Undercover police on campus

Soviet Russia and Drugs

Available in JSTOR.

Open Access with log-in to your personal bookshelf

Preprints: alternative views

Con:

https://jamanetwork.com/journals/jama/fullarticle/2654797

Pro:

https://jamanetwork.com/journals/jama/fullarticle/2664389?resultClick=1

Fast forward to 1970, and notice the Marihuana advert.

CSF taps and diagnosis of AD and MCI

"Grazing Material"

Dementia

Plasma and Cerebrospinal Fluid Amyloid Beta for the Diagnosis of Alzheimer's Disease Dementia and Other Dementias in People With Mild Cognitive Impairment (MCI)

C Ritchie et al. Cochrane Database Syst Rev (6), CD008782. 2014 Jun 10. 

https://www.ncbi.nlm.nih.gov/labs/articles/24913723/

CSF Tau and the CSF Tau/ABeta Ratio for the Diagnosis of Alzheimer's Disease Dementia and Other Dementias in People With Mild Cognitive Impairment (MCI)

C Ritchie et al. Cochrane Database Syst Rev 3, CD010803. 2017 Mar 22.

https://www.ncbi.nlm.nih.gov/labs/articles/28328043/

(11)c-Pib-Pet for the Early Diagnosis of Alzheimer's Disease Dementia and Other Dementias in People With Mild Cognitive Impairment (MCI)

S Zhang et al. Cochrane Database Syst Rev (7), CD010386. 2014 Jul 23.

https://www.ncbi.nlm.nih.gov/labs/articles/25052054/

https://www.ncbi.nlm.nih.gov/labs/articles/25052054/

Santa is a Psychedelic Mushroom?

Short Santa film

Cannabis and alcohol in the news, 1967

More on the concept of race

https://mobile.nytimes.com/2017/12/08/opinion/sunday/should-medicine-discard-race.html?referer=https%3A%2F%2Ft.co%2FckYAAukHOR

Overview of TMS and other non-pharmacological interventions for drug dependence

Stalling and Martinez, 2016

Introductory overview

Cited by Dr. Nora Volkow at ACNP 2017.

Cognitive games mentioned by Dr. Tom Insel at ACNP

He said they were capturing responses and using them to screen for neuropsychiatric disturbances.

USCF.EDU

Phenibut, GABA agonist

https://www.ncbi.nlm.nih.gov/pubmed/23391959

https://www.ncbi.nlm.nih.gov/pubmed/?term=phenibut

Of potential interest.

The Gin Craze Podcast

Another 'In Our Time' BBC podcast of note.

Everyone should know about the 'Gin Craze' that occurred in Great Britain once distilling came to rival and in some instances to displace fermentation of wine and brewing of beer/ale.

Example of a tech-shift akin to what happened when crack-cocaine in unit dose form was devised during the US cocaine powder insufflation epidemic of the 1975-1985 era, with crack displacing a much more hazardous 'freebase cocaine' self-administration process that involved serious inflammation. (See tragic Richard Pryor story for an example of a freebase casualty.)

Which data did Twenge use? Did she stratify by year of birth?

Or just use age-bins like 12-17?

Measurement of depression? Major Depression? Screener?

Economist article.

Economist

OED on mariguana mariahuana marijuana cannabis

OED mark-up

Need daily monitor for MTF portal availability.

https://www.ncbi.nlm.nih.gov/pubmed/29109106

T32-1A: regular agenda item

Gender in the news

Germany 3

Drug cocktails

1. http://www.asahq.org/lifeline/anesthesia%20topics/faq%20robo%20trippingoverthecounter%20drug%20abuse

2. https://pointsadhsblog.wordpress.com/2011/11/21/forgotten-drugs-of-abuse-part-1-ts-and-blues/

3. https://www.washingtonpost.com/news/morning-mix/wp/2017/08/21/the-rise-and-fall-of-miamis-ceo-of-purple-drank/?utm_term=.429f67a1880f

One of the most widely glorified opioids in hip-hop is lean, which is a mix of codeine syrup — a prescription opiate, promethazine and Sprite. It is referenced in a multitude of rap songs and is often referred to as "syrup" or "purple drank."

Lil Peep: RIP

Forsyth: History of Drunkenness

His podcast: History Extra episode:

http://www.historyextra.com/podcast/food/drinking-history

Easy listen on long drive: <45"

His book:

https://www.penguinrandomhouse.com/books/576101/a-short-history-of-drunkenness-by-mark-forsyth/9780525575375/

Anti-drug campaigns

Anti-drug campaigns

Mad in America podcast

Of potential interest.

See especially Jim van Os podcast. Jim has done more than most to clear up links of cannabis-schizophrenia, but uncertainties remain. Some of the uncertainties disappear if you re-conceptualize a schizophrenia pychosis as a dimension of 'hyper-meaning.' But would you get much news coverage or citation impact if yo report than cannabis use is followed by an upward shift on the dimension of hyper-meaning?

P.s. Many of the interviewees are not based in the U.S.

Mendelian Randomization?

How does MR differ in any substantive way from econometrics' "Instrumental Variables" Approach?

JAMA Psychiatry

Estimating its effect

Do you know how to do it?

If not, why not?

Heroin tales

Interesting take on Oxycontin story

Will be interested in "the rest of the story," once it's told.

