Research Supporting the Video

Boost ’em in the Back Seat: A Safe Ride Program

Summary of Results

A complete report of this research is published in Accident Analysis and Prevention (Will, Sabo, & Porter, 2009). The main findings are summarized here. With funding from the Centers for Disease Control and Prevention (New Investigator Grant # 1 R49 CE000240-01), Dr. Kelli England Will’s research team at Eastern Virginia Medical School created and tested a 6-minute video-intervention entitled Boost ’em in the Back Seat that used a threat appeal approach.

The video’s threat-appeal approach represents a unique and innovative methodology in child occupant protection, as most programs are primarily informational in nature and are not designed according to best practices in risk communication. Research indicates that health threat messages that evoke a high sense of vulnerability to a hazard andpromote high efficacy for protecting oneself from the hazard inspire greater adoption of recommended health behaviors than messages that aren’t designed to induce feelings of high fear and high efficacy (Leventhal & Cameron, 1994; Witte, 1998; Witte & Allen, 2000).

The booster-seat video-intervention program was evaluated in afterschool care settings in four Hampton Roads, VA cities (N = 226 parents) via an interrupted time series design with similar control sites for comparison. Demographics of study participants are included in Table 1. Most participants were female (80.2%) and most were parents (93%) of a child at the daycare (versus grandparent, etc.). The research team used several dependent measures to assist with evaluation of the video, including a sophisticated parking-lot behavioral observation methodology, a Knowledge, Attitudes, and Practice survey, and a Risk Estimation scale. A pre-existing Risk Behavior Diagnosis Scale (Witte, Cameron, McKeon, & Berkowitz, 1996) was also used to evaluate the video’s threat and efficacy components.

Overall, the video was well-received by participants and the traffic safety community. Ninety-nine percent of participants thought that every parent of a young child should see the video and 86% of participants stated that they learned a lot from the video. Further, the video has been praised by the traffic safety community, as it has been endorsed by the national Emergency Nurses Association and received an award for Traffic Safety Excellence in Education and Prevention from the regional DRIVE SAFE Coalition in Hampton Roads, Virginia.

The study’s results support the hypotheses and indicate that the video program was successful. Specifically, compared to baseline and control assessments (which were equivalent as expected, t(217)= 1.22, n.s.), the treatment groups’ (N=100) child passenger safety knowledge, risk-reduction attitudes, and behavioral intentions related to booster-seat and back-seat use increased significantly from pre-test (M=98.6) to post-test (M=116.2), t(99) = 12.25, p<.001 (see Figure 1)i. For instance, surveys indicate that parents learned that the seat belt does not provide the same protection as a booster seat and that children should remain in a booster seat until approximately 80 pounds. Parents also learned that booster seats are recommended for most 7-year-olds. Compared to baseline and control conditions, parents exposed to the video reported having less favorable attitudes toward children traveling in the front vehicle seat, felt more comfortable with booster seat installation, and perceived cost to be less of a barrier.

The video’s threat and efficacy components were evaluated using Witte and colleagues’ Risk Behavior Diagnosis Scale (Witte, Cameron, McKeon, & Berkowitz, 1996). Compared to control and baseline levels of threat (which were equivalent as expected, t(218)= 0.72, n.s.), the video significantly increased parents’ overall sense of threat related to the hazard from pre-test (M=25.9) to post-test (M=27.6), t(99) = 4.64, p<.001. Further, compared to control sites and baseline levels of efficacy (which were equivalent as expected, t(218)= 0.19, n.s.), the video significantly increased parent’s sense of efficacy related to the recommended behaviors (including response-efficacy and self-efficacy) from pre-test (M=23.6) to post-test (M=27.5), t(99) = 8.08, p<.001 (see Figure 2).

In addition to survey data, systematic behavioral observations were conducted weekly at each site to observe any changes in restraint use or back seat use. A “clicker-board” was designed by the research team to collect these data. The clicker-board was composed of twelve standard tally counters mounted to a masonite board and divided into quadrants. Each tally counter was labeled and used to record data for a specific type of observation made (i.e. unrestrained, riding in the back seat, etc.). Three of the quadrants were used to record the data for each specific age group (infant/toddler, booster-size, or belt-size), while the fourth quadrant was used to record a child’s location in the car (front seat or back seat). (See the diagram of the clicker board in Figure 3.) Two observers simultaneously collected data for 13% of the observation days in order to determine inter-rater reliability. Inter-rater reliability was calculated using two methods. The first method followed a standard inter-rater reliability formula: the number of observations that both researchers agreed upon, divided by the total number of agreements plus disagreements. All inter-rater reliability values were excellent, at above .90. A more conservative measure that corrects for chance agreement, Cohen’s Kappa, was also computed to analyze reliability. According to Fleiss (1981), Kappa values of above .40 are acceptable, while values above .75 are considered excellent. All Kappa reliability values were in the excellent range, at above .75.

