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“You Can’t Manage What You Can’t Measure”: Perspectives of Transplant Recipients on Two Lifestyle Interventions for Weight Management

2021· article· en· W3167879285 on OpenAlexaff
Suzanne E. Anderson, Catherine Brown, Katherine Venneri, Justine Horne, June I. Matthews, Janet Madill

Bibliographic record

VenueTransplantology · 2021
Typearticle
Languageen
FieldMedicine
TopicChildhood Cancer Survivors' Quality of Life
Canadian institutionsWestern University
Fundersnot available
KeywordsOverweightNutrigenomicsPsychological interventionFocus groupWeight managementMedicineIntervention (counseling)CurriculumPopulationGerontologyObesityMedical educationPsychologyFamily medicineNursingEnvironmental healthInternal medicinePedagogy

Abstract

fetched live from OpenAlex

Previous research suggests that effective lifestyle interventions for solid organ transplant (SOT) recipients must be tailored to address the unique life circumstances of this population. As few studies have investigated this design consideration, this study aimed to explore the perspectives and experiences of SOT recipients after completing a Group Lifestyle Balance™ [GLB]-based intervention incorporating either (a) standard population-based nutrition guidance or (b) nutrigenomics-based nutrition guidance. All active participants in the Nutrigenomics, Overweight/Obesity, and Weight Management-Transplant (NOW-Tx) pilot study were invited to participate. Data were collected through focus groups and individual interviews. Ninety-five percent (n = 18) of the NOW-Tx pilot study participants enrolled in the current study: 15 participated in 3 focus groups; 3 were interviewed individually. Three themes were common to both intervention groups: (1) the post-transplant experience; (2) beneficial program components; (3) suggestions for improvement. A unique theme was identified for the nutrigenomics-based intervention, comprising the sub-themes of intervention-specific advantages, challenges, and problem-solving. The readily available and adaptable GLB curriculum demonstrated both feasibility and acceptability and was aligned with participants’ needs and existing health self-management skills. The addition of nutrigenomics-based guidance to the GLB curriculum may enhance motivation for behaviour change in this patient population.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.275
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
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 head0.039
GPT teacher head0.331
Teacher spread0.292 · 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.

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

Citations0
Published2021
Admission routes1
Has abstractyes

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