Sample Characteristics
The total sample includes data sets of n = 210 students. Of these students, n = 160 participated in the post-testing and n = 49 in the follow-up testing. About 29% of the students (n = 60) had visited lectures about sexualized violence before (curriculum group: n = 48 or 30%; control group: n = 12 or 22%).
Of the curriculum group, n = 156 students (90% female) took part in the pre-testing. On average, they were M = 23.05 years old (SD = 5.12, range = 17–50) and had been attending university M = 3.83 semesters (SD = 2.9, range = 1–23). Of these students, n = 86 (55%) also took part in the post-testing and n = 49 (31%) in the follow-up testing. The sample size including students who took part in all three testings was n = 33 students (21%).
Of the control group,
n = 54 students (89% female) participated in the pre-testing. These students were
M = 22.23 years old (
SD = 2.8, range 19–31) and had been studying
M = 4.66 semesters (
SD = 1.62, range 2–12). Twenty students (37%) also participated in the post-testing. Table
2 shows the descriptive statistics separated by groups.
Table 2
Descriptive statistics: raw means of the pre-, post- and follow-up testings separated by groups
Outcome | Time | Participants | M ± SD* | Participants | M ± SD* |
SAK | Pre | 154 | 3.53 ± 0.68 | 52 | 3.29 ± 0.61 |
Post | 85 | 2.51 ± 0.59 | 20 | 3.09 ± 0.41 |
Follow-up | 48 | 2.43 ± 0.52 | – | – |
DK | Pre | 156 | 14.00 ± 3.47 | 54 | 12.94 ± 3.49 |
Post | 86 | 15.36 ± 3.67 | 20 | 14.60 ± 3.15 |
Follow-up | 49 | 15.73 ± 2.89 | – | – |
PC | Pre | 156 | 3.46 ± 0.76 | 54 | 3.35 ± 0.73 |
Post | 86 | 2.73 ± 0.60 | 20 | 3.5 ± 0.60 |
Follow-up | 49 | 2.56 ± 0.60 | – | – |
AMMSA* | Pre | 154 | 2.10 [1.36; 3.09] | 51 | 2.18 [1.27; 3.09] |
Post | 85 | 1.55 [1.09; 2.27] | 20 | 1.82 [1.14; 2.55] |
Follow-up | 49 | 1.55 [1.23; 2.73] | – | – |
CSAM* | Pre | 156 | 1.40 [1.20; 1.67] | 53 | 1.27 [1.20; 1.57] |
Post | 85 | 1.20 [1.07; 1.47] | 20 | 1.31 [1.27; 1.43] |
Follow-up | 49 | 1.27 [1.07; 1.50] | – | – |
Impact of the Curriculum
First, we examined the impact of Seminar (A, B, C) and Time (post, follow-up) on the change from baseline in the main outcome measures. For all participants of the curriculum group, estimated margins were conducted for self-assessed knowledge (SAK), declarative knowledge (DK), and professional confidence (PC); logarithmized values were conducted for Child Sexual Abuse Myths (CSAM) and Acceptance of Modern Myths about Sexual Aggression (AMMSA). For all variables despite DK, negative values express the students’ improvement on the scales. For the variable DK, positive values express an improvement on the scale.
SAK, DK, AMMSA, and CSAM revealed global effects. Neither significant interaction effects of Seminar and Time nor significant main effects were found (see Table
3). In detail, the SAK improved by 1.08 points, 95% CI [−1.19; −0.98], and
p < 0.001. The DK increased by 1.07 points, 95% CI [0.58; 1.55], and
p < 0.001. A global effect of the curriculum also revealed for the AMMSA scale, whereby the average answer was reduced by 12% (est. multiple of BL = 0.88, 95% CI [0.82; 0.94],
p < 0.001), as well as for the CSAM scale, which was reduced by 8% (est. multiple of BL
= 0.92, 95% CI [0.90; 0.95],
p < 0.001). Thus, the students rejected sex-related myths even more after participating in the curriculum.
