This review aimed to synthesize evidence on the effectiveness of shared decision-making (SDM) tools for cancer screening and explored the preferences of vulnerable people and clinicians regarding the specific characteristics of the SDM tools. A mixed-method convergent segregated approach was employed, which involved an independent synthesis of quantitative and qualitative data. Articles were systematically selected and screened, resulting in the inclusion and critical appraisal of 55 studies. Results from the meta-analysis revealed that SDM tools were more effective for improving knowledge, reducing decisional conflict, and increasing screening intentions among vulnerable populations compared to non-vulnerable populations. Subgroup analyses showed minimal heterogeneity for decisional conflict outcomes measured over a six-month period. Insights from the qualitative findings revealed the complexities of clinicians’ and vulnerable populations’ preferences for an SDM tool in cancer screening. Vulnerable populations highly preferred SDM tools with relevant information, culturally tailored content, and appropriate communication strategies. Clinicians, on the other hand, highly preferred tools that can be easily integrated into their medical systems for efficient use and can effectively guide their practice for cancer screening while considering patients’ values. Considering the complexities of patients’ and clinicians’ preferences in SDM tool characteristics, fostering collaboration between patients and clinicians during the creation of an SDM tool for cancer screening is essential. This collaboration may ensure effective communication about the specific tool characteristics that best support the needs and preferences of both parties.

Individualized risk prediction models for colorectal cancer (CRC) play a pivotal role in shaping risk-based screening approaches, garnering attention for use in informed decision making by patients and clinicians. While the incorporation of new predictors and the development of advanced yet complex prediction models can enhance model performance, their practical implementation in clinical settings remains challenging. This systematic review assessed individualized CRC risk prediction models for their validity and potential clinical utility. Utilizing the Cochrane Collaboration methods and PROBAST tool, we conducted comprehensive searches across key databases and risk of bias assessment, respectively. Out of 41 studies included evaluating 44 risk prediction models, 12 conventional and 3 composite models underwent external validation. All risk models exhibited varying discriminatory accuracy, with the area under the curve (AUCs) ranging from 0.57 to 0.90. However, most studies showed an unclear or high risk of bias, with concerns about applicability. Of the five models with promising clinical utility, only two underwent external validation and one employed a decision curve analysis. These models demonstrated a discriminating and well-calibrated performance. While high-performing CRC risk prediction models exist, a need for transparent reporting of performance metrics and their clinical utility persists. Further research on this area is needed to facilitate the integration of these models into clinical practice, particularly in CRC screening.

This study aimed to investigate the association between inclusion to Pantawid Pamilyang Pilipino Program (4Ps), a CCT program in the Philippines, and malnutrition in children and adolescents and examine the perceptions and experiences of parents and other stakeholders on how 4Ps influenced child nutrition. A concurrent mixed-method study was conducted in the Caraga Region, Philippines. Quantitative data from 5541 children and adolescents aged 3 to 19 were analyzed using multilevel mixed-effect logistic models. To allow in-depth understanding of the programmatic components that support the findings from the quantitative study, eight focused group discussions (FGDs) were concurrently conducted, cumulating 33 participants, including 4Ps parents, school coordinators/teachers, and school nurses. A constructivist grounded theory approach was used for analysis, and joint displays were employed to integrate quantitative and qualitative results. Quantitative findings revealed high rates of malnutrition, with significant rates of stunting (12.0%), wasting/thinness (9.4%), and overweight/obesity (16.4%) among children and adolescents. 4Ps beneficiaries had higher odds of stunting and overweight/obesity compared to non-4Ps beneficiaries (AOR = 1.43, 95%CI: 1.08–1.91; AOR = 1.21, 95%CI: 1.01–1.45, respectively). However, no significant association was observed between inclusion to 4Ps and concurrent stunting and wasting/thinness or overweight/obesity (AOR = 1.05, 95%CI: 0.72–1.55). Geographic variations were observed, with 4Ps children in Agusan del Sur having lower odds of stunting than those in Agusan del Norte (AOR = 0.41, 95%CI: 0.23–0.71). Age and gender also showed significant associations with malnutrition. The qualitative analysis provided insights into the challenges contributing to malnutrition, including child labor, sickness, long distances to school, limited access to healthy food, and larger families. Unintended consequences such as cash card mismanagement, inappropriate cash grant allocation, and falsification of school attendance were identified. However, teachers and parents demonstrated resilience by implementing adaptive approaches to enhance child nutrition. While 4Ps beneficiaries exhibit higher odds of stunting and overweight/obesity, the program’s association with malnutrition was significantly influenced by geographic variations. It is crucial for social protection programs to prioritize comprehensive support strategies that effectively counter unintended consequences and challenges faced by beneficiaries and other stakeholders and address malnutrition in children and adolescents.

