Are community-based health worker interventions an effective approach for early diagnosis of cancer? A systematic review and meta-analysis.

PSYCHO-ONCOLOGY(2018)

引用 21|浏览15
暂无评分
摘要
Objective: This systematic review aimed to assess the effectiveness of community-based health worker (CBHW) interventions for early detection of cancer. Secondary aims were to consider the extent that interventions were based on theory, and potential moderators including behaviour change techniques (BCTs). Methods: Six databases were searched for randomized controlled trials. Random-effects meta-analyses were applied to 30 eligible studies with a cancer screening outcome. Results: Participation in CBHW interventions was associated with increased receipt of screening (OR = 1.901, 95% CI: 1.60-2.26, P < 0.001) for breast, cervical, and bowel cancer. Larger effect sizes were observed in participants previously non-adherent with recommended schedules of cancer screening. Twenty-five out of 30 studies were conducted with ethnic minority groups. Only 15 (45%) studies explicitly reported a theoretical foundation for intervention. The number of BCTs used by CBHWs had a trend level association with observed effect size (P=0.08). Study quality was generally poor, and common limitations were inadequate blinding and reliance on self-reported outcomes. Conclusions: Community-based health worker interventions are an effective resource for increasing uptake of all 3 types of cancer screening in ethnic minority groups. Those previously non-adherent with recommended schedules of cancer screening benefitted the most from the CBHW approach. However, better quality studies based on more explicit evidence-based theory are needed to optimise the effectiveness of CBHW interventions on screening uptake. Further research is needed to ascertain whether CBHWs can help promote symptom recognition and help-seeking behaviour to facilitate early diagnosis of cancer.
更多
查看译文
关键词
behaviour change techniques,cancer,community health worker,early diagnosis,meta-analysis,oncology and systematic review
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要