The Role of Perceived Social Support and Aspects of Personality in the Prediction of Marital instability: The Mediating Role of Occupational Stress

Mohammadi, Elham; Bagheri, Masoud; Asgarizadeh, Ghasem

doi:10.24200/ijpb.2018.58147

Cited by 4 publications

(3 citation statements)

References 19 publications

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“…Social support at the workplace is helpful in coping with occupational stress (Mohammadi et al, 2018) as it is the predictor of well-being. Landy (1992) proved that the quality supervision consisting of social support has a positive influence on employee well-being by making it at the maximum level.…”

Section: Social Supportmentioning

confidence: 99%

“…And having perception of this social support from the surrounded ones is called Perceived Social Support, which is measured through the level of help received (Ilies et al, 2011). As social support can reduce negative psychological pressure, it is proven a predictor of well-being, which is positively related to well-being (Mohammadi et al, 2018). The quality supervision consisting of social support has a positive influence on employee well-being (Landy, 1992).…”

Section: The Impact Of Perceived Social Support On the Well-being Of Employees With Special Needsmentioning

confidence: 99%

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Moderating influence of social support on the relationship of workplace loneliness and well-being of employees with special needs in Pakistan

Ramzan

Mukarram

et al. 2021

J. Humanit. Soc. Manag. Sci.

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Workplace Loneliness is a process, which begins with the psychological requirement of belongingness, and exposes on the reality of social relations within the organizations. This research finds out the impact of workplace loneliness of employees with special needs on their psychological well-being with moderating impact of perceived social support from co-workers and managers. For this purpose, 120 employees with special needs working on managerial role, belonging from public (37%), private (32%), and non-governmental (32%) sectors participated as respondents of the questionnaire-based survey, which was developed on a website according to international accessibility standards. The data was collected by circulating it through multiple social media platforms. The analysis of collected data was performed in MS Excel and IBM SPSS Statistics. Results are clearly showing that social support is an important factor in reducing workplace loneliness and in increasing the well-being of employees with special needs. Therefore, these special employees must be treated as differently abled bodies instead of disabled ones. Hindrances including Covid-19 and software inaccessibility were also faced during the whole process. On the basis of this study, future researchers can research further about type of social support that should be provided on workplace to employees with special needs.

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Section: Social Supportmentioning

confidence: 99%

Section: The Impact Of Perceived Social Support On the Well-being Of Employees With Special Needsmentioning

confidence: 99%

Moderating influence of social support on the relationship of workplace loneliness and well-being of employees with special needs in Pakistan

Ramzan

Mukarram

et al. 2021

J. Humanit. Soc. Manag. Sci.

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“…aggressive and violent behavior [37], antisocial behavior [38], delinquency [39], gambling [40], alcohol use [41], good citizenship and civic duty [42], emotion regulation strategies [43], marital instability [44], investment and trading performance [45], consumer behaviors [46], trustability [47], entrepreneurship [48], job burnout and job engagement [49], employability analysis to find best candidate [50], decision making [51], orienting voting choices [52], political attitudes [53] and preference [54], academic/workplace performance [55], academic motivations and achievements [56][57], learning style [58] and learning goal orientation [59], personal goals [60], forgiveness [61], subjective well-being [62], and Internet of Things (IoT) [63].…”

Section: Literature Reviewmentioning

confidence: 99%

Automatic Personality Prediction; an Enhanced Method Using Ensemble Modeling

Ramezani,

Feizi-Derakhshi,

Balafar

et al. 2020

Preprint

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Human personality is significantly represented by those words which he/she uses in his/her speech or writing. As a consequence of spreading the information infrastructures (specifically the Internet and social media), human communications have reformed notably from face to face communication. Generally, Automatic Personality Prediction (or Perception) (APP) is the automated forecasting of the personality on different types of human generated/exchanged contents (like text, speech, image, video, etc.). The major objective of this study is to enhance the accuracy of APP from the text. To this end, we suggest five new APP methods including term frequency vector-based, ontology-based, enriched ontology-based, latent semantic analysis (LSA)-based, and deep learning-based (BiLSTM) methods. These methods as the base ones, contribute to each other to enhance the APP accuracy through ensemble modeling (stacking) based on a hierarchical attention network (HAN) as the meta-model. The results show that ensemble modeling enhances the accuracy of APP.

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