{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,15]],"date-time":"2026-09-15T11:15:05Z","timestamp":1789470905648,"version":"build-2803163510"},"reference-count":40,"publisher":"BMJ","license":[{"start":{"date-parts":[[2026,4,15]],"date-time":"2026-04-15T00:00:00Z","timestamp":1776211200000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["bmj.com"],"crossmark-restriction":true},"short-container-title":["BMJ"],"accepted":{"date-parts":[[2026,3,16]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Objectives<\/jats:title>\n                    <jats:p>To identify the effective components of interventions to increase vaccine uptake and to explore variations in effectiveness by population group and in relation to the covid-19 pandemic.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Design<\/jats:title>\n                    <jats:p>Component network meta-analysis.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Setting<\/jats:title>\n                    <jats:p>Systematic review of randomised controlled trials in high and upper middle income countries.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Participants<\/jats:title>\n                    <jats:p>237 studies with 570 intervention arms and 4\u2009361\u2009717 participants.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Interventions<\/jats:title>\n                    <jats:p>Any intervention targeting vaccine recipients or their caregivers aiming to increase demand for, or access to, vaccinations on the UK immunisation schedule. Key content and delivery features of interventions were identified using a bespoke coding framework co-developed with stakeholders.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Main outcome measures<\/jats:title>\n                    <jats:p>The outcome of interest was vaccine uptake. Bayesian component level meta-regression estimated relative effects of intervention components as ratios of odds ratios with 95% credible intervals (CrIs).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Of the included studies, 110 were at low risk of bias, 96 had some concerns, and 31 were at high risk. 40% (n=1\u2009744\u2009686) of the participants were male. For children, there was evidence of beneficial effects for payments to cover costs (ratio of odds ratios 3.01, 95% CrI 1.49 to 6.06) and decision aids (2.73, 1.14 to 7.06), and some evidence for extended opportunities (1.37, 0.98 to 1.95) and social factors (1.27, 0.99 to 1.65). For adolescents and young adults, there were beneficial effects for personal delivery formats (2.13, 1.09 to 4.40), delivery by community members alongside healthcare professionals (6.42, 1.94 to 25.62), and social factors (2.62, 1.45 to 5.04), and negative effects for decision aids (0.43, 0.18 to 0.98) and human versus non-human interaction (0.47, 0.21 to 1.02). For adults, beneficial effects were shown for human interaction (1.86, 1.42 to 2.45), extended opportunities (1.63, 1.35 to 2.00), help with appointment scheduling (1.38, 1.06 to 1.78), payments to cover costs (1.47, 1.03 to 2.16), and motivational interviewing (1.79, 1.21 to 2.64), and there was some evidence for financial incentives (1.15, 0.99 to 1.35) and information on vaccine safety and\/or efficacy (1.15, 0.99 to 1.32). For adults, evidence also showed a negative effect of non-human interaction versus no interaction (0.72, 0.57 to 0.92). Subgroup analyses showed variation for underserved populations and in relation to the covid-19 pandemic (before 2020 and 2020 onwards).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Overall, extended opportunities, appointment scheduling help, financial incentives, payments to cover costs, and motivational interviewing were effective content components of interventions to increase vaccine uptake. Effective delivery components overall were human interaction and delivery by community members alongside healthcare professionals. However, effective components varied by age group, for underserved populations, and in analyses investigating the impact of the covid-19 pandemic. These findings have important implications for designing, optimising, and implementing targeted interventions, highlighting which components are effective across different populations and contexts. Consideration of the economic data on interventions should further support resource informed decision making.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1136\/bmj-2025-087578","type":"journal-article","created":{"date-parts":[[2026,4,16]],"date-time":"2026-04-16T00:00:11Z","timestamp":1776297611000},"page":"e087578","update-policy":"https:\/\/doi.org\/10.1136\/crossmarkpolicy","source":"Crossref","is-referenced-by-count":2,"title":["Effectiveness of interventions to increase vaccine uptake: component network meta-analysis"],"prefix":"10.1136","volume":"393","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1321-7826","authenticated-orcid":false,"given":"Sarah R","family":"Davies","sequence":"first","affiliation":[{"name":"Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK"},{"name":"NIHR Health Protection Research Unit in Evaluation and Behavioural Science at University of Bristol, Bristol, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Annabel L","family":"Davies","sequence":"additional","affiliation":[{"name":"Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Julian P T","family":"Higgins","sequence":"additional","affiliation":[{"name":"Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK"},{"name":"NIHR Health Protection Research Unit in Evaluation and Behavioural Science at University of Bristol, Bristol, UK"},{"name":"NIHR Applied Research Collaboration West (ARC West) at University Hospitals Bristol and Weston NHS Foundation Trust, Bristol, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Deborah M","family":"Caldwell","sequence":"additional","affiliation":[{"name":"Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, 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