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A Clinician's Guide to Statistics and Epidemiology in Mental Health: Measuring Truth and Uncertainty

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Overview

Accessible and clinically relevant, A Clinician's Guide to Statistics and Epidemiology in Mental Health describes statistical concepts in plain English with minimal mathematical content, making it perfect for the busy health professional. Using clear language in favour of complex terminology, limitations of statistical techniques are emphasized, as well as the importance of interpretation - as opposed to 'number-crunching' - in analysis. Uniquely for a text of this kind, there is extensive coverage of causation and the conceptual, philosophical and political factors involved, with forthright discussion of the pharmaceutical industry's role in psychiatric research. By creating a greater understanding of the world of research, this book empowers health professionals to make their own judgments on which statistics to believe - and why.

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Editorial Reviews

From the Publisher
"Overall, the book is one of the more thought-provoking of its genre, and reminiscent of the writings of Kenneth Rothman."
--Doody's Review Service
Doody's Review Service
Reviewer: Howard M. Kravitz, DO, MPH (Rush University Medical Center)
Description: This slim book is written by S. Nassir Ghaemi, MD, MPH, to introduce clinicians, residents, and students to the science behind the art of reading and critically appraising research studies.
Purpose: Dr. Ghaemi describes himself as a "clinical researcher in psychiatry," who has written this book "for clinicians and researchers in the mental health professions." Statisticians are categorically excluded from his audience because he expects they will "find it unsatisfying." The purpose is to teach readers how to understand, not to do, statistics. In sharing his insights and opinions, Dr. Ghaemi wants readers to understand conceptually what the numbers mean, to become better consumers of the literature rather than data technicians.
Audience: The target audience includes clinicians and researchers in the mental health professions, as well as residents and students. Although the content draws from the psychiatric and psychopharmacologic literature, the basic learning points will inform practitioners in all fields of medicine who need to read and apply the literature to patient care. Dr. Ghaemi notes: "one cannot be a good clinician unless one understands research." Learning to "navigate the scientific literature" bridges these two worlds.
Features: The 18 chapters are grouped into six sections (2 to 4 chapters per section): basic concepts, bias, chance, causation, the limits of statistics, and the politics of statistics. The book, a relatively short 137 pages, ends with a brief appendix on regression models and multivariable analysis. All references are compiled in a separate section. Historical perspectives and examples bring real-life relevancy to the book. The chapter on Bayesian statistics is particularly well written. True to the author's word, numbers make only cameo appearances. In total, I counted 10 figures, half in the chapter on Bayesian statistics, and six tables. The index is only moderately helpful. Clinical trials are described in a chapter on hypothesis testing, but an important omission is a chapter on research design, an essential journal club topic. Another concern is the author's sometimes and seemingly idiosyncratic use of terms, for example, "confounding bias." Whereas bias involves error in measuring a variable, confounding involves error in interpreting what may be an accurate measurement; conflating these two terms can be, well, confounding.
Assessment: This is an explication of Dr. Ghaemi's philosophy of numbers in the service of science. In reflecting on his learning and experiences, he tends to reveal his leanings, sometimes to the point of dogmatism. While informative, Dr. Ghaemi's nuanced explanations and reasoning might be better appreciated by persons who have some familiarity with the content. Overall, the book is one of the more thought-provoking of its genre, and reminiscent of the writings of Kenneth Rothman.
From The Critics
Reviewer:Howard M. Kravitz, DO, MPH(Rush University Medical Center)
Description:This slim book is written by S. Nassir Ghaemi, MD, MPH, to introduce clinicians, residents, and students to the science behind the art of reading and critically appraising research studies.
Purpose:Dr. Ghaemi describes himself as a "clinical researcher in psychiatry," who has written this book "for clinicians and researchers in the mental health professions." Statisticians are categorically excluded from his audience because he expects they will "find it unsatisfying." The purpose is to teach readers how to understand, not to do, statistics. In sharing his insights and opinions, Dr. Ghaemi wants readers to understand conceptually what the numbers mean, to become better consumers of the literature rather than data technicians.
Audience:The target audience includes clinicians and researchers in the mental health professions, as well as residents and students. Although the content draws from the psychiatric and psychopharmacologic literature, the basic learning points will inform practitioners in all fields of medicine who need to read and apply the literature to patient care. Dr. Ghaemi notes: "one cannot be a good clinician unless one understands research." Learning to "navigate the scientific literature" bridges these two worlds.
Features:The 18 chapters are grouped into six sections (2 to 4 chapters per section): basic concepts, bias, chance, causation, the limits of statistics, and the politics of statistics. The book, a relatively short 137 pages, ends with a brief appendix on regression models and multivariable analysis. All references are compiled in a separate section. Historical perspectives and examples bring real-life relevancy to the book. The chapter on Bayesian statistics is particularly well written. True to the author's word, numbers make only cameo appearances. In total, I counted 10 figures, half in the chapter on Bayesian statistics, and six tables. The index is only moderately helpful. Clinical trials are described in a chapter on hypothesis testing, but an important omission is a chapter on research design, an essential journal club topic. Another concern is the author's sometimes and seemingly idiosyncratic use of terms, for example, "confounding bias." Whereas bias involves error in measuring a variable, confounding involves error in interpreting what may be an accurate measurement; conflating these two terms can be, well, confounding.
Assessment:This is an explication of Dr. Ghaemi's philosophy of numbers in the service of science. In reflecting on his learning and experiences, he tends to reveal his leanings, sometimes to the point of dogmatism. While informative, Dr. Ghaemi's nuanced explanations and reasoning might be better appreciated by persons who have some familiarity with the content. Overall, the book is one of the more thought-provoking of its genre, and reminiscent of the writings of Kenneth Rothman.
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Product Details

  • ISBN-13: 9780521709583
  • Publisher: Cambridge University Press
  • Publication date: 8/31/2009
  • Edition description: New Edition
  • Pages: 166
  • Product dimensions: 6.10 (w) x 9.10 (h) x 0.40 (d)

Meet the Author

S. Nassir Ghaemi MD MPH is Professor of Psychiatry at Tufts University School of Medicine, and Director of the Mood Disorders and Psychopharmacology Programs, Department of Psychiatry, Tufts Medical Center, Boston, Massachusetts, USA.

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Table of Contents

Preface; Acknowledgements; Part I. Basic Concepts: 1. Why data never speak for themselves; 2. Why you cannot believe your eyes: the three C's; 3. Levels of evidence; Part II. Bias: 4. Types of bias; 5. Randomization; 6. Regression; Part III. Chance: 7. Hypothesis testing: the dreaded p-value and statistical significance; 8. The use of hypothesis testing statistics in clinical trials; 9. The alternative effect estimation; Part IV. Causation: 10. What does causation mean?; 11. A philosophy of statistics; Part V. The Limits of Statistics: 12. Evidence-based medicine: defense and criticisms; 13. The alchemy of meta-analysis; 14. Bayesian statistics: why your opinion counts; Part VI. The Politics of Statistics: 15. How journal articles get published; 16. How scientific research impacts practice; 17. Dollars, data, and drugs; 18. Bioethics and the clinician/researcher divide; Appendix. Regression models and multivariable analysis.

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