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Much research focuses on producing maximal intervention effects. This has generally not resulted in interventions being rapidly or widely adopted or seen as feasible given resources, time, and expertise constraints in the majority of real-world settings. We present a definition and key characteristics of a minimum intervention needed to produce change (MINC). To illustrate use of a MINC condition, we describe a computer-assisted, interactive minimal intervention, titled Healthy Habits, used in three different controlled studies and its effects. This minimal intervention produced modest to sizable health behavior and psychosocial improvements, depending on the intensity of personal contacts, producing larger effects at longer-term assessments. MINC comparison conditions could help to advance both health care and health research, especially comparative effectiveness research. Policy and funding implications of requiring an intervention to be demonstrated more effective than a simpler, less costly MINC alternative are discussed.

Abstract Background Much has been written about how the medical home model can enhance patient-centeredness, care continuity, and follow-up, but few comprehensive aids or resources exist to help practices accomplish these aims. The complexity of primary care can overwhelm those concerned with quality improvement. Methods The RE-AIM planning and evaluation model was used to develop a multimedia, multiple-health behavior tool with psychosocial assessment and feedback features to facilitate and guide patient-centered communication, care, and follow-up related to prevention and self-management of the most common adult chronic illnesses seen in primary care. Results The Connection to Health Patient Self-Management System, a web-based patient assessment and support resource, was developed using the RE-AIM factors of reach (e.g., allowing input and output via choice of different modalities), effectiveness (e.g., using evidence-based intervention strategies), adoption (e.g., assistance in integrating the system into practice workflows and permitting customization of the website and feedback materials by practice teams), implementation (e.g., identifying and targeting actionable priority behavioral and psychosocial issues for patients and teams), and maintenance/sustainability (e.g., integration with current National Committee for Quality Assurance recommendations and clinical pathways of care). Connection to Health can work on a variety of input and output platforms, and assesses and provides feedback on multiple health behaviors and multiple chronic conditions frequently managed in adult primary care. As such, it should help to make patient-healthcare team encounters more informed and patient-centered. Formative research with clinicians indicated that the program addressed a number of practical concerns and they appreciated the flexibility and how the Connection to Health program could be customized to their office. Conclusions This primary care practice tool based on an implementation science model has the potential to guide patients to more healthful behaviors and improved self-management of chronic conditions, while fostering effective and efficient communication between patients and their healthcare team. RE-AIM and similar models can help clinicians and media developers create practical products more likely to be widely adopted, feasible in busy medical practices, and able to produce public health impact.

Tested the efficacy of a computer-assisted counseling intervention to reduce diet-related cancer risk. Healthy female HMO members were randomly assigned to nutrition counseling or attention-control interventions. Women completed dietary recalls and eating behavior questionnaires. Four-month follow-up results indicated that this moderate-intensity dietary intervention was effective in reducing fat consumption and increasing fruit and vegetable consumption. (SM)

Do distinct sources of social support have differential effects on health? Although previous research has contrasted family and friend support (naturalistic support), research on the relative effects of naturalistic support and constructed support (e.g., support groups) is extremely rare. Two studies of women with type 2 diabetes were conducted that assessed the independent effects of naturalistic and constructed support on physical activity and glycosylated hemoglobin (HbA1c). Participants were women diagnosed with type 2 diabetes from the intervention arms of two randomized controlled trials: primarily European American women (Study 1; N = 163) and exclusively Hispanic women (Study 2; N = 142). Measures assessed physical activity, HbA1c, and friend and family support at baseline and at 6 months, as well as group support after 6 months of intervention. In Study 1, only group support was related to increases in physical activity ([DELTA][R.sup.2] = .036). In Study 2, group support and family support showed independent effects on increases in physical activity ([DELTA][R.sup.2] = .047 and .060, respectively). Also, group support was related to decreases in HbA1c in Study 1 ([DELTA][R.sup.2] = .031) and Study 2 ([DELTA][R.sup.2] = .065). Overall, constructed (group) support was related to outcomes most consistently, but naturalistic (family) support showed some independent relation to physical activity improvement. Keywords Social support * Support groups * Type 2 diabetes * Physical activity * HbA1c, Introduction Social relationships are hypothesized to affect health through a variety of mechanisms. They may facilitate the practice of healthful lifestyle behaviors, and promote healthful cardiovascular, neuroendocrine, and immune system [...]

