Living with Stargardt disease: insights from patients and their parents.

Background: Stargardt disease (STGD), a rare, inherited macular degeneration most commonly affecting children and young adults, is a rapidly progressive disease leading to severe central vision loss. This research aimed to develop a conceptual disease model describing STGD symptoms and their impact on patients' lives.Material and Methods: Qualitative interviews were conducted with patients (juvenile and adult) and parents of children and adolescents with STGD. Interviewed subjects were enrolled through ophthalmologists from specialized eye centers in the USA and in France. Trained interviewers used semi-structured techniques to elicit concepts relevant to patients and their parents. Thematic analysis of interview transcripts led to the identification of concepts which were organized to generate a disease model.Results: A total of 21 patients (12 in the US; 9 in France) - 14 adults, 7 juveniles - and 7 parents were interviewed. The most cited ocular symptoms were photosensitivity and central vision decline. Interviewees reported limitations on Physical (e.g. difficulty with sports/physical activities), Mental (e.g. frustration and worry, reduced ability to concentrate), Social (e.g. issue with facial recognition and difficulty discussing disease) and Role (e.g. impact on driving and reading, difficulties at school/work) functioning. These impacts were, when possible, mitigated by coping strategies and support (e.g. using electronic devices, setting up routines or accepting the disease).Conclusions: This research provides an overview of symptoms experienced by patients with STGD and highlights the dramatic impact these have on patients' lives, allowing the identification of concepts of importance when evaluating new therapeutic options for STGD.

Estimating measures of latent variables from m-alternative forced choice responses.

Signal Detection Theory is the standard method used in psychophysics to estimate person ability in m-alternative forced choice tasks where stimuli are typically generated with known physical properties (e.g., size, frequency, contrast, etc …) and lie at known locations on a physical measurement axis. In contrast, variants of Item Response Theory are preferred in fields such as medical research and educational testing where the axis locations of items on questionnaires or multiple choice tests are not defined by any observable physical property and are instead defined by a latent (or unobservable) variable. We provide an extension of Signal Detection Theory to latent variables that employs the same strategy used in Item Response Theory and demonstrate the practical utility of our method by applying it to a set of clinically relevant face perception tasks with visually impaired individuals as subjects. A key advantage of our approach is that Signal Detection Theory explicitly models the m-alternative forced choice task while Item Response Theory does not. We show that Item Response Theory is inconsistent with key assumptions of the m-alternative forced choice task and is not a valid model for this paradigm. However, the simplest Item Response Theory model-the dichotomous Rasch model-is found to be a special case of SDT and provides a good approximation as long as the number of response alternatives m is small and remains fixed for all items.