Newspaper coverage of advance care planning during the COVID-19 pandemic: Content analysis
Bibliographic record
Abstract
COVID-19 may cause sudden serious illness, and relatives having to act on patients’ behalf, emphasizing the relevance of advance care planning (ACP). We explored how ACP was portrayed in newspapers during year one of the pandemic. In ‘LexisNexis Uni’, we identified English-language newspaper articles about ACP and COVID-19, published January–November 2020. We applied content analysis; unitizing, sampling, recording or coding, reducing, inferring, and narrating the data. We identified 131 articles, published in UK (n = 59), Canada (n = 32), US (n = 15), Australia (n = 14), Ireland (n = 6), and one each from Israel, Uganda, India, New-Zealand, and France. Forty articles (31%) included definitions of ACP. Most mentioned exploring (93%), discussing (71%), and recording (72%) treatment preferences; 28% described exploration of values/goals, 66% encouraged engaging in ACP. No false or sensationalist information about ACP was provided. ACP was often not fully described. Public campaigns about ACP might improve the full picture of ACP to the 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 | 0.012 | 0.058 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.018 | 0.025 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".