Implementing the LifeSkills Training drug prevention program: factors related to implementation fidelity

<p>Abstract</p> <p>Background</p> <p>Widespread replication of effective prevention programs is unlikely to affect the incidence of adolescent delinquency, violent crime, and substance use until the quality of implementation of these programs by community-based organizations can be assured.</p> <p>Methods</p> <p>This paper presents the results of a process evaluation employing qualitative and quantitative methods to assess the extent to which 432 schools in 105 sites implemented the LifeSkills Training (LST) drug prevention program with fidelity. Regression analysis was used to examine factors influencing four dimensions of fidelity: adherence, dosage, quality of delivery, and student responsiveness.</p> <p>Results</p> <p>Although most sites faced common barriers, such as finding room in the school schedule for the program, gaining full support from key participants (i.e., site coordinators, principals, and LST teachers), ensuring teacher participation in training workshops, and classroom management difficulties, most schools involved in the project implemented LST with very high levels of fidelity. Across sites, 86% of program objectives and activities required in the three-year curriculum were delivered to students. Moreover, teachers were observed using all four recommended teaching practices, and 71% of instructors taught all the required LST lessons. Multivariate analyses found that highly rated LST program characteristics and better student behavior were significantly related to a greater proportion of material taught by teachers (adherence). Instructors who rated the LST program characteristics as ideal were more likely to teach all lessons (dosage). Student behavior and use of interactive teaching techniques (quality of delivery) were positively related. No variables were related to student participation (student responsiveness).</p> <p>Conclusion</p> <p>Although difficult, high implementation fidelity by community-based organizations can be achieved. This study suggests some important factors that organizations should consider to ensure fidelity, such as selecting programs with features that minimize complexity while maximizing flexibility. Time constraints in the classroom should be considered when choosing a program. Student behavior also influences program delivery, so schools should train teachers in the use of classroom management skills. This project involved comprehensive program monitoring and technical assistance that likely facilitated the identification and resolution of problems and contributed to the overall high quality of implementation. Schools should recognize the importance of training and technical assistance to ensure quality program delivery.</p

Melanoma: A model for testing new agents in combination therapies

Treatment for both early and advanced melanoma has changed little since the introduction of interferon and IL-2 in the early 1990s. Recent data from trials testing targeted agents or immune modulators suggest the promise of new strategies to treat patients with advanced melanoma. These include a new generation of B-RAF inhibitors with greater selectivity for the mutant protein, c-Kit inhibitors, anti-angiogenesis agents, the immune modulators anti-CTLA4, anti-PD-1, and anti-CD40, and adoptive cellular therapies. The high success rate of mutant B-RAF and c-Kit inhibitors relies on the selection of patients with corresponding mutations. However, although response rates with small molecule inhibitors are high, most are not durable. Moreover, for a large subset of patients, reliable predictive biomarkers especially for immunologic modulators have not yet been identified. Progress may also depend on identifying additional molecular targets, which in turn depends upon a better understanding of the mechanisms leading to response or resistance. More challenging but equally important will be understanding how to optimize the treatment of individual patients using these active agents sequentially or in combination with each other, with other experimental treatment, or with traditional anticancer modalities such as chemotherapy, radiation, or surgery. Compared to the standard approach of developing new single agents for licensing in advanced disease, the identification and validation of patient specific and multi-modality treatments will require increased involvement by several stakeholders in designing trials aimed at identifying, even in early stages of drug development, the most effective way to use molecularly guided approaches to treat tumors as they evolve over time

The Neuronal Correlates of Digits Backward Are Revealed by Voxel-Based Morphometry and Resting-State Functional Connectivity Analyses

Digits backward (DB) is a widely used neuropsychological measure that is believed to be a simple and effective index of the capacity of the verbal working memory. However, its neural correlates remain elusive. The aim of this study is to investigate the neural correlates of DB in 299 healthy young adults by combining voxel-based morphometry (VBM) and resting-state functional connectivity (rsFC) analyses. The VBM analysis showed positive correlations between the DB scores and the gray matter volumes in the right anterior superior temporal gyrus (STG), the right posterior STG, the left inferior frontal gyrus and the left Rolandic operculum, which are four critical areas in the auditory phonological loop of the verbal working memory. Voxel-based correlation analysis was then performed between the positive rsFCs of these four clusters and the DB scores. We found that the DB scores were positively correlated with the rsFCs within the salience network (SN), that is, between the right anterior STG, the dorsal anterior cingulate cortex and the right fronto-insular cortex. We also found that the DB scores were negatively correlated with the rsFC within an anti-correlation network of the SN, between the right posterior STG and the left posterior insula. Our findings suggest that DB performance is related to the structural and functional organizations of the brain areas that are involved in the auditory phonological loop and the SN

