761 resultados para Health behavior model


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Objective: Improved treatment has increased the survival of childhood cancer patients in recent decades, but follow-up care is recommended to detect and treat late effects. We investigated relationships between health beliefs and follow-up attendance in adult childhood cancer survivors. Methods: Childhood cancer survivors aged younger than 16 years when diagnosed between 1976 and 2003, who had survived for more than 5 years and were currently aged 201 years, received a postal questionnaire. We asked survivors whether they attended follow-up in the past year. Concepts from the Health Belief Model (perceived susceptibility and severity of future late effects, potential benefits and barriers to follow-up, general health value and cues to action) were assessed. Medical information was extracted from the Swiss Childhood Cancer Registry. Results: Of 1075 survivors (response rate 72.3%), 250 (23.3%) still attended regular followup care. In unadjusted analyses, all health belief concepts were significantly associated with follow-up (po0.05). Adjusting for other health beliefs, demographic, and medical variables, only barriers (OR50.59; 95%CI: 0.43–0.82) remained significant. Younger survivors, those with lower educational background, diagnosed at an older age, treated with chemotherapy, radiotherapy, or bone marrow transplantation and with a relapse were more likely to attend follow-up care. Conclusions: Our study showed that more survivors at high risk of cancer- and treatmentrelated late effects attend follow-up care in Switzerland. Patient-perceived barriers hinder attendance even after accounting for medical variables. Information about the potential effectiveness and value of follow-up needs to be available to increase the attendance among childhood cancer survivors.

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Background. To explore effects of a health risk appraisal for older people (HRA-O) program with reinforcement, we conducted a randomized controlled trial in 21 general practices in Hamburg, Germany. Methods. Overall, 2,580 older patients of 14 general practitioners trained in reinforcing recommendations related to HRA-O-identified risk factors were randomized into intervention (n = 878) and control (n = 1,702) groups. Patients (n = 746) of seven additional matched general practitioners who did not receive this training served as a comparison group. Patients allocated to the intervention group, and their general practitioners, received computer-tailored written recommendations, and patients were offered the choice between interdisciplinary group sessions (geriatrician, physiotherapist, social worker, and nutritionist) and home visits (nurse). Results. Among the intervention group, 580 (66%) persons made use of personal reinforcement (group sessions: 503 [87%], home visits: 77 [13%]). At 1-year follow-up, persons in the intervention group had higher use of preventive services (eg, influenza vaccinations, adjusted odds ratio 1.7; 95% confidence interval 1.4–2.1) and more favorable health behavior (eg, high fruit/fiber intake, odds ratio 2.0; 95% confidence interval 1.6–2.6), as compared with controls. Comparisons between intervention and comparison group data revealed similar effects, suggesting that physician training alone had no effect. Subgroup analyses indicated favorable effects for HRA-O with personal reinforcement, but not for HRA-O without reinforcement. Conclusions. HRA-O combined with physician training and personal reinforcement had favorable effects on preventive care use and health behavior.

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In a matched experimental design, the effectiveness of matching in reducing bias and increasing power depends on the strength of the association between the matching variable and the outcome of interest. In particular, in the design of a community health intervention trial, the effectiveness of a matched design, where communities are matched according to some community characteristic, depends on the strength of the correlation between the matching characteristic and the change in the health behavior being measured. We attempt to estimate the correlation between community characteristics and changes in health behaviors in four datasets from community intervention trials and observational studies. Community characteristics that are highly correlated with changes in health behaviors would potentially be effective matching variables in studies of health intervention programs designed to change those behaviors. Among the community characteristics considered, the urban-rural character of the community was the most highly correlated with changes in health behaviors. The correlations between Per Capita Income, Percent Low Income & Percent aged over 65 and changes in health behaviors were marginally statistically significant (p < 0.08).

