Psychology Reader

What Counts as Meaningful Individual Change?

Neil S. Jacobson and Paula Truax · 1991 · Journal of Consulting and Clinical Psychology

Role
Foundational argument · Methodological contribution
Difficulty
Moderate
Full work length
8 pages
Type
Journal article

Access

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Reading focus

Syllabus: How Do We Know When Psychotherapy Helps—or Harms?

Use the couples example to separate reliable change from the cutoff used to classify recovery.

Why you’re reading it. Turn the broad question of benefit into explicit, inspectable measurement decisions.

A question to consider. If a client improves substantially but remains outside the selected reference range, how should that result be described without erasing either progress or remaining difficulty?

Why this reading

A statistically detectable average difference does not tell us which people improved enough to matter. Jacobson and Truax distinguish change larger than expected measurement error from crossing a threshold intended to mark a meaningful outcome. Their couples-therapy example makes the consequences of those definitions visible.

Before you read

A reliable change index compares a person’s change with the variation expected from measurement imprecision. A clinical cutoff classifies the person’s final status. These answer different questions; neither by itself identifies what caused the change.

Read for

  1. Use Figure 2 to distinguish reliable improvement, crossing a cutoff and meeting both criteria.
  2. Trace how reference populations, reliability estimates and choice of measure alter classifications in the worked example.

Consider afterwards

  1. Describe someone who improves reliably but remains above a difficulty threshold, and someone who crosses it without reliable change.
  2. What important personal outcome could remain invisible even when both statistical criteria are met?

Editorial context

The paper proposes an influential operational definition, not a universal definition of recovery. Its historical language of functional and dysfunctional populations embeds assumptions about what counts as a desirable endpoint. Norms, measurement quality and uncertainty near cutoffs matter. The illustrative data combine treatment groups, so these classifications do not estimate a treatment’s causal effect. The authors themselves discuss limitations of recovery-based standards.