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Related Experiment Video

Updated: Jun 28, 2026

Using Visual and Narrative Methods to Achieve Fair Process in Clinical Care

Using Visual and Narrative Methods to Achieve Fair Process in Clinical Care

Published on: February 16, 2011

Improving care, improving performance, or just improving numbers?

Daniel J Luchins¹

¹Jesse Brown Veterans Affairs Medical Center, Chicago, IL 60612, USA. daniel.luchins@va.gov

Psychiatric Services (Washington, D.C.)

|October 31, 2008

Summary

This summary is machine-generated.

Computerized systems for mental health care lack empirical support. Non-quantitative methods may complement or correct these digital tools, highlighting the limitations of solely measuring outcomes.

Related Experiment Videos

Last Updated: Jun 28, 2026

Using Visual and Narrative Methods to Achieve Fair Process in Clinical Care

Using Visual and Narrative Methods to Achieve Fair Process in Clinical Care

Published on: February 16, 2011

Area of Science:

Mental Health
Health Informatics
Clinical Psychology

Background:

Review of literature on computerized systems in mental health care.
Limited empirical evidence supports claims of assessment or improvement.
Author's experience aligns with literature limitations.

Purpose of the Study:

To critically evaluate the empirical support for computerized systems in mental health.
To explore the role of non-quantitative methods in clinical care.
To discuss the implications of measurement-driven changes in healthcare.

Main Methods:

Literature review of computerized systems for mental health assessment and improvement.
Synthesis of empirical evidence and author's practical experience.
Argumentative analysis of quantitative vs. non-quantitative assessment methods.

Main Results:

Scarcity of empirical data validating computerized mental health systems.
Identified limitations in current digital health assessment tools.
Potential for non-quantitative methods to enhance or rectify digital assessments.

Conclusions:

Computerized mental health systems require more robust empirical validation.
Non-quantitative assessment approaches offer valuable complementary and corrective functions.
Over-reliance on measurable outcomes may distort actual clinical care improvements.