106 research outputs found

    Fatalism, Diabetes Management Outcomes, and the Role of Religiosity

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    This study aimed to determine whether fatalistic beliefs were associated with elevated levels of glycated hemoglobin (HbA1c) and to establish the role of religiosity in this relationship. A cross-sectional survey was conducted on a sample of 183 Jewish adults with diabetes visiting a large medical center in northern Israel. Self-administered questionnaires assessed level of religiosity, fatalistic beliefs, diabetes management behaviors, and demographic/personal characteristics; laboratory tests were used to measure HbA1c. Multivariate regression indicated that fatalism was significantly associated with HbA1c (β = 0.51, p = 0.01). The association was no longer statistically significant after including self-reported religiosity in the model (β = 0.31, p = 0.13). This phenomenon is likely due to a confounding relationship between the religious/spiritual coping component of the fatalism index and self-reported religiosity (r = 0.69). The results indicate that addressing fatalistic attitudes may be a viable strategy for improving diabetes management, but call for a better understanding of the interplay between religiosity and fatalism in this context

    Identifying the substance abuse treatment needs of caregivers involved with child welfare

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    Parental substance use significantly increases risk of child maltreatment, but is often under-identified by child protective services. This study examined how agency use of standardized substance use assessments and child welfare investigative caseworker education, experience, and caseload affected caseworkers’ identification of parental substance abuse treatment needs. Data are from a national probability sample of permanent, primary caregivers involved with child protective services whose children initially remained at home and whose confidential responses on two validated instruments indicated harmful substance use or dependence. Investigative caseworkers reported use of a formal assessment in over two thirds of cases in which substance use was accurately identified. However, weighted logistic regression indicated that agency provision of standardized assessment instruments was not associated with caseworker identification of caregiver needs. Caseworkers were also less likely to identify substance abuse when their caseloads were high and when caregivers were fathers. Implications for agency practice are discussed

    Computational Model for Behavior Shaping as an Adaptive Health Intervention Strategy

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    Adaptive behavioral interventions that automatically adjust in real-time to participants’ changing behavior, environmental contexts, and individual history are becoming more feasible as the use of real-time sensing technology expands. This development is expected to improve shortcomings associated with traditional behavioral interventions, such as the reliance on imprecise intervention procedures and limited/short-lived effects. JITAI adaptation strategies often lack a theoretical foundation. Increasing the theoretical fidelity of a trial has been shown to increase effectiveness. This research explores the use of shaping, a well-known process from behavioral theory for engendering or maintaining a target behavior, as a JITAI adaptation strategy. A computational model of behavior dynamics and operant conditioning was modified to incorporate the construct of behavior shaping by adding the ability to vary, over time, the range of behaviors that were reinforced when emitted. Digital experiments were performed with this updated model for a range of parameters in order to identify the behavior shaping features that optimally generated target behavior. Narrowing the range of reinforced behaviors continuously in time led to better outcomes compared with a discrete narrowing of the reinforcement window. Rapid narrowing followed by more moderate decreases in window size was more effective in generating target behavior than the inverse scenario. The computational shaping model represents an effective tool for investigating JITAI adaptation strategies. Model parameters must now be translated from the digital domain to real-world experiments so that model findings can be validated

    Contrasting compositions of sitting, standing, stepping, and sleeping time: associations with glycaemic outcome by diabetes risk

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    BACKGROUND: Recent evidence suggests that prolonged sitting and its adverse impact on glycaemic indicators appear to be proportional to the degree of insulin resistance. To investigate this finding in a free-living context, we aimed to examine associations of device-measured 24-h time-use compositions of sitting, standing, stepping, and sleeping with fasting glucose (FPG) and 2 h post-load glucose (2hPLG) levels, and to examine separately the associations with time-use compositions among those at lower and at higher risk of developing type 2 diabetes. METHODS: Cross-sectional analyses examined thigh-worn inclinometer data (activPAL, 7 day, 24 h/day protocol) from 648 participants (aged 36-80 years) at either lower (< 39 mmol/mol; < 5.7% HbA1c) or higher (≥39 mmol/mol; ≥5.7% HbA1c) diabetes risk from the 2011-2012 Australian Diabetes, Obesity and Lifestyle study. Multiple linear regression models were used to examine associations of differing compositions with FPG and 2hPLG, with time spent in each behaviour allowed to vary up to 60 min. RESULTS: In general, the associations with the FPG within the time-use compositions were small, with statistically significant associations observed for sitting and sleeping (in the lower diabetes risk group) and standing (in higher diabetes risk group) only. For 2hPLG, statistically significant associations were observed for stepping only, with findings similar between lower (β = - 0.12 95%CI:-0.22, - 0.02) and higher (β = - 0.13 95%CI:-0.26, - 0.01) risk groups. Varying the composition had minimal impact on FPG; however 1 h less sitting time and equivalent increase in standing time was associated with attenuated FPG levels in higher risk only (Δ FPG% = - 1.5 95%CI: - 2.4, - 0.5). Large differences in 2hPLG were observed for both groups when varying the composition. One hour less sitting with equivalent increase in stepping was associated with attenuated 2hPLG, with estimations similar in lower (Δ 2hPLG% = - 3.8 95%CI: - 7.3, - 0.2) and higher (Δ 2hPLG% = - 5.0 95%CI: - 9.7, - 0.0) risk for diabetes. CONCLUSIONS: In middle-aged and older adults, glycaemic control could be improved by reducing daily sitting time and replacing it with stepping. Standing could also be beneficial for those at higher risk of developing type 2 diabetes

    Comparison of Questionnaire and Device Measures of Physical Activity and Sedentary Behavior in a Multi-Ethnic Cohort of Older Women

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    Background: Limited data are available regarding the correlation between questionnaire and device-measured physical activity (PA) and sedentary behavior (SB) in older women. Methods:We evaluated these correlations in 5,992 women, aged 63 and older, who completed the Women’s Health Initiative (WHI) and Community Healthy Activities Model Program for Seniors (CHAMPS) PA questionnaires and the CARDIA SB questionnaire prior to wearing a hip-worn accelerometer for 7 consecutive days. Accelerometer-measured total, light, and moderate-to-vigorous PA (MVPA), and total SB time were defined according to cutpoints established in a calibration study. Spearman coefficients were used to evaluate correlations between questionnaire and device-measures. Results: Mean time spent in PA and SB was lower for questionnaire than accelerometer measures, with variation in means according to age, race/ethnicity, bodymass index, and functional status. Overall, correlations between questionnaires and accelerometer measures were moderate for total PA, MVPA, and SB (r ≈ 0.20–0.40). Light intensity PA correlated weakly for WHI (r ≈ 0.01–0.06) and was variable for CHAMPS (r ≈ 0.07–0.22). Conclusion: Questionnaire and accelerometer estimates of total PA, MVPA, and SB have at best moderate correlations in older women and should not be assumed to be measuring the same behaviors or quantity of behavior. Light intensity PA is poorly measured by questionnaire. Because light intensity activities account for the largest proportion of daily activity time in older adults, and likely contribute to its health benefits, further research should investigate how to improve measurement of light intensity PA by questionnaires
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