Evaluation of Type A personality

Kittel, F.; Kornitzer, Marcel; Dramaix, M.

doi:10.1136/pgmj.62.730.781

Cited by 7 publications

(5 citation statements)

References 13 publications

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“…Stress has been traditionally measured by monitoring indicative parameters such as heart rates [3], galvanic skin response [4] and pupil diameter [5]. Another method is to use questionnaires to find stress-prone Type A personalities [6] or stress-inducing life events [7]. These methods are mostly reactive in nature, requiring the researchers to continuously monitor expensive sensors or rely on users who might be reluctant to share direct observations on their own mental states or manipulate their responses to meet self-imposed psychological images.…”

Section: Traditional Methods Of Stress/relaxation Measurementmentioning

confidence: 99%

Detection of Stress and Relaxation Magnitudes for Tweets

Pillai

Thelwall

Orăsan

2018

Companion of the the Web Conference 2018 on the Web Conference 2018 - WWW '18

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The ability to automatically detect human stress and relaxation is crucial for timely diagnosing stress-related diseases, ensuring customer satisfaction in services and managing human-centric applications such as traffic management. Traditional methods employ stress-measuring scales or physiological monitoring which may be intrusive and inconvenient. Instead, the ubiquitous nature of the social media can be leveraged to identify stress and relaxation, since many people habitually share their recent life experiences through social networking sites. This paper introduces an improved method to detect expressions of stress and relaxation in social media content. It uses word sense disambiguation by word sense vectors to improve the performance of the first and only lexicon-based stress/relaxation detection algorithm TensiStrength. Experimental results show that incorporating word sense disambiguation substantially improves the performance of the original TensiStrength. It performs better than state-of-the-art machine learning methods too in terms of Pearson correlation and percentage of exact matches. We also propose a novel framework for identifying the causal agents of stress and relaxation in tweets as future work. CCS CONCEPTS•

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Section: Traditional Methods Of Stress/relaxation Measurementmentioning

confidence: 99%

Detection of Stress and Relaxation Magnitudes for Tweets

Pillai

Thelwall

Orăsan

2018

Companion of the the Web Conference 2018 on the Web Conference 2018 - WWW '18

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“…A review of these studies shows mixed conclusions [5]. Some illustrate a correlation between type-A personality and coronary risk factors including high cholesterol and blood pressure, smoking, and increased body-mass index, but others find no significant relationship between the two.…”

mentioning

confidence: 99%

“…Some argue that this inconsistency demonstrates a lack of reproducibility and, thus, causality cannot be concluded [5]. Others argue that type-A personality does not predict if adverse cardiac events will occur, but rather when cardiac events will occur.…”

mentioning

confidence: 99%

What Is the Consensus about Managing Health Risks Associated with Type-A Personality?

Jayaprabhu

2009

AMA Journal of Ethics

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“…9 The Belgian-French heart study of initially healthy men, which used a self-rating scale designed by Bortner to measure type A, again found that the incidence of Coronary Heart Disease associated with Type A Behavioural pattern (BelgianFrench Pooling Project, 1984). 10 Type A assessed by Bortner questionnaire has been found to be associated with coronary Heart Disease in a study among men in the U.K. (Heller, 1979). 11 Final results revealed no relation between Type A Behavioural Pattern and any clinical manifestation of coronary heart disease (Shekelle et al, 1985).…”

Section: Introductionmentioning

confidence: 99%