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Record W2054908118 · doi:10.5539/ijps.v5n3p43

Collaborative Informal Social Support Initiative as Perceived by the Nursing Students

2013· article· en· W2054908118 on OpenAlexvenueno aff
Siham. M. Al- Momani

Bibliographic record

VenueInternational Journal of Psychological Studies · 2013
Typearticle
Languageen
FieldNursing
TopicNursing education and management
Canadian institutionsnot available
Fundersnot available
KeywordsSWOT analysisNursingPsychologyMedical educationSocial supportMedicineSocial psychology

Abstract

fetched live from OpenAlex

Few studies have explored the experiences of nursing students participating in a collaborative informal socialsupport initiative. This study describes and explores how nursing students perceived their experiences ofparticipating in a pilot collaborative social support initiative program. The collaborative program initiated by thefaculty member, planned to facilitate the collaboration between the academic and clinical staffs in order tomanage the stress experienced by the mothers of cancer children, and to develop the nursing students knowledgeand skills.Mixed method approach was used. Convenience sample of nursing students practiced to fulfill the requirementof advanced nursing course objectives - a required last-semester nursing program course participating in the pilotsocial support program. Qualitative data were collected using team and individual reflection. Self report reactionindex was used to collect quantitative data. SWOT analysis framework to analyze the internal and externalstrengths, weaknesses, opportunities, and threats that impact the program was utilized. Nursing studentsparticipating in the initiative program were highly positive about their experiences.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0040.003
Scholarly communication0.0050.001
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.058
GPT teacher head0.463
Teacher spread0.405 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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".

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Citations0
Published2013
Admission routes1
Has abstractyes

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