IMPROVING THE HEALTH BEHAVIOURS OF COPD PATIENTS: IS HEALTH LITERACY THE ANSWER?
Bibliographic record
Abstract
Chronic Obstructive Pulmonary Disease (COPD) is a leading cause of morbidity and mortality and contributes to substantial social and economic burden There is no cure for COPD, however, medications are available which slow disease progression and control symptoms. Adherence to prescribed medications is critical for optimal management of the disease as is the proper use of the medication delivery device. Health literacy, according to the Process-Knowledge Model, consists of both processing capacity and knowledge (Chin et al., 2015). COPD most commonly occurs in older adults Older adults tend to have lower processing capacity, but lower processing capacity can be mitigated by knowledge (Chin et al., 2015). The purpose of this study was to determine if health literacy was associated with medication adherence and/or inhalation technique. Fifty-seven participants (age range 55-94 years) completed a questionnaire package that included the REALM, TOFHLA, and demographic questions. Information was gathered on medication refill adherence and inhalation technique. A subset of twenty COPD patients participated in qualitative interviews. Results indicated that lower health literacy was associated with both lower medication adherence and poor inhalation technique. One of the themes expressed by the qualitative participants was the need for further information. Given that health literacy is associated with health behaviours in older adults with COPD and there is an expressed need for information, an example of how current educational materials may be reformatted to meet the lower processing capacity of older adults will be discussed. An action-oriented research project where pharmacists and COPD patients collaborate to design needed educational materials and interventions is suggested as a next step.
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 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 | 0.006 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| 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".