With respect to trend analyses of behavioral observation data, the C-Statistic (Tryon, 1982) was computed to evaluate the presence of changes due to the treatment intervention in serially dependent time series data. During the baseline phase (36 observation days completed over 9 weeks) the data were tested to observe the presence of any trends for overall restraint use and booster seat use at intervention sites compared to control sites. As expected, the resulting C-statistic indicated the absence of any trends during baseline for overall restraint use (Z = 0.34, n.s. for the intervention group and Z = 1.00, n.s. for the control group)and for booster seat use (Z = -0.10, n.s. for the intervention group and Z = -1.04, n.s. for the control group). This confirmed that our groups did not differ and the baseline was stable prior to intervention.

During the intervention phase (44 observation days over 11 weeks), the video intervention was implemented in intervention sites and resulted in the appearance of a significant upward trend in both restraint use and booster seat use for the intervention sites (see Figure 4 and Figure 5). The analysis of observed restraint use across the 20 observation weeks (baseline + phase 2) at intervention sites demonstrated a significant upward trend following the intervention for overall restraint use (Z = 2.60,p<.05) and for booster seat use (Z = 3.60, p<.05). Comparison sites (which did not receive the intervention) did not show a significant trend change from baseline to phase 2 (20 observation weeks) for either overall restraint use, Z = .75, n.s., or booster seat use, Z = .56, n.s. These analyses confirmed that, as hypothesized, there were significant increases in observed overall restraint use and booster seat use following exposure to the intervention video compared to both baseline and to control sites.

C-statistic analyses of observed rear-seat use indicated the absence of any significant trends from baseline to Phase 2 for either the intervention (Z = .47, n.s.) or control groups (Z = .08, n.s.). This is potentially due to ceiling effects, as mean rear-seat use at baseline was 92.2% for the intervention group and 94.1% for the control group. During Phase 2, mean rear-seat use was 92.5% and 93.9% for the intervention and control groups, respectively.

This quasi-experimental study tested the use of a properly designed high-threat message to increase booster-seat use. Results support the effectiveness of the program, with significant improvements in knowledge, attitudes, fear, efficacy, and observed safety behavior following exposure to the video. Although no changes were noted regarding rear-seat use (possibly due to ceiling effects), the intervention resulted in a 16% increase in booster-seat use over baseline level and a 15% increase in overall restraint use (for all ages of children observed) over baseline level. The Boost ’em in the Back Seat Safe Ride Program is thought to be the first intervention of its kind, as no other child passenger safety programs are known that specifically target an increase in caregivers’ perception of vulnerability to motor vehicle injury to their children.

For the Complete Report of the Study:

Will, K. E., Sabo, C. S., & Porter, B. E. (2009). Evaluation of the Boost ’em in the Back Seat Program: Using fear and efficacy to increase booster seat use. Accident Analysis and Prevention, 41, 57-65.
Download PDF or visit doi:10.1016/j.aap.2008.09.007.


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Leventhal, H., & Cameron, L. (1994). Persuasion and health attitudes. In S. Shavitt & T. Brock (Eds.), Persuasion: Psychological insights and perspectives (pp. 219-249). Nedam Heights, MA: Paramount Publishing.

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Will, K. E., Sabo, C. S., & Porter, B. E. (2009). Evaluation of the Boost em in the Back Seat Program: Using fear and efficacy to increase booster seat use. Accident Analysis and Prevention, 41, 57-65.

Witte, K. (1998). Fear as motivator, fear as inhibitor: Using the extended parallel process model to explain fear appeal successes and failures. In P. A. Andersen & L. K. Guerrero (Eds.), Handbook of communication and emotion (424-451). San Diego, CA: Academic Press.

Witte, K., & Allen, M. (2000). A meta-analysis of fear appeals: Implications for effective public health campaigns. Health Education & Behavior, 27(5), 591-615.

Witte, K., Cameron, K., McKeon, J., & Berkowitz, J. (1996). Predicting risk behaviors: Development and validation of a diagnostic scale. Journal of Health Communication, 1, 317-341.