Predictors of successful electronic support of psychological well-being of a person in crisis
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Abstract
The purpose of the research is to determine the socio-psychological predictors of the successful electronic support of the psychological well-being of Ukrainian citizens in a crisis.
The main research methods are systematic theoretical analysis of sources, author surveys, statistical data processing, and generalization.
Results. Four main socio-psychological predictors associated with the success of electronic support of the psychological well-being of a person during the crisis period were identified: 1) sociodemographic features, 2) identification with the electronic support community, 3) online behavior regarding the support search, 4) ability to get electronic support. The first predictor considers age, satisfaction with financial security, education, gender, and living conditions status. Thus, the most successful remote format of psychological well-being support organization (communities in social networks, messengers, online therapy) is for the audience of 19-24 years old, satisfied with their finances, having secondary/ secondary special education, female, living separately from their families. The second predictor explains the relational component: the user should enjoy visiting the corresponding electronic community to get support successfully. The third predictor involves frequent and active use of online tools: searches on the web, presence in social networks and messengers, use of relevant sites, applications, and chatbots, reading information and online reacting to it, such as questions, comments, messages, posts and answers to questions. The fourth predictor is the positive experience of users solving their problems and receiving the ideas they need, precisely in electronic format.
Conclusion. The outlined predictors can be considered when developing remote psychosocial intervention programs for various categories of citizens in a crisis.
The perspective of the research is to check the effectiveness of applying the presented predictors when developing the relevant programs.
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