Explore the vast range of titles available.

Background: In the last decade, the clinician-patient relationship has become more of a partnership. There is growing interest in shared decision-making (SDM) in which the clinician and patient go through all phases of the decision-making process together, share treatment preferences, and reach an agreement on treatment choice. The purpose of this review is to determine the extent, quality, and consistency of the evidence about the effectiveness of SDM. Method: This is a systematic review of randomised controlled trials (RCTs) comparing SDM interventions with non-SDM interventions. Eleven RCTs met the required criteria, and were included in this review. Results: The methodological quality of the studies included in this review was high overall. Five RCTs showed no difference between SDM and control, one RCT showed no short-term effects but showed positive longer-term effects, and five RCTs reported a positive effect of SDM on outcome measures. The two studies included of people with mental healthcare problems reported a positive effect of SDM. Conclusions: Despite the considerable interest in applying SDM clinically, little research regarding its effectiveness has been done to date. It has been argued that SDM is particularly suitable for long-term decisions, especially in the context of a chronic illness, and when the intervention contains more than one session. Our results show that under such circumstances, SDM can be an effective method of reaching a treatment agreement. Evidence for the effectiveness of SDM in the context of other types of decisions, or in general, is still inconclusive. Future studies of SDM should probably focus on long-term decisions.

Background: In the last decades, shared decision-making (SDM) models have been developed to increase patient involvement in treatment decisions. The purpose of this study was to evaluate a SDM intervention (SDMI) for patients dependent on psychoactive substances in addiction health care programs. The intervention consisted of a structured procedure to reach a treatment agreement and comprised 5 sessions. Methods: Clinicians in 3 treatment centres in the Netherlands were randomly assigned to the SDMI or a standard procedure to reach a treatment agreement. Results: A total of 220 substance-dependent patients receiving inpatient treatment were randomised either to the intervention (n = 111) or control (n = 109) conditions. Reductions in primary substance use (F (1, 124) = 248.38, p < 0.01) and addiction severity (F (8) = 27.76, p < 0.01) were found in the total population. Significant change was found in the total population regarding patients’ quality of life measured at baseline, exit and follow-up (F (2, 146) = 5.66, p < 0.01). On the European Addiction Severity Index, SDMI showed significantly better improvements than standard decision-making regarding drug use (F (1, 164) = 7.40, p < 0.01) and psychiatric problems (F (1, 164) = 5.91, p = 0.02) at 3-month follow-up. Conclusion: SDMI showed a significant add-on effect on top of a well-established 3-month inpatient intervention. SDMI offers an effective, structured, frequent and well-balanced intervention to carry out and evaluate a treatment agreement.

Noncompliance in substance dependence treatment seriously threatens its effectiveness. Pretreatment identification of those at the highest risk allows targeting of specific compliance enhancing interventions to those who may benefit most from it. In a cohort of 292 patients entering a 30-day treatment program for substance abuse treatment, several potential predictors of noncompliance were recorded before treatment. Compliance was registered when treatment was discontinued before the 30th day. Logistic regression was used to identify independent predictors of noncompliance and the area under the receiver-operating characteristic (ROC) curve was quantified to assess their joint predictive value. Mean age was 35 years, 80% were male. During follow-up 31% became noncompliant. Independent predictors of noncompliance were male gender, less than 10 years of education, severity of medical and drug problems, and behavioral intention to comply with treatment. The area under the ROC curve was 0.70 (95% CI: 0.64–0.76). In conclusion, noncompliance in a substance abuse treatment program can be predicted using five easy to assess patient characteristics. These results may be useful in preventing noncompliant behavior early in treatment by motivational counseling strategies.

This paper focuses on exploring the association between the patient’s perception of his own interpersonal behaviour on the one hand, and that of the therapist’s behaviour and of helping alliance on the other hand. A cross-sectional study was conducted, including 83 patients from substance dependence programs in The Netherlands. They completed the Helping Alliance Questionnaire (HAQ) and the Interpersonal Check List (ICL). Results indicate that the patient’s perception of the therapeutic alliance, and his perception of his own and of the therapist’s interpersonal behaviour are three separate domains, each playing their role in the context of the therapeutic relationship. Helping Alliance scores are predicted by both the patient’s (complaisance) and the therapist’s interpersonal behaviour (dominance). We conclude that patient’s cognitions about himself and about his therapist do contribute significantly to the perception of the therapeutic relationship. Limitations to the study are discussed, as well as some clinical implications.