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ObjectiveCancer patients in Zimbabwe typically access health services with advanced disease, limiting treatment choices and lessening the likelihood of positive treatment outcomes. We outline experiences of patients with advanced cancer prior to interaction with palliative care services to identify targets for future intervention development to enhance care delivery in Zimbabwe.MethodsParticipants were purposively sampled adult patients with advanced cancer. We adopted a thematic approach to guide a qualitative secondary data analysis exploring factors influencing support sought by participants, external factors influencing decision making across the disease trajectory and the process for seeking and accessing palliative care.ResultsParticipants reported fragmented and uncoordinated care, from initial symptom experience and throughout disease progression. A recurring notion of disjuncture was present through participants' experiences of gaps, breaks and discontinuity across the disease trajectory. Each step had a beginning and end without clear routes for transition with movement between steps as a result of happenstance or informal encounters.ConclusionTargets for intervention development at the patient and family level exist that may reduce the disjuncture currently experienced between need and care provision. A holistic response that incorporates engagement with policy actors is critical to addressing prominent financial constraints for patients.

IntroductionPalliative care is a clinically and cost-effective component of cancer services in sub-Saharan Africa (SSA). Despite the significant need for palliative cancer care in SSA, coverage remains inadequate. The exploration of digital health approaches could support increases in the quality and reach of palliative cancer care services in SSA. However, there is currently a lack of any theoretical underpinning or data to understand stakeholder drivers for digital health components in this context. This project addresses this gap through engaging with key stakeholders to determine data and information needs that could be supported through digital health interventions.Methods and analysisThis is a multicountry, cross-sectional, qualitative study conducted in Nigeria, Uganda and Zimbabwe. In-depth interviews will be conducted in patients with advanced cancer (n=20), caregivers (n=15), health professionals (n=20) and policy-makers (n=10) in each of the three participating countries. Data from a total of 195 interviews will transcribed verbatim and translated into English before being imported into NVivo software for deductive framework analysis. The analysis will seek to understand the acceptability and define mechanisms of patient-level data capture and usage via digital technologies.Ethics and disseminationEthics approvals have been obtained from the Institutional Review Boards of University of Leeds (Ref: MREC 18-032), Research Council of Zimbabwe (Ref: 03507), Medical Research Council of Zimbabwe (Ref: MRCZ/A/2421), Uganda Cancer Institute (Ref: 19-2018), Uganda National Council of Science and Technology (Ref: HS325ES) and College of Medicine University of Lagos (Ref: HREC/15/04/2015). The project seeks to determine optimal mechanisms for the design and development of subsequent digital health interventions to support development, access to, and delivery of palliative cancer care in SSA. Dissemination of these findings will occur through newsletters and press releases, conference presentations, peer-reviewed journals and social media.Trial registration numberISRCTN15727711.

Background: Digital approaches are being explored internationally to support the elicitation, documentation and sharing of advance care planning information. However, the views and experiences of patients and carers are little understood, impeding the development and impact of digital approaches to strengthen palliative and end-of-life care. Aim: To explore perspectives of patients with progressive illness and their carers on digital approaches to advance care planning, anticipated impact from their use and expectations for their future development. Design: A qualitative study employing thematic framework analysis of data collected from focus groups and semi-structured interviews. Setting/participants: Purposive sample of 29 patients and 15 current or bereaved carers in London and West Yorkshire from hospice settings, non-governmental support and advocacy groups, and care home residents. Results: Four generated themes included: 1. ' Why haven't you read what's wrong with me? '; uncertainty around professionals' documenting, sharing and use of information; 2. The art of decision-making relies on the art of conversation; 3. The perceived value in having ' a say in matters ': control and responsibility; 4. Enabling patient and carer control of their records: ' custodianship is key '. Conclusions: Lived experiences of information sharing influenced trust and confidence in digital advance care planning systems. Despite scepticism about the extent that care can be delivered in line with their preferences, patients and carers acknowledge digital systems could facilitate care through contemporaneous and accurately documented wishes and preferences. There remains a need to determine how independent patient and public-facing advance care planning resources might be integrated with existing digital health record systems. [ABSTRACT FROM AUTHOR]

