Adolescents' Beliefs About Peers' Engagement in an Online Self-Harm Challenge: Exploring the Role of Individual Characteristics Through a Latent Class Analysis

In the last decade considerable attention has been devoted to the possible contribution of social media, and the Internet generally, to instigating adolescents' engagement in self-harm activities, which are considered the result of a combination of multidimensional variables, such as depression and anxiety. This study aimed to identify, using latent class analysis (LCA), classes homogeneous for adolescents' beliefs about peers' motivations in taking part in the recent Blue Whale Challenge Game, and to analyze the individual predictors (gender, mental health problems, self-harm and risk-taking behaviors, and problematic Internet use) of the adolescent's latent class membership. We performed an LCA using "perceived attraction" and "perceived constraint" as nominal indicators. Relative fit indices suggested the two class solution as the best measurement model: the first class was mostly composed of adolescents who attributed a central role to the adolescent (internal causality), while the second class mostly composed of adolescents who attributed a central role to the recruiters (external causality). In addition, we explored some individual characteristics to test whether they could predict adolescents' class membership. Results suggests that it is significantly more likely for adolescents with higher level of stress and risk-taking to attribute a central role to their peers' internal motivation, rather than to the recruiter, in deciding to take part in the online self-harm challenge game. Implications for preventive interventions are discussed

Measurement of a model of implementation for health care: toward a testable theory

<p>Abstract</p> <p>Background</p> <p>Greenhalgh et al. used a considerable evidence-base to develop a comprehensive model of implementation of innovations in healthcare organizations [1]. However, these authors did not fully operationalize their model, making it difficult to test formally. The present paper represents a first step in operationalizing Greenhalgh et al.’s model by providing background, rationale, working definitions, and measurement of key constructs.</p> <p>Methods</p> <p>A systematic review of the literature was conducted for key words representing 53 separate sub-constructs from six of the model’s broad constructs. Using an iterative process, we reviewed existing measures and utilized or adapted items. Where no one measure was deemed appropriate, we developed other items to measure the constructs through consensus.</p> <p>Results</p> <p>The review and iterative process of team consensus identified three types of data that can been used to operationalize the constructs in the model: survey items, interview questions, and administrative data. Specific examples of each of these are reported.</p> <p>Conclusion</p> <p>Despite limitations, the mixed-methods approach to measurement using the survey, interview measure, and administrative data can facilitate research on implementation by providing investigators with a measurement tool that captures most of the constructs identified by the Greenhalgh model. These measures are currently being used to collect data concerning the implementation of two evidence-based psychotherapies disseminated nationally within Department of Veterans Affairs. Testing of psychometric properties and subsequent refinement should enhance the utility of the measures.</p