Examining the Relationship between Message Variables, Affective Reactions, and Parents’ Instrumental Attitudes toward Their Child’s Physical Activity: The “<i>Mr. Lonely”</i> Public Service Announcement
Bibliographic record
Abstract
This study examined the relationship between message variables and affective reactions with parents' attitudes after seeing a physical activity mass media public service announcement (PSA). It was hypothesized that there would be a positive relationship between message variables (i.e., personal relevance, novelty of information, and feelings toward sponsoring organization) and parents' attitudes toward their child/children's physical activity after viewing the PSA. Furthermore, we explored whether discrete affective reactions were related to attitudes, beyond the effect of message variables. A secondary data analysis was conducted with parental responses to an online campaign evaluation survey (n = 267). Hierarchical regression analyses showed an overall positive relationship between all three message variables and attitudes. Furthermore, two discrete affective reactions were positively related to attitudes. Parents who endorsed feeling motivated or guilty after viewing the advertisement had more positive attitudes toward their children's physical activity levels. This study represents an ecologically valid assessment of how message variables and affective reactions are related to attitudes within the context of a physical activity mass media campaign. The results provide guidance for the effective design of mass media physical activity campaigns.
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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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".