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Related Concept Videos

Decision Making: P-value Method01:09

Decision Making: P-value Method

The process of hypothesis testing based on the P-value method includes calculating the P- value using the sample data and interpreting it.
First, a specific claim about the population parameter is proposed. The claim is based on the research question and is stated in a simple form. Further, an opposing statement to the claim  is also stated. These statements can act as null and alternative hypotheses:  a null hypothesis would be a neutral statement while the alternative hypothesis can have a...
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Decision Making

Decision-making is a fundamental cognitive process that involves evaluating alternatives and selecting among them. This process can range from simple choices, such as deciding what to wear, to complex decisions, like choosing a major in college or a career path. The complexity of the decision often dictates the approach we use, which can be broadly categorized into two types: automatic and controlled decision-making.
Automatic decision-making is fast, intuitive, and relies on gut feelings...

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A Structured Rehabilitation Protocol for Improved Multifunctional Prosthetic Control: A Case Study
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User-Complexity and Decision-Making in Upper Limb Prosthetic Device Selection: Discrete Choice Measurement Tool

Ruben Vargas1, Todd Castleberry2, Kristin Nalivaika2

  • 1Department of Clinical Pharmacy, University of California San Francisco, San Francisco, CA.

Archives of Physical Medicine and Rehabilitation
|January 6, 2026
PubMed
Summary
This summary is machine-generated.

A new choice-based conjoint tool helps individuals with upper limb amputation (ULA/D) weigh prosthetic risks and benefits. User complexity influences preferences, guiding personalized device selection for better outcomes.

Keywords:
AmputationPatient preferenceProsthesis designRehabilitationUpper extremityUser-centered design

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Area of Science:

  • Biomedical Engineering
  • Rehabilitation Science
  • Prosthetics and Orthotics

Background:

  • Individuals with upper limb amputation or difference (ULA/D) face complex choices when selecting prosthetic devices.
  • Assessing risk-benefit trade-offs is crucial for optimizing prosthetic device selection and user satisfaction.
  • Understanding how user complexity influences prosthetic preferences is essential for personalized rehabilitation.

Purpose of the Study:

  • To develop and pilot-test a choice-based conjoint (CBC) tool to assess risk-benefit trade-offs in prosthetic device selection for individuals with ULA/D.
  • To explore the influence of user complexity on prosthetic preferences among individuals with ULA/D.

Main Methods:

  • A survey-based study employed a choice-based conjoint (CBC) tool with a full-profile, balanced-overlap experimental design.
  • Qualitative interviews with individuals with ULA/D and content experts informed attribute selection.
  • Pilot testing involved 54 individuals with ULA/D completing the CBC tool, with remote interviews and online survey participation.

Main Results:

  • Eight key attributes were identified: functional usefulness, life goals, noticeability, weight/comfort, durability/repairs, concentration/energy, body connection, and training.
  • Participants showed a strong preference for precision control via implanted electrodes (62.1%) and highly durable devices (56.0%).
  • Preferences varied by user complexity, with moderate-complexity devices favored over low-complexity (70%) and high-complexity (56%) options.

Conclusions:

  • The developed CBC tool effectively captures user preferences and risk-benefit trade-offs in prosthetic selection.
  • Preliminary findings suggest the tool can guide personalized prosthetic decision-making based on user complexity.
  • The study highlights the importance of considering individual user capabilities when selecting prosthetic devices.