Two short frequency questionnaires, the NCI 19-item Fruit and Vegetable Screener (FVS) and a single question on overall fruit and vegetable consumption (1-item), were evaluated for their ability to assess change in fruit and vegetable (FV) consumption over time and in response to intervention among participants in 5 health promotion trials in the Behavior Change Consortium. Crosssectional differences and correlations of FV estimates at baseline and at follow-up were compared for the FVS (n = 315) and the 1-item (n = 227), relative to multiple 24-h recall interviews (24HR). The FVS significantly overestimated daily intake by 1.27 servings at baseline among men and by 1.42 and 1.59 servings at baseline and follow-up, respectively, in women, whereas the 1-item measure significantly underestimated intake at both time points in men (0.98 serving at baseline, 0.75 serving at follow-up) and women (0.61 and 0.41 serving). Cross-sectional deattenuated correlations with 24HR at follow-up were 0.48 (FVS) and 0.50 (1-item). To evaluate the capacity of the 2 screeners to assess FV change, we compared mean posttest effects with 24HR by treatment group overall and by gender. Treatment group differences were not significant for either 24HR or 1-item. Among 315 subjects, the FVS treatment group differences were significant both overall and within gender but not when repeated in the sample of 227. Findings suggest multiple 24H R at multiple time points in adequate sample sizes remain the gold standard for FV reports. Biases in FVS estimates may reflect participants' lifestyles and sociodemographic characteristics and require further examination in longitudinal samples representative of diverse populations.

The purpose of this article is to describe the baseline design elements and sample characteristics of the Behavior Change Consortium (BCC) Dietary Measurement studies for each of the 7 sites that comprised the BCC Nutrition Working Group (NWG). This article summarizes the project designs, including descriptions of diverse study populations, primary assessment methods, and study outcomes. Common measures used across sites included the National Cancer Institute (NCI) Fruit and Vegetable Screener, NCI Percentage Energy from Fat Screener, 24-h dietary recalls, and a single- or 2-item fruit and vegetable measure. Data on sociodemographic characteristics, body weight and height, smoking status, and serum carotenoids were also collected. Study design information such as assessment time points, as well as baseline sample characteristics, is also described. This paper provides the overall framework and descriptive information and serves as the reference for the BCC NWG special supplement.

Despite widespread use of dietary supplements, little is known about correlates and determinants of their use. Using a diverse sample from 7 interventions participating in the Behavior Change Consortium (n = 2539), signal detection methodology (SDM) demonstrated a method for identifying subgroups with varying supplement use. An SDM model was explored with an exploratory half of the entire sample (n = 1268) and used 5 variables to predict dietary supplement use: cigarette smoking, fruit and vegetable intake, dietary fat consumption, BMI, and stage of change for physical activity. A comparison of rates of supplement use between the exploratory model groups and comparably identified groups in the reserved, confirmatory sample (n = 1271) indicates that these analyses may be generalizable. Significant indicators of any supplement use included smoking status, percentage of energy from fat, and fruit and vegetable consumption. Although higher supplement use was associated with healthy behaviors overall, many of the identified groups exhibited mixed combinations of healthy and unhealthy behaviors. The results of this study suggest that patterns of dietary supplement use are complex and support the use of SDM to identify possible population characteristics for targeted and tailored health communication interventions.

Measurement of percentage energy from fat is important in surveillance of populations and in epidemiologic studies examining relationships between diet and disease as well as for behavioral intervention studies seeking to change dietary behavior. The NCI percentage energy from fat screener (PFat) has adequately predicted percentage of energy from fat compared with 24-h recalls (24HR) in cross-sectional analyses. However, the instrument has not been evaluated for its ability to assess change of percentage energy from fat over time or in response to interventions to change dietary intake of fat. The objective of this analysis is to evaluate the performance of the PFat in assessing change in percentage energy intake from fat in a behavioral intervention setting. Four individual sites participating in the Behavior Change Consortium Nutrition Working Group administered both the PF at and multiple 24HR at baseline and follow-up to 278 participants. A measurement error model was used to assess agreement between the PFat and 24HR at baseline and follow-up. The PFat was consistent with 24HR in finding there was no significant change in percentage energy from fat as a result of the intervention. Both male and female participants in the intervention group demonstrated a significant increase in the correlation between PFat and 24HR from baseline to follow-up. Percentage energy from fat measured by PFat may be useful to provide estimates of change in mean intake of populations over time in longitudinal studies. Further methodologic research is called for in interventions producing significant changes and in diverse populations with adequate sample size.

The need for an inexpensive measure of dietary intake in intervention studies led to evaluation of the National Cancer Institute (NCI) Percentage Energy from Fat short instrument (PFat) in a subgroup of the Behavioral Change Consortium (BCC) intervention sites. The PFat's performance was evaluated using multiple nonconsecutive 24-h dietary recalls (24HR) as a reference instrument among participants at baseline in 4 demographically diverse intervention sites of the BCC. Mean estimates of percentage energy from fat for 24HR and PFat were within 2.1 percentage points of each other in all but 2 site/gender comparisons. 24HR and PFat estimates were not significantly different (P< 0.05) among men for 2 of 3 sites, and among women for 2 of 4 sites. Deattenuated Pearson correlation coefficients for the PFat and true intake (as estimated from the 24HR using a measurement error model) were significantly different from 0 (P < 0.05) for men and women in all sites, ranging from 0.52 to 0.77 among men and 0.36 to 0.59 among women. Besides gender and site, no other factors examined (age, education, smoking status, and BMI) consistently moderated validity estimates. If accurate assessment of diet at baseline (and presumably at follow-up) is essential, a more detailed instrument such as multiple 24HR may be warranted. The question of whether the PFat adequately measures change in diet is addressed in another article in this supplement.

