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Record W3109593235 · doi:10.5539/ies.v13n12p27

The Role of Social Support in the Relationship Between Adolescents’ Level of Loss and Grief and Well-Being

2020· article· en· W3109593235 on OpenAlexvenueno aff
Firdevs Savi Çakar

Bibliographic record

VenueInternational Education Studies · 2020
Typearticle
Languageen
FieldPsychology
TopicGrief, Bereavement, and Mental Health
Canadian institutionsnot available
Fundersnot available
KeywordsGriefPsychologySocial supportStructural equation modelingScale (ratio)Mental healthAssociation (psychology)Developmental psychologyLongitudinal studyClinical psychologySocial psychologyPsychotherapistMedicine

Abstract

fetched live from OpenAlex

In this study, the model, developed to examine the role of social support in the relationship between adolescents’ level of loss and grief and well-being, was tested. In this study, the descriptive research method was used, and its participants consisted of 216 adolescents who were high school students, in Turkey. Scales used in this study include Personal Information Form; Grief Scale; Five-Dimensional Well-Being Scale for Adolescents (EPOCH); Social Support Assessment Scale for Children and Adolescents (CASSS and Personal Information Form). The structural equation model was used to examine the mediator role of the social support in the association between grief and well-being among adolescents. It was found the hypothesized model fit the data well, and social support fully mediated in the association between grief and well-being. The high level of social support in the loss and mourning process of adolescents makes it easier to cope with grief and positively affects their well-beings. These results are important for focusing on adolescents who experience lost and grief, providing effective mental health services and demonstrating the importance of strengthening social support systems. Future studies with longitudinal follow-ups are suggested to explore actual causal relationships.

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.

How this classification was reachedexpand

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.055
Threshold uncertainty score0.156

Codex and Gemma teacher scores by category

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

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 head0.164
GPT teacher head0.449
Teacher spread0.285 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations18
Published2020
Admission routes1
Has abstractyes

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