Radden podcast

Anxiety: students-in-the-age-of-trump.

http://www.npr.org/sections/ed/2017/10/26/559914440/teachers-report-stressed-anxious-students-in-the-age-of-trump

Opioid relapse: A crime?

Opioid relapse: should-it-be-a-crime?

Epidemiology for clinical neurologists

Recent review article:

 

Sackler and opioids

Worth reading URL

Don't believe everything you read.

Sociometry

G.A. Lundberg, 1941, URL

An interesting sociological perspective:

 

Balfour's Neuroepidemiology of 1845

Balfour JSTOR URL. Look for diseases of the brain in naval versus military (ground forces).

 

 

 

Healy and R code data visualization

Healy' online data visualization book with intro to R code

Why isn’t treatment for depression leading to lower prevalence?

Depression:

Tony Jorm:

His talk

Stigma: inherently disparaging?

From the Oxford English Dictionary online, with my annotation: stigma.

Prompted by a discussion with Ron Cox, who asks whether we want to remove or reduce social stigma attached to drug use before we have definitive evidence on the degree to which stigma now deters and reduces the incidence of drug use. The result might be an increased incidence rate.

He notes that an analogy might be found in "loving and aiding the sinner" but "hating the sin."

Would anyone like to add comments in a respectful and dignified social policy discussion -- i.e., one that respects and treats comments as we would like our comments to be treated in a university-based discussion of alternative points of view and hypotheses? Let's welcome an exchange.

Socrates might ask whether we can use this line of reasoning for other purposes -- e.g., to reduce health care costs and the federal government expenditures on mental health and neurological care care via an initiative to increase the stigma attached to (1) being a recipient of mental health care or (2) receiving neurological services such as a brain scan after a consciousness-affecting blow to the head during a college football game?

Or, if we cannot ban sales and purchases of pain relievers, can we try to attach more stigma to taking these compounds in order to achieve pain relief?

You can think of other analogies that Socrates might work up with respect to obesity, failing to earn a 4.0 GPA, getting free breakfast or lunch at school,....

Are there pre-emptive values that should be called into play?

How would you describe those values?

Where in the university curriculum for epidemiology and public health do we introduce, explore, and debate these values and their policy implications?

 

Emergence of drug development after Dalton's atomic theory

Professor Tom Ban just contributed a useful short essay on the background of neuropsychopharmacology, with some details that embellish what I've described in relation to Woods' first use of a syringe to inject morphine for pain relief and the emergence of drug development from the aniline dye industries.

Ban, 2017

For more on John Dalton, this 43 minute podcast is instructive: In Our Time

In Our Time

More from BBC:

Dyes

Why would someone like Perkin want to synthesize quinine?

Why do the people of Peru jealously guard their supply of quinoa?

From: Fred Skeberg, 2017:  https://medium.com/@matgalen/everything-you-need-to-know-about-the-gin-and-tonic-82bde029b269

"What is Quinine

The story is that Spanish colonists discovered that the bark from the Quinquina tree in Peru could be used to treat Malaria. This likely happened in the early 1600’s. In Europe this ground bitter bark became known as Fever Tree bark or Jesuit’s powder. It is believed that the discovery and usage of the bark was one of the reasons why European countries managed to colonize the tropics.

The most active ingredient in the bark is quinine. In 1817 a couple of French scientists discovered a way to extract the quinine from the bark and from then on pure quinine powder became available to prevent the Malaria. It was this powder that was prescribed to the British officers which they created the first Tonic water with.

In the beginning most bark for quinine came from its original country of Peru. But seeds was smuggled out in 1860 and was sold to the Dutch government. They set up big plantations in Java, Indonesia where they could have full control of the market. During World War II the Japanese occupied Java which lead to a shortage in quinine. To prevent this from being a future problem trees was planted in Africa and synthetic quinine was developed.

Both the planting in Africa and the creation of synthetic quinine turned out successful and now there are quinine exported from Africa as well as synthetic quinine."

APC models

This evening I truly enjoyed reading this paper on APC analyses, which includes many provocative thoughts and interesting claoms (not all of which are matters of general agreement).

If you have or will use APC modeling, see the critiques, and pay attention to them in your measurement plans.

The MTF data ask about grade of first use, rather than age at first use of a drug, rendering the measurement problem for APC modeling even more difficult than it is in the typical public use data context when birthdate is not disclosed.

No need to repeat the MTF or NSDUH mistakes in your measurements or construction of variables.

Is the NSDUH approach a mistake? Only when the goal requires more refined data than the PUF offer us. It could offer us other information such as number of days from a specified origin to an event (or the month of an event) -- i.e., a constructed variable that gives the time dimension a fine-grained rather than coarse-grained unit of measurement.

Switching variables also could be provided, such as a switch to say whether the event occurred before or after a specific birthday.

Is the MTF approach a mistake? Here, grade of first use rather than age of first use is even more useless than what is faced in NSDUH.

Why a change in measurement approach has not followed the papers from MTF that speak of APC modeling escapes me. "Grade" is a very fuzzy construct in demography and in epidemiology. Its utility in APC models is not at all clear, for reasons described in this paper , with some very nice graphical displays:

APC and Russian mortality

 

Beer?

Beer and civilization?

A theory.

