COVID-19 information and self-protective behaviors among rural communities in tropical forests
Bibliographic record
Abstract
BACKGROUND: Health risk communication plays a key role in promoting self-protective measures, which are critical in suppressing COVID-19 contagion. Relatively little is known about the communication channels used by rural poor populations to learn novel measures and their effectiveness in promoting self-protective behaviors. Behavioral change can be shaped by people's trust in government institutions which may be differentiated by social identity, including indigeneity. METHODS: During an early phase of the pandemic, we conducted two telephone surveys with over 460 communities - both Indigenous and mestizo - without road access and limited communication access in the Peruvian Amazon. This is the first report on the association of information sources about self-protective measures against COVID-19 with the adoption of self-protective behaviors in remote rural areas in developing countries. RESULTS: People mainly relied on mass media (radio, television, newspapers) and interpersonal sources (local authorities, health workers, neighbors/relatives) for information and adopted handwashing, mask-wearing, social distancing, and social restrictions to varying degrees. Overall, self-protective behaviors were largely positively and negatively associated with mass media and interpersonal sources, respectively, depending on the source-measure combination. Mistrust of the government seems to have shaped how Indigenous and mestizo peoples distinctively responded to interpersonal information sources and relied on mass media. CONCLUSIONS: Our findings call for improved media access to better manage pandemics in rural areas, especially among remote Indigenous communities.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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; a candidate call from one teacher head, 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".