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Record W2461393888 · doi:10.1186/s40697-016-0127-4

The Association between Individual Counselling and Health Behaviour Change: The See Kidney Disease (SeeKD) Targeted Screening Programme for Chronic Kidney Disease

2016· article· en· W2461393888 on OpenAlexafffund
Lauren Galbraith, Brenda R. Hemmelgarn, Braden Manns, Susan Samuel, Joanne Kappel, Nadine Valk, Paul E. Ronksley

Bibliographic record

VenueCanadian Journal of Kidney Health and Disease · 2016
Typearticle
Languageen
FieldMedicine
TopicChronic Kidney Disease and Diabetes
Canadian institutionsKidney Foundation of CanadaUniversity of SaskatchewanUniversity of Calgary
FundersO'Brien Institute for Public Health, University of CalgaryKidney Foundation of CanadaCanadian Institutes of Health ResearchAlberta Innovates - Health Solutions
KeywordsMedicineKidney diseaseRespondentPublic healthDiseaseBehavior changeBehaviour changeHealth careDescriptive statisticsFamily medicinePhysical therapyInternal medicinePsychiatryPathologyPsychological intervention

Abstract

fetched live from OpenAlex

BACKGROUND: Health behaviour change is an important component of management for patients with chronic kidney disease (CKD); however, the optimal method to promote health behaviour change for self-management of CKD is unknown. The See Kidney Disease (SeeKD) targeted screening programme screened Canadians at risk for CKD and promoted health behaviour change through individual counselling and goal setting. OBJECTIVES: The objectives of this study are to determine the effectiveness of individual counselling sessions for eliciting behaviour change and to describe participant characteristics associated with behaviour change. DESIGN: This is a cross-sectional, descriptive study. SETTING: The study setting is the National SeeKD targeted screening programme. PATIENTS: The participants are all 'at risk' patients who were screened for CKD and returned a follow-up health behaviour survey (n = 1129). MEASUREMENTS: Health behaviour change was defined as a self-reported change in lifestyle, including dietary changes or medication adherence. METHODS: An individual counselling session was provided to participants by allied healthcare professionals to promote health behaviour change. A survey was mailed to all participants at risk of CKD within 2-4 weeks following the screening event to determine if behaviour changes had been initiated. Descriptive statistics were used to describe respondent characteristics and self-reported behaviour change following screening events. Results were stratified by estimated glomerular filtration rate (eGFR) (< 60 and ≥ 60 mL/min/1.73 m(2)). Log binomial regression analysis was used to determine the predictors of behaviour change. RESULTS: Of the 1129 respondents, the majority (89.8 %) reported making a health behaviour change after the screening event. Respondents who were overweight (body mass index [BMI] 25-29.9 kg/m(2)) or obese (BMI ≥ 30.0 kg/m(2)) were more likely to report a behaviour change (prevalence rate ratio (PRR) 0.66, 95 % confidence interval (CI) 0.44-0.99 and PRR 0.49, 95 % CI 0.30-0.80, respectively). Further, participants with a prior intent to change their behaviour were more likely to make a behaviour change (PRR 0.58, 95 % CI 0.35-0.96). Results did not vary by eGFR category. LIMITATIONS: We are unable to determine the effectiveness of the behaviour change intervention given the lack of a control group. Potential response bias and social desirability bias must also be considered when interpreting the study findings. CONCLUSIONS: Individual counselling and goal setting provided at screening events may stimulate behaviour change amongst individuals at risk for CKD. However, further research is required to determine if this behaviour change is sustained and the impact on CKD progression and outcomes.

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)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.089
Threshold uncertainty score0.176

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
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 head0.046
GPT teacher head0.305
Teacher spread0.259 · 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 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

Citations8
Published2016
Admission routes2
Has abstractyes

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