna Hypothesis," first proposed by University of Illinois psychologists in 1969, asserts that there is a universal human tendency to use positive words more frequently and diversely than negative words when communicating.
The new study examined individual words from 10 diverse languages and 24 source types including books, news media, social media, websites, music lyrics, and television and movie subtitles. Tweets alone accounted for roughly 100 billion words. Researchers pinpointed about 10,000 frequently used words in English, Spanish, French, German, Brazilian Portuguese, Korean, Chinese (simplified), Russian, Indonesian and Arabic. The team then paid native speakers to rate words by assigning them a smiling or frowning face; in all, some 500 million human scores were obtained.
These findings will help us to develop potent language-based tools to measure emotion, the research team said.
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