Missing data due to a 'checklist misconception-effect'.
OBJECTIVE
To analyze the extent and relevance of a postulated "checklist misconception-effect" (a specific response pattern characterized by symptom-free persons not checking the "not at all"-category).


METHODS
Our data is derived from a survey of blue collar workers (n = 228) who previously had filed in applications for medical rehabilitation benefits. We defined the "checklist misconception-effect" by the following response pattern: (1) at least one missing value and (2) at least one valid item response and (3) no 'not at all' responses.


RESULTS
75% of the responders had complete data, 16.2% a postulated 'checklist misconception-effect'. Substantial co-variations with socio-demographic characteristics or health status indicators could not be found. Additional imputation of missing values under the assumption of a "checklist misconception-effect" led to a reduction of missing data in the somatisation-subscale score from 12.3% to 0.4% compared to a simple manual-based calculation. Correlation with various external criteria (general health perception, level of functioning, depression) remained unchanged.


CONCLUSIONS
Ignoring the "checklist misconception-effect" would overestimate symptom load. However, the validity of this effect has still to be proven in methodological studies.
Meyer
Thorsten
T
Institute for Social Medicine, University Clinics Schleswig-Holstein, Luebeck, Germany. thorsten.meyer@sozmed.uni-luebeck.de
Schäfer
Ines
I
Matthis
Christine
C
Kohlmann
Thomas
T
Mittag
Oskar
O
D000328:Adult; D015982:Bias; D003625:Data Collection / Q000706:statistics & numerical data; D005260:Female; D005858:Germany; D006305:Health Status Indicators; D006306:Health Surveys; D006801:Humans; D008297:Male; D008875:Middle Aged; D009784:Occupational Diseases / Q000453:epidemiology* / Q000534:rehabilitation; D012107:Research Design; D013001:Somatoform Disorders / Q000453:epidemiology / Q000534:rehabilitation; D011795:Surveys and Questionnaires; D014942:Workers' Compensation / Q000706:statistics & numerical data