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      Health belief model based evaluation of school health education programme for injury prevention among high school students in the community context

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      BMC Public Health
      BioMed Central

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          Abstract

          Background

          Although multifaceted community-based programmes have been widely developed, there remains a paucity of evaluation of the effectiveness of multifaceted injury prevention programmes implemented in different settings in the community context. This study was to provide information for the evaluation of community-based health education programmes of injury prevention among high school students.

          Methods

          The pre-intervention survey was conducted in November 2009. Health belief model (HBM) based health education for injury prevention started in January 2010 and stopped in the end of 2011 among high school students in the community context in Shanghai, China. A post-intervention survey was conducted six weeks after the completion of intervention. Injury-related health belief indicators were captured by a short questionnaire before and after the intervention. Health belief scores were calculated and compared using the simple sum score (SSS) method and the confirmatory factor analysis weighted score (CFAWS) method, respectively.

          Results

          The average reliability coefficient for the questionnaire was 0.89. The factor structure of HBM was given and the data fit HBM in the confirmatory factor analysis (CFA) very well. The result of CFA showed that Perceived Benefits of Taking Action (BEN) and Perceived Seriousness (SER) had the greatest impact on the health belief, Perceived Susceptibility (SUS) and Cues to Action (CTA) were the second and third most important components of HBM respectively. Barriers to Taking Action (BAR) had no notable impact on HBM. The standardized path coefficient was only 0.35, with only a small impact on CTA. The health belief score was significantly higher after intervention ( p < 0.001), which was similar in the CFAWS method and in the SSS method. However, the 95% confidential interval in the CFAWS method was narrower than that in the SSS method.

          Conclusions

          The results of CFA provide further empirical support for the HBM in injury intervention. The CFAWS method can be used to calculate the health belief scores and evaluate the injury related intervention. The community-based school health education might improve injury-related health belief among high school students; however, this preliminary observation needs to be confirmed in further research.

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          Most cited references21

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          The Health Belief Model: a decade later.

          Since the last comprehensive review in 1974, the Health Belief Model (HBM) has continued to be the focus of considerable theoretical and research attention. This article presents a critical review of 29 HBM-related investigations published during the period of 1974-1984, tabulates the findings from 17 studies conducted prior to 1974, and provides a summary of the total 46 HBM studies (18 prospective, 28 retrospective). Twenty-four studies examined preventive-health behaviors (PHB), 19 explored sick-role behaviors (SRB), and three addressed clinic utilization. A "significance ratio" was constructed which divides the number of positive, statistically-significant findings for an HBM dimension by the total number of studies reporting significance levels for that dimension. Summary results provide substantial empirical support for the HBM, with findings from prospective studies at least as favorable as those obtained from retrospective research. "Perceived barriers" proved to be the most powerful of the HBM dimensions across the various study designs and behaviors. While both were important overall, "perceived susceptibility" was a stronger contributor to understanding PHB than SRB, while the reverse was true for "perceived benefits." "Perceived severity" produced the lowest overall significance ratios; however, while only weakly associated with PHB, this dimension was strongly related to SRB. On the basis of the evidence compiled, it is recommended that consideration of HBM dimensions be a part of health education programming. Suggestions are offered for further research.
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            The global burden of unintentional injuries and an agenda for progress.

            According to the World Health Organization, unintentional injuries were responsible for over 3.9 million deaths and over 138 million disability-adjusted life-years in 2004, with over 90% of those occurring in low- and middle-income countries (LMIC). This paper utilizes the year 2004 World Health Organization Global Burden of Disease Study estimates to illustrate the global and regional burden of unintentional injuries and injury rates, stratified by cause, region, age, and gender. The worldwide rate of unintentional injuries is 61 per 100,000 population per year. Overall, road traffic injuries make up the largest proportion of unintentional injury deaths (33%). When standardized per 100,000 population, the death rate is nearly double in LMIC versus high-income countries (65 vs. 35 per 100,000), and the rate of disability-adjusted life-years is more than triple in LMIC (2,398 vs. 774 per 100,000). This paper calls for more action around 5 core areas that need research investments and capacity development, particularly in LMIC: 1) improving injury data collection, 2) defining the epidemiology of unintentional injuries, 3) estimating the costs of injuries, 4) understanding public perceptions about injury causation, and 5) engaging with policy makers to improve injury prevention and control.
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              Mathematical models in the evaluation of health programmes.

              Modelling is valuable in the planning and evaluation of interventions, especially when a controlled trial is ethically or logistically impossible. Models are often used to calculate the expected course of events in the absence of more formal assessments. They are also used to derive estimates of rare or future events from recorded intermediate points. When developing models, decisions are needed about the appropriate level of complexity to be represented and about model structure and assumptions. The degree of rigor in model development and assessment can vary greatly, and there is a danger that existing beliefs inappropriately influence judgments about model assumptions and results. Copyright © 2011 Elsevier Ltd. All rights reserved.
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                Author and article information

                Journal
                BMC Public Health
                BMC Public Health
                BMC Public Health
                BioMed Central
                1471-2458
                2014
                10 January 2014
                : 14
                : 26
                Affiliations
                [1 ]School of Public Health, “Key Laboratory of Public Health Safety, Ministry of Education”, Fudan University, 130 Dong’ an Road, Xuhui District, Shanghai, China
                [2 ]Department of Epidemiology and Community Medicine, University of Ottawa, 451 Smyth Road Ontario, K1H 8 M5 Ottawa, Canada
                Article
                1471-2458-14-26
                10.1186/1471-2458-14-26
                3922908
                24410991
                5b17eb16-61f9-4042-a02c-5d850b936b7e
                Copyright © 2014 Cao et al.; licensee BioMed Central Ltd.

                This is an open access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 10 May 2013
                : 7 January 2014
                Categories
                Research Article

                Public health
                Public health

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