Relationships

See the upcoming research article on Digital Society on discovery-driven In-App research:
MyBioethics: How Ed-Tech Enables Discovery-Driven Empirical Bioethics Research

This page includes screenshots of the automatically processed dilemma and survey data. The values and images are periodically updated, most recently in May 2024.

Install the application for free to review the detailed dilemma scenarios and survey questions. Also, see the list of most promising Research Findings with dilemma descriptions and graphs.

Dilemmas and surveys

The creation of new lessons and integration of surveys depend on our development team’s research interests and our institutional partners’ input.

LessonAcronymDilemmasEntries*
Moral ImaginationMI2263
Healthcare InequalityHI2100
Ethical ArgumentationEA2290
Healthcare LGBTQHL255
GeneticsGe2289
Informed ConsentIC782
Self-experimentationSE2159
ProfessionalismPr226
CommodificationCo296
NeuroethicsNe295
Healthcare AutonomyHA2296
On PsychedelicsOP312
PatienthoodPa3140
High-cost DrugsHD425
Animal EthicsAE447
*User completed all dilemmas of the lesson
SurveyAcronymEntries
Existential QuestEQ153
Need for CognitionNC121
Need for Affect*NA
ApproachAP60
AvoidanceAV57
Nature RelatednessNR113
Life OrientationLO32
*Survey has multiple subfactors, these are listed below it

Connections

To uncover factors that play a part in moral decision-making, data from user interaction is processed to identify possible connections between entries. To do this, correlation and probability values are calculated to evaluate these relationships. Even though the data is quantitative, this is still explorative research, and all findings are preliminary and indicative.

Between dilemmas

Correlations between answers to the dilemma scenarios and the respective sample sizes. A high positive correlation means that A-A and B-B connections are more likely, in turn, a high negative correlation means that A-B and B-A connections are more likely. A value close to zero means no connection between the two dilemmas. Many dilemma pairs still have too few overlapping entries to have reliable correlation values.

With surveys

The correlation, probability, and sample size tables assist in analyzing whether these factors are determinants of the dilemma answers. High (positive or negative) effect size (or correlation), low p-value, and a large sample indicate a connection between the dilemma and the measured tendency. Some findings may seem over-promising because dilemma answers were overly uneven (A: 95% B: 5%), which can distort the result. Importantly, these can only be used to rule out false positives, the only thing helping with false negatives is additional data.

Effect size = High positive value means that users with a high survey score are likely to answer A. Same reversed.
Probability = Low value means that it is likely that the survey is connected to the dilemma answer.
Sample size = The bigger the sample, the more reliable the result.

NOTE: Due to the desire to automate the initial data screening process, Microsoft Excel is used to calculate correlations and probabilities. For publications, we instead use JMP with more advanced statistical methods.

Relationships between surveys and dilemmas hint that these factors affect our moral judgements.

Sign up for updates on the Research page or contact the development team via Support to request access to data.