Perceived Effectiveness of COVID-19 Preventive Practices and Behavioral Intention: Survey of a Representative Adult Sample in the United States
Bibliographic record
Abstract
BACKGROUND: Using existing models of behavioral health promotion, specifically the Extended Parallel Process Model, previous research has identified factors that may impact engagement in preventive health behaviors during the COVID-19 pandemic such as perceived threat, perceived susceptibility to the threat, perceived severity, and perceived efficacy. OBJECTIVE: This study aims to examine the role of perceived effectiveness of COVID-19 preventive behaviors, perceived susceptibility, perceived threat, and perceived severity of COVID-19 in participants' intentions to engage in Centers for Disease Control (CDC)-recommended individual health behaviors in the first year of the pandemic. METHODS: In October 2020, a representative sample of 506 US adults completed a web-based survey through the RAND American Life Panel. RESULTS: The study primarily found that participants who perceived that CDC-recommended health practices were effective had stronger intentions to engage in those practices. The second strongest correlate was participants' perceived severity of COVID-19 across the United States. Perceived effectiveness of recommended practices accounted for the largest variance in behavioral intention. However, analysis of individual behaviors indicated a mismatch in the behaviors perceived to be the most effective (avoiding sick people and mask-wearing) and those participants indicated intention to engage in (throwing away used tissues, avoiding sick people, and coughing into their elbows) in the next 30 days. CONCLUSIONS: The authors recommend tailoring public health messaging to address the perceived threat of COVID-19 and self-efficacy. Thus, health promotion efforts should emphasize the effectiveness of CDC-recommended practices while highlighting the pandemic's severity. Additionally, rebuilding trust in public health messaging and messengers is necessary to increase perceived self-efficacy. As the COVID-19 pandemic continues, health messaging must continue to promote and build trust in CDC-recommended health practices and educate regarding the efficacy of vaccination and other preventive behaviors.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".