Evidence-based Kernels: Fundamental Units of Behavioral Influence

This paper describes evidence-based kernels, fundamental units of behavioral influence that appear to underlie effective prevention and treatment for children, adults, and families. A kernel is a behavior–influence procedure shown through experimental analysis to affect a specific behavior and that is indivisible in the sense that removing any of its components would render it inert. Existing evidence shows that a variety of kernels can influence behavior in context, and some evidence suggests that frequent use or sufficient use of some kernels may produce longer lasting behavioral shifts. The analysis of kernels could contribute to an empirically based theory of behavioral influence, augment existing prevention or treatment efforts, facilitate the dissemination of effective prevention and treatment practices, clarify the active ingredients in existing interventions, and contribute to efficiently developing interventions that are more effective. Kernels involve one or more of the following mechanisms of behavior influence: reinforcement, altering antecedents, changing verbal relational responding, or changing physiological states directly. The paper describes 52 of these kernels, and details practical, theoretical, and research implications, including calling for a national database of kernels that influence human behavior

Cancer Biomarker Discovery: The Entropic Hallmark

Background: It is a commonly accepted belief that cancer cells modify their transcriptional state during the progression of the disease. We propose that the progression of cancer cells towards malignant phenotypes can be efficiently tracked using high-throughput technologies that follow the gradual changes observed in the gene expression profiles by employing Shannon's mathematical theory of communication. Methods based on Information Theory can then quantify the divergence of cancer cells' transcriptional profiles from those of normally appearing cells of the originating tissues. The relevance of the proposed methods can be evaluated using microarray datasets available in the public domain but the method is in principle applicable to other high-throughput methods. Methodology/Principal Findings: Using melanoma and prostate cancer datasets we illustrate how it is possible to employ Shannon Entropy and the Jensen-Shannon divergence to trace the transcriptional changes progression of the disease. We establish how the variations of these two measures correlate with established biomarkers of cancer progression. The Information Theory measures allow us to identify novel biomarkers for both progressive and relatively more sudden transcriptional changes leading to malignant phenotypes. At the same time, the methodology was able to validate a large number of genes and processes that seem to be implicated in the progression of melanoma and prostate cancer. Conclusions/Significance: We thus present a quantitative guiding rule, a new unifying hallmark of cancer: the cancer cell's transcriptome changes lead to measurable observed transitions of Normalized Shannon Entropy values (as measured by high-throughput technologies). At the same time, tumor cells increment their divergence from the normal tissue profile increasing their disorder via creation of states that we might not directly measure. This unifying hallmark allows, via the the Jensen-Shannon divergence, to identify the arrow of time of the processes from the gene expression profiles, and helps to map the phenotypical and molecular hallmarks of specific cancer subtypes. The deep mathematical basis of the approach allows us to suggest that this principle is, hopefully, of general applicability for other diseases

predictive precision medicine towards the computational challenge

The emerging fields of predictive and precision medicine are changing the traditional medical approach to disease and patient. Current discoveries in medicine enable to deepen the comprehension of diseases, whereas the adoption of high-quality methods such as novel imaging techniques (e.g. MRI, PET) and computational approaches (i.e. machine learning) to analyse data allows researchers to have meaningful clinical and statistical information. Indeed, applications of radiology techniques and machine learning algorithms rose in the last years to study neurology, cardiology and oncology conditions. In this chapter, we will provide an overview on predictive precision medicine that uses artificial intelligence to analyse medical images to enhance diagnosis, prognosis and treatment of diseases. In particular, the chapter will focus on neurodegenerative disorders that are one of the main fields of application. Despite some critical issues of this new approach, adopting a patient-centred approach could bring remarkable improvement on individual, social and business level

Older Persons' Preferences for Site of Treatment in Acute Illness: ANNOUNCEMENT

OBJECTIVE: To explore how older persons form preferences for site of medical care by examining their perceptions of home care and hospital care. DESIGN: Qualitative analysis of in-depth interviews using the constant comparative method. SETTING: Respondents' homes. PARTICIPANTS: Twenty-nine persons age 65 to 89 years who had been hospitalized with congestive heart failure, chronic obstructive pulmonary disease, or pneumonia and were receiving home care services. MAIN RESULTS: Respondents, who thought of home care only as a means to provide low-intensity and low-frequency services, were initially skeptical about expanded home care services to treat acute illness. Regardless of their opinions about home and hospital, all respondents preferred the site associated with the greatest chance of survival. If the sites offered equal survival, 52% of the respondents preferred treatment at home because of freedom from the constraints of the hospital and the comfort of familiar surroundings. For respondents who preferred the hospital, the home represented a frightening and lonely place to be sick. Respondents' views of the home and hospital were shaped by their social supports, self-reliance, religious beliefs, and past illness experiences. CONCLUSIONS: Because survival appears to be the most important determinant of preference, home treatment of acute illness is a viable alternative only if it provides outcomes equivalent to those of hospitalization. Strongly held perceptions that home care can only be a low-intensity service may limit preferences for home treatment. When expected outcomes at the two sites are similar, the challenge to the health care system will be incorporating patient preference about the process of care into decisions about the appropriate site of care