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BACKGROUND: Circulating progenitor cells have been implicated with maintaining vascular integrity. Low counts are found in adults with high cardiovascular risk and are associated with impaired endothelial function. It remains unknown whether psychosocial risk factors are independently related to counts of circulating progenitor cells. METHODS: We investigated a random sample of 468 adult industrial employees (mean age 41.2 years, 89% men) of Caucasian origin. Cardiovascular risk factors (blood pressure, LDL, HDL and C-reactive protein), health behavior (smoking, alcohol and physical exercise), psychological variables (effort-reward imbalance social support, negative affectivity) and interaction terms served as predictors of circulating progenitor cells (CD34+ CD31dim) as enumerated by flow-cytometry. FINDINGS: Psychosocial variables were independently associated with progenitor cell counts. The association with risk factors increased with age (explained variance in 18-36 year olds R(2)=0.17, p=0.55; age 36.1-46 R(2)=0.32, p=0.001; age>46 R(2)=0.27, p<0.001). Data revealed a shift from a larger association between behavioral and psychosocial variables and cell counts to a stronger association between biological variables and cell counts in older individuals. A significant interaction was observed between smoking and effort-reward imbalance in middle-aged subjects, those with both risk factors present had lower cell counts. In older employees, the interaction between biological risk factors and smoking was related to lower cell counts. INTERPRETATION: In working middle-aged and older men, psychosocial risk factors were related to circulating counts of progenitor cells. Smoking interacted negatively with psychosocial risk factors (middle-aged men) or with biological risk factors (older employees).

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A common form of social regulation of an individual’s health behavior is social control. The contextual model of social control assumes that higher relationship quality goes along with more beneficial effects of social control on health behavior. This study examined potential differential moderating effects of different dimensions of relationship quality on the associations between positive and negative social control and smoking behavior and hiding smoking. The sample consisted of 144 smokers (n = 72 women; mean age = 31.78, SD = 10.04) with a nonsmoking partner. Positive and negative social control, dimensions of relationship quality consensus, cohesion and satisfaction, numbers of cigarettes smoked (NCS), hiding smoking (HS), and control variables were assessed at baseline. Four weeks later NCS and HS were assessed again. Only for smokers with high consensus, but not cohesion and satisfaction, a negative association between positive control and NCS emerged. Moreover, smokers with high consensus tended to report more HS when being positively and negatively socially controlled. This also emerged for cohesion and positive control. Satisfaction with the relationship did not display any interaction effects. This study’s results emphasize the importance of differentiating not only between positive and negative social control but also between different dimensions of relationship quality in order to gain a comprehensive understanding of the dynamics in romantic dyads with regard to social regulation of behavioral change.

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Background: The health action process approach (hapa) is a well-established model in predicting health behavior and assumes that volitional processes are important for effective behavioral change. however, only few studies have so far tested associations on the intraindividual level. thus, this study examined the inter- and intraindividual associations between volitional predictors and daily smoking around a quit attempt. method: overall, 105 smokers completed daily electronic questionnaires 10 days before and 21 days after a self-set quit date, including measures of intentions, self-efficacy, planning, action control and numbers of cigarettes smoked. multilevel analysis was applied. findings: at the interindividual level, higher mean levels of volitional predictors across the 32 days were associated with less numbers of cigarettes smoked. negative associations emerged also at the intraindividual level, indicating that on days with higher intentions, self-efficacy, planning and action control than usual, less cigarettes were smoked. moreover, these effects were stronger after the quit date than before the quit date. intentions and action control emerged as most powerful predictors at the intraindividual level. discussion: findings confirm assumptions of the hapa and emphasize the importance of volitional processes at the inter- and intraindividual level in the context of quitting smoking.

