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Record W3025202695 · doi:10.1007/s11892-020-01305-z

Using Person-Reported Outcomes (PROs) to Motivate Young People with Diabetes

2020· review· en· W3025202695 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.

Bibliographic record

VenueCurrent Diabetes Reports · 2020
Typereview
Languageen
FieldHealth Professions
TopicAdolescent and Pediatric Healthcare
Canadian institutionsUniversity of TorontoTrillium Health Centre
FundersAmsterdam University Medical Centers
KeywordsConversationAutonomyPsychologyContext (archaeology)Diabetes managementGlycemicApplied psychologyMedicineDiabetes mellitusType 2 diabetes

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: This manuscript describes how person-reported outcomes (PROs) can be utilized in care for young people with diabetes in the context of motivation. RECENT FINDINGS: The use of person-reported outcome measures (PROMS) in clinical care is feasible and acceptable, and helps focus the clinical encounter on life domains important to the person with diabetes. Results with regard to impact on self-management and glycemic outcomes are limited. Motivation is an important factor for self-management. Based on self-determination theory, autonomy-supportive, person-centered, and collaborative communication by diabetes care providers is associated with better outcomes. PROMs can facilitate this conversation. Understanding of youth motivation for maintaining or improving self-management behaviors requires a person-centered approach. PROMs can be used to facilitate an autonomy-supportive and person-centered conversation in clinical care. Training diabetes care providers in autonomy-supportive, person-centered conversation skills to discuss PROs might help to tap into youth's motivation, but further research is needed.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.942
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.003
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 head0.215
GPT teacher head0.465
Teacher spread0.251 · 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