Heroin in a day: A day in Ohio city (not epidemiology, but pertinent. Why? Post your reasons in comments.)

Cincie Ohio heroin

The Emergence of the Modern Scientific Method

Some of you have asked about the approach of direct experience and observation leading to potential lawful relationships, and then these laws (theories) forming particular predictions (hypotheses), and then subjecting these predictions to mathematical evaluation.

I found this book, available to us on JSTOR, to be useful.

These chapters and the work of Roger Bacon, an apparent student of a Robert Grosseteste at Oxford, describe crucial developments:

The Scientific Achievement of the Middle Ages

There is a BBC4 podcast on the life of Bacon if you get tired of reading after Chapter 3:

Roger Bacon podcast

Witness Seminar Transcript: Medicalization of Cannabis

Link to PDF

Excerpt from Mechoulam's testimony:

Opioids harms: difficult to count

Report from a Tennessee:

Unknowns in opioid deaths

Gender Issues and Drug Use

33 minute CBC podcast on Gender Issues and Drug Use

Starts with over-representation of males among opioid overdose patients.

CBC On Drugs series

Opioids harms overview document - useful citation

Link to FDA document on opioids harms.

(CM Dormitzer is NIDA T32 alumna.)

MDMA in the news

http://www.maps.org/news/media/6786-press-release-fda-grants-breakthrough-therapy-designation-for-mdma-assisted-psychotherapy-for-ptsd,-agrees-on-special-protocol-assessment-for-phase-3-trials

NIDA source for this image.

RCT in trials registry,

FDA designation of breakthrough therapy. 

AUGUST 25, 2017 This American War on Drugs

NPR On the Media podcast with short and mainly accurate portrayal of the US war on drugs.

It will help you understand racist origins and mistakes made in US drug policy, how Harry Anslinger used "race-baiting" to revise the US tax code to his advantage and to the disadvantage of laborers from Mexico, in an echo of prior local and state anti-opium ordinances used to control immigrant-labor from China, and gives a quick overview of CSA1970 Schedule I, but makes factual errors in places. (Treated more thoroughly in the 1974 book I mentioned about a month ago. Search this blog label: #history for a web link.)

Use search link for AUGUST 25, 2017 podcast in archives of On the Media, if this link does not take you to the 50 minute recording and download page:

This American War on Drugs

Take it on a walk or our stationary bike ride and listen while you get some exercise.

On Marijuana and its many names

Fugs: Marijuana

Posters of the era on sale via Pinterest (Shameless commercial mention so as to share culture of that era)

Time to discuss what epidemic means?

Dual meanings inside and outside of epidemiology.

An anonymous AJE reviewer recently objected to our mention of the current cannabis epidemic, and argued that it no longer is an epidemic, but rather is "endemic."

For a different perspective, see the CDC use of the term in this report from August 2016, and notice the trend in estimates:

 

 

Plus, an opinion recently voiced in a JAMA Viepoint article:

 

Standard epi definition is an unexpected increase in numbers of newly incident cases or in the incidence rate (i.e., relative to expectation based on prior estimates for that population).

And see Frost and Van Volkenburgh (1935) for a somewhat muddled exposition -- i.e. muddled because "prevalence" is not clearly differentiated from " incidence" in some paragraphs, but context makes the meaning clear:

 

 

Heroin in Habitina, 1910

 

Earlier JAMA post on Habitina and blindness.

Methanol as vehicle for delivery of morphing and heroin?

 

 

MDHHS and LARA in social media: opioids

What pops up when I log into MSU E-resources and search JAMA articles:

MAPS stimulus:

 

State level opioid work

State efforts to reduce Rx opioid casualties, 2008.

Questions for you to answer:

Where are we now?

Report been updated?

What is the current set of public health components in this specific area: "evidence-based guidelines for prescribers;  effective policy and programmatic tools"?

https://www.cdc.gov/drugoverdose/pdf/rxreport_web-a.pdf

Bullet point quotations:

• Most states recognize prescription drug overdoses as a growing issue, although some states only recently became aware of its magnitude locally. Most states became aware of the problem through mortality data.

  States rely heavily on measures such as interagency task forces and prescription monitoring programs to address the problem. Less common are educational and regulatory initiatives. 

  States cited lack of awareness of the problem, insufficient data, privacy and confidentiality concerns, and lack of state-based injury prevention capacity as barriers to implementing a response.

  States cited the need to increase the visibility of the prescription overdose problem.

  States need evidence-based guidelines for prescribers and effective policy and programmatic tools. Although many states have implemented responses, their effectiveness is unclear. 

  
  

  
  

Oldie but goodie

Should be read by anyone contemplating use of this BLS data resource.

BLS Longitudinal Research

US and opioids

Carl Hart Editorial

NYTimes Opinion

p.s. the comments also are interesting.

Subjectively Felt Tolerance and the Steppingstone/Gateway Process

The only song I know about subjectively felt tolerance in the steppingstone/gateway process.

Fugs: I Couldn't Get High

When the page comes up, press the play button.

