Abstract 575
Background
People with dementia have poorer cancer outcomes than those without. Little information exists concerning implications of comorbid cancer-dementia for people having cancer treatment in an ambulatory care setting. The purpose of this focused ethnography is to characterise the environment, behaviour and processes that comprise the setting, and to explore what constitutes ‘good care’ in this context.
Trial design
The aim of this focused ethnography is to establish an empirically-based conceptual foundation to inform development of innovations to improve the way treatment and support is offered to people with dementia having cancer treatment. Objectives include: Understanding the physical fabric of the ambulatory care environment, and how this shapes patterns of behaviour and processes; Understanding the actions of those involved in the receipt or provision of care for people with dementia having cancer treatment, through exploration of interactions, perceptions, and language. Understanding the processes involved in care delivery, and how these shape treatment and support offered to patients. Identify characteristics that constitute ‘good care’ and gain an understanding of barriers and facilitators. Identify which aspects of the ambulatory care setting are amenable to modification to meet the needs of this complex population. This project will allow formation of a rich picture of the cultural context in which behaviour, environment and processes are situated, and identify ways in which the organisation of care might be structured to provide a person-centred service for people with dementia. Participants: Participation will be invited from people with dementia having cancer treatment (n ≤ 10), informal carers (n ≤ 10), and staff members (oncologists, nurses, radiographers, support workers, administrative staff, and allied health professionals) (n ≤ 30). Methods: Data will be collected via observations, interviews and document analysis. Data will be analysed using constant comparison, informed by the analytic tradition of grounded theory (Glaser & Strauss 1967), to allow the researchers to establish an empirically-based conceptual and theoretical foundation that is grounded in the original data.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
Naomi Farrington.
Funding
National Institute for Health Research, United Kingdom.
Disclosure
All authors have declared no conflicts of interest.
Resources from the same session
2152 - Inferring the correlation between incidence rates of melanoma and the average tumor-specific epitope binding ability of HLA class I molecules in different populations
Presenter: Istvan Miklos
Session: Poster Display session 3
Resources:
Abstract
4382 - Thermal Liquid Biopsy as a Valuable Tool in Lung Cancer Screening Programs
Presenter: Alberto Rodrigo
Session: Poster Display session 3
Resources:
Abstract
2465 - Towards a screening test for cancer by circulating DNA analysis
Presenter: Rita Tanos
Session: Poster Display session 3
Resources:
Abstract
3788 - Evaluation of a successful launch of the MammaPrint and BluePrint NGS kit
Presenter: Leonie Delahaye
Session: Poster Display session 3
Resources:
Abstract
3863 - Analysis of prognostic factors on overall survival in elderly women treated for early breast cancer using data mining and machine learning
Presenter: Pierre Heudel
Session: Poster Display session 3
Resources:
Abstract
1993 - Circulating tumor cell detection in epithelial ovarian cancer using dual-component antibodies targeting EpCAM and FRα
Presenter: Na Li
Session: Poster Display session 3
Resources:
Abstract
4281 - CEUS of the breast: Is it feasible in improved performance of BI-RADS evaluation of critical breast lesions?——A multi-center prospective study in China
Presenter: Jun Luo
Session: Poster Display session 3
Resources:
Abstract
2268 - Classification of abnormal findings on ring-type dedicated breast PET for detecting breast cancer
Presenter: Shinsuke Sasada
Session: Poster Display session 3
Resources:
Abstract
4035 - Prediction of benign and malignant breast masses using digital mammograms texture features
Presenter: Cui Yanhua
Session: Poster Display session 3
Resources:
Abstract
5678 - Nanomaterials Augmented LDI-TOF-MS for Hepatocellular Carcinoma Diagnosis and Classification
Presenter: Jian Zhou
Session: Poster Display session 3
Resources:
Abstract