Differences in salient beliefs associated with voluntary exercise training among South Korean firefighters before and after COVID-19
Bibliographic record
Abstract
BACKGROUND: Participating in voluntary exercise training is important to meet occupational requirements as well as firefighters' health and safety. The purpose of this study is to identify salient beliefs associated with voluntary exercise training among firefighters in the pandemic era by comparing outcomes with those from a previous elicitation study, which was carried out before the COVID-19 outbreak. METHODS: A total of 57 firefighters are recruited to participate in an elicitation study. Participants are requested to respond to six open-ended questions related to voluntary exercise training. Content analysis is used to create categories that combine similar factors in each belief. Beliefs mentioned by more than 30% of participants are used for comparison with the results of the previous research. RESULTS: "Improves my physical ability" (n = 44) and "cause injury" (n = 17) are identified as behavioral beliefs in the present study, whereas "makes me tired" and "takes too much time" were also elicited in Lee's study. Normative beliefs are "family members" (n = 45) and "colleagues" (n = 27) and these results are consistent with those in Lee's study. "Lack of time" (n = 28), "exercise facilities" (n = 19), and "COVID-19" (n = 19) are elicited as control beliefs in the present study, whereas "physical condition" (n = 21) and "exercise partners" (n = 14) were elicited as other control beliefs, and "COVID-19" was not mentioned in Lee's study. CONCLUSION: This study can contribute valuable information about salient beliefs associated with exercise training behavior among firefighters, particularly under pandemic conditions. Future researchers should develop tailored exercise training programs for firefighters based on current elicited beliefs.
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 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 | 0.001 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".