Colloquial concerns about self-report data

Scotland drug survey

http://theconversation.com/if-you-use-drugs-you-must-be-very-naive-or-very-principled-to-answer-a-survey-honestly-28372

More case studies assembled by the recovery community

More case studies

https://www.recoveryanswers.org/addiction-101/phenomenology/

The Atlantic: A World Without Suicide

https://www.theatlantic.com/health/archive/2017/08/zero-suicide-strategy/535587/

From time to time, a case study: Heroin

From time to time, a case study

Racism, Labor Conflict, and Drugs

CBC focus on the topic, with coverage of 1st Nation vulnerabilities and alcohol.

http://one.npr.org/i/537762064:537762066

If nothing else, listen to Carl Hart segment at 17:20 - 20:00.

Read up on it to get the chemistry right as you think about cocaine powder HCl and crack-cocaine

Skips over the difference between nasal insufflation and inhaling fumes into lungs ("smoking"?).

Also see book by Helmer & Vietorisz, 1974, an early introduction to racism and labor conflict described in the podcast.

https://libcom.org/history/drug-use-labour-market-class-conflict-john-helmer-thomas-vietorisz

Eric download

Recent news story pertinent to  this topic:

Former NFL Player Sues Jeff Sessions Over ‘Unconstitutional’ Marijuana Laws

http://www.huffingtonpost.com/entry/marvin-washington-jeff-sessions-marijuana-lawsuit_us_597746f6e4b0a8a40e825949?section=us_politics

Shaffer Library of Drug Policy

The online library is pretty impressive.

Library link

"The Facts about Drug Abuse"

Concluding paragraph of the report:

"Recognizing that deeply felt attitudes and established policies reflect fears and judgments that will yield slowly, if ever, to facts and conditions described in the council's publications, we recommend that serious consideration be given to the use of individual state or local option as a means of attempting solutions appropriate in one place but not in others. Local option could encourage greater flexibility and ingenuity rather than reliance upon an unrealistic, rigid homogeneity in national drug policy. We need to respond to the diversity of people who use and misuse drugs, base all our policies on a consistent set of principles seeking to discourage misuse, and keep our seemingly innate drug-using behavior within reasonable limits through means which do not themselves cause more harm than they prevent."

Drug Abuse Council final report, 1980.

Cross-sectional Schmosh-sectional. What is the issue?

I have stopped accepting "cross-sectional design" as a weakness in descriptions of study limitations.

This is like saying a US sample in 2017 is a limitation because it is not a sampling of the totality of human experience.

My most recent critique says this:

They confess cross-sectional design as weakness, but that actually is not right. 

The cross-sectional design is not the impediment to inference.

The impediment is failure to assess/know temporal sequencing of construct values.

The work might have been constructed with cross-sectional design, to sort out the temporal sequences, thereby avoiding sample attrition, measurement reactivity, and other biases that plague prospective and longitudinal studies.

Framed in this way, the problem is not one of cross-sectionality in design.

Rather, it is failure to sort out temporal sequences.

True, you can sort out temporal sequences more readily in a longitudinal design, but suppose you don't assess temporal sequencing.

All you know is that X converted from a value of 0 to a value of 1, during the same interval within which Y converted to a value of 0 to a value of 1. You have done a longitudinal study, but you haven't kept track of whether X changed from 0 to 1 before Y changed from 0 to 1.

 Clearly, the limitation is not the cross-sectional nature of the design.

Rather, it is failure to keep track of and to manage the temporal sequencing.

Does this distinction matter?

Textbook learning teaches you to think of the cross-sectional design as always inferior to the longitudinal design.

Experience teaches you that the cross-section, per se, is not necessarily a weakness.

Bittersweet symphony

What Cookies and Meth Have in Common?

Interesting question. The implicated assumption here is that cookies and meth do have something in common. Do they? Is the engagement of the brain reward system after intake what they have in common, or the other way around-- stress-induced changes to the reward system alters the risk for both eating and drug problems? Food is for survival. Meth is not. Meth interacts with dopamine transporters directly; cookies don't. (Cookie Monster's sad face)

Is stress and high accessibility the deadly combination for obesity and drug problems? Don't we need a 3*3 factorial design to test it out? I'd bet my money on accessibility. 

Thoughts are welcome!

Keith Connors, Ph.D., R.I.P., July 5, 2017

Excerpt from interesting BMJ linked obituary co-written by Allen Frances and by Connors, with primary focus on ADHD:

"Keith believed that the overdiagnosis and overmedication of millions of children resulted from aggressive marketing by pharmaceutical companies, careless doctoring, worried parents, and schoolroom chaos."

BMJ link: http://www.bmj.com/content/358/bmj.j2253

Describes his early work with Leon Eisenberg, then at the Hop.

In the 1980s it was interesting to watch and learn how Connors was focused on careful standardization of clinician examination protocols, with diagnostic cross-examination and workup, and to contrast the standardized questionnaire approach advocated by Tom Achenbach (with no cross-examination involved during assessment).

Interesting BBC news article on gender issues pertinent in research

Link to article

Intoxication among the Eskimo: Ethnographic Observations

Hough: The Lamp of the Eskimo

Sumerian drinking song

Ninkasi was the goddess of brewing.

Sumerian drinking song from 4000 years ago

William H. McGlothlin

Most of us in epidemiology knew Bill for his "clinical epidemiology" work on the California Civil Commitment Act outcomes, described below by Doug Anglin, one of his protégés.

He also studied hallucinogens, and wrote about them here:

A Chemistry for World Peace

Interview with Doug Anglin

A different era, perhaps.

