FROM MY PT SCHOOL NOTES · EVIDENCE-BASED PHYSICAL THERAPY · CHAPTER 5
What Makes a Study Result Biased?
The study’s conclusions may look persuasive until you consider the people, measurements and events that shaped its results.
What else could explain the result?
This chapter asks whether results are believable and useful. Internal validity concerns competing explanations for an observed effect; construct validity concerns what is actually represented or measured; external validity addresses transfer of results across patients, places and time.
The course lists selection and allocation differences, attrition, maturation, treatment contamination, compensatory rivalry or demoralization, and regression toward the mean among participant-related threats.
Where can bias enter?
History events, instrumentation changes, testing/practice effects, assessor expectations and unequal extra attention are additional threats. The notes emphasize comparison groups, consistent protocols, training, measurement calibration, masking where feasible and transparent reporting.
What safeguards help?
Intention-to-treat (ITT) analysis keeps randomized participants in their assigned groups when analyzing outcomes. The lecture also discusses adjustment for measured confounding and triangulation/reflexivity as trustworthiness concepts for qualitative inquiry.
Check your reasoning: Does statistical adjustment remove every threat to validity?
No. Models can address measured confounding under assumptions; unmeasured variables, selection and missing data can still distort results.
Updated-standard note
The original slides list trimming extreme values or replacing dropouts as possible fixes. Doing either after seeing results can introduce bias. CONSORT 2025 (which replaced CONSORT 2010) now emphasizes transparent reporting of trial flow, missing data, harms and intervention delivery. It is a reporting guide, not a guarantee of study quality. Compare your class’s terminology with https://www.consort-spirit.org/published-statements.
Put it into practice
Scenario: Participants most motivated to recover disproportionately choose the new program; the researchers then report better outcomes for that group.
What should you conclude?
Reasoning: Self-selection and motivation may confound the apparent effect. Look for allocation methods, baseline differences, prognostic factors and how missing data were handled before attributing change to the program.
Common trap: Assuming a statistical adjustment fixes all unmeasured confounding. Remember: Name a plausible alternative explanation and how it could alter the result.
Course basis: my Evidence-Based PT school notes, source lecture Chapter 8. New questions and headings are teaching aids, not official exam items. For full definitions and examples, use the class notes and assigned readings.
