“Your Life, Your Health: Tips and Information for Health and Well-Being”: Development of a World Health Organization Digital Resource to Support Universal Access to Trustworthy Health Information
Bibliographic record
Abstract
Background: Access to trustworthy, understandable, and actionable health information is a key determinant of health and is an essential component of universal health coverage and primary health care. The World Health Organization has developed a new digital resource for the general public to improve health and well-being across different life phases and to support people in caring for themselves, their families, and their communities. The goal was to make trustworthy health information accessible, understandable, and actionable for the general public in a digital format and at the global scale. Objective: The aim of this paper was to describe the multistage approach and methodology used to develop the resource Your life, your health: Tips and information for health and well-being (hereafter, Your life, your health). Methods: A 5-step process was used to develop Your life, your health, including (1) reviewing and synthesizing existing World Health Organization technical guidance, member state health and health literacy plans, and international human rights frameworks to identify priority messages; (2) developing messages and graphics that are accessible, understandable, and actionable for the public using health literacy principles; (3) engaging with experts and stakeholders to refine messages and message delivery; (4) presenting priority content in an accessible digital format; and (5) adapting the resource based on feedback and new evidences. Results: The Your life, your health online resource adopts a life-course approach to organize health information based on priority actions and rights that support peoples' health and well-being across different life stages and specific health topics. The resource promotes health literacy by offering advice on asking questions to health workers, making informed decisions about personal and family health, and effectively using digital media to obtain reliable health information. Additionally, it reflects the ambitions of the Sustainable Development Goals by providing essential information on the social determinants of health and clarifies the distinct roles of individuals, frontline workers, governments, and the media in promoting and protecting health. Conclusions: Making health information available-including to the public-is an essential step in strengthening the global health information system. The development process for the Your life, your health online resource outlined in this article offers a structured approach to translate technical health guidelines into accessible, understandable, and actionable health information for the general public.
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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 | 0.018 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.004 |
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".