Development and Pretesting of a New Functional-Based Health Literacy Measurement Tool for Chronic Obstructive Pulmonary Disease (COPD) and Asthma Management
Bibliographic record
Abstract
Iraj Poureslami, 1, 2 Jessica Shum, 1, 2 Jacek Kopec, 3 Richard Sawatzky, 4 Samir Gupta, 5 Smita Pakhale, 6 Saron Kassay, 1, 2 Kassie Starnes, 1, 2 Alizeh Akhtar, 2 J Mark FitzGerald 1, 2 On behalf of the Canadian Airways Health Literacy Study Group 1Division of Respiratory Medicine, Department of Medicine, Institute for Heart and Lung Health, The University of British Columbia, Gordon and Leslie Diamond Health Care Centre, Vancouver, BC V5Z 1M9, Canada; 2Centre for Clinical Epidemiology and Evaluation, Vancouver Coastal Health Research Institute, The University of British Columbia, Vancouver, BC V5Z 1M9, Canada; 3Division of Epidemiology, Biostatistics, and Public Health Practice, School of Population and Public Health, The University of British Columbia, Vancouver, BC V6T 1Z3, Canada; 4School of Nursing, Trinity Western University, Langley, BC V2Y 1Y1, Canada; 5Division of Respirology, Department of Medicine, St. Michael’s Hospital, Toronto, ON M5B 1W8, Canada; 6Ottawa Hospital Research Institute, University of Ottawa, Ottawa, ON K1H 8L6, CanadaCorrespondence: J Mark FitzGeraldDivision of Respiratory Medicine, Department of Medicine, Institute for Heart and Lung Health, The University of British Columbia, Gordon and Leslie Diamond Healthcare Centre, The Lung Centre, 7th Floor, 2775 Laurel Street, Vancouver, BC V5Z 1M9, CanadaTel +1 604 875 4122Email mark.fitzgerald@vch.caBackground: Health literacy (HL) is a person’s ability to practically apply a wide range of cognitive and non-cognitive skills in health-related decisions. HL includes five domains: navigate/access, understand, communicate, evaluate, and use of health information and services. Currently, no tool accurately captures and measures HL in adult patients with asthma and COPD, while utilizing all 5-HL domains.Objective: Develop a comprehensive functional-based measurement tool for adult asthma and/or COPD patients, while assessing HL on routine actions required to manage their chronic respiratory condition(s).Methods: We developed our HL tool based on a conceptualization of the link between HL and asthma and COPD management, during needs assessment stage including; a systematic review, which was followed by patient-oriented focus groups, and key-informant and respirologist interviews. Preliminary face and content validation were obtained by patients’ and health professionals’ input prior to the pretesting stage. The needs assessment information enabled us to develop passages in scenario-format and corresponding items to assess HL core domains, in addition to numeracy skills, across nine self-management topics: peak flow meters, prednisone use, pulmonary rehabilitation, action plans, flu shots, inhaler technique, lifestyle (nutrition and exercise), trigger control, and map navigation. The tool was pretested with asthma and COPD patients to assess its relevance, clarity, and difficulty.Results: Our systematic review identified the deficiencies of existing HL tools that assessed the HL skills of asthma and COPD patients. The patient-oriented focus groups (n=93) enabled us to identify self-management topics and develop items for our proposed HL tool, which were enriched by input from 45 key informants (eg, policy makers, clinicians, etc.) and 17 respiratory physicians. Preliminary pretesting with a new cohort of participants (36 asthma and COPD patients and 39 key informants) aided in the refinement and finalized our tool. The modified tool included passages and corresponding items related to asthma and COPD management was pretested with 75 asthma/COPD patients who completed the questionnaire and provided their feedback on the clarity, relevance, and difficulty of the tool. The main barrier to self-management pertained to “communication” skills. The flu shot was the most relevant topic (91.2%), while map navigation was the least relevant (63.9%). Action plans were the most difficult topic, where only 55% knew when to utilize their action plans. Numeracy items challenged COPD patients the most.Conclusion: We summarized findings from the development and preliminary testing stages of a new asthma/COPD HL tool. This tool will now be validated with a new cohort of patients.Practice Implications: Knowledge gained in this study has been applied to the final version of the tool, which is currently being validated.Keywords: COPD and asthma management, health literacy, measurement tool, functional skills
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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 | 0.008 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".