1 Overview

This HTML report is designed as a professor-facing summary of the pilot results. The code is hidden by default, and the report focuses on the sample, manipulation checks, key dependent-variable results, full 2 × 2 × 2 ANOVA results, and interpretable plots.

2 Sample and Scale Reliability

Sample Summary
Raw rows after dropping Qualtrics metadata rows Final N after attention-check and debrief filters
1102 1051
Risk Scale Reliability
Scale Cronbach's alpha Standardized alpha Number of items
Risk scale: R1, R2, R3 0.899 0.899 3

3 Key Findings at a Glance

The final analytic sample includes 1051 participants after excluding incomplete/invalid responses, attention-check failures, and participants who did not complete the debrief.

The risk scale showed a Cronbach’s alpha of 0.899, indicating the internal consistency of the three risk items.

For the manipulation checks, the following MC tests were significant at p < .05: MC_3, MC_5, MC_4. The full table below shows which condition each item differed across.

For the dependent variables, at least one simple condition comparison was significant at p < .05. Significant DVs included: Risk (average of R1, R2, R3), Time (T2_1). See the DV results table for the exact condition, means, p-values, and Cohen’s d.

For the full 2 × 2 × 2 model, the three-way interaction was significant for: Time (T1). The corresponding plots are especially important to inspect.

Significance codes used throughout: *** p < .001, ** p < .01, * p < .05, . p < .10.

4 Manipulation Checks

This section shows whether the manipulation-check items differed across the relevant experimental conditions. Means and standard deviations are shown within each condition, followed by independent-samples t-tests.

Manipulation Check Results
Means (SD), sample sizes, and independent-samples t-tests
MC Item Cell 1: M (SD), n Cell 2: M (SD), n t df p
Personalisation: Not Personalised vs. Personalised
MC_1 Not Personalised: -0.88 (1.75), n=522 Personalised: -0.77 (1.76), n=529 -1.04 1048.9 0.301
MC_2 Not Personalised: 1.10 (1.51), n=522 Personalised: 0.99 (1.58), n=529 1.18 1047.9 0.238
MC_3 Not Personalised: -1.42 (1.53), n=522 Personalised: 0.16 (1.97), n=529 -14.46 994.8 < .001 ***
MC_4 Not Personalised: 0.82 (1.75), n=522 Personalised: 0.88 (1.77), n=529 -0.53 1049.0 0.599
MC_5 Not Personalised: 0.79 (1.70), n=522 Personalised: 0.71 (1.80), n=529 0.80 1047.0 0.426
Schema: Cosmetic vs. Drug
MC_1 Cosmetic: -0.83 (1.76), n=533 Drug: -0.82 (1.75), n=518 -0.01 1048.6 0.991
MC_2 Cosmetic: 1.11 (1.50), n=533 Drug: 0.98 (1.60), n=518 1.40 1039.9 0.162
MC_3 Cosmetic: -0.59 (1.95), n=533 Drug: -0.67 (1.92), n=518 0.66 1048.9 0.509
MC_4 Cosmetic: 0.89 (1.73), n=533 Drug: 0.80 (1.80), n=518 0.86 1044.4 0.389
MC_5 Cosmetic: 0.82 (1.74), n=533 Drug: 0.68 (1.77), n=518 1.28 1046.9 0.201
Goal: Prevention vs. Cure
MC_1 Prevention: -0.92 (1.73), n=504 Cure: -0.73 (1.77), n=547 -1.77 1045.8 0.076 .
MC_2 Prevention: 1.06 (1.61), n=504 Cure: 1.04 (1.49), n=547 0.22 1023.1 0.827
MC_3 Prevention: -0.67 (1.90), n=504 Cure: -0.58 (1.96), n=547 -0.78 1046.1 0.434
MC_4 Prevention: 1.44 (1.50), n=504 Cure: 0.30 (1.81), n=547 11.16 1038.7 < .001 ***
MC_5 Prevention: 0.05 (1.77), n=504 Cure: 1.39 (1.48), n=547 -13.26 984.2 < .001 ***
Significance: *** p < .001, ** p < .01, * p < .05, . p < .10.

