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Background: Recently, awareness of children’s decision making has increased in an effort to enhance palliative care. However, the conceptual framework for decision making among children with cancer remains unclear. Aims: We clarified the decision-making process of children with cancer regarding their care, treatment, and support from family and health care professionals, and identified their needs and preferences. Design: We used metaethnography to conduct a metasynthesis of relevant studies. Data sources: We searched PubMed, EMBASE, PsycINFO, MEDLINE, and CINAHL. This report was prepared in accordance with the PRISMA statement. Results: Of the 7,237 retrieved studies, 27 met our inclusion criteria. Four themes emerged that reflected the decision-making process of children with cancer: (a) facing changes brought about by a health threat, (b) preparing for action, (c) asserting one’s choice, and (d) internal and external influences. Conclusion: Children with cancer initially undergo a decision-making process. Respecting children’s preferences, values, and emotions may help build trusting relationships and promote their decision-making capability. Future research should focus on children’s emotions, cognition, development, and interactions with parents and health care professionals.

Background The poor coverage of essential maternal services, such as antenatal care (ANC) and skilled delivery care utilization, accounts for higher maternal and infant mortality in low- and middle-income countries (LMICs). Although mobile health (mHealth) interventions could potentially improve the service utilization in resource-limited settings, their effectiveness remains unclear. Objective This review aimed to summarize the effect of mHealth interventions on improving the uptake of ANC visits, skilled birth attendance at the time of delivery, and facility delivery among pregnant women in LMICs. Methods We conducted a comprehensive search on 9 electronic databases and other resources from inception to October 2020. We included individual randomized controlled trials and cluster randomized controlled trials that assessed the effectiveness of mHealth interventions for improving perinatal health care utilization among healthy pregnant women in LMICs. We performed a random-effects meta-analysis and estimated the pooled effect size by using risk ratios (RRs) with 95% CIs. In addition, 2 reviewers independently assessed the risk of bias of the included studies by using the Cochrane risk of bias tool and the certainty of the evidence by using the Grading of Recommendation, Assessment, Development and Evaluation approach. Results A total of 9 studies (10 articles) that randomized 10,348 pregnant women (n=6254, 60.44% in the intervention group; n=4094, 39.56% in the control group) were included in this synthesis. The pooled estimates showed a positive effect of mHealth interventions on improving 4 or more ANC visit utilizations among pregnant women in LMICs, irrespective of the direction of interventions (1-way communications: RR 2.14, 95% CI 1.76-2.60, I2=36%, 2 studies, moderate certainty; 2-way communications: RR 1.17, 95% CI 1.08-1.27, I2=59%, 3 studies, low certainty). Only 2-way mHealth interventions were effective in improving the use of skilled birth attendance during delivery (RR 1.23, 95% CI 1.14-1.33, I2=0%, 2 studies, moderate certainty), but the effects were unclear for 1-way mHealth interventions (RR 1.04, 95% CI 0.97-1.10, I2=73%, 3 studies, very low certainty) when compared with standard care. For facility delivery, the interventions were effective in settings where fewer pregnant women used facility delivery (RR 1.68, 95% CI 1.30-2.19, I2=36%, 2 studies, moderate certainty); however, the effects were unclear in settings where most pregnant women already used facility delivery (RR 1.01, 95% CI 0.97-1.04, I2=0%, 1 study, low certainty). Conclusions mHealth interventions may contribute to improving ANC and skilled delivery care utilization among pregnant women in LMICs. However, more studies are required to improve their reproducibility and efficiency or strengthen the evidence of different forms of mHealth interventions because of the considerable heterogeneity observed in the meta-analyses. Trial Registration PROSPERO CRD42020210813; https://tinyurl.com/2n7ny9a7

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