Craig Reinarmand, Intoxication, and US Culture

I never met Reinarman, but I wish I had.

In this post, I will add some notes about his perspectives, and invite you to comment.

Reinarman on intoxication and US culture

Later on, if Hui or I have time, we'll add some additional interviews and readings.

Tom Ungerleider , RIP

Tom Ungerleider

I was lucky to interview Tom in the early 1970s as part of a DEA research contract that helped me understand the US drug policy structure. (At the time I drafted that research contract proposal, I was a 'wet behind the ears' Instructor at the University of Minnesota College of Pharmacy, and it helped sustain me through both my master of science studies and my PhD studies. I came away with a serious pessimism about learning anything definitive from analyses of already-gathered data, and a commitment to gather my own data. The search for definitive evidence and understanding must include analysis of already gathered data, but do not count on analyses of already gathered data to win you anything more than a seat testifying before the US Congress as the highest honor. Hard to speak definitively on any subject if all you do is analyze hard-won data that comes from protocols you did not design to 'sing' to the research question you seek to answer.)

Some notes on Tom and his contributions to our field:

Life history information

Bias and cannabis research

Drugs and adolescents

PubMed trace of his work over the years

On some occasions, we learn from a short interaction with an important field leader.
My interaction with Professor Ungerleider was a short one.
I called him on the telephone, set up the interview appointment, and flew out to meet him, returning with notes and valuable insights about how the DEA and FDA do and do not work together.
But the most profound insight involves compassion coupled with science.
Compassion for people using drugs and the use of science to harness the energy of that compassion in the direction of 'betterment'.
Thanks to Tom Ungerleider for what he taught me on that important front.

Tales on the Cannabis Road

Tales on the Cannabis Road.

Notes on Denver and Seattle.

I will post some images later.

Although I have purchased anything, the cannabis shop owners have been quite willing to allow me to take photographs.

What will they think of next?

"Cultivated Travel"

 

  

Instrumental variables background reading

Heckman

JSTOR article

 

Love of my life

SB & Jim  

Is this the kind of society you wish for your children or grandchildren?

You can make a difference.

atrocious

Web sales of fentanyl

NYT article

Neglected classics

Balter's work with Nurco was in the criminological tradition: https://www.ncbi.nlm.nih.gov/pubmed/1211378

(I'm looking for someone to do a literature review based on this line of studies, and the most highly cited of the work that subsequently cited these studies: https://www.ncbi.nlm.nih.gov/pubmed/7327796 . I think DAD would publish that lit review.)

This line of studies, sustained by the late David Nurco, as well as John Ball, from a base in the Friends Research Institute in Baltimore, is important reading for anyone seeking to master drug dependence epidemiology. David was at University of Maryland and John had been a NIDA Intramural Program researcher (Lexington, KY: Addiction Research Center) before he moved to the Baltimore area. They were somewhat dismissive of the kind of field surveys we were doing -- didn't think 'serious' drug users would participate and be found in our samples (left truncation problem, and a sense of left-censoring, although they did not use those terms).

After Mary Monk and I submitted and got trashed for our NIDA proposal to create a primary care study base in Washington County, Maryland (with primary care and community controls) which we wanted to start to  use to conduct a series of case control studies on cannabis dependence, before studying other IRD, David came up to me at a seminar. He disclosed that he had been on the study section, and asked me why I was interested in marijuana, whether I truly thought people become dependent on marijuana, and why I wasn't studying 'real' drug problems like cocaine and heroin. My next proposal to NIDA was to study cocaine use and problems in the United States. It got the equivalent of 1.8 and then 1.7 priority scores, not good enough for funding, mainly because we only had cross-sectional samples of users, and too few newly incident users from the 1-year followup of the ECA samples.

Some of you know what happened next, and how it came to pass that my first NIDA R01 award was to complete these proposed studies in cocaine epidemiology. I thank David for that advice, even though he had misjudged the public health importance of cannabis.

(As of last December, John Ball was still alive, per our mutual friends Faith and Jerry Jaffe.)

R.I.P. for Mitch and for David.

Age of Anxiety now?

Echoes of the 1960s.

NYT article

Expert opinion about dependence, 1999

Literature review

US only?

This team, led by Mitchell Balster, my 'teacher' at NIMH when I was Assistant Professor at Hopkins, were responsible for the first field surveys on this topic.

More by that group:

California survey before national survey.

US survey

When I read this article, I learned what kind of research methods I wanted to try to master. At that time, I didn't think of it as epidemiology. I thought of it as social science survey research.

Reading, Writing, and Reefer

Scare tactics of the 1960s-70s.

This one from 1979.

Educational film

Heroin by Velvet Underground

URLs to the right: Top one opened a new web page and the song started playing once I used cursor to press PLAY triangle.

Heroin

Live Version, top of page: 

Live version

Julie Bosman's NYT article from January 2017 is here.

Background reading: children and adolescent mental health, IACAPAP

Could be a useful resource for those interested in children and adolescent mental health:

IACAPAP text

Please leave comments if you find something particularly interesting, especially if it involves neuropsychiatric epidemiology.

I am looking for pediatric psychiatry examples to illustrate clearly how neuropsychiatric epidemiology should strive to be neither mindless nor brainless.

