S. Zaza et al., Data collection instrument and procedure for systematic reviews in the Guide to Community Preventive Services, AM J PREV M, 18(1), 2000, pp. 44-74
Introduction. A standardized abstraction form and procedure was developed t
o provide consistency, reduce bias, and improve validity and reliability in
the Guide to Community Preventative Services: Systematic Reviews and Evide
nce-Based Recommendations (the Guide).
Data Collection Instrument. The content of the abstraction form was based o
n methodologies used in other systematic reviews; reporting standards estab
lished by major health and social science journals; the evaluation, statist
ical and meta-analytic literature; expert opinion and review; and pilot-tes
ting. The form is used to classify and describe key characteristics of the
intervention and evaluation (26 questions) and assess the quality of the st
udy's execution (23 questions). Study procedures and results are collected
and specific threats to the validity of the study are assessed across six c
ategories (intervention and study descriptions, sampling, measurement, anal
ysis, interpretation of results and other execution issues),
Data CollectionProcedures. Each study is abstracted by two independent revi
ewers and reconciled by the chapter development team. Reviewers are trained
and provided with feedback,
Discussion. What to abstract and how to summarize the data are discretionar
y choices that influence conclusions drawn on the quality of execution of t
he study and its effectiveness. The form balances flexibility for the evalu
ation of papers with different study designs and intervention types with th
e need to ask specific questions to maximize validity and reliability. It p
rovides a structured format that researchers and others can use to rede-Lv
the content and quality of papers, conduct systematic reviews, or develop m
anuscripts. A systematic approach to developing and evaluating manuscripts
will help to promote overall improvement of the scientific literature.
Medical Subject Headings (MeSH): data abstraction, evaluation, study design
, study quality (C) 2000 American Journal of Preventive Medicine.