5 Dependent Variable Results: Simple Condition Comparisons

This section shows simple comparisons for each dependent variable across each experimental condition. These are useful for seeing whether any single manipulation moved price, time, or risk perceptions on its own.

Dependent Variable Results by Condition
Means (SD), sample sizes, t-tests, and Cohen's d
Dependent Variable Cell 1: M (SD), n Cell 2: M (SD), n t df p Cohen's d
Personalisation: Not Personalised vs. Personalised
Price (FP_1) Not Personalised: 20.09 (14.29), n=522 Personalised: 19.45 (13.73), n=529 0.74 1046.0 0.461 0.05
Time (T1) Not Personalised: -0.76 (1.31), n=522 Personalised: -0.67 (1.30), n=529 -1.09 1048.4 0.276 -0.07
Time (T2_1) Not Personalised: 2.98 (1.56), n=522 Personalised: 2.91 (1.54), n=529 0.73 1048.2 0.466 0.05
Risk (average of R1, R2, R3) Not Personalised: -0.59 (1.27), n=522 Personalised: -0.57 (1.33), n=529 -0.23 1048.1 0.817 -0.01
Schema: Cosmetic vs. Drug
Price (FP_1) Cosmetic: 19.45 (14.05), n=533 Drug: 20.09 (13.96), n=518 -0.75 1048.5 0.455 -0.05
Time (T1) Cosmetic: -0.75 (1.29), n=533 Drug: -0.68 (1.31), n=518 -0.81 1046.9 0.418 -0.05
Time (T2_1) Cosmetic: 2.99 (1.57), n=533 Drug: 2.91 (1.53), n=518 0.87 1049.0 0.383 0.05
Risk (average of R1, R2, R3) Cosmetic: -0.72 (1.29), n=533 Drug: -0.45 (1.30), n=518 -3.38 1047.5 < .001 -0.21 ***
Goal: Prevention vs. Cure
Price (FP_1) Prevention: 19.02 (14.53), n=504 Cure: 20.45 (13.48), n=547 -1.65 1024.1 0.099 -0.10 .
Time (T1) Prevention: -0.75 (1.32), n=504 Cure: -0.69 (1.28), n=547 -0.75 1036.4 0.452 -0.05
Time (T2_1) Prevention: 3.05 (1.58), n=504 Cure: 2.85 (1.51), n=547 2.13 1031.8 0.034 0.13 *
Risk (average of R1, R2, R3) Prevention: -0.55 (1.31), n=504 Cure: -0.62 (1.29), n=547 0.82 1039.0 0.412 0.05
Significance: *** p < .001, ** p < .01, * p < .05, . p < .10.

6 Full 2 × 2 × 2 Interaction Results by Dependent Variable

Each section below presents the full factorial model for one dependent variable, followed immediately by the matching interaction plot. This keeps the statistical test and visual interpretation together for each DV.

6.1 Price (FP_1) DV: 3-Way Interaction Full Model + Plot

Full 2 × 2 × 2 ANOVA: Price (FP_1)
Model: DV ~ Personalisation × Schema × Goal
DV Effect df Sum Sq F p Partial eta-squared
Price (FP_1) Cond1 1 116.15 0.59 0.442 0.001
Price (FP_1) Cond2 1 81.76 0.42 0.519 0.000
Price (FP_1) Cond3 1 568.31 2.90 0.089 0.003 .
Price (FP_1) Cond1:Cond2 1 157.21 0.80 0.371 0.001
Price (FP_1) Cond1:Cond3 1 62.03 0.32 0.574 0.000
Price (FP_1) Cond2:Cond3 1 222.21 1.13 0.288 0.001
Price (FP_1) Cond1:Cond2:Cond3 1 45.94 0.23 0.629 0.000
Type III tests use sum-to-zero contrasts. Significance: *** p < .001, ** p < .01, * p < .05, . p < .10.

