Thursday, October 6, 2016

Structural Trauma and Toxic Stress: Lifecourse Roots of Health Inequities

Presentation given to the California Conference of Local Health Officer (CCLHP), HOAC Semi-annual meeting, Claremont, CA, October 6, 2016




Saturday, September 10, 2016

Population Health Data Science with R

Transforming data into actionable knowledge

I am writing this book to introduce R—a language and environment for statistical computing and graphics—for health data analysts conducting population health studies. From my experience in public health practice, sometimes even formally trained epidemiologists lack the breadth of analytic skills required at health departments where resources are very limited. Recent graduates come prepared with a solid foundation in epidemiological and statistical concepts and principles and they are ready to run a multivariable analysis (which is not a bad thing we are grateful for highly trained staff). However, what is sometimes lacking is the practical knowledge, skills, and abilities to collect and process data from multiple sources (e.g., Census data; reportable diseases, death and birth registries) and to adequately implement new methods they did not learn in school. One approach to implementing new methods is to look for the “commands” among their favorite statistical packages (or to buy a new software program). If the commands do not exist, then the method may not be implemented. In a sense, they are looking for a custom-made solution that makes their work quick and easy.

Sunday, September 4, 2016

Applied Epidemiology Using R, 2016

Public Health 215D, 2016, fall

UC Berkeley School of Public Health
Division of Epidemiology
Mondays 4pm--6pm, Valley Life Sciences 2030
Berkeley Academic Calendar: http://registrar.berkeley.edu/calendar

Course description

This is an intensive one-semester introduction to the R programming language for applied epidemiology. This year we will be experimenting with a population health data science perspective. Population health is a systems framework for studying and improving the health of a population through collective action and learning. Data science is the art and science of transforming data into actionable knowledge. Population health data science is the art and science of transforming public health health data into actionable knowledge to improve population health. The key words are actionable knowledge. Traditionally, epidemiology has focused primarily on descriptive and explanatory (causal) methods. Data science extends this to include exploratory, predictive, and prescriptive methods.

The core of population health data science is the timely analysis and synthesis of data using programming and computing power. Fortunately for us we have R! R is a freely available, multi-platform (Linux, Mac OS, Windows, etc.), versatile, and powerful program for statistical computing and graphics (http://www.r-project.org). This course will focus on core basics of organizing, managing, and manipulating population health data; basic population health applications; introduction to R programming; and basic R graphics. Students will complete and present a project in their field of interest.

Course book

Population Health Data Science

This book is early in its development and feedback is welcome and appreciated.

Thanks!!!

Tomas
aragon@berkeley.edu

Saturday, July 30, 2016

Practical LaTeX for the Health Sciences

Download full PDF article (first section printed below)
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The purpose of this tutorial is to introduce health scientists, analysts, and writers to LaTeX for preparing scientific documents. LaTeX is a document preparation system for creating professionally typeset scientific documents.  LaTeX is freely available and widely used by data scientists, mathematicians, physicists, statisticians, engineers, demographers, and many other disciplines. Specifically, we will learn how to prepare a scientific article, report, and doctoral thesis. Additionally, we introduce selected software solutions that enhance the publication process.

The purpose of scientific writing is to communicate, persuade, educate, inform, or alert readers using content that is well-organized and clear.  Scientific and technical documents can be divided into the following components (in order of importance!):

  1. Content
  2. Structure
  3. Appearance

The document content is the main reason for writing anything: we want to effectively communicate, and perhaps persuade, our audience with our narrative and supporting tables and figures.  As writers, we want to spend our time and intellectual energy producing excellent content.  Next in importance is document structure: that is, how our document is organized for logic and flow: title, section headings, subheadings, bibliography, tables, figures, etc.  Good document structure optimizes the logic and flow of our content.  Last in importance is document appearance. We do not want to waste our time worrying about how the content will appear---this can be accomplished efficiently later if the document is well-structured to begin with.

Therefore, as we write, we should spend most of our time on content production, spend time on determining organization to optimize the order and flow of our content, and spend minimal time on formatting appearance.  All too often writers spend an extensive amount of time formatting the appearance of their document to give it a desired structure and appearance.  This is problematic for documents that are long or that require frequent updating.  Additionally, most writers are not trained in typography: the time wasted on formatting is much better spent on improving content.

Preparing scientific documents is not writing a fiction novel.  In many ways preparing a scientific document is easier.  First, the organization has an expected structure. For example, a scientific article generally has the following sections: introduction, methods, results, and discussion.  Second, scientific writing should be factual, concise, and clear.  And third, displays are generally limited to tables and figures.