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PURPOSE    Segmentation of the proximal femur in digital antero-posterior (AP) pelvic radiographs is required to create a three-dimensional model of the hip joint for use in planning and treatment. However, manually extracting the femoral contour is tedious and prone to subjective bias, while automatic segmentation must accommodate poor image quality, anatomical structure overlap, and femur deformity. A new method was developed for femur segmentation in AP pelvic radiographs. METHODS    Using manual annotations on 100 AP pelvic radiographs, a statistical shape model (SSM) and a statistical appearance model (SAM) of the femur contour were constructed. The SSM and SAM were used to segment new AP pelvic radiographs with a three-stage approach. At initialization, the mean SSM model is coarsely registered to the femur in the AP radiograph through a scaled rigid registration. Mahalanobis distance defined on the SAM is employed as the search criteria for each annotated suggested landmark location. Dynamic programming was used to eliminate ambiguities. After all landmarks are assigned, a regularized non-rigid registration method deforms the current mean shape of SSM to produce a new segmentation of proximal femur. The second and third stages are iteratively executed to convergence. RESULTS    A set of 100 clinical AP pelvic radiographs (not used for training) were evaluated. The mean segmentation error was [Formula: see text], requiring [Formula: see text] s per case when implemented with Matlab. The influence of the initialization on segmentation results was tested by six clinicians, demonstrating no significance difference. CONCLUSIONS    A fast, robust and accurate method for femur segmentation in digital AP pelvic radiographs was developed by combining SSM and SAM with dynamic programming. This method can be extended to segmentation of other bony structures such as the pelvis.

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BACKGROUND: Most theories of health-behavior change focus exclusively on individual self-regulation without taking social factors, such as social support, into account. This study's first aim was to systematically test the added value of received instrumental and emotional social support within the Health Action Process Approach (HAPA) in the context of dietary change. In the social support literature, gender effects emerge with regard to the effectiveness of social support. Thus, a second aim was the examination of gender differences in the association of social support with dietary behavior. METHODS: Participants were 252 overweight and obese individuals. At baseline and 12 months later, participants completed questionnaires on HAPA variables; diet-specific received social support and low-fat diet. RESULTS: For the prediction of intentions 12 months later, instrumental support was more beneficial for men than for women over and above individual self-regulation. In terms of dietary behavior at T2, a moderate main effect of instrumental support emerged. Moreover, received emotional social support was beneficial for men, but not for women in terms of a low-fat diet 12 months later. CONCLUSIONS: Effects of received instrumental social support found in this study provide new evidence for the added value of integrating social support into the HAPA.

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BACKGROUND: Enhancing physical activity in overweight and obese individuals is an important means to promote health in this target population. The Health Action Process Approach (HAPA), which was the theoretical framework of this study, focuses on individual self-regulation variables for successful health behavior change. One key self-regulation variable of this model is action control with its three subfacets awareness of intentions, self-monitoring and regulatory effort. The social context of individuals, however, is usually neglected in common health behavior change theories. In order to integrate social influences into the HAPA, this randomized controlled trial investigated the effectiveness of a dyadic conceptualization of action control for promoting physical activity. METHODS/DESIGN: This protocol describes the design of a single-blind randomized controlled trial, which comprises four experimental groups: a dyadic action control group, an individual action control group and two control groups. Participants of this study are overweight or obese, heterosexual adult couples who intend to increase their physical activity. Blocking as means of a gender-balanced randomization is used to allocate couples to conditions and partners to either being the target person of the intervention or to the partner condition. The ecological momentary intervention takes place in the first 14 days after baseline assessment and is followed by another 14 days diary phase without intervention. Follow-ups are one month and six months later. Subsequent to the six-months follow-up another 14 days diary phase takes place.The main outcome measures are self-reported and accelerometer-assessed physical activity. Secondary outcome measures are Body Mass Index (BMI), aerobic fitness and habitual physical activity. DISCUSSION: This is the first study examining a dyadic action control intervention in comparison to an individual action control condition and two control groups applying a single-blind randomized control trial. Challenges with running couples studies as well as advantages and disadvantages of certain design-related decisions are discussed. This RCT was funded by the Swiss National Science Foundation (PP00P1_133632/1) and was registered on 27/04/2012 at http://www.isrctn.com/ISRCTN15705531.