Women in science (biodiversity)

Biodiversity Exhibition on women in science before 1922.

Smithsonian

Who did they miss?

Add your suggested entries in the comments.

Drug dependence neurobiology

Thoughtful review article.

Everitt & Robbins, 2016

George Comstock on Wade Hampton Frost

 

From Frost Biography:

 

Mary Gover: I have not found a biography.

Project on history of women in epidemiological research 

Hopkins School ScD graduating class of 1923:

 

 

LT and LC biases in drug dependence epidemiology

Perhaps more than is the case for any other neuropsychiatric or behavioral condition, except perhaps suicide ideation, attempts, and planning, we should have special concern about left-truncation and left-censoring biases in "clinical investigations" of quitting drug use or being in remission or recovery after having become drug dependent.

Leaving aside these biases, think about denominator and numerator issues.

When we estimate newly incident use or dependence, we generally have large denominators to work with. The S.E. help us deal with uncertainty such as the relatively small numbers of users who will die within the first 1-2 years after first use, or soon after dependence onset.

In contrast, the estimates for quitting among cases are constrained by the relatively small number of observed cases in each survey. Wide S.E. as a result, even if we ignore the LT and LC biases.

Make sure you can describe LT versus LC in the survey context.

A paper that I think over-values our epidemiological survey evidence on quitting: 

URL for Heyman, 2013

Perhaps "clinical investigation" samples are better than epidemiological samples in this domain of inquiry, if they can document zlT and LC bias constraints better than we can?

"Solutions Epidemiology"

About one decade ago, the concept of "consequential epidemiology" was introduced, but it seemed a bit gimmicky, and perhaps a bit of special pleading about a field possibly in need of a morale boost.

Thinking about our currently Balkanized epidemiology, I am re-visiting the idea with a different term.

I call it "Solutions Epidemiology," and with this term I invoke a return to the roots of epidemiology as a disciplined speeded-up way to achieve near-term solutions to pressing public health problems.

Other bullet points:

1. A deliberate choice of health problems that now qualify as low-hanging fruit, by which I mean defined problems that can be solved in the near-term, and that might qualify either as epidemics or as the equivalent in localized settings: e.g., hospital-acquired MRSA infections; unintended pregnancies; high death rates if near-term or full-term infants.

2. A deliberate reach from the more languorous flow of research and resulting evidence in chronic disease epidemiology in the direction of an accelerated flow of evidence toward implementation science issues faced in public health departments year by year, as opposed to decaf by decade.

3. A deliberate alliance of academic epidemiology researchers with public health department officials charged with solving problems in real time.

4. A deliberate abandonment of Balkanized epidemiology that organizes itself in terms of domains of the explanation or 'scale' of its variables of interest (e.g., genetic epidemiology, social epidemiology, molecular epidemiology) in the direction of a more holistic epidemiology that organizes itself with a focus on a population health problem that requires a near-term solution.

5. Leaving in the hands of others all epidemiological problems that require a languorous approach and cannot be accelerated more rapidly toward actin research with near-term yield.

6. Differentiation from allied endeavors such as "implementation science" by virtue of a clear point of departure in terms of definition of specified populations and keeping track of the sequence epidemiologists use (1) to ensure at least a limited but 'built-in' external generalizability of our work, and (2) to study the sick AND the well in each population with due attention to bias in estimates when sampling frames or achieved samples depart from pre-specified populations for our studies.

I could go on and on, but my intent is simply to plant the seed of an idea for "Solutions Epidemiolgy" and to elicit some comments to guide its future development.

We have an opportunity to show Solutions Epidemiology at work in relation to the current heroin epidemic in US counties. There are counties with zero or few heroin overdose events, fatal and non-fatal. Other counties are suffering. What differentiates them? Isn't that an important epidemiological question that can be answered quite speedily in the direction of action research to see what can be done (e.g., via randomized trials) to keep the low rate counties at steady state low rates? And wouldn't it be important to learn that evidence sooner rather than later?

Operations research traditions come to mind, along the lines that Deming devised to find flaws in manufacturing processes. Surely, the work of Deming and other operations researchers deserves attention in the education of 'solutions epidemiologists' of the future. At present, I see few epidemiologists who know of Deming and his operations research tradition. Sad state of affairs, and the next generation of epidemiologists can do something about it.

Obituary for Deming

Your thoughts?

I will return to this topic later, after I elicit some comments and give the idea more thought. Maybe it's not worth pursuing.

(HC: Please fix any typos that I have not caught. No need for comment on them. Just fix them. Thank you!)

Importing Econometric Models into Psychiatric Epidemiology, A Start

Leaving aside earlier history of probability and statistics that anticipated least squares regression, a potted history in this area can start with William Farr and his 'hero of concept,' the Marquis de Condorcet (Nicholas de Condorcet).

Sidebar 1: Let me ask one of your to make a comment about Condorcet for me to edit and add as a later sidebar, with attribution. Why was Condorcet important to Farr? How might Farr have learned about him? You can answer these questions by reading my copy of Humphreys' version of Farr's selected works, but it might be easier to search for Condorcet (and France) in the online version of Farr's work. In the process, you will learn that Farr's studies in France were in part financed by an elderly benefactor, and that Farr was accompanied by a wealthier physician-friend to study with Pierre Charles-Alexandre Louis. Many characterize Louis as the physician who formalized clinical trial elements such as randomized assignments.

