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Michael I. Bennett

Researcher at University of Leeds

Publications -  290
Citations -  17312

Michael I. Bennett is an academic researcher from University of Leeds. The author has contributed to research in topics: Palliative care & Cancer pain. The author has an hindex of 52, co-authored 266 publications receiving 13680 citations. Previous affiliations of Michael I. Bennett include United Nations Industrial Development Organization & Lancaster University.

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Managing Pain in People with Cancer—a Systematic Review of the Attitudes and Knowledge of Professionals, Patients, Caregivers and Public

TL;DR: Among professionals, patients, caregivers and the public there were similar attitudinal barriers to effective CPM, and the most commonly cited barriers were fear of drug addiction, tolerance of medication and side effects of opioids.
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Patient and caregiver perspectives on managing pain in advanced cancer: A qualitative longitudinal study.

TL;DR: The main drivers of help-seeking and action by patients to manage pain were the sensory experiences of pain and meaning attached to it, not beliefs about analgesia.
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Delivering research in end-of-life care: problems, pitfalls and future priorities

TL;DR: The challenges facing the delivery of research in end-of-life care in the UK and internationally as health policies begin to focus on improving care are reviewed, including the problems of terminology and lack of emphasis on clinical studies.
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Is regular systemic opioid analgesia associated with shorter survival in adult patients with cancer? A systematic literature review.

TL;DR: While opioid analgesia does not affect survival at the end of life, in the context of longer-term treatment, higher-quality studies, with survival as a primary endpoint, are needed to confirm an independent association between opioids analgesia and shorter survival.
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Analysing the SF-36 in population-based research. A comparison of methods of statistical approaches using chronic pain as an example.

TL;DR: The conventional approach, using straightforward parametric tests, is both simplest and the best for allowing comparison with other studies, and is likely to adopt in future studies.