The Association between Individual Counselling and Health Behaviour Change: The See Kidney Disease (SeeKD) Targeted Screening Programme for Chronic Kidney Disease
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".