This study aims to investigate the treatment preferences of patients with Neuroendocrine Tumors (NETS) and nurses who are involved in the care of individuals with NETs. NETs are a type of abnormal growth that can develop in various parts of the body, such as the lungs, pancreas, gastrointestinal tract, or other organs. NETs originate from specialized cells called neuroendocrine cells, which are responsible for producing hormones in our bodies. The study focuses on hypothetical preferences regarding the use of two different type of devices for administering Somatostatin analogues (SSAs), which could be used in the treatment of NETs. SSAs work by imitating the actions of a hormone called somatostatin that naturally exists in our bodies. These treatment help to control the symptoms of NETs by blocking the release of hormones from the tumor cells. The devices under consideration are a motorized injector versus a manual injector. Participants in the study will be asked to take part in: 1. An interview based on a draft survey: 60-minute interview over videocall, to examine participants understanding of the online survey; or 2. Final online survey: 30-minute online survey. This involves presenting patients and nurses with different treatment options and asking them to choose their preferred option. By analysing the choices made by participants, researchers can understand which attributes of the injector devices are most important to patients and nurses. Individual participation is limited to the interview based on a draft survey (60 minutes) or the final online survey (30 minutes). No further participation is required beyond this.
Study Type
OBSERVATIONAL
Enrollment
191
CAPPRE
Sydney, Australia
Attribute importance
Using the data from the survey scenarios (the DCE component of the survey) the DCE model estimates the parameters (β's) for each feature (attribute) level. These β's describe the magnitude and direction of influence of each of the attribute (levels) in the choice context. The β's can include negative and positive values which indicate the direction of the effect in relation to the attribute levels.
Time frame: At the end of the survey completion (approximatively 3 months)
Relative attribute importance
Attribute importance is described by the magnitude of the β's (i.e., the size of the values). The magnitude of the β's are interpreted and understood relative to each other (relative attribute importance).
Time frame: At the end of the survey completion (approximatively 3 months)
Measures of segmentation
Identify which patients (e.g., age, gender, tumor grade, carcinoid syndrome status, treatment history) and nurses characteristics (e.g., years of experience, caseload, public or private place of work, NETs specialist clinic or not) are predictive of the assessment of the benefits and risks of treatment options (segmentation) Segmentation: The econometric methods to be employed will recognise that preferences may vary across participants, even after controlling for observed characteristics like treatment experiences. This allows for preference heterogeneity (i.e., different participants can have different marginal utility or parameter weights for each of the features).
Time frame: At the end of the survey completion (approximatively 3 months)
Predicted uptake (preference share)
Preference share: Predicted uptake for the different treatments available will be calculated, based on attribute importance..
Time frame: At the end of the survey completion (approximatively 3 months)
This platform is for informational purposes only and does not constitute medical advice. Always consult a qualified healthcare professional.