Mindfulness and Health Behavior Change: Insights from Individuals Managing Hypertension
Bibliographic record
Abstract
This study aimed to explore the lived experiences of individuals with hypertension who engage in mindfulness practices to understand how mindfulness supports health behavior change. This qualitative study utilized a descriptive phenomenological design to investigate the role of mindfulness in health behavior change among adults diagnosed with hypertension. Sixteen participants (9 females, 7 males) from Canada, all of whom had practiced mindfulness for at least three months, were recruited through purposive sampling. Data were collected through semi-structured interviews focused on participants' experiences with mindfulness in managing hypertension-related behaviors such as stress reduction, medication adherence, diet, and physical activity. Interviews were transcribed verbatim and analyzed thematically using NVivo software. Thematic saturation was reached after the 16th interview. Three main themes emerged from the data: Awareness and Self-Regulation, Motivation and Empowerment, and Lifestyle Integration and Behavior Adaptation. Participants reported enhanced bodily awareness, improved emotional regulation, and reduced reactivity to stress through mindfulness practice. They also described a heightened sense of control and internal motivation to make healthier choices, as well as the successful integration of mindfulness into daily behaviors such as eating, exercising, and medication adherence. Many participants reframed their hypertension as an opportunity for growth and reported improved relationships and communication through mindful connection with others. The findings suggest that mindfulness supports meaningful and sustainable health behavior changes in individuals with hypertension by fostering self-awareness, intrinsic motivation, and daily behavioral adaptation. Integrating mindfulness into hypertension care may enhance patient self-efficacy and support long-term lifestyle management.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".