How far does screening women for domestic (partner) - NIHR Health ...

DOI: 10.3310/hta13160 Health Technology Assessment 2009; Vol. 13: No. 16
method of identification/disclosure) and, in the
case of intervention studies, the nature of the
intervention. We performed narrative sensitivity
analysis for each question, testing whether the
overall findings persisted when the poor-quality
studies were excluded. When effect sizes were not
reported, we calculated Cohen’s d if the mean
changes and standard deviations were reported in
the papers or were available from the authors. For
the quantitative studies, after consideration of the
heterogeneity of interventions and outcomes and
the overall purpose of this review – assessing the
extent to which criteria for a screening programme
were fulfilled – we chose not to pool the data from
different studies.
Application of the appraisal
criteria to our reviews
We appraised our reviews of intervention studies
(Questions 4 and 8) using the Quality of Reporting
of Meta-analyses of Randomised Controlled Trials
(QUORUM) criteria. 21 We appraised our review
of prevalence studies using the Meta-analysis of
Observational Studies in Epidemiology (MOOSE)
criteria. 22
Synthesis of the
qualitative data
There is no standard method for combining
qualitative studies. We therefore used a type
of qualitative meta-analysis. 23 We drew on
Schutz’s framework of constructs 24 and on the
metaethnographic method articulated by Britten
and colleagues, 25,26 although we prefer the term
‘meta-analysis’ as the studies analysed were not
ethnographies. The analysis started with two
parallel strands: (1) identification and examination
of first- and second-order constructs in the primary
studies, and (2) methodological appraisal. These
strands were brought together in the formulation
of third-order constructs expressing the conclusions
of the meta-analysis.
First-order constructs were based on results in the
primary studies relevant to the review question.
Second-order constructs were the interpretations
or conclusions of the primary investigators that
related to the review question. These constructs
were identified and grouped from data on the
extraction forms, referring back to the original
papers when necessary. For identification of
second-order constructs, where the investigators
only presented recommendations, we interpreted
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these as the authors’ conclusions. We intended
to examine three different types of relationship
between the constructs extracted from the studies:
1. constructs that were similar across a number
of studies (reciprocal constructs) and, through
a process of repeated reading and discussion,
would yield third-order constructs that would
express our synthesis of findings that were
directly supported across different studies
2. constructs that seemed in contradiction
between studies; we planned to explain these
contradictions by examining factors in the
studies and, where there was a plausible
explanation, to articulate these as third-order
constructs
3. unfounded second-order constructs; i.e.
conclusions by primary study authors that
did not seem to be supported by first-order
constructs.
This method allows generalisations to be made that
are not possible from individual qualitative studies.
Further details of the analysis by review question
are given below.
Question I: What is the prevalence of partner violence
against women and its health consequences?
We summarised the prevalence data reported
in primary studies and the evidence for health
consequences in systematic reviews. We plotted
incidence and prevalence with 95% confidence
intervals and tested the effect on variation of type
of population (clinical versus community) and
types of violence with logistic regression models.
For health consequences, when we cited primary
studies this was for illustrative purposes only.
Question II: Are screening tools valid and reliable?
In our narrative analysis of the results of these
studies we evaluated the effectiveness and accuracy
of the screening tools in terms of: test sensitivity
and specificity, test positive and negative predictive
values, positive and negative likelihood ratios, and
the diagnostic odds ratio. Where feasible, we had
also planned to pool results from primary studies
of the same screening tool that were graded good
or fair and that had comparable effect measures
(e.g. sensitivity/specificity, predictive values, risk
estimates). 27 However, no meta-analyses of the
screening tool evaluations were possible because
of the heterogeneity of the index tools used in the
primary studies. Some of the primary studies did
not fully report diagnostic accuracy, but did report
the numbers of true positives, false positives, true
negatives and false negatives for both the index
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