Table 3
Results of the linear mixed models: changes from baseline in self-assessed knowledge, declarative knowledge, and professional confidence
The analysis of the students’ PC shows a significant linear effect of Time on the difference to baseline. A post hoc contrast analysis reveals that the difference to baseline increased significantly from post to follow-up testing (est. diff. to BL = −0.20, 95% CI [−0.35, −0.05], p = 0.007).
Second, we examined the impact of Seminar (A, B, C) and Time (post, follow-up) on the subtopics a, b, and c. The analyses are separately reported for self-assessed knowledge (SAK; see Table
4) and declarative knowledge (DK; see Table
5).
Table 4
Results of the linear mixed models: changes from baseline in self-assessed knowledge separated by topics
Table 5
Results of the linear mixed models: changes from baseline in declarative knowledge separated by topics
Starting with the analyses of SAK, main effects of Seminar revealed for all three topics. In all three seminars, the students’ specific SAK about Topic A improved significantly, whereby a post hoc contrast analysis showed that Seminar A improved the SAK about Topic A more than Seminars B (est. diff. to BL = −0.35, 95% CI [−0.59, −0.1], p = 0.005) and C (est. diff. to BL = −0.27, 95% CI [−0.52, 0.02], p = 0.036). For Topic B, the analyses of the specific SAK not only revealed a significant main effect of Seminar but also of Time. Post hoc contrast analysis shows that Seminar B improved the SAK about Topic B more than Seminars A (est. diff. to BL = −0.84, 95% CI [−1.18, −0.51], p < 0.001) and C (est. diff. to BL = −0.83, 95% CI [−1.18, −0.48], p < 0.001). Furthermore, the difference to baseline at the follow-up testing was significantly greater than at post-testing (est. diff. to BL = −0.21, 95% CI [−0.40, −0.02], p = 0.032). For the specific SAK about Topic C, post hoc contrast analysis of the main effect of Seminar shows that Seminar C improved the specific SAK about Topic C more than Seminars A (est. diff. to BL = −0.49, 95% CI [−0.86, −0.13], p = 0.007) and B (est. diff. to BL = −0.83, 95% CI [−1.21, −0.46], p < 0.001). In summary, each of the seminars had the most impact on its main topic.
The analyses of DK only yielded main effects of Seminar for topics a and b (Table
5). The specific DK about Topic A improved significantly in Seminars A and C, but not in Seminar B. Post hoc contrast analysis shows that Seminar A improved the DK about Topic A more than Seminar B (est. diff. to BL = 0.72, 95% CI [0.19, 1.25],
p = 0.007) but not more than Seminar C (est. diff. to BL = 0.36, 95% CI [−0.18, 0.89],
p = 0.192). For DK about Topic B, solely Seminar B increased the DK significantly from baseline. Contrast analysis reveals that Seminar B improved the DK more than Seminars A (est. diff. to BL = 0.69, 95% CI [0.13, 1.24],
p = 0.015) and C (est. diff. to BL = 0.75, 95% CI [0.17, 1.33],
p = 0.011). For Topic C, a global effect over all seminars and time points improved the DK by 0.47 points, 95% CI [0.22; 0.74], and
p < 0.001.
Curriculum vs. Control Group
The baseline adjusted linear regressions show that group affiliation is a significant predictor for changes in SAK (t(101) = −0.65, p < 0.001, R2 = 0.58) and PC (t(102) = −0.72, p < 0.001, R2 = 0.29), but not in DK (t(102) = 0.28, p = 0.617, R2 < 0.01). Regarding SAK, both groups showed significant differences to baseline, whereby the difference was greater in the curriculum than in the control group; regarding DK and PC, the differences to baseline were only significant in the curriculum group but not in the control group. Group affiliation neither predicted the multiple of baseline for AMMSA (t(100) = −0.03, p = 0.827, R2 < 0.01) nor for CSAM (t(100) = −0.09, p = 0.190, R2 = 0.02). For both AMMSA and CSAM, significant multiples of baseline only revealed in the curriculum group but not in the control group.