Temporal Distance, Message Framing, and Consideration of Future Consequences: Parents’ Willingness to Vaccinate Children Aged 5–11 Against COVID-19

ABSTRACT

Based on the construal level theory (CLT), this experiment employed a 2 (message framing: gain vs. loss) × 2 (temporal framing: proximal vs. distal) × 2 (consideration of future consequences: low vs. high) between-subjects factorial design. Parents (N = 409) of 5- to 11-year-old children in the United States from a pool of candidates pre-screened by Qualtrics participated in this study. Results indicated that parents with high CFC-Future were more receptive to messages advocating getting their children vaccinated against COVID-19. Parents with high CFC-Future reported higher risk perception in response to the proximal messages compared to the distal messages. For parents focusing on more distant outcomes, proximal messages generated more positive attitude and greater intention compared to distal messages in the loss-framed condition. The difference was not significant in the gain-framed condition. Theoretical and practical implications were discussed. Limitations and directions for future research were outlined.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1. Two items in the scale are related to perceived morality, which may render this measurement to lean toward morality-related attitudes. We chose this approach because of the following reasons: 1) General attitudes (whether it is good or wise to perform a behavior) are generic, which provide little guidance for health campaigns promoting vaccination. Specific attitudes tell us what aspects to focus on during campaign design. Pediatric vaccination (such as COVID-19 vaccination) among young children has been predominantly framed as a moral act (e.g., parents are expected to care for their children; it’s a greater good for society at large), which is prevalent in the media discourse and scholarly research (e.g., Fahlquist, 2023; Schmidtke et al., 2022). There were risk and care aspects in the experimental stimuli, we also measured health-related risk perceptions, and the care/value/morality-related attitudes were assessed to supplement risk beliefs. 2) There is a general attitudinal item in this scale (i.e., “Getting my child(ren) vaccinated … . – It is a correct thing to do”). We have performed additional analysis using this single-item measure, and the results were largely unchanged.

2. We understand that risk perception is typically conceptualized as having two components: perceived severity and perceived susceptibility. Because our focus is the overall measure of perceived risk on the individual level, we averaged the values of perceived susceptibility and perceived severity to create a composite score. This approach has been practiced in various contexts in health communication, including COVID-19 protective behaviors (Duong, 2022), cancer prevention (Rimal & Juon, 2010) and detection (Su & Shi, 2023), HPV vaccination (Pask & Rawlins, 2016), and combatting climate change (Shi et al., 2023) across cultural backgrounds (e.g., U.S., China, and Vietnam). In addition, the data indicated that these seven items loaded on one factor. Using the maximum likelihood method and the direct Oblimin rotation, one factor emerged: all seven items formed a unidimensional scale with factor loadings ranging from .73 to .87.

3. The 5 original future-related CFC items were redundant, two items were double-barreled, and two items shared high error covariance rendering one of them was unnecessary (e.g., Wang & Zhao, 2018). Therefore, we edited the language to make the items simpler while preserving the meaning of the original items. Our items formed a unidimensional measure based on the maximum likelihood estimate and oliblim rotation in EFA. We have clarified the language throughout to indicate this measure as CFC-Future (e.g., not CFC-Immediate). A common procedure used in previous research (e.g., Kees, 2010; Kim & Nan, 2016; Orbell & Hagger, 2006) categorized participants as either low or high CFC-Future based on a median split, which may reduce the power of analysis or create spurious results. Therefore, we have used Model 3 in PROCESS (Hayes, 2022) to test the interaction effects of the two message manipulations and CFC (which was entered as a continuous measure without a median split).