6.2 Time (T1) DV: 3-Way Interaction Full Model + Plot

Full 2 × 2 × 2 ANOVA: Time (T1)
Model: DV ~ Personalisation × Schema × Goal
DV Effect df Sum Sq F p Partial eta-squared
Time (T1) Cond1 1 1.91 1.13 0.289 0.001
Time (T1) Cond2 1 0.92 0.54 0.462 0.001
Time (T1) Cond3 1 0.95 0.56 0.455 0.001
Time (T1) Cond1:Cond2 1 0.02 0.01 0.918 0.000
Time (T1) Cond1:Cond3 1 0.05 0.03 0.863 0.000
Time (T1) Cond2:Cond3 1 0.51 0.30 0.583 0.000
Time (T1) Cond1:Cond2:Cond3 1 8.42 4.97 0.026 0.005 *
Type III tests use sum-to-zero contrasts. Significance: *** p < .001, ** p < .01, * p < .05, . p < .10.

6.3 Time (T2_1) DV: 3-Way Interaction Full Model + Plot

Full 2 × 2 × 2 ANOVA: Time (T2_1)
Model: DV ~ Personalisation × Schema × Goal
DV Effect df Sum Sq F p Partial eta-squared
Time (T2_1) Cond1 1 0.99 0.42 0.519 0.000
Time (T2_1) Cond2 1 2.11 0.88 0.348 0.001
Time (T2_1) Cond3 1 10.58 4.42 0.036 0.004 *
Time (T2_1) Cond1:Cond2 1 4.08 1.71 0.192 0.002
Time (T2_1) Cond1:Cond3 1 0.66 0.27 0.600 0.000
Time (T2_1) Cond2:Cond3 1 2.82 1.18 0.278 0.001
Time (T2_1) Cond1:Cond2:Cond3 1 0.44 0.18 0.668 0.000
Type III tests use sum-to-zero contrasts. Significance: *** p < .001, ** p < .01, * p < .05, . p < .10.

6.4 Risk DV: 3-Way Interaction Full Model + Plot

Full 2 × 2 × 2 ANOVA: Risk (average of R1, R2, R3)
Model: DV ~ Personalisation × Schema × Goal
DV Effect df Sum Sq F p Partial eta-squared
Risk (average of R1, R2, R3) Cond1 1 0.30 0.18 0.670 0.000
Risk (average of R1, R2, R3) Cond2 1 18.33 10.93 < .001 0.010 ***
Risk (average of R1, R2, R3) Cond3 1 1.12 0.67 0.414 0.001
Risk (average of R1, R2, R3) Cond1:Cond2 1 0.00 0.00 0.981 0.000
Risk (average of R1, R2, R3) Cond1:Cond3 1 0.32 0.19 0.663 0.000
Risk (average of R1, R2, R3) Cond2:Cond3 1 2.22 1.32 0.251 0.001
Risk (average of R1, R2, R3) Cond1:Cond2:Cond3 1 0.03 0.02 0.892 0.000
Type III tests use sum-to-zero contrasts. Significance: *** p < .001, ** p < .01, * p < .05, . p < .10.

7 Eight-Cell Descriptive Means

This section gives the raw descriptive means across all eight experimental cells. This is especially useful for interpreting any interaction effects or directional movement in the plots.

Eight-Cell Means
Descriptive statistics by Personalisation × Schema × Goal
Cond1 Cond2 Cond3 n Price M Price SD T1 M T1 SD T2_1 M T2_1 SD Risk M Risk SD
Not Personalised Cosmetic Prevention 134 18.69 14.93 -0.94 1.30 3.12 1.56 -0.67 1.31
Not Personalised Cosmetic Cure 123 20.15 13.87 -0.64 1.36 2.80 1.53 -0.79 1.31
Not Personalised Drug Prevention 131 19.52 13.86 -0.65 1.34 3.09 1.61 -0.49 1.30
Not Personalised Drug Cure 134 21.99 14.37 -0.80 1.24 2.90 1.54 -0.44 1.14
Personalised Cosmetic Prevention 121 19.70 15.44 -0.65 1.24 3.17 1.66 -0.59 1.29
Personalised Cosmetic Cure 155 19.35 12.26 -0.74 1.27 2.88 1.53 -0.80 1.25
Personalised Drug Prevention 118 18.14 13.93 -0.74 1.40 2.81 1.51 -0.43 1.34
Personalised Drug Cure 135 20.47 13.56 -0.56 1.28 2.81 1.44 -0.43 1.41