Four Principles Bioethics Balance Simulator

Clinical Scenario

A competent adult with a life-threatening condition refuses the recommended treatment on religious grounds.

Principle Weights

Autonomy 1.00

Beneficence 1.00

Non-maleficence 1.00

Justice 1.00

Balance of Influence

25%

Node speed |v|

0.000

Residual to equilibrium

0.000

Dominant principle: Autonomy — settled resolution leans toward respecting the patient's decision.

How it works

Beauchamp & Childress' "four principles" approach treats autonomy, beneficence, non-maleficence and justice as prima facie duties — each binding unless it conflicts with another, in which case clinicians "balance" them for the case at hand. This simulator makes that balancing act literal physics.

Each principle is a fixed anchor point in 3D. A spring pulls the central decision node toward anchor i with force proportional to a spring constant k_i = (your weight slider) × (how strongly that principle applies to the chosen scenario):

F_i = k_i · (anchor_i − x)
x(t+dt) = x(t) + v·dt,   v(t+dt) = (v(t) + ΣF_i/m·dt) · (1 − c·dt)

Equilibrium (ΣF_i = 0):
x_eq = Σ(k_i · anchor_i) / Σ(k_i)   ← the weighted centroid

Weight sliders — how much ethical importance you personally assign to each principle right now (0 = ignored, 2 = double weight).
Scenario score — how strongly the principle is engaged by the facts of the case (fixed per scenario, drawn from the underlying clinical dilemma).
The node always settles at the weighted average of the four anchors — exactly the same arithmetic as a weighted mean, just reached by damped spring dynamics instead of computed directly.
Perturb node gives it a random kick so you can watch it re-converge; Reset weights returns all four sliders to 1.0 (unweighted balancing).

This is a model of the reasoning process, not an algorithm that decides real cases — in practice a clinical ethics committee weighs these same four principles qualitatively, case by case.

Autonomy Beneficence Non-maleficence Justice

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