Preparing scientific documents present the following challenges:

  • Organization is structured (introduction, methods, results,  etc.)
  • Document length may be long
  • Document may require periodic updating
  • Use of mathematical notation and equations
  • Management of references
  • Creation of bibliographies
  • Cross-references to equations, tables, and figures
  • Re-number equations, tables, and figures
  • Generation of table of contents, tables, and figures 

Because article manuscripts are relatively short (about 20 pages double-spaced), these issues are less problematic.  For a doctoral thesis (or long report), these issues are either addressed efficiently and save time, addressed incorrectly and waste someone's time (possibly an administrative assistant---or worse, the author---spending hours reformatting), or not addressed at all---resulting in a lower quality, less user-friendly document.

In general, document preparation systems can be classified as either visual design or logical design. Microsoft (MS) Word is a familiar example of a visual design system; it is also known as "what you see is what you get" (WYSIWYG).  What you see on the computer screen is almost identical to what you get when you print the document.  In MS Word, basic word processing is easy to learn, user-friendly, and convenient for local formatting.  Local formatting is achieved by highlighting a string a text and then formatting it: for example, italicizing, bolding, or changing font face, size or color.  A major limitation of visual design is that local formatting of appearance is so easy that it becomes (unintentionally) the formatting method of choice for structuring long documents.  Extensive local formatting of long documents become onerous and impractical; WYSIWYG comes to mean "what you see is what you got."

In contrast, logical design separates the process of content production from the processes of formatting structure and formatting appearance. LaTeX is a logical design system: it provides a "markup language" to mark up content to have structural and conceptual meaning.  This facilitates global formatting of structure and appearance using established typographical standards for scientific documents.  Once the content is marked up, the content is compiled into a professionally typeset document using well established formats for scientific publication.  The writer spends little time worrying about formatting structure and appearance, and more time on preparing high quality narrative content.  The best way to understand this is to experience it firsthand.
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Download full PDF article (first section above) 

Thursday, July 14, 2016

Saturday, June 11, 2016

Cultural Humility --- and why it matters!

Cultural Humility










My road to discovering cultural humility was long, complex, and iterative. I have struggled with how to use our technical expertise to address health inequities and reduce health disparities. In April 2014, the San Francisco Department Public Health launched the Black/African American Health Initiative (BAAHI) which required me to question my assumptions and redefine my role. This happened by improving how we listen to our African American staff and communities.

I initially focused on technical solutions, but quickly learned (again!) that technical solutions---no matter how great and well-intentioned---will not take root and spread if we do not address underlying mental models, and explicit and implicit biases. Through an iterative process BAAHI emerged into three components:
  • Cultural humility (focused on racial humility)
  • Workforce development
  • Collective impact for health disparities
Cultural humility brings together and synergizes two important concepts: culture and humility. Culture is a "set of patterns of human activity within a social group and the symbols that give such activity meaning. Customs, laws, dress, architectural style, social standards, religious beliefs, and traditions are all examples of cultural elements. At every level, societies to individuals, culture is multi-dimensional and each individual has their own unique, multi-dimensional expression of culture which is dynamic and changing. Much of culture is hidden: we only see the symbols (behaviors, words, customs, traditions) but not the underlying beliefs, values, assumptions, and thought processes.

Humility is "the noble choice to forgo your status, and to use your influence for the good of others before yourself" (John Dickson). Humility is a universal character virtue because it is positively valued in nearly every society, culture and religion, and throughout modern history. Cultivating humility enables one to seek honest, critical feedback, and to improve relationships, trust building, team performance, and intellectual growth.

In 1998, Melanie Tervalon and Jann Murray-García published a groundbreaking article that challenged the concept of "cultural competency" with the concept of "cultural humility." When you accept cultural humility, by definition, you acknowledge that you can never truly achieve cultural competency. Cultural humility is committing to lifelong learning, critical self-reflection, and continuous personal transformation.

Here is my synthesis of their classic paper on this concept:
  1. Commit to lifelong learning and critical self-reflection.
  2. Cultivate humility, opening our heart to transformation.
  3. Realize our own power, privilege, and prejudices.
  4. Redress power imbalances for respectful partnerships.
  5. Recognize and validate our common humanity.
  6. Promote institutional accountability.

“Humility is the noble choice to forgo your status and use your influence for the good of others. It is
to hold your power in service of others” (Source: John Dickson, Humilitas, http://a.co/gV1cldW). I have come to believe that cultivating humility and practicing humble inquiry is central to leader, team, and organizational learning, performance improvement, and transformation. Organization culture is transformed through relationships (dyads and teams). Prejudices include explicit and implicit biases.

Humility and humble inquiry builds trust. Trust enables cooperation. Cooperation is necessary for shared visioning, shared decision making, and shared learning.

I believe that promoting cultural humility is one path to organizational transformation that will enable continuous improvement internally and externally with the diverse communities we serve.

For a more information on cultural humility visit: http://melanietervalon.com/resources/