Hard-to-treat childhood cancers are those where standard treatment options do not exist and the prognosis is poor. Healthcare professionals (HCPs) are responsible for communicating with families about prognosis and complex experimental treatments. We aimed to identify HCPs’ key challenges and skills required when communicating with families about hard-to-treat cancers and their perceptions of communication-related training.

We interviewed Australian HCPs who had direct responsibilities in managing children/adolescents with hard-to-treat cancer within the past 24 months. Interviews were analyzed using qualitative content analysis.

We interviewed 10 oncologists, 7 nurses, and 3 social workers. HCPs identified several challenges for communication with families including: balancing information provision while maintaining realistic hope; managing their own uncertainty; and nurses and social workers being underutilized during conversations with families, despite widespread preferences for multidisciplinary teamwork. HCPs perceived that making themselves available to families, empowering them to ask questions, and repeating information helped to establish and maintain trusting relationships with families. Half the HCPs reported receiving no formal training for communicating prognosis and treatment options with families of children with hard-to-treat cancers. Nurses, social workers, and less experienced oncologists supported the development of communication training resources, more so than more experienced oncologists.

Resources are needed which support HCPs to communicate with families of children with hard-to-treat cancers. Such resources may be particularly beneficial for junior oncologists and other HCPs during their training, and they should aim to prepare them for common challenges and foster greater multidisciplinary collaboration.

To identify cognitive phenotypes in late-life depression (LLD) and describe relationships with sociodemographic and clinical characteristics.

Observational cohort study

Baseline data from participants recruited via clinical referrals and community advertisements who enrolled in two separate studies.

Non-demented adults with LLD (n = 120; mean age = 66.73 ± 5.35 years) and non-depressed elders (n = 56; mean age = 67.95 ± 6.34 years).

All completed a neuropsychological battery, and individual cognitive test scores were standardized across the entire sample without correcting for demographics. Five empirically derived cognitive domain composites were created, and cluster analytic approaches (hierarchical, k-means) were independently conducted to classify cognitive patterns in the depressed cohort only. Baseline sociodemographic and clinical characteristics were then compared across groups.

A three-cluster solution best reflected the data, including “High Normal” (n = 47), “Reduced Normal” (n = 35), and “Low Executive Function” (n = 37) groups. The “High Normal” group was younger, more educated, predominantly Caucasian, and had fewer vascular risk factors and higher Mini-Mental Status Examination compared to “Low Executive Function” group. No differences were observed on other sociodemographic or clinical characteristics. Exploration of the “High Normal” group found two subgroups that only differed in attention/working memory performance and length of the current depressive episode.

Three cognitive phenotypes in LLD were identified that slightly differed in sociodemographic and disease-specific variables, but not in the quality of specific symptoms reported. Future work on these cognitive phenotypes will examine relationships to treatment response, vulnerability to cognitive decline, and neuroimaging markers to help disentangle the heterogeneity seen in this patient population

To systematically review and synthesise qualitative evidence about determinants of self-management in adults with SMI. The goal is to use findings from this review to inform the design of effective self-management strategies for people with SMI and LTCs.

People living with serious mental illness (SMI) have a reduced life expectancy by around 15–20 years, mainly due to the high prevalence of long-term physical conditions such as diabetes and heart disease. People with SMI face many challenges when trying to manage their physical health. Little is known about the determinants of self-management – managing the emotional and practical issues – of long-term conditions (LTCs) for people with SMI.

Six databases, including CINAHL and MEDLINE, were searched to identify qualitative studies that explored people's perceptions about determinants of self-management in adults with SMI (with or without comorbid LTCs). Self-management was defined according to the American Association of Diabetes Educator's self-care behaviours (AADE7). Determinants were defined according to the Capabilities, Opportunity, Motivations and Behaviours (COM-B) framework. Eligible studies were purposively sampled for synthesis according to the richness of the data (assessed using Ames et al (2017)'s data richness scale), and thematically synthesised.

Twenty-six articles were included in the synthesis. Seven studies focused on self-management of LTCs, with the remaining articles exploring self-management of SMI. Six analytic themes and 28 sub-themes were identified from the synthesis. The themes included: the additional burden of SMI; living with comorbidities; beliefs and attitudes about self-management; support from others for self-management; social and environmental factors; routine, structure and planning. Capabilities for self-management were linked to people's perceptions about the support they received for their SMI and LTC from healthcare professionals, family and friends. Opportunities for self-management were more commonly expressed in the context of social and environmental factors. Motivation for self-management was influenced by beliefs and attitudes, whilst being closely related to the burden of SMI.

The themes identified from the synthesis suggest that capabilities, opportunities and motivations for self-management can be negatively influenced by the experience of SMI, whilst social and professional support, improved access to resources, and increased involvement in care, could promote self-management. Support programmes for people with SMI and LTCs need to account for these experiences and adapt to meet the unique needs of this population.

The need to use evidence in humanitarian settings is recognized, yet utilizing that evidence to make decisions about humanitarian response remains a challenge.

To identify how, when, and why decision makers in humanitarian response use scientific, peer-reviewed evidence to make decisions.

An online cross-sectional survey of fifteen open- and closed-ended questions on demographics, experience, and role in humanitarian response was developed by Evidence Aid (EA) and Karolinska Institutet (KI). The online survey was available on the EA website from August 2015 to October 2018. Participants were self-selected, recruited through social media channels and mailing lists of EA and KI. All respondents and responses were anonymized. Responses were analyzed with descriptive statistics and content analysis.

47 people responded, primarily working in Europe or North America with roles of humanitarian response director/manager, independent consultant, or policymaker. Personal assessment of the quality of information, trust in the source, and information that was contextually relevant or based on field experience were factors for deciding whether information should be considered evidence. Reasons for using evidence when making decisions included adhering to good practice to maximize impact and effectiveness of aid, reassurance that the right decisions were being made, personal or organizational values, and using evidence as a tool to protect beneficiaries and organizations from poor quality decisions and program content.

Using evidence for decision making was common practice during the process of designing implementing and evaluating humanitarian response content, yet reasons for use varied. The importance of evidence developed and validated from field experience and trust in the source reported by this sample suggests that strengthening collaborative efforts between decisionmakers and evidence generators could be one approach to improve evidence and evidence use in humanitarian response.