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Record W2963098301 · doi:10.24908/iqurcp.13383

Can you get emotional support through a screen? A look into digital and in-person emotional support and emotion regulation

2019· article· en· W2963098301 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueInquiry Queen s Undergraduate Research Conference Proceedings · 2019
Typearticle
Languageen
FieldPsychology
TopicDigital Mental Health Interventions
Canadian institutionsQueen's University
Fundersnot available
KeywordsPsychologyExperience sampling methodSocial supportSocial psychologyPsychological intervention

Abstract

fetched live from OpenAlex

Social support is positively related to overall well-being and relationship quality with others, and specifically, may help with successful emotion regulation (Himle, Jayaratne, & Thyness, 2008; Liang, Ho, Li, & Turban, 2014; Strine, Chapman, Balluz, & Mokdad, 2008; Thoits, 2011). With the rapid increase in the use of information and communication technologies (ICT), much social support is now sought and received digitally rather than in person, which involves different methods of interacting with others. The current study examines the indirect effects of seeking and receiving social support both digitally and in-person on the relationship between emotion intensity and emotion regulation success. Two hundred participants were recruited from the Queen’s University psychology participant pool. Participants were prompted through a smart phone experience sampling app three times a day for two weeks to answer questions about their emotions and social support. We predict that emotion intensity will be related to lower emotion regulation success but more seeking and receiving social support. We also predict that seeking and receiving social support will be related to each other and that they will both be related to higher emotion regulation success. Additionally, it is expected that seeking and receiving emotional support in-person and digitally will be part of two indirect pathways from emotion intensity and emotion regulation success. The current study will provide information on whether digital emotional support has equivalent beneficial effects on emotion regulation as in-person emotional support, which could inform targets for future emotion regulation interventions.
 References: 
 Himle, D. P., Jayaratne, S., & Thyness, P. (1989). The effects of emotional support on burnout, work stress and mental health among Norwegian and American social workers. Journal of social service research, 13(1), 27-45. doi: 10.1300/J079v13n01_02
 Liang, T. P., Ho, Y. T., Li, Y. W., & Turban, E. (2011). What drives social commerce: The role of social support and relationship quality. International Journal of Electronic Commerce, 16(2), 69-90. doi: 10.2753/JEC1086-4415160204
 Strine, T. W., Chapman, D. P., Balluz, L., & Mokdad, A. H. (2008). Health-related quality of life and health behaviors by social and emotional support. Social psychiatry and psychiatric epidemiology, 43(2), 151-159. doi: 10.1007/s00127-007-0277-x
 Thoits, P. A. (2011). Mechanisms linking social ties and support to physical and mental health. Journal of health and social behavior, 52(2), 145-161. doi: 10.1177/0022146510395592

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.108
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.101
GPT teacher head0.404
Teacher spread0.303 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it