Browsing by Person "Sharpe, M."

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Clinically relevant fatigue in cancer outpatients: the Edinburgh Cancer Centre symptom study
(2007-09-05) Storey, D. J.; Waters, Rachael A.; Hibberd, Carina J.; Rush, Robert; Cargill, A.; Wall, L. R.; Fallon, Marie T.; Strong, V.; Walker, J.; Sharpe, M.
Background: Fatigue is associated with cancer and its treatment but we know little about how many and which patients suffer fatigue of clinical severity. We aimed to determine the prevalence of clinically relevant fatigue (CRF) and its associations in outpatients with various cancer diagnoses. Patients and methods: A survey of outpatients with colorectal, breast, gynaecological, genitourinary, sarcoma, melanoma and miscellaneous tumours at a regional cancer centre. Patients completed the European Organisation for Research and Treatment of Cancer (EORTC) fatigue subscale and the Hospital Anxiety and Depression Scale (HADS). These self-report data were linked to demographic and clinical variables. Data were available on 2867 outpatients. Results: The prevalence of CRF (EORTC fatigue subscale ‡40) was 32% (95% confidence interval 31–34%). The variables independently associated with CRF were primary cancer site, having disease present, type of cancer treatment and emotional distress (total HADS score ‡15). Emotional distress had the strongest association with fatigue but half the cases of CRF were not distressed. Conclusion: CRF is common in cancer outpatients and is associated with type of disease and treatment, as well as with emotional distress. The association between CRF and emotional distress is strong but they are not equivalent conditions. Key words: associations, cancer, fatigue, predictors, prevalence, treatment
Contextual effects in suicidal behaviour: evidence, exploration and implications.
(Oxford University Press, 2005) Platt, S.; Pavis, S.; Sharpe, M.; O'May, Fiona; Hawton, K.
Emotional distress in cancer patients: the Edinburgh Cancer Centre symptom study
(2007-02-20) Strong, V.; Waters, Rachael A.; Hibberd, Carina J.; Rush, Robert; Cargill, A.; Storey, D. J.; Walker, J.; Wall, L.; Fallon, Marie T.; Sharpe, M.
To: (1) estimate the prevalence of clinically significant emotional distress in patients attending a cancer outpatient department and (2) determine the associations between distress and demographic and clinical variables, we conducted a survey of outpatients attending selected clinics of a regional cancer centre in Edinburgh, UK. Patients completed the Hospital Anxiety and Depression Scale (HADS) on touch-screen computers and the scores were linked to clinical variables on the hospital database. Nearly one quarter of the cancer outpatients 674 out of 3071 (22%; 95% confidence interval (CI) 20–23%) met our criterion for clinically significant emotional distress (total HADS score 15 or more). Univariate analysis identified the following statistically significant associations: age <65, female gender, cancer type and extent of disease. Multivariate analysis indicated that age <65 (odds ratio 1.41; 95% CI 1.18–1.69), female gender (odds ratio 1.58; 95% CI 1.31–1.92) and active disease (odds ratio 1.72; 95% CI 1.43–2.05) but not cancer diagnosis, were the independent predictors of clinically significant emotional distress. Services to treat distress in cancer patients should be organised to target patients by characteristics other than their cancer diagnosis.
Rasch fit statistics and sample size considerations for polytomous data
(2008-05-29) Smith, Adam B.; Rush, Robert; Fallowfield, Lesley J.; Velikova, Galina; Sharpe, M.
Background: Previous research on educational data has demonstrated that Rasch fit statistics (mean squares and t-statistics) are highly susceptible to sample size variation for dichotomously scored rating data, although little is known about this relationship for polytomous data. These statistics help inform researchers about how well items fit to a unidimensional latent trait, and are an important adjunct to modern psychometrics. Given the increasing use of Rasch models in health research the purpose of this study was therefore to explore the relationship between fit statistics and sample size for polytomous data. Methods: Data were collated from a heterogeneous sample of cancer patients (n = 4072) who had completed both the Patient Health Questionnaire – 9 and the Hospital Anxiety and Depression Scale. Ten samples were drawn with replacement for each of eight sample sizes (n = 25 to n = 3200). The Rating and Partial Credit Models were applied and the mean square and t-fit statistics (infit/outfit) derived for each model. Results: The results demonstrated that t-statistics were highly sensitive to sample size, whereas mean square statistics remained relatively stable for polytomous data. Conclusion: It was concluded that mean square statistics were relatively independent of sample size for polytomous data and that misfit to the model could be identified using published recommended ranges.
Validation of an item bank for detecting and assessing psychological distress in cancer patients.
(2009) Smith, A.; Rush, R.; Wright, P.; Stark, D.; Velikova, G.; Sharpe, M.
Objective: To validate an item bank for assessing and detecting psychological distress in cancer patients by (1) identifying whether additional items are required in the full item bank; (2) identifying any item bias in the existing item bank; (3) linking levels of distress against thresholds derived from gold-standard psychiatric interviews (PSE/SCAN/SCID). Method: A Rasch analysis was conducted on a heterogeneous sample of cancer patients (n=4919) who had completed a combination of eight psychological distress screening instruments. A subset of patients had completed a psychiatric interview along with the HADS (n=381) or PHQ-9 (n=440). Item thresholds were plotted along the latent trait. Furthermore, items were assessed for differential item functioning (DIF) by age and gender. Finally, optimum thresholds were derived for the HADS and PHQ-9 and plotted along the latent trait distribution for the entire item bank. Result: Item thresholds exceeded the range of person measures, although a gap was still present along the latent trait. No DIF was observed for either age or gender. Putative cut-offs were derived for the item bank detecting moderate to severe levels of psychological distress. Conclusion: The item bank covers the majority of levels of emotional distress reported by cancer patients. Additionally, initial thresholds have been derived on the item bank, which correspond to a formal psychiatric assessment. Further work is required to ascertain the stability of the item bank over time and by diagnosis and stage of disease, as well as to determine additional thresholds for levels of distress.