AIMS: To compare representative treatment and untreated samples of alcohol-dependent individuals in rates of abstinence and non-problematic use at 1-year follow-up. PARTICIPANTS AND DESIGN: A total of 482 alcohol-dependent adults in a northern California county identified through a probability survey of problem drinkers in the general population (n = 111) or a survey of consecutive admissions to public and private substance abuse programs (n = 371) were interviewed in person at baseline and by telephone at 1 year. MEASUREMENTS: Logistic regression models were used to predict 30-day abstinence and 12-month non-problematic alcohol use. RESULTS: At follow-up, alcohol-dependent individuals in the treatment sample had higher abstinence rates and non-problematic use outcomes than those in the untreated general population sample. In logistic regression models of the merged samples, being in the treatment sample was related strongly and positively to abstinence and non-problematic use. Having more drug users and heavy drinkers in one's social network, higher psychiatric comorbidity, and more social consequences were inversely related to abstinence and non-problematic use in the treatment sample. The number of drug users and heavy drinkers in one's social network was also inversely related to abstinence in both the treatment and untreated general population samples. Results predicting non-problematic use were similar. CONCLUSIONS: These results are consistent with other studies that examine treatment effectiveness in the absence of a controlled trial. Although natural recovery also occurs, alcohol-dependent individuals benefit from treatment. Co-occurring psychiatric problems continue to be major barriers to treatment effectiveness. An emphasis on changing social networks to be conducive to recovery could heighten both clinical effectiveness and prevention efforts within communities.
AIMS: To compare representative treatment and untreated samples of alcohol-dependent individuals in rates of abstinence and non-problematic use at 1-year follow-up. PARTICIPANTS AND DESIGN: A total of 482 alcohol-dependent adults in a northern California county identified through a probability survey of problem drinkers in the general population (n = 111) or a survey of consecutive admissions to public and private substance abuse programs (n = 371) were interviewed in person at baseline and by telephone at 1 year. MEASUREMENTS: Logistic regression models were used to predict 30-day abstinence and 12-month non-problematic alcohol use. RESULTS: At follow-up, alcohol-dependent individuals in the treatment sample had higher abstinence rates and non-problematic use outcomes than those in the untreated general population sample. In logistic regression models of the merged samples, being in the treatment sample was related strongly and positively to abstinence and non-problematic use. Having more drug users and heavy drinkers in one's social network, higher psychiatric comorbidity, and more social consequences were inversely related to abstinence and non-problematic use in the treatment sample. The number of drug users and heavy drinkers in one's social network was also inversely related to abstinence in both the treatment and untreated general population samples. Results predicting non-problematic use were similar. CONCLUSIONS: These results are consistent with other studies that examine treatment effectiveness in the absence of a controlled trial. Although natural recovery also occurs, alcohol-dependent individuals benefit from treatment. Co-occurring psychiatric problems continue to be major barriers to treatment effectiveness. An emphasis on changing social networks to be conducive to recovery could heighten both clinical effectiveness and prevention efforts within communities.
Authors: Emily C Williams; Anna D Rubinsky; Laura J Chavez; Gwen T Lapham; Stacey E Rittmueller; Carol E Achtmeyer; Katharine A Bradley Journal: Addiction Date: 2014-06-12 Impact factor: 6.526
Authors: Anita Palepu; Michelle Patterson; Verena Strehlau; Akm Moniruzzamen; Jason Tan de Bibiana; James Frankish; Michael Krausz; Julian Somers Journal: J Urban Health Date: 2013-08 Impact factor: 3.671