Influence of funding cuts on Texas school tobacco programs

The WHO Health Promoting School framework for improving the health and well-being of students and their academic achievement

BACKGROUND

The World Health Organization's (WHO's) Health Promoting Schools (HPS) framework is an holistic, settings-based approach to promoting health and educational attainment in school. The effectiveness of this approach has not been previously rigorously reviewed.

OBJECTIVES

To assess the effectiveness of the Health Promoting Schools (HPS) framework in improving the health and well-being of students and their academic achievement.

SEARCH METHODS

We searched the following electronic databases in January 2011 and again in March and April 2013: Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, EMBASE, PsycINFO, CINAHL, Campbell Library, ASSIA, BiblioMap, CAB Abstracts, IBSS, Social Science Citation Index, Sociological Abstracts, TRoPHI, Global Health Database, SIGLE, Australian Education Index, British Education Index, Education Resources Information Centre, Database of Education Research, Dissertation Express, Index to Theses in Great Britain and Ireland, ClinicalTrials.gov, Current controlled trials, and WHO International Clinical Trials Registry Platform. We also searched relevant websites, handsearched reference lists, and used citation tracking to identify other relevant articles.

SELECTION CRITERIA

We included cluster-randomised controlled trials where randomisation took place at the level of school, district or other geographical area. Participants were children and young people aged four to 18 years, attending schools or colleges. In this review, we define HPS interventions as comprising the following three elements: input to the curriculum; changes to the school's ethos or environment or both; and engagement with families or communities, or both. We compared this intervention against schools that implemented either no intervention or continued with their usual practice, or any programme that included just one or two of the above mentioned HPS elements.

DATA COLLECTION AND ANALYSIS

At least two review authors identified relevant trials, extracted data, and assessed risk of bias in the trials. We grouped different types of interventions according to the health topic targeted or the approach used, or both. Where data permitted, we performed random-effects meta-analyses to provide a summary of results across studies.

MAIN RESULTS

We included 67 eligible cluster trials, randomising 1443 schools or districts. This is made up of 1345 schools and 98 districts. The studies tackled a range of health issues: physical activity (4), nutrition (12), physical activity and nutrition combined (18), bullying (7), tobacco (5), alcohol (2), sexual health (2), violence (2), mental health (2), hand-washing (2), multiple risk behaviours (7), cycle-helmet use (1), eating disorders (1), sun protection (1), and oral health (1). The quality of evidence overall was low to moderate as determined by the GRADE approach. 'Risk of bias' assessments identified methodological limitations, including heavy reliance on self-reported data and high attrition rates for some studies. In addition, there was a lack of long-term follow-up data for most studies.We found positive effects for some interventions for: body mass index (BMI), physical activity, physical fitness, fruit and vegetable intake, tobacco use, and being bullied. Intervention effects were generally small but have the potential to produce public health benefits at the population level. We found little evidence of effectiveness for standardised body mass index (zBMI) and no evidence of effectiveness for fat intake, alcohol use, drug use, mental health, violence and bullying others; however, only a small number of studies focused on these latter outcomes. It was not possible to meta-analyse data on other health outcomes due to lack of data. Few studies provided details on adverse events or outcomes related to the interventions. In addition, few studies included any academic, attendance or school-related outcomes. We therefore cannot draw any clear conclusions as to the effectiveness of this approach for improving academic achievement.

AUTHORS' CONCLUSIONS

The results of this review provide evidence for the effectiveness of some interventions based on the HPS framework for improving certain health outcomes but not others. More well-designed research is required to establish the effectiveness of this approach for other health topics and academic achievement.

Evaluating public health resources: what happens when funding disappears?

Introduction

Although various factors affect the sustainability of public health programs, funding levels can influence many aspects of program continuity. Program evaluation in public health typically does not assess the progress of initiatives after discontinuation of funding. The objective of this study was to describe the effect of funding loss following expiration of a 5-year federal grant awarded to state health departments for development of statewide obesity prevention partnerships.

Methods

The study used qualitative methods involving semistructured key informant interviews with state health departments. Data were analyzed using thematic analysis for effect of funding loss on staffing, programs, partnerships, and implementation of state plans.

Results

Many of the programs that continued to run after the grant expired operated at reduced capacity, either reaching fewer people or conducting fewer program activities for the same population. Although many states were able to leverage funding from other sources, this shift in funding source often resulted in priorities changing to meet new funding requirements. Evaluation capacity suffered in all states. Nearly all states reported losing infrastructure and capacity to communicate widely with partners. All states reported a severe or complete loss of their ability to provide training and technical assistance to partners. Despite these reduced capacities, states reported several key resources that facilitated continued work on the state plan.

Conclusions

Decisions regarding continuation of funding are often dependent on budget constraints, evidence of success, and perceived ability to succeed in the future. Evaluating public health funding decisions may help guide development of best practice strategies for supporting long-term program success.

Exposure to school and community based prevention programs and reductions in cigarette smoking among adolescents in the United States, 2000-08

Smoking remains prevalent among US youth despite decades of antismoking efforts. Effects from exposure to prevention programs at national level may provide informative and compelling data supporting better planning and strategy for tobacco control. A national representative sample of youth 12-17 years of age from the National Survey on Drug Use and Health was analyzed. A 3-stage model was devised to estimate smoking behavior transitions using cross-sectional data and the Probabilistic Discrete Event System method. Cigarette smoking measures (prevalence rates and odds ratios) were compared between exposed and non-exposed youth. More than 95% of the sample was exposed to prevention programs. Exposure was negatively associated with lifetime smoking and past 30-day smoking with a dose-response relation. Reduction in smoking was related to increased quitting in 2000-02, to increased quitting and declined initiation in 2003-05, and to initiation, quitting and relapse in 2005-08. Findings of this analysis suggest that intervention programs in the United States can reduce cigarette smoking among youth. Quitting smoking was most responsive to program exposure and relapse was most sensitive to funding cuts since 2003. Health policy and decision makers should consider these factors in planning and revising tobacco control strategies.

Salient latent constructs underlying smoking initiation and continuous use by student-smokers of Huazhong University of Science and Technology, China

The factor analysis model was used to parsimoniously reduce the number of variables that influence smoking among students to salient factors that cut across continents, race, and sociocultural settings among university students in China. Stratified random sampling and snowball techniques were employed to obtain the sample. A Likert-type questionnaire was used to collect data. The results revealed that of the 39 variables identified to influence smoking, 34 were retained and regrouped in terms of common features they share into 13 salient factors that accounted for 58% of variances in the original variables. The predominant hidden construct was influence by association. The other 12 factors were labeled and ordered as follows: emotional needs, family history, addiction, peer pressure, lack of full realization of the consequences of their action as regards the expense of smoking, social needs, advertisement, psychological needs, self-image, environmental factors, ineffective policies, and underestimation of health risks. Irrespective of regional demarcations, factors that influence smoking initiation and continuous use are same.