Background: Caring for patients with advanced cancer is complex and challenging, requiring varied expertise, including symptom management, communication skills, care coordination and emotional resilience. Within existing literature, the lived experiences of oncology nurses are poorly articulated in countries with a lower income where formal palliative care (PC) is absent. Aim: To explore the lived experiences of Gazan oncology nurses who provide care to patients with advanced cancer in healthcare systems, without formal palliative care infrastructure. Methods: A phenomenological approach was adopted. Semi-structured interviews were conducted between January and April 2022, in the Turkish Palestinian Friendship Hospital. Thematic analysis used the themes (corporeality, relationality, spatiality and temporality) to facilitate reflection on the meaning of participants' lived experiences. Results: Interviews were undertaken with 16 oncology nurses. The experience of the 'erosion of nurses' work when coping with anxious attachments to patients and families' was the overarching theme in nurses' views, characterised by five sub-themes: (1) inadequacy of PC training and resources, (2) serving humanity, (3) pride in their profession, (4) existential distress and the coping strategies used by nurses, and (5) reported stress and anxiety when caring for seriously ill patients and their families. Conclusions: The study sheds light on the challenges and powerful emotions experienced by oncology nurses who care for patients with advanced cancer, yet lack the necessary PC training and institutional resources. The findings indicate an urgent need for PC training for nurses within the Gazan healthcare system and other lower-income settings. Assessing nurses' emotions and relationships with patients and family caregivers is imperative to enable optimum care for patients with cancer and to foster resilience among their nurses. [ABSTRACT FROM AUTHOR]

While previous reviews found a positive association between pre‐existing cancer diagnosis and COVID‐19‐related death, most early studies did not distinguish long‐term cancer survivors from those recently diagnosed/treated, nor adjust for important confounders including age. We aimed to consolidate higher‐quality evidence on risk of COVID‐19‐related death for people with recent/active cancer (compared to people without) in the pre‐COVID‐19‐vaccination period. We searched the WHO COVID‐19 Global Research Database (20 December 2021), and Medline and Embase (10 May 2023). We included studies adjusting for age and sex, and providing details of cancer status. Risk‐of‐bias assessment was based on the Newcastle‐Ottawa Scale. Pooled adjusted odds or risk ratios (aORs, aRRs) or hazard ratios (aHRs) and 95% confidence intervals (95% CIs) were calculated using generic inverse‐variance random‐effects models. Random‐effects meta‐regressions were used to assess associations between effect estimates and time since cancer diagnosis/treatment. Of 23 773 unique title/abstract records, 39 studies were eligible for inclusion (2 low, 17 moderate, 20 high risk of bias). Risk of COVID‐19‐related death was higher for people with active or recently diagnosed/treated cancer (general population: aOR = 1.48, 95% CI: 1.36‐1.61, I2 = 0; people with COVID‐19: aOR = 1.58, 95% CI: 1.41‐1.77, I2 = 0.58; inpatients with COVID‐19: aOR = 1.66, 95% CI: 1.34‐2.06, I2 = 0.98). Risks were more elevated for lung (general population: aOR = 3.4, 95% CI: 2.4‐4.7) and hematological cancers (general population: aOR = 2.13, 95% CI: 1.68‐2.68, I2 = 0.43), and for metastatic cancers. Meta‐regression suggested risk of COVID‐19‐related death decreased with time since diagnosis/treatment, for example, for any/solid cancers, fitted aOR = 1.55 (95% CI: 1.37‐1.75) at 1 year and aOR = 0.98 (95% CI: 0.80‐1.20) at 5 years post‐cancer diagnosis/treatment. In conclusion, before COVID‐19‐vaccination, risk of COVID‐19‐related death was higher for people with recent cancer, with risk depending on cancer type and time since diagnosis/treatment. [ABSTRACT FROM AUTHOR]

