Bibliographic record
Abstract
Back to table of contents Previous article Next article Clinical & Research NewsFull AccessSeveral Obstacles Interfere With Alcohol TreatmentJoan Arehart-TreichelJoan Arehart-TreichelSearch for more papers by this authorPublished Online:2 Jan 2009https://doi.org/10.1176/pn.44.1.0011b“My father was a doctor and an alcoholic who died on skid row,” Graeme Cunningham, M.D., director of the Addiction Division of Homewood Health Center in Guelph, Ontario, reported at the Canadian Psychiatric Association meeting last September. “My mother was also an alcoholic. And I became one as well. For years I practiced medicine impaired, I was disciplined by my colleagues, I had lawsuits going against me. My 'M.D.' stood for 'master of denial.'”Such a denial is probably the biggest obstacle to helping alcoholic patients, Henry Kranzler, M.D., an addiction psychiatrist and associate scientific director of the University of Connecticut's Alcohol Research Center, said in an interview. And the reason is hardly surprising, he added—“Alcohol is widely used in society, is widely accepted, and people have a hard time seeing it for what it often can be, which is a real source of problems for people.”Another major hurdle involved in trying to help alcoholic patients, Kranzler noted, is that alcohol tends to be so reinforcing that many patients view it as a friend. “So it is very hard to get them to initially begin, or to subsequently stick with, quitting or with substantially reducing [their alcohol intake], depending on what their goals are.”A further challenge is engaging patients' families and friends in the endeavor, Marc Galanter, M.D., a professor of psychiatry and director of the Division of Alcoholism and Drug Abuse at New York University, said in an interview. He and his colleagues have developed a technique called“ network therapy” to facilitate such engagement. A book and video program about the technique, both titled Network Therapy for Alcohol and Drug Abuse, are available from American Psychiatric Publishing Inc. (More information about the book and video can be accessed at<www.appi.org>).Still another barrier to a successful outcome, Galanter continued, is that“ there is a real gulf between alcoholism rehab centers and practitioners in the communities where patients live. Let's say that someone receives residential treatment for alcoholism at Hazelden in Minnesota and afterward returns to his home in North Dakota. The continuity of care after discharge may not be very good, prompting him to relapse.”Finally, a frequent stumbling block to the rehabilitation of alcoholic patients is that health insurance plans may not cover alcoholism treatment, Galanter reported. However, the mental health insurance parity law passed this fall should help, he believes.Even in countries with universal health care insurance, alcoholism treatment is not always covered by health insurance. For example, two German researchers who have created a successful long-term alcohol recovery program called OLITA have failed to get either Germany's universal health insurance program or private health insurance plans to underwrite it. In fact, private insurance plans were especially opposed to the idea, one of the researchers—Hannelore Ehrenreich, M.D., Ph.D., a psychiatrist with the Max Planck Institute of Experimental Medicine in Goettingen—said in an interview.“They will not cover any disease that they believe is a person's own fault, and in their opinion, alcoholism falls in that category. They are 30 years behind the times.” ▪ ISSUES NewArchived
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".