Occasionally, this column does not undertake a singular research to practice theme but, rather, presents a number of different useful research ideas for practitioners. This column will cover three dissimilar research studies.

Item #1: Pregnant Women and the Risk for Early Attrition

There is more recent evidence suggesting that if you ignore certain variables in female clients you risk that a percentage will drop out of your program. For example, Kissen, et al (2004), noted of 29 women who left a seven-day residential treatment program for pregnant women, the main reasons centered on:

• Drug craving
• Withdrawal
• Not receiving methadone maintenance
• Reporting more prior drug treatment programs

Using this research in your practice

The treatment implications for programs that serve pregnant women with substance abuse problems are to first identify these trends in this population. If there are any that resemble the ones mentioned above, it should raise a red flag. You need to give such cases special attention and focus. For example, train your staff to recognize heroin withdrawal. Then have a ready made plan on hand so if a client begins to demonstrate withdrawal symptoms, you can act fast to get this individual the appropriate medical care. The same approach (training and action plan) might easily apply to feelings of amplified cravings.

One more treatment example based on this data would be to assess the number of prior treatment experiences of the client. Determine what did not work from these facilities (just ask the client in a straightforward manner). Once you figure out what didn’t work in the past, do not repeat those interventions in your program.

Try it: Do your own research

If you have an inpatient program that treats pregnant women, you may want to conduct a little experiment. First, determine your current drop out rate. Simply review your past records, and list the number of clients who left early (establish a baseline). Second, train a team or your whole staff to recognize the drop-out symptoms noted above; or even identify your own drop-out variables. Third, conduct additional training for your team or whole staff on different treatment methods that could be used to address these drop-out factors. Finally, compare your original baseline drop-out rate to the post training drop-out rate.

Item # 2: Connections Between Cocaine Abuse, Thinking and Decision-making

Practitioners have long suspected that individuals who abuse drugs may lose an edge in their thinking. More evidence has been found to support that notion. For example, a recent piece of research has noted that chronic cocaine abuse is directly related to dysfunction in the brain that is associated with higher thought and decision-making (Hester & Garavan, 2004). Basically, the research publication notes that cocaine abuse can damage the dopamine system. And, it just so happens that there is a concentration of dopamine located in the higher order decision-making parts of the brain. So, the researchers hypothesized that the cocaine-dependent individuals studied in this report would have a more difficult time inhibiting their actions, particularly when they needed the executive (decision) function of their brain. The study showed that these individuals did have such problems.

Using this research in your practice

When you are working with a population, such as the one in this research, the big treatment implication is to adjust your treatment from those interventions that require higher thought and decision-making to those that use more reinforcement and support. Essentially, you may want to stay away from therapies that require the cocaine-dependent individuals to make a lot of decisions early in their recovery. Since the decision-making functions may be damaged, a more appropriate set of methods might involve cognitive-behavioral reinforcement approaches. But, make sure the reinforcement you use is important to the client and, as an added measure, try to use supportive types of interventions. The support will assist in improving the trust and alliance between you and the client.

One last thought on using interventions with this population — you may need to repeat a set of strategies a number of times before a new behavior sticks. Bear in mind, the research indicates that cocaine-dependent individuals may not have a good memory.

Try it: Do your own research

The suggested research design in this case is similar to the pregnant female approach. First, establish a response-to-treatment (or something similar) baseline from your past records. For instance, you may note at what rate your treatment plan objectives are being met. Then, institute a training process by which a team or your entire staff shifts to more reinforcement and supportive treatment strategies. After the initial training and the implementation of the different strategies, compare the completion of treatment plan objectives from the pre-training phase to the post-training implementation phase.

Item # 3: Genetic Differences in Opiate Receptor Genes Affects the Response to Alcohol

Very recent data suggests that a certain gene (G allele of the OPRMI) has greater subjective feelings toward alcohol (Ray & Hutchison, 2004). This means that people with this particular gene react differently to alcohol than so-called normals. That is, the G-allele individuals have increased feelings of intoxication, stimulation, sedation, and happiness when they drink. In addition, these same individuals have a greater likelihood — three times more likely — of having a family history of alcohol-use disorders. The finding further supports the growing notion that some alcoholics are genetically different from the so-called normals. This has two important treatment implications.

Using this research in your practice

The first treatment implication is trying to identify these people. However, testing your clients for the G allele in most facilities is going to be difficult. Unless you are affiliated with a university medical center, you are most likely not equipped for genetic testing. But, recall that the research indicates that this allele is found three times more often in families with alcohol problems. So, if you ask your client and his/her family members if alcohol disorders run in the family, and you get a positive response, you may assume this G allele has a good probability of being present in your client.

Armed with that information, a significant treatment implication is the use of naltrexone, a drug used to reduce the feelings of euphoria associated with alcohol. In cases such as these, naltrexone can be used in addition to your other treatment interventions.

The second treatment possibility involves reducing the stigma associated with alcohol abuse. Stigma is certainly still around, and its sting often impacts a client’s sense of guilt and shame. As most clinicians know, these feelings, if suf-ficiently strong, can take the wind out of a good recovery process. However, upon being told they could harbor the G allele, a client who has a strong family alcohol abuse history may experience negative stigma feelings which could prove detrimental to the client’s motivation level.

Try it: Do your own research

An interesting piece of research you could conduct related to the stigma issue might run something like this: if clients, who match the family profile noted in the gene research, come to your facility and have some level of stigma attached to themselves, you could conceivably assess their level of motivation in a pre-test, post-test survey. All you would need to do is create a few questions, such as, “My level of motivation is ...” or “My present stigma level is ...” and place a 5- or 7-point likert scale after such statements. Then, tell the client about the G allele. Let them know they may be predisposed to abuse and, therefore, are more likely to have a disease, not a moral failing. Take the stigma measures before (pre) and after (post) you talk with a client and compare the results.

As always, these research suggestions are not meant to be rigorous. So, while they may not be publishable, they could still be useful clinically. And, I remain interested in your results.

References
Hester, R. & Garavan, H. (2004). The Journal of Neuroscience 24(49), 11017-11022

Kissen, W.B., Svikis, D.S., Moylan, P., Haug, N.A. & Stitzer, M.L. (2004). Identifying pregnant women at risk for early attrition from substance abuse treatment. Journal of Substance Abuse Treatment, 27, 1, 31-38.

Ray, L.A. & Hutchison, K.E. (December 2004). A polymorphism of the [mu]-opioid receptor gene (OPRMI) and the sensitivity to the effects of alcohol in humans. Alcoholism: Clinical and Experimental Research, 28(12), 1789-1795.

Mike Taleff, PhD, CSAC, MAC is an instructor at the University of Hawaii Manoa and West Oahu campuses. He can be contacted at This e-mail address is being protected from spam bots, you need JavaScript enabled to view it

This article is published in Counselor,The Magazine for Addiction Professionals, June 2005, v.6, n.3, pp.38-40.

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