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BACKGROUND: Enhancing physical activity in overweight and obese individuals is an important means to promote health in this target population. The Health Action Process Approach (HAPA), which was the theoretical framework of this study, focuses on individual self-regulation variables for successful health behavior change. One key self-regulation variable of this model is action control with its three subfacets awareness of intentions, self-monitoring and regulatory effort. The social context of individuals, however, is usually neglected in common health behavior change theories. In order to integrate social influences into the HAPA, this randomized controlled trial investigated the effectiveness of a dyadic conceptualization of action control for promoting physical activity. METHODS/DESIGN: This protocol describes the design of a single-blind randomized controlled trial, which comprises four experimental groups: a dyadic action control group, an individual action control group and two control groups. Participants of this study are overweight or obese, heterosexual adult couples who intend to increase their physical activity. Blocking as means of a gender-balanced randomization is used to allocate couples to conditions and partners to either being the target person of the intervention or to the partner condition. The ecological momentary intervention takes place in the first 14 days after baseline assessment and is followed by another 14 days diary phase without intervention. Follow-ups are one month and six months later. Subsequent to the six-months follow-up another 14 days diary phase takes place.The main outcome measures are self-reported and accelerometer-assessed physical activity. Secondary outcome measures are Body Mass Index (BMI), aerobic fitness and habitual physical activity. DISCUSSION: This is the first study examining a dyadic action control intervention in comparison to an individual action control condition and two control groups applying a single-blind randomized control trial. Challenges with running couples studies as well as advantages and disadvantages of certain design-related decisions are discussed. This RCT was funded by the Swiss National Science Foundation (PP00P1_133632/1) and was registered on 27/04/2012 at http://www.isrctn.com/ISRCTN15705531.

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Objectives: The dual-effects model of social control proposes that social control leads to better health practices, but also arouses psychological distress. However, findings are inconsistent in relation to health behavior and psychological distress. Recent research suggests that the most effective control is unnoticed by the receiver (i.e., invisible). There is some evidence that invisible social control is beneficial for positive and negative affective reactions. Yet, investigations of the influence of invisible social control on daily smoking and distress have been limited. In daily diaries, we investigated how invisible social control is associated with number of cigarettes smoked and negative affect on a daily basis. Methods: Overall, 99 smokers (72.0% men, mean age M = 40.48, SD = 9.82) and their non-smoking partners completed electronic diaries from a self-set quit date for 22 consecutive days within the hour before going to bed, reporting received and provided social control, daily number of cigarettes smoked, and negative affect. Results: Multilevel analyses indicated that between-person levels of invisible social control were associated with lower negative affect, whereas they were unrelated to number of cigarettes smoked. On days with higher-than-average invisible social control, smokers reported less cigarettes smoked and more negative affect. Conclusions: Between-person level findings indicate that invisible social control can be beneficial for negative affect. However, findings on the within-person level are in line with the assumptions of the dual-effects model of social control: Invisible social control reduced daily smoking and simultaneously increased daily negative affect within person.

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Correct predictions of future blood glucose levels in individuals with Type 1 Diabetes (T1D) can be used to provide early warning of upcoming hypo-/hyperglycemic events and thus to improve the patient's safety. To increase prediction accuracy and efficiency, various approaches have been proposed which combine multiple predictors to produce superior results compared to single predictors. Three methods for model fusion are presented and comparatively assessed. Data from 23 T1D subjects under sensor-augmented pump (SAP) therapy were used in two adaptive data-driven models (an autoregressive model with output correction - cARX, and a recurrent neural network - RNN). Data fusion techniques based on i) Dempster-Shafer Evidential Theory (DST), ii) Genetic Algorithms (GA), and iii) Genetic Programming (GP) were used to merge the complimentary performances of the prediction models. The fused output is used in a warning algorithm to issue alarms of upcoming hypo-/hyperglycemic events. The fusion schemes showed improved performance with lower root mean square errors, lower time lags, and higher correlation. In the warning algorithm, median daily false alarms (DFA) of 0.25%, and 100% correct alarms (CA) were obtained for both event types. The detection times (DT) before occurrence of events were 13.0 and 12.1 min respectively for hypo-/hyperglycemic events. Compared to the cARX and RNN models, and a linear fusion of the two, the proposed fusion schemes represents a significant improvement.