Objective Extensive research has focused on hyper‐palatable foods (HPF); however, HPF are defined using descriptive terms (e.g., fast foods, sweets), which are not standardized and lack specificity. The study purpose was to develop a quantitative definition of HPF and apply the definition to the Food and Nutrient Database for Dietary Studies (FNDDS) to determine HPF prevalence in the US food system. Methods A numeric definition of HPF was developed by extracting common HPF descriptive definitions from the literature and using nutrition software to quantify ingredients of fat, simple sugars, carbohydrates, and sodium. The definition was applied to the FNDDS. Results HPF from the literature aligned with three clusters: (1) fat and sodium (> 25% kcal from fat, ≥ 0.30% sodium by weight), (2) fat and simple sugars (> 20% kcal from fat, > 20% kcal from sugar), and (3) carbohydrates and sodium (> 40% kcal from carbohydrates, ≥ 0.20% sodium by weight). In the FNDDS, 62% (4,795/7,757) of foods met HPF criteria. The HPF criteria identified a variety of foods, including some labeled reduced or low fat and vegetables cooked in creams, sauces, or fats. Conclusions A data‐derived HPF definition revealed that a substantial percentage of foods in the US food system may be hyper‐palatable, including foods not previously conceptualized as hyper‐palatable.

A range of innovative computer-based interventions for psychiatric disorders have been developed, and are promising for drug use disorders, due to reduced cost and greater availability compared to traditional treatment. Electronic searches were conducted from 1966 to November 19, 2009 using MEDLINE, Psychlit, and EMBASE. 468 non-duplicate records were identified. Two reviewers classified abstracts for study inclusion, resulting in 12 studies of moderate quality. Eleven studies were pilot or full-scale trials compared to a control condition. Interventions showed high acceptability despite substantial variation in type and amount of treatment. Compared to treatment-as-usual, computer-based interventions led to less substance use as well as higher motivation to change, better retention, and greater knowledge of presented information. Computerbased interventions for drug use disorders have the potential to dramatically expand and alter the landscape of treatment. Evaluation of internet and phone-based delivery that allow for treatmenton-demand in patients' own environment is needed.Automated computer-based treatment is a promising vehicle for providing behaviorallybased interventions for drug use disorders. These systems offer a number of potential advantages, including low cost, greater accessibility and 24-hour availability, opportunity for more frequent and/or longer therapeutic contact, greater confidentiality, increased flexibility and convenience, and increased opportunities for practicing skills (Budman, 2000;Marks, Shaw, & Parkin, 1998;Nadelson, 1987). Such systems may even be preferred by some clients who dislike therapy or have concerns about confidentiality, and may be particularly useful in rural or remote settings, where access to psychotherapy for substance use disorders may be limited and accompanied by increased stigma (Connors, Tonnigan, & Miller, 2001;Hall & Huber, 2000). Automated computer-based systems also offer more consistent and precise delivery of interventions across patients. This standardization can be of value therapeutically and, from a scientific perspective, may permit a detailed examination of active components. The current systematic review evaluated computer-based interventions for drug use disorders. Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. , 2008). This may be due to differences in length of respective computer-based interventions since interventions in tobacco studies (e.g., 10-12 weeks) tend to be longer than those in alcohol studies (e.g., short assessment with personalized feedback). Moreover, within computer-based smok...

Purpose Obesity is prevalent in breast cancer survivors and is a significant risk factor for recurrence and mortality. Weight management interventions for survivors have been diverse in design (in-person vs. phone-based, group vs. individual) and yielded varying weight loss results. Given these issues, participants themselves may provide insight into treatment-based factors that contributed to their weight loss outcomes. Here we report qualitative results from interviews with survivors in a group phone-based weight loss intervention, with the objective of identifying mechanisms that facilitated or hindered adherence and weight loss. We explored interest in paying for continued treatment as an indicator of dissemination potential. Methods Individual interviews were conducted with 186 rural, obese breast cancer survivors upon completion of a six-month weight loss intervention that produced clinically meaningful weight loss (> 5%) in 91% of participants. A thematic analysis of the interview data was performed. Results Five themes were identified as impacting adherence and success: 1) accountability, 2) importance of the group, with varying levels of connectedness, 3) dietary convenience, 4) difficulty maintaining intervention components that required more effort, and 5) importance of internal motivation to attributions of physical activity success or failure. Most were interested in paying to continue the program if it were extended beyond the study. Conclusions Key intervention components that participants attributed to their success included supportive group processes and convenience. Results highlight the group phone-based approach as a potential venue for disseminating an effective weight loss program for breast cancer survivors.

Objective The study examined the effects of a group-phone based weight management intervention on change in physical activity as measured via accelerometer and self-report in rural breast cancer survivors. The study also evaluated the role of physical activity on clinically meaningful cut-points for weight loss (baseline to 6 months) and weight loss maintenance (6 to 18 months). Methods Participants were breast cancer survivors in a weight management intervention who provided valid weight and accelerometer data (N=142). We categorized participants into four groups based on weight loss ≥10% and weight regain ≥5% at 18 months. Results Accelerometer-measured moderate-to-vigorous physical activity (MVPA) significantly increased from baseline to 6 months (+46.9 minutes). MVPA declined during maintenance; however remained significantly greater than baseline. Self-reported MVPA followed a similar pattern as accelerometer MVPA, but estimates were significantly higher. Participants in the high loss, low regain group had significantly higher MVPA at all points. Conclusions A distance-based weight management intervention for survivors improved physical activity outcomes over 18 months. Self-reported physical activity was substantially higher than accelerometer-measured. Findings highlight the importance of device-based measurement for characterizing the magnitude of physical activity change, as well as the role of physical activity in weight management outcomes.

The current pilot study evaluated feasibility, acceptability, and initial efficacy of a therapeutic Interactive Voice Response (IVR) system (“The Recovery Line”) for patients receiving methadone maintenance who continue to use illicit drugs. Patients were randomized (N=36) to four weeks of Treatment-as-Usual (TAU) or Recovery Line plus TAU. Ratings of The Recovery Line were high and remained stable throughout the study. However, despite instructions and reminders, patients used substantially less than the recommended daily use (<10 days of 28). Patients were more likely to report abstinence for opioids and cocaine on days they used the Recovery Line (p = .01) than those they did not. Conditions did not differ significantly on patient satisfaction, urine screen outcomes, or coping efficacy. As with other computer-based treatments, findings suggest the Recovery Line is acceptable and feasible. However, additional methods to increase patient utilization of automated systems and larger clinical trials are needed.