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FA-BA107 Prisma guidelines schema. Uitgebreid schema die ieder soort bias zoals bedoeld in de prisma guidelines behandeld en hierbij ook voorbeelden geeft.

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  • 18 juli 2024
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Supplementary Material to:


PRISMA 2020 explanation and elaboration: updated guidance and exemplars for reporting
systematic reviews
Matthew J Page*, David Moher, Patrick M Bossuyt, Isabelle Boutron, Tammy C Hoffmann, Cynthia D
Mulrow, Larissa Shamseer, Jennifer M Tetzlaff, Elie A Akl, Sue E Brennan, Roger Chou, Julie Glanville,
Jeremy M Grimshaw, Asbjørn Hróbjartsson, Manoj M Lalu, Tianjing Li, Elizabeth W Loder, Evan
Mayo-Wilson, Steve McDonald, Luke A McGuinness, Lesley A Stewart, James Thomas, Andrea C
Tricco, Vivian A Welch, Penny Whiting, Joanne E McKenzie


*Correspondence to: Dr. Matthew Page, School of Public Health and Preventive Medicine, Monash
University, 553 St Kilda Road, Melbourne, Victoria, 3004, Australia. Email address:
matthew.page@monash.edu




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,Supplementary Table 1. PRISMA 2020 examples

Note: We edited the examples by removing all citations within them (to avoid potential confusion with the citation for each example) and spelled out
abbreviations to aid comprehension.

Checklist item Examples
Item 1. TITLE: Identify Example 1: In a review examining the effects of rivaroxaban versus warfarin for people with antiphospholipid syndrome, the
the report as a authors identify the report as a systematic review:
systematic review.
“Comparison of the Therapeutic Effects of Rivaroxaban Versus Warfarin in Antiphospholipid Syndrome: A Systematic Review” (1)
Example 2: In a review examining the effects of repetitive transcranial magnetic stimulation on patients post-stroke, the
authors identify the report as a systematic review and note that meta-analysis was conducted:
“Repetitive transcranial magnetic stimulation for the treatment of lower limb dysfunction in patients poststroke: a systematic
review with meta-analysis” (2)
Example 3: In a review examining the effects of cannabis-based medicines for cancer pain, the authors identify the report as a
systematic review with meta-analysis, and indicate that the review includes evidence from randomized trials only:
“Efficacy, tolerability and safety of cannabis-based medicines for cancer pain: A systematic review with meta-analysis of
randomised controlled trials” (3)
Example 4: In a review examining the effects of routine anti-osteoporosis medication in men, the authors identify the report as
an updated systematic review with meta-analysis:
“Does routine anti-osteoporosis medication lower the risk of fractures in male subjects? An updated systematic review with
meta-analysis of clinical trials” (4)
Item 2. ABSTRACT: Example 1: In a review examining the effects of psychological interventions for common mental disorders in women
See the PRISMA 2020 experiencing intimate partner violence in low-income and middle-income countries, the authors summarise the objectives,
for Abstracts eligibility criteria, databases consulted, methods for collecting data, assessing risk of bias and synthesising results, along with
checklist. presenting results and commenting on the limitations of the evidence, and specify the registration number and funding source
for the review.
“Background: Evidence on the effectiveness of psychological interventions for women with common mental disorders (CMDs)
who also experience intimate partner violence is scarce. We aimed to test our hypothesis that exposure to intimate partner
violence would reduce intervention effectiveness for CMDs in low-income and middle-income countries (LMICs). Methods: For

