Air Force Web Preventive Health Assessment (AF WEBPHA) mental health screening effectiveness

The U.S. Air Force assesses Active Duty Air Force (ADAF) health annually using the Air Force Web-based Preventative Health Assessment (AF WebPHA). The assessment is based on a self-administered survey used to determine the overall Air Force health and readiness, as well as, the individual health of each airman. Individual survey responses as well as groups of responses generate further computer generated assessment and result in a classification of 'Critical', 'Priority', or 'Routine', depending on the need and urgency for further evaluation by a health care provider. The importance of the 'Priority' and 'Critical' classifications is to provide timely intervention to prevent or limit unfavorable outcomes that may threaten an airman. Though the USAF has been transitioning from a paper form to the online WebPHA survey for the last three years it was not made mandatory for all airmen until 2009. The survey covers many health aspects including family history, tobacco use, exercise, alcohol use, and mental health. ^ Military stressors such as deployment, change of station, and the trauma of war can aggravate and intensify the common baseline worries experienced by the general population and place airmen at additional risks for mental health concerns and illness. This study assesses the effectiveness of the AF WebPHA mental health screening questions in predicting a mental health disorder diagnosis according to International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) codes generated by physicians or their surrogates. In order to assess the sensitivity, specificity, and positive predictive value of the AF WebPHA as a screening tool for mental health, survey results were compared to ascertain if they generated any mental health disorder related diagnosis for the period from January 1, 2009 to March 31, 2010. ^ Statistical analysis of the AF WebPHA mental health responses when compared with matching ICD-9-CM codes found that the sensitivity for 'Critical' or 'Priority' responses was only 3.4% and that it would correctly predict those who had the selected mental health diagnosis 9% of the time.^

Interrelationships between the structural and functional aspects of social relationships, comorbidity and health related quality of life in breast cancer survivors

It is widely acknowledged in theoretical and empirical literature that social relationships, comprising of structural measures (social networks) and functional measures (perceived social support) have an undeniable effect on health outcomes. However, the actual mechanism of this effect has yet to be clearly understood or explicated. In addition, comorbidity is found to adversely affect social relationships and health related quality of life (a valued outcome measure in cancer patients and survivors). ^ This cross sectional study uses selected baseline data (N=3088) from the Women's Healthy Eating and Living (WHEL) study. Lisrel 8.72 was used for the latent variable structural equation modeling. Due to the ordinal nature of the data, Weighted Least Squares (WLS) method of estimation using Asymptotic Distribution Free covariance matrices was chosen for this analysis. The primary exogenous predictor variables are Social Networks and Comorbidity; Perceived Social Support is the endogenous predictor variable. Three dimensions of HRQoL, physical, mental and satisfaction with current quality of life were the outcome variables. ^ This study hypothesizes and tests the mechanism and pathways between comorbidity, social relationships and HRQoL using latent variable structural equation modeling. After testing the measurement models of social networks and perceived social support, a structural model hypothesizing associations between the latent exogenous and endogenous variables was tested. The results of the study after listwise deletion (N=2131) mostly confirmed the hypothesized relationships (TLI, CFI >0.95, RMSEA = 0.05, p=0.15). Comorbidity was adversely associated with all three HRQoL outcomes. Strong ties were negatively associated with perceived social support; social network had a strong positive association with perceived social support, which served as a mediator between social networks and HRQoL. Mental health quality of life was the most adversely affected by the predictor variables. ^ This study is a preliminary look at the integration of structural and functional measures of social relationships, comorbidity and three HRQoL indicators using LVSEM. Developing stronger social networks and forming supportive relationships is beneficial for health outcomes such as HRQoL of cancer survivors. Thus, the medical community treating cancer survivors as well as the survivor's social networks need to be informed and cognizant of these possible relationships. ^

A formative evaluation of the American Diabetes Association's Choosing Health and Sensible Exercise childhood obesity intervention

Background. The increasing prevalence of overweight among youth in the United States, and the parallel rise in related medical comorbidities has led to a growing need for efficient weight-management interventions. Purpose. The aim of this study was to evaluate the effects of the Choosing Health and Sensible Exercise (C.H.A.S.E.) childhood obesity prevention program on Body Mass Index (BMI), physical activity and dietary behaviors. Methods. This study utilized de-identified data collected during the fall 2006 session of the C.H.A.S.E. program. A total of 65 students at Woodview Elementary School and Deepwater Elementary School participated in this intervention. The C.H.A.S.E. program is a 10-week obesity prevention program that focuses on nutrition and physical activity education. Collection of height and weight data, and a health behavior survey was conducted during the first and last week of the intervention. Paired t-tests were used to determine statistically significant differences between pre- and post-intervention measurements. One-way analysis of variance was used to adjust for potential confounders, such as gender, age, BMI category ("normal weight", "at risk overweight", or "overweight"), and self-reported weight loss goals. Data were analyzed using STATA, v. 9.2. Results. A significant decrease in mean BMI (p< 0.05) was found after the 10-week intervention. While the results were statistically significant for the group as a whole, changes in BMI were not significant when stratified by age, sex, or ethnicity. The mean overall scores for the behavior survey did not change significantly pre- and post-intervention; however, significant differences were found in the dietary intention scale, indicating that students were more likely to intend to make healthier food choices (p<0.05). No statistically significant decreases in BMI were found when stratified for baseline BMI-for-age percentiles or baseline weight loss efforts (p>0.05). Conclusion. The results of this evaluation provide information that will be useful in planning and implementing an effective childhood obesity intervention in the future. Changes in the self-reported dietary intentions and BMI show that the C.H.A.S.E. program is capable of modifying food choice selection and decreasing BMI. Results from the behavior questionnaire indicate that students in the intervention program were making changes in a positive direction. Future implementation of the C.H.A.S.E. program, as well as other childhood obesity interventions, may want to consider incorporating additional strategies to increase knowledge and other behavioral constructs associated with decreased BMI. In addition, obesity prevention programs may want to increase parental involvement and increase the dose or intensity of the intervention. ^

A path analysis of an after-school health and exercise program for elementary school children in El Paso, Texas

As schools are pressured to perform on academics and standardized examinations, schools are reluctant to dedicate increased time to physical activity. After-school exercise and health programs may provide an opportunity to engage in more physical activity without taking time away from coursework during the day. The current study is a secondary data analysis of data from a randomized trial of a 10-week after-school program (six schools, n = 903) that implemented an exercise component based on the CATCH physical activity component and health modules based on the culturally-tailored Bienestar health education program. Outcome variables included BMI and aerobic capacity, health knowledge and healthy food intentions as assessed through path analysis techniques. Both the baseline model (χ2 (df = 8) = 16.90, p = .031; RMSEA = .035 (90% CI of .010–.058), NNFI = 0.983 and the CFI = 0.995) and the model incorporating intervention participation proved to be a good fit to the data (χ2 (df = 10) = 11.59, p = .314. RMSEA = .013 (90% CI of .010–.039); NNFI = 0.996 and CFI = 0.999). Experimental group participation was not predictive of changes in health knowledge, intentions to eat healthy foods or changes in Body Mass Index, but it was associated with increased aerobic capacity, β = .067, p < .05. School characteristics including SES and Language proficiency proved to be significantly associated with changes in knowledge and physical indicators. Further effects of school level variables on intervention outcomes are recommended so that tailored interventions can be developed aimed at the specific characteristics of each participating school. ^