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Record W2898935264

Stress, appraisal, autonomous support and coping: an integrative perspective of adult type 2 diabetes management in Newfoundland and Labrador

2018· dissertation· en· W2898935264 on OpenAlexaboutno aff
Krishna Roy

Bibliographic record

VenueMemorial University Research Repository (Memorial University) · 2018
Typedissertation
Languageen
FieldMedicine
TopicDiabetes Management and Education
Canadian institutionsnot available
Fundersnot available
KeywordsCoping (psychology)PsychosocialGlycemicPsychologyCognitive appraisalPerceptionCritical appraisalType 2 diabetesClinical psychologyPath analysis (statistics)Stress managementDiabetes mellitusDiabetes managementDevelopmental psychologyMedicinePsychotherapistStatisticsEndocrinologyMathematicsAlternative medicinePathology
DOInot available

Abstract

fetched live from OpenAlex

In the present study, data was collected from 165 adult type 2 diabetes patients in Newfoundland \nand Labrador to understand their psychosocial behaviour associated with blood glucose (HbA1c). \nPatient characteristics and the effect of four types of psychosocial behaviour on HbA1c are \nexamined. A high prevalence of poor glycemic control is found in the participants having BMI ≥ \n35. The participants with higher stress have a negative appraisal of diabetes. The highly stressed \ngroup has a tendency to use emotion-oriented coping and to have a poor perception of autonomous \nsupportiveness. \nTwo path models are developed conducting regressions analyses. The first one shows that stress, \nappraisal and coping can explain 7.4% of the variance in HbA1c. The second path model shows \nthat appraisal plays a role of mediator and can explain 5.8% of the variance in HbA1c. Finally, \n50.4% of the variance in stress can be explained by appraisal, coping and autonomous perception.

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)0.001
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.365
Threshold uncertainty score0.734

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.017
GPT teacher head0.301
Teacher spread0.283 · 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".

Quick stats

Citations1
Published2018
Admission routes1
Has abstractyes

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