PURPOSE: This discussion paper outlines challenges and proposes solutions for successfully implementing prediction models that incorporate patient-reported outcomes (PROs) in cancer practice. METHODS: We organized a full-day multidisciplinary meeting of people with expertise in cancer care delivery, PRO collection, PRO use in prediction modeling, computing, implementation, and decision science. The discussions presented here focused on identifying challenges to the development, implementation and use of prediction models incorporating PROs, and suggesting possible solutions. RESULTS: Specific challenges and solutions were identified across three broad areas. (1) Understanding decision making and implementation: necessitating multidisciplinary collaboration in the early stages and throughout; early stakeholder engagement to define the decision problem and ensure acceptability of PROs in prediction; understanding patient/clinician interpretation of PRO predictions and uncertainty to optimize prediction impact; striving for model integration into existing electronic health records; and early regulatory alignment. (2) Recognizing the limitations to PRO collection and their impact on prediction: incorporating validated, clinically important PROs to maximize model generalizability and clinical engagement; and minimizing missing PRO data (resulting from both structural digital exclusion and time-varying factors) to avoid exacerbating existing inequalities. (3) Statistical and modeling challenges: incorporating statistical methods to address missing data; ensuring predictive modeling recognizes complex causal relationships; and considering temporal and geographic recalibration so that model predictions reflect the relevant population. CONCLUSION: Developing and implementing PRO-based prediction models in cancer care requires extensive multidisciplinary working from the earliest stages, recognition of implementation challenges because of PRO collection and model presentation, and robust statistical methods to manage missing data, causality, and calibration. Prediction models incorporating PROs should be viewed as complex interventions, with their development and impact assessment carried out to reflect this. Challenges and solutions to implementing patient-reported outcome–based predictive models in cancer. [ABSTRACT FROM AUTHOR]

The global threat which continues to accompany SARS‐CoV‐2 has led to a global response which adopts lockdown and stays home policy as means of curtailing its spread. This study investigates compliance with the Stay Home policy and exposure to COVID‐19 in Nigeria. A survey was conducted from April 4 to May 8, 2020 using a cross‐sectional mixed‐methods approach to elicit responses from 879 participants across six geopolitical zones of Nigeria. Descriptive, χ2, and multiple regression tests were used to analyze survey data using SPSS, whereas NVivo v12 was used for thematic analysis of qualitative data. States with complete lockdown had 72.4% of respondents complying fully with the policy compared with 44.2% of respondents in zones with the partial lockdown. Market places, classified as high‐risk zones, were the most visited (n = 505; 71.0%). Though compliance was influenced by the nature of lockdown enforced (χ2 = 70.385, df = 2; p < 0.05), being a female, a widow, and unemployed were associated with increased compliance. Exposure to COVID‐19 was associated with being married, unemployed, and having no income. Fear, anxiety, and misperception play major roles in compliance. The authors conclude that compliance is not uniform and a more nuanced and targeted approach is required as the government continues to respond to the COVID‐19 global pandemic. Key Points: Exposure to risk of COVID‐19 infection was conditioned by social and economic realities.The nature of lockdown (partial or complete) influenced compliance with stay Home Policy.Visits among family members was higher in areas with complete lockdown compared to area with partial lockdown.Places classified as high‐risk zones (market and religious centres) were the most patronised.Fear, anxiety and misperception play significant roles in compliance with Stay Home Policy. [ABSTRACT FROM AUTHOR]

Digital advance care planning systems are used internationally to document and share patients’ wishes and preferences to inform care delivery. However, their use is impeded by a limited understanding of factors influencing implementation and evaluation.To develop mid-range programme theory to account for technological, infrastructure and human factor influences on digital advance care planning systems.Exploratory qualitative research design incorporating Theory of Change workshops that explored contextual assumptions affecting digital advance care planning in practice. A mid-range programme theory was developed through thematic framework analysis using the Non-adoption, Abandonment, Scale-up, Spread and Sustainability (NASSS) framework, generating a conceptual model depicting contextual assumptions, interventions and outcomes influencing implementation.A total of 38 participants (16 from London, 14 from West Yorkshire and 8 online) including patients, carers and health and care professionals (including those with commissioning responsibilities).A conceptual model was generated depicting five distinct components relating to digital advance care planning system use: (sociocultural, technical and structural prerequisites; recognition of the clinical need for conversation; having conversations and documenting decisions; accessing, actioning and amending; and using data to support evaluation, use and implementation). There were differences and uncertainty relating to what digital advance care planning systems are, who they are for and how they should be evaluated.Digital advance care planning lacks shared beliefs and practices, despite these being essential for complex technology implementation. Our mid-range programme theory can guide their further development and application by considering technological, infrastructure and human factor influences to optimise their implementation. [ABSTRACT FROM AUTHOR]