Background: Colorectal cancer (CRC) remains a leading cause of cancer-related mortality worldwide. While screening tools such as the fecal immunochemical test (FIT) aid in early detection, they do not provide insights into individual risk factors or strategies for primary prevention. This study aimed to develop and internally validate an interpretable machine learning-based model that estimates an individual’s probability of developing CRC using readily available clinical and lifestyle factors. Methods: We analyzed data from 154,887 adults, aged 55–74 years, who participated in the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial. A risk prediction model was built using the Light Gradient Boosting Machine (LightGBM) algorithm. To translate these findings into clinical practice, we implemented the model into a risk estimator that categorizes individuals as average, increased, or high risk, highlighting modifiable risk factors to support patient–clinician discussions on lifestyle changes. Results: The LightGBM model incorporated 12 predictive variables, with age, weight, and smoking history identified as the strongest CRC risk factors, while heart medication use appeared to have a potentially protective effect. The model achieved an area under the receiver operating characteristic curve (AUROC) of 0.726 (95% confidence interval [CI]: 0.698–0.753), correctly distinguishing high-risk from average-risk individuals 73 out of 100 times. Conclusions: Our findings suggest that this model could support clinicians and individuals considering screening by guiding informed decision making and facilitating patient–clinician discussions on CRC prevention through personalized lifestyle modifications. However, before clinical implementation, external validation is needed to ensure its reliability across diverse populations and confirm its effectiveness in real-world healthcare settings.

Background COVID-19 vaccination rates remain low for children aged 11 and below, and understanding the extent to which parental decisions impact their children’s vaccination status remains a challenge. This study aimed to explore the concordance and motivations for vaccination among parent–child dyads and determine the associated factors influencing their children’s vaccination status. Design A cross-sectional study was conducted from 1 March 2023 to 30 March 2023, recruiting parents from six representative primary schools across Butuan City, the Philippines. Pilot-tested, self-administered questionnaires were used during the face-to-face surveys with parent participants. To determine the associated factors of parental decisions to vaccinate their children, mixed-effects logistic regression was used, with school districts as a random effect. Participants A total of 593 participating parents were included in the study, with the majority being females (n=484, 81.6%) and underserved, characterised by lacking a college degree (n=305, 51.4%) and having low to no income (n=511, 86.1%). Results While 80.6% (n=478) of parents reported being vaccinated against COVID-19, only 36.2% (n=215) of them chose to vaccinate their children. A significant number of parents (n=285, 48.1%) reported psychological distress, with higher levels of distress prevalent among those who are indigenous, reside in rural areas and have lower income levels. Parental education and vaccination status emerged as influential factors. Specifically, parents with advanced degrees were 48% less likely to have unvaccinated children (adj OR (AOR)=0.52; 95% CI 0.30, 0.87), while unvaccinated parents had a sixfold increase in the likelihood of having unvaccinated children (AOR 6.1; 95% CI 3.14, 12.02) compared with their counterparts. Conclusions Efforts to increase paediatric vaccination rates should focus more on actively engaging parents, educating them about the vaccine’s benefits and necessity, rather than solely relying on mandates to improve paediatric vaccination rates. Further research is needed to understand the reluctance of unvaccinated parents to vaccinate themselves and their children against COVID-19, identifying specific facilitators and barriers to develop more effective communication strategies and bolster vaccine acceptance.