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Diabetes distress: understanding the hidden struggles of living with diabetes and exploring intervention strategies

2015· review· en· W2131171108 on OpenAlexfundno aff
Emma Berry, Sam Lockhart, Mark Davies, John R. Lindsay, Martin Dempster

Bibliographic record

VenuePostgraduate Medical Journal · 2015
Typereview
Languageen
FieldMedicine
TopicDiabetes Management and Education
Canadian institutionsnot available
FundersQueen's UniversityQueen's University Belfast
KeywordsDistressMedicinePsychosocialDiabetes mellitusPsychological interventionDiabetes managementIntervention (counseling)Clinical psychologyGerontologyType 2 diabetesPsychiatry

Abstract

fetched live from OpenAlex

Diabetes distress is a rational emotional response to the threat of a life-changing illness. Distinct from depression, it is conceptually rooted in the demands of diabetes management and is a product of emotional adjustment. Diabetes distress has been found to be significantly associated with glycated haemoglobin (HbA1c) level and the likelihood of an individual adopting self-care behaviours. The lack of perceived support from family, friends and healthcare professionals significantly contributes to elevated diabetes distress, and this issue tends to be overlooked when designing interventions. Pioneering large-scale research, DAWN2, gives voices to the families of those with diabetes and reaffirms the need to consider psychosocial factors in routine diabetes care. Structured diabetes education programmes are the most widely used in helping individuals cope with diabetes, but they tend not to include the psychological or interpersonal aspects of diabetes management in their curricula. The need for health practitioners, irrespective of background, to demonstrate an understanding of diabetes distress and to actively engage in discussion with individuals struggling to cope with diabetes is emphasised.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.979
Threshold uncertainty score0.758

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.148
GPT teacher head0.347
Teacher spread0.199 · 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 designOther design
Domainnot available
GenreReview

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

Citations100
Published2015
Admission routes1
Has abstractyes

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