Five sites participating in the NCI Behavior Change Consortium administered the NCI Fruit and Vegetable Screener (FVS) and multiple, nonconsecutive 24-h dietary recall interviews (24HR) to 590 participants. Three sites also obtained serum carotenoids (n = 295). Participants were primarily female, ethnically diverse, and varied by age and education. Correlations between 24HR and FVS by site ranged from 0.31 (P= 0.07) to 0.47 (P< 0.01) in men and from 0.43 to 0.63 (P< 0.01) in women. Compared with 24HR, FVS significantly (P< 0.05) overestimated intake at 2 of 4 sites for men and all 4 sites for women. Differences in estimated total servings of fruits and vegetables/d ranged from 0. 16 to 3.06 servings. On average, the FVS overestimated intake by 1.76 servings in men and 2.11 servings in women. Alternative FVS scoring procedures and a 1-item screener lowered correlations with 24HR as well as serum carotenoids but alternate scoring procedures generally improved estimations of servings.

The Food Habits Questionnaire (FHQ) is an effective method for the determination of the dietary behavior in worksites and medical office settings. The FHQ method is economical, gives reliable results, and is more responsive to intervention effects than the other methods. The easy to score FHQ method is related to the body mass index and glycosylated haemoglobin level. The FHQ method determines the behaviors that increase dietary-fat intake.

Abstract Background Pedometers offer researchers a convenient and inexpensive tool for objective measurement of physical activity. However, many unanswered questions remain about expected values for steps/day for different populations, sources of variation in the data, and reliability of pedometer measurements. Methods This study documented and compared mean steps/day, demographic predictors of steps/day, and pedometer reliability in two longitudinal investigations, one involving a population-based youth sample (N = 367) and the other targeting postmenopausal women with type 2 diabetes (N = 270). Individuals were asked to wear pedometers (Yamax model SW-701) at the waist for 7 days and record steps/per day. They were also asked to record daily physical activities, duration, and perceived intensity (1 = low/light, 2 = medium/moderate, 3 = high/hard) for the same 7 days. In addition, survey data regarding usual physical activity was collected. Analyses of variance (ANOVA) were conducted to determine whether there were significant differences in pedometer results according to sex, age, and body mass index. Repeated measures ANOVAs were used to examine potential differences in results among differing numbers of days. Results Mean steps/day were 10,365 steps in the youth sample and 4,352 steps in the sample of older women. Girls took significantly fewer steps than boys, older women took fewer steps than younger women, and both youth and women with greater body mass took fewer steps than those with lower body mass. Reliability coefficients of .80 or greater were obtained with 5 or more days of data collection in the youth sample and 2 or more days in the sample of older women. Youth and older women were more active on weekdays than on weekends. Low but significant associations were found between step counts and self-report measures of physical activity in both samples. Conclusion Mean steps/day and reliability estimates in the two samples were generally consistent with previously published studies of pedometer use. Based on these two studies, unsealed pedometers were found to offer an easy-to-use and cost-effective objective measure of physical activity in both youth and older adult populations.

Abstract Background Multiple-risk-factor interventions offer a promising means for addressing the complex interactions between lifestyle behaviors, psychosocial factors, and the social environment. This report examines the long-term effects of a multiple-risk-factor intervention. Methods Postmenopausal women (N = 279) with type 2 diabetes participated in the Mediterranean Lifestyle Program (MLP), a randomized, comprehensive lifestyle intervention study. The intervention targeted healthful eating, physical activity, stress management, smoking cessation, and social support. Outcomes included lifestyle behaviors (i.e., dietary intake, physical activity, stress management, smoking cessation), psychosocial variables (e.g., social support, problem solving, self-efficacy, depression, quality of life), and cost analyses at baseline, and 6, 12, and 24 months. Results MLP participants showed significant 12- and 24-month improvements in all targeted lifestyle behaviors with one exception (there were too few smokers to analyze tobacco use effects), and in psychosocial measures of use of supportive resources, problem solving, self-efficacy, and quality of life. Conclusion The MLP was more effective than usual care over 24 months in producing improvements on behavioral and psychosocial outcomes. Directions for future research include replication with other populations.