The interplay between ovarian cancer and social relationships: an analysis of patients' metaphors.

Objective: Research showed that ovarian cancer poses unique challenges to patients' care experiences and that patients' social networks could affect their care path significantly. The present study aimed to analyse the metaphors that patients used to signify the impact of the illness on their social relationships and the role of relationships in dealing with cancer.

Design: Following a qualitative description approach we conducted 38 semi-structured interviews with Australian (14) and Italian (24) women diagnosed at different stages of ovarian cancer.

Data Centre Profile: The Provincial Health Data Centre of the Western Cape Province, South Africa.

Introduction: The Western Cape Provincial Health Data Centre (PHDC) consolidates person-level clinical data across government services, leveraging sustained investments in patient registration systems, a unique identifier, and maturation of administrative and clinical digital health systems.

Objectives: The PHDC supports clinical care directly through tools for clinicians which integrate patient data or identify patients in need of interventions, and indirectly through supporting operational and epidemiological analyses.

Methods: The PHDC is housed entirely within government.

Development and validation of the healthcare providers patient-activation scale.

Objective: It has become increasingly important to assess healthcare providers' role in chronic disease self-management (CDSM) and patient activation (PA). The present study extends previous work relating to patients' behaviours by assessing healthcare providers' own behaviours in supporting PA.

Method: 50 items were generated: half assessed a PA approach; half reflected a non-patient-activation approach.

Spatially varying auto-regressive models for prediction of new human immunodeficiency virus diagnoses.

In demand of predicting new HIV diagnosis rates based on publicly available HIV data that is abundant in space but has few points in time, we propose a class of spatially varying autoregressive (SVAR) models compounded with conditional autoregressive (CAR) spatial correlation structures. We then propose to use the copula approach and a flexible CAR formulation to model the dependence between adjacent counties. These models allow for spatial and temporal correlation as well as space-time interactions and are naturally suitable for predicting HIV cases and other spatio-temporal disease data that feature a similar data structure.

Experiences and health care preferences of women with ovarian cancer during the diagnosis phase.

Objective: An ovarian cancer diagnosis presents physical and psychological challenges. Usually identified at an advanced stage, the disease involves invasive treatment and has a high mortality rate. The diagnosis phase is generally a time of heightened distress.