Interactive computer-based interventions for weight loss or weight maintenance in overweight or obese people

BACKGROUND: The World Health Organization (WHO) estimates that the number of obese or overweight individuals worldwide will increase to 1.5 billion by 2015. Chronic diseases associated with overweight or obesity include diabetes, heart disease, hypertension and stroke. OBJECTIVES: To assess the effects of interactive computer-based interventions for weight loss or weight maintenance in overweight or obese people. SEARCH METHODS: We searched several electronic databases, including CENTRAL, MEDLINE, EMBASE, CINAHL, LILACS and PsycINFO, through 25 May 2011. We also searched clinical trials registries to identify studies. We scanned reference lists of included studies and relevant systematic reviews. SELECTION CRITERIA: Studies were included if they were randomized controlled trials or quasi-randomized controlled trials that evaluated interactive computer-based weight loss or weight maintenance programs in adults with overweight or obesity. We excluded trials if the duration of the intervention was less than four weeks or the loss to follow-up was greater than 20% overall. DATA COLLECTION AND ANALYSIS: Two authors independently extracted study data and assessed risk of bias. Where interventions, control conditions, outcomes and time frames were similar between studies, we combined study data using meta-analysis. MAIN RESULTS: We included 14 weight loss studies with a total of 2537 participants, and four weight maintenance studies with a total of 1603 participants. Treatment duration was between four weeks and 30 months. At six months, computer-based interventions led to greater weight loss than minimal interventions (mean difference (MD) -1.5 kg; 95% confidence interval (CI) -2.1 to -0.9; two trials) but less weight loss than in-person treatment (MD 2.1 kg; 95% CI 0.8 to 3.4; one trial). At six months, computer-based interventions were superior to a minimal control intervention in limiting weight regain (MD -0.7 kg; 95% CI -1.2 to -0.2; two trials), but not superior to infrequent in-person treatment (MD 0.5 kg; 95% -0.5 to 1.6; two trials). We did not observe consistent differences in dietary or physical activity behaviors between intervention and control groups in either weight loss or weight maintenance trials. Three weight loss studies estimated the costs of computer-based interventions compared to usual care, however two of the studies were 11 and 28 years old, and recent advances in technology render these estimates unlikely to be applicable to current or future interventions, while the third study was conducted in active duty military personnel, and it is unclear whether the costs are relevant to other settings. One weight loss study reported the cost-effectiveness ratio for a weekly in-person weight loss intervention relative to a computer-based intervention as USD 7177 (EUR 5678) per life year gained (80% CI USD 3055 to USD 60,291 (EUR 2417 to EUR 47,702)). It is unclear whether this could be extrapolated to other studies. No data were identified on adverse events, morbidity, complications or health-related quality of life. AUTHORS' CONCLUSIONS: Compared to no intervention or minimal interventions (pamphlets, usual care), interactive computer-based interventions are an effective intervention for weight loss and weight maintenance. Compared to in-person interventions, interactive computer-based interventions result in smaller weight losses and lower levels of weight maintenance. The amount of additional weight loss, however, is relatively small and of brief duration, making the clinical significance of these differences unclear

Motivation to quit using substances among individuals with schizophrenia: implications for a motivation-based treatment model

Although the motivation to quit using substances is an important prognostic and treatment-matching factor in substance abuse treatment, there is limited information on motivation to quit among individuals with schizophrenia. This study used the five-stages-of-change model to evaluate the motivational levels of 497 individuals with schizophrenia or schizoaffective disorder in an outpatient mental health clinic. Rates of substance abuse, motivation levels to quit each specific substance, and correlates to motivational levels were evaluated. At least one substance use disorder was diagnosed in 224 of the subjects (45%); however, there was significant variability among the caseloads of the outpatient division teams. The patients in the triage/acute services and community outreach teams had substance abuse rates of about 70 percent. Most subjects had low motivation to quit substances, and the rates varied according to substance (range of 41% for opiates to 60% for cocaine). Treatment-matching strategies are suggested in the motivation-based treatment model

A primer on current evidence-based review systems and their implications for behavioral medicine

BACKGROUND: Multiple review systems have been established within medicine and psychology to evaluate and disseminate research findings to clinical practice. PURPOSE: Within this article, five evidence-based review systems are reviewed to inform the development or the use of an evidence review system for the behavioral medicine field. METHODS: Each review system is described on several dimensions: history of the review system, the review process, and details about translation/sustainability efforts. RESULTS: Various factors from each system have been identified that would benefit a behavioral medicine evidence review system, such as a discussion of clinical features that influence the generalizability of review findings (i.e., the American Psychiatric Association) and the use of pre-review protocols (i.e., the Cochrane Collaboration). CONCLUSIONS: Although each review system has limitations, it is important for behavioral medicine to join one system because (a) systematic reviews are the only feasible means to evaluate and judge the usefulness of our interventions, and (b) reviews can inform policy, and, with effort, influence patient well-being. This group of behavioral medicine experts recommends that the Cochrane Collaboration review behavioral medicine interventions

Chat: Development and Validation Of A Computer-Delivered, Self-Report, Substance Use Assessment for Adolescents.

The current study was conducted to construct and validate a computer-delivered, multimedia, substance use self-assessment for adolescents. Reliability and validity of six problem dimensions were evaluated in two studies, conducted from 2003 to 2008. Study 1 included 192 adolescents from five treatment settings throughout the United States (N = 142) and two high schools from Greater Boston, Massachusetts (N = 50). Study 2 included 356 adolescents (treatment: N = 260; school: N = 94). The final version of Comprehensive Health Assessment for Teens (CHAT) demonstrated relatively strong psychometric properties. The limitations and implications of this study are noted

Invitation to a dialogue between researchers and clinicians about evidence-based behavioral medicine

BACKGROUND: Evidence-based behavioral medicine (EBBM) aims to improve the process through which best scientific research evidence can be obtained and translated into best clinical decisions regarding behavioral treatments to improve health. PURPOSE: The objective was to examine some legitimate concerns raised by both clinicians and researchers about the evidence-based movement. METHODS: This article begins with a discussion of clinicians\u27 fears that EBBM devalues clinical judgment and the therapist-patient relationship, will be used to restrict practice, is unnecessary, and is based on research that is irrelevant to clinical decision making. Next we consider researchers\u27 worries that EBBM neglects evidence not based on randomized controlled trials and ignores causal mechanisms. RESULTS: We find that these fears, although understandable, largely reflect misinterpretations of the evidence-based movement. Further, it is suggested that behavioral medicine is in a unique position to enhance the evidence-based movement by encouraging increased attention to treatment mechanisms and to knowledge translation. CONCLUSIONS: Clinicians, researchers, and, importantly, the public will benefit from the evidence-based movement by having a health care system that is built on solid grounds of evidence in determining which treatments should constitute the standard of care. A full partnership between clinicians and researchers is called for to generate the practical, rigorous evidence base needed to take behavioral health treatments to the next level of scientific support and implementation