Sidebar 2: While his friend was hiking the Alps, what was Farr doing, which is pertinent to his abiding interests in what we now call neuropsychiatric epidemiology of developmental disabilities?

Sidebar 3: Find and describe Farr's post-Snow description of factors x,y,z, etc., mentally held constant while the source of water supply was allowed to vary, an early conceptualization of what was to become the familiar multiple regression model for a univariate response. (Hint: You can find a rendition in one of my papers.)

Fast-forward, and skip over a lot of progress until you encounter:

(1) Sewell Wright, son of P. Wright, and discover their contributions to this topic, with particular focus on path analysis, and its contribution to a field called "Population Genetics," which now is seen no more than rarely as an acedimic department in universities. Can you figure out why and how it came and went?

(2) Contributions made to model-building in econometrics, which should be understood by epidemiologists. Why not read January Tinbergen's Nobel Prize lecture, which is about as good an explanation of models and model-building as I have seen lately:

January Tinbergen Nobel Prize lecture, 1969

P.s. Next up, error terms, Keynes, and Haavelmo, as we work our way toward comparison of Directed Acyclic Graphs and their sequences of univariate response models with simultaneous equations models for a multivariate response world.

Heart-warming story about friends and phages

Tom Patterson and Steff Strathdee

Courage in action story: 

link

Old Age Psychiatry: The Baby Boom Generation and What to Expect: Performance-Enhancing Drugs

A scholarly review through 2004-5 that identifies some important gaps in epidemiological evidence that remain unfilled:

Link to the review

Where I found this interesting report: 

Link to the page

Re-Thinking Epidemiology for the Mid-21st Century

Let me get started with a provocative idea. Before 1980, epidemiology stopped generating new ideas and theories. What passed for theory in epidemiology had become little more than borrowing from other scientific disciplines. The rest of this blog post is about that idea.

<snip>

 

Anyone who knows me appreciates that I was destined to be no more than a limited 'futurist' as compared to the best futurists. I lay the blame on the Catholic Church, becoming an altar boy, studying Latin for more years than I wish to count (including a year of self-study), and gaining too much respect for early origins and roots. Think about me as a conservative radical, conserving the roots. I might be too 'conservative' to be a good futurist.

 

At the same time, I also am known as an iconoclast, because I do not hesitate to challenge bogus concepts when they creep into our field of epidemiology, among which I can specify 'risk factor' and 'reverse causality' as special within-field jargon terms that have almost no communication value when we, as epidemiologists, try to describe our evidence to audiences beyond the local 'tribe'. (Worse yet, there are non-tribe members who actually think they know what we mean when we use these jargon-terms, as has occurred when my non-baseball friends have thought I'm talking about mental health when I use the term 'screwball' when describing a baseball pitcher.)

 

With that background in mind, you can imagine my response when I was giving an end-of-semester talk to my research trainees and students about some challenges that epidemiologists are going to face during the next few decades. I thought back to two issues raised when I was early in my studies of epidemiology back in the late 1970s: (1) an idea that David Mechanic and Bill Eaton mentioned about epidemiology having run out of ideas and theories, and (2) an idea that Bruce Dohrenwend offered about epidemiology being little more than a toolkit or collection of methodological approaches.

 

For my students, I framed my response to a hypothetical question about the challenges they might face in relation to these two ideas, and I offered this statement: "The most serious challenge you will face in your career is running out of substantive ideas and theories that deserve testing."

 

For the past day, I have been thinking about what I told them, and I realized that there might be an empirical indication of the degree to which epidemiology, as a discipline, has started to run out of ideas and theories, and has entered a terminal (?) stage of being a methods-oriented field of study as might be distinguished from a science, akin to the way we'd differentiate 'operations research' as a field of study without thinking about it as a 'science' in the generally accepted sense of the term.

 

My realization of an empirical approach required a reflection on (a) an early expression of Wade Hampton Frost's idea that epidemiology has to do with infective agents and infectious diseases, and he was uncertain about whether it made sense to think about epidemiology as applied to other conditions that did not originate with an exposure to an infective agent, (b) Mort Levin's assertion in a Milbank Memorial Fund session that Ernie Gruenberg had organized, which amounted to this statement: "There can be an epidemiology, and there can be a set of psychiatric disorders, but I'm not sure there needs to be an epidemiology of psychiatric disorders," and (c) a general principle I first learned from my PhD advisor Len Schuman at University of Minnesota, which also later was stressed by my local colleague and friend Nigel Paneth, along the lines of the advantages gained by restricting the prefix adjective for epidemiology to the domain of individual disease entities or disease classification names, as in 'cholera epidemiology' and 'infectious disease epidemiology,' as opposed to alternatives based on prefix adjectives that shifted attention from the epidemiological response under study in the direction of the causal explanations under study (e.g., 'genetic epidemiology').