2

,Checklist item Examples
this systematic review and meta-analysis, we searched MEDLINE, Embase, PsycINFO, Web of Knowledge, Scopus, CINAHL, LILACS,
ScieELO, Cochrane, PubMed databases, trials registries, 3ie, Google Scholar, and forward and backward citations for studies
published between database inception and Aug 16, 2019. All randomised controlled trials (RCTs) of psychological interventions
for CMDs in LMICs which measured intimate partner violence were included, without language or date restrictions. We
approached study authors to obtain unpublished aggregate subgroup data for women who did and did not report intimate
partner violence. We did separate random-effects meta-analyses for anxiety, depression, post-traumatic stress disorder (PTSD),
and psychological distress outcomes. Evidence from randomised controlled trials was synthesised as differences between
standardised mean differences (SMDs) for change in symptoms, comparing women who did and who did not report intimate
partner violence via random-effects meta-analyses. The quality of the evidence was assessed with the Cochrane risk of bias tool.
This study is registered on PROSPERO, number CRD42017078611. Findings: Of 8122 records identified, 21 were eligible and data
were available for 15 RCTs, all of which had a low to moderate risk of overall bias. Anxiety (five interventions, 728 participants)
showed a greater response to intervention among women reporting intimate partner violence than among those who did not
(difference in standardised mean differences [dSMD] 0.31, 95% CI 0.04 to 0.57, I2=49.4%). No differences in response to
intervention were seen in women reporting intimate partner violence for PTSD (eight interventions, n=1436; dSMD 0.14, 95% CI -
0.06 to 0.33, I2=42.6%), depression (12 interventions, n=2940; 0.10, -0.04 to 0.25, I2=49.3%), and psychological distress (four
interventions, n=1591; 0.07, -0.05 to 0.18, I2=0.0%, p=0.681). Interpretation: Psychological interventions treat anxiety effectively
in women with current or recent intimate partner violence exposure in LMICs when delivered by appropriately trained and
supervised health-care staff, even when not tailored for this population or targeting intimate partner violence directly. Future
research should investigate whether adapting evidence-based psychological interventions for CMDs to address intimate partner
violence enhances their acceptability, feasibility, and effectiveness in LMICs. Funding: UK National Institute for Health Research
ASSET and King's IoPPN Clinician Investigator Scholarship.” (5)
Example 2: In a review examining the effects of cognitive bias modification interventions for people with anxiety and
depressive disorders, the authors summarise the objectives, eligibility criteria, databases consulted, methods for collecting
data, assessing risk of bias and synthesising results, along with presenting results and commenting on the limitations of the
evidence, and specify the registration number and funding source for the review.
“Background: Cognitive bias modification (CBM) therapies, including attention bias modification, interpretation bias modification,
or approach and avoidance training, are prototypical examples of mechanistically derived treatments, but their effectiveness is
contentious. We aimed to assess the relative effectiveness of various CBM interventions for anxious and depressive
symptomatology. Methods: For this systematic review and network meta-analysis, we searched PubMed, PsycINFO, Embase, and
Cochrane Central Register from database inception up until Feb 7, 2020. We included randomised controlled trials of CBM versus
control conditions or other forms of CBM for adults aged 18 years and older with clinical or subclinical anxiety or depression

3

, Checklist item Examples
measured with a diagnostic interview or a validated clinical scale. We excluded studies comparing CBM with a non-CBM active
intervention. Two researchers independently selected studies and evaluated risk of bias with the Cochrane Collaboration tool.
Primary outcomes encompassed anxiety and depressive symptoms measured with validated clinical scales. We computed
standardised mean differences (SMDs) with a restricted maximum likelihood random effects model. This study is registered with
PROSPERO, CRD42018086113. Findings: From 2125 records we selected 85 trials, 65 (n=3897) on anxiety and 20 (n=1116) on
depression. In a well-connected network of anxiety trials, interpretation bias modification outperformed waitlist (SMD -0.55, 95%
CI -0.91 to -0.19) and sham training (SMD -0.30, -0.50 to -0.10) for the primary outcome. Attention bias modification showed
benefits only in post-hoc sensitivity analyses excluding post-traumatic stress disorder trials. Prediction intervals for all findings
were large, including an SMD of 0. Networks of depression trials displayed evidence of inconsistency. Only four randomised
controlled trials had low risk of bias on all six domains assessed. Interpretation: CBM interventions showed consistent but small
benefits; however heterogeneity and risk of bias undermine the reliability of these findings. Larger, definitive trials for
interpretation bias modification for anxiety might be warranted, but insufficient evidence precludes conclusions for depression.
Funding: Romanian Ministry of Research and Innovation, The National Council for Scientific Research-The Executive Agency for
Higher Education, Research, Development and Innovation Funding.” (6)
Example 3: In a review examining the effects of interventions designed to reduce antibiotic use and/or inappropriate use in
long-term care facilities, the authors summarise the objectives, eligibility criteria, databases searched, and methods to assess
risk of bias and synthesise results, along with results of meta-analyses, indicating the number of studies and participants
included in each:
“Objectives: There are high levels of inappropriate antibiotic use in long-term care facilities (LTCFs). Our objective was to examine
evidence of the effectiveness of interventions designed to reduce antibiotic use and/or inappropriate use in LTCFs. Design:
Systematic review and meta-analysis. Data sources: MEDLINE, Embase and CINAHL from 1997 until November 2018. Eligibility
criteria: Controlled and uncontrolled studies in LTCFs measuring intervention effects on rates of overall antibiotic use and/or
appropriateness of use were included. Secondary outcomes were intervention implementation barriers from process evaluations.
Data extraction and synthesis: Two reviewers independently applied the Cochrane Effective Practice and Organisation of Care
group’s resources to classify interventions and assess risk of bias. Meta-analyses used random effects models to pool results.
Results: Of include studies (n=19), 10 had a control group and 17 had a high risk of bias. All interventions had multiple
components. Eight studies (with high risk of bias) showed positive impacts on outcomes and included one of the following
interventions: audit and feedback, introduction of care pathways or an infectious disease team. Meta-analyses on change in the
percentage of residents on antibiotics (pooled relative risk (RR) (three studies, 6862 residents): 0.85, 95% CI: 0.61 to 1.18),
appropriateness of decision to treat with antibiotics (pooled RR (three studies, 993 antibiotic orders): 1.10, 95% CI: 0.64 to 1.91)
and appropriateness of antibiotic selection for respiratory tract infections (pooled RR (three studies, 292 orders): 1.15, 95% CI:

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