A critical review of published research literature reviews on nursing and healthcare ageism
Bibliographic record
Abstract
AIMS AND OBJECTIVES: To establish how common and impactful nursing and healthcare ageism is and whether proven interventions or prevention methods exist. BACKGROUND: Ageism has been a concern since 1969 when it was first introduced as a concept for social reform. As ageism has been linked to lower quality health services and reduced health care access, it is imperative that healthcare and nursing ageism is prevented or identified and reduced or eliminated. DESIGN: A qualitative narrative review of published research literature reviews using a scoping design to map all published reviews was undertaken. The EBSCO Discovery Service (providing access to articles in 271 databases, including MEDLINE and CINAHL) and Directory of Open Access Journals (providing access to over 9,000 open access journals) were used to find review articles. Using predetermined inclusion and exclusion criteria, and limited by English language and peer-review publications, 12 eligible reviews were identified and information from them was systematically identified, assessed and synthesised. RESULTS: The 12 reviews did not provide clear and convincing information to determine how common and impactful nursing or healthcare ageism is, nor what can best be done to prevent or address it. Although each review had value since research literature was collected and discussed on nursing or healthcare ageism, the array of literature search and analysis methods, and diversity in conclusions reached about the evidence is highly problematic. CONCLUSION: Research literature reviews offering a more balanced perspective and demonstrating greater care in finding and using quality evidence are needed. RELEVANCE TO CLINICAL PRACTICE: At this point in time, there is no clear understanding of how widespread and impactful nursing or healthcare ageism is, and what can best be done to prevent or address it. Nurses need to be aware that ageism may be common and impactful, and guard against it.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.042 | 0.052 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.008 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.011 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".