 

When I first appreciated this point as it was being made by Len Schuman in my early years after starting graduate studies in epidemiology, I had not read Wade Hampton Frost nor had I met Mort Levin. I was out in Minnesota, ignorant of Mechanic's medical sociology program at University of Wisconsin, and completely ignorant about Bruce and Barbara Dohrenwend's social psychological research program at Columbia. Nonetheless, it was not long until I was reading the Lilienfeld-Gifford 'Chronic Diseases and Public Health' book assigned by Schuman, and I recognized a clear distinction being made between 'Infectious Disease Epidemiology' and 'Chronic Disease Epidemiology' (hereinafter abbreviated as ID and CD).

 

[At this point, I stopped for refreshment and I pick up the thread down below.]

 

Now that I have drawn attention to this separation of 'ID epidemiology' from 'chronic disease' epidemiology, I can offer a thought experiment that some enterprising young epidemiologist might try to pursue. (The most valuable thought experiments are those that can be investigated empirically once the experiment has been specified.)

 

The empirical work involves the study of time trends in appearance of adjectives used to modify the term 'epidemiology' as can be seen in traces such as Web of Science or Google Search or JSTOR or other bibliographic search tools that have emerged as a consequence of internet advances.

 

An initial interesting time trend will depict the relative frequency of 'infectious disease epidemiology' and 'chronic disease epidemiology' as these terms appeared in the published literature, year by year, over time. Here, the expectation would be an increasing frequency of both terms, but in addition, even with de-trending, the ID/CD ratio might be expected to decline, at least until the mid-1980s, given (1) increasing prominence of work in CD epidemiology until (2) emergence of HIV/AIDS research as priorities for NIH before 1990. (I have not studied these trends so these expectations are based solely on my 'seat of the pants' reckoning, and I might well be wrong.)

 

A savvy approach will put into play de-trending research approaches that compensate for generally increasing frequencies of 'epidemiology' as a search term, based on knowledge that NIH and other funding sources increased their investments in epidemiology across these years. A more savvy approach will take other interesting issues into account, such as might be illuminated by studying citation counts as opposed to what can be learned via 'topic' or 'title' restricted searches over these years.

 

But I leave these issues up to others in order to focus on the possibility that epidemiology's de-celerating rate of innovative ideas might be reflected by studying (1) the relative frequency of 'disease entity' adjectives positioned as prefix terms before 'epidemiology' appears as a noun, and (2) the corresponding relative frequency of 'non-disease-entity' adjectives positioned as prefix terms. Here, by 'disease entity' adjectives, I'll use as examples 'cancer epidemiology' and 'dementia epidemiology.' For 'non-disease-entity' examples, I'll use examples 'social epidemiology' and 'genetic epidemiology' or 'nutrtional epidemiology' or 'life-course epidemiology.'

 

It is fair to ask why the relative frequency of these prefix adjectives might convey something important about the content of epidemiological research and the inherent generativity of epidemiology as a source of new ideas and theories. I have little more than a simple answer of the following form, expressed in relation to 'Types' of epidemiology:

 

(Type 1) When the prefix adjective is focused on the response variable, such as a cancer or a dementia, then the domain of potential explanations is expanded almost infinitely to cover whatever might be accounting for variation in the incidence rates and prevalence proportions for that response. The epidemiologist is faced with the challenge of drawing from multiple disciplines in an effort to understand what might account for the population-level variations in the epidemiological parameters. Let's think of the specification of the response variable as one dimension of epidemiology.

 

(Type 2) When the prefix adjective is focused on a domain of explanation (e.g., 'social' or 'nutritional' or 'genetic'), there is a greater constraint on the range of sources of variation. The epidemiologist is faced with a more circumscribed challenge, which is to ask whether and under what circumstances that domain of explanation might be more or less important in attempts to account for population-level variations in the epidemiological parameters. Let's think of the specification of the explanatory domain as a second dimension of epidemiology, when 'second' denotes a time sequence rather than my own pre-judgement (prejudice) about the ordinal ranking of importance or public health significance.

 

(Type 3) When the prefix adjective is focused on a domain of process (e.g., life-course'), there is a third dimension that can be considered quite separately from the first two dimensions, and the third dimension has a correlation with time. This dimension might reflect age (considered subgroup by subgroup, as in a cohort-sequential study), or aging (considered as a progression from one birthday to the next), or as developmental (as in the relatively fuzzy sets that we use to distinguish developmental stages along the lines of (a) pre-term, full-term, etc., with respect to measured gestational age of a newborn, or (b) 'pre-pubertal,' 'pubertal,' etc., along the lines of the Tanner stages, or (c) pre-senile versus senile, as in the differentiation of age of onset of dementia syndromes based on when the syndrome was detected, earlier for those with trisomy-21, at mid-life for those with certain familial histories of early-onset, or later for those formerly known as 'sporadic' due to the absence of the family history of mid-life onset of the dementia syndrome. This is a third dimension, separable from the first two dimensions.

 

It is my speculation that an increasing frequency of prefix adjectives of type (2) and (3), relative to type (1), over time, can serve as an indication of the degree to which epidemiology, per se, has stopped generating its new ideas and theories, and instead is turning in the direction of other disciplines to fill a gap of imagination or generativity that otherwise would not require turning toward these other disciplines.

 

I have no idea whether this speculation has merit. I offer it as a suggestion for epidemiologists and historians of science who might wish to seek quantitive evidence about the degree to which a discipline has 'run out of its own ideas and theories' versus the alternative of borrowing from other disciplines.

 

I look forward to comments and to any empirical evidence on these matters.