91Ó°ÊÓ

An experiment to determine if an online intervention can reduce references to sex and substance abuse on social networking web sites of adolescents is described in the paper "Reducing At-Risk Adolescents' Display of Risk Behavior on a Social Networking Web Site" (Archives of Pediatrics and Adolescent Medicine [2009]: 35-41). Researchers selected public MySpace profiles of people who described themselves as between 18 and 20 years old and who referenced sex or substance use (alcohol or drugs) in their profiles. The selected subjects were assigned at random to an intervention group or a control group. Those in the intervention group were sent an e-mail from a physician about the risks associated with having a public profile and of referencing sex or substance use in their profile. Three months later, networking sites were revisited to see if any changes had been made. The following excerpt is from the paper: At baseline, \(54.2 \%\) of subjects referenced sex and \(85.3 \%\) referenced substance use on their social networking site profiles. The proportion of profiles in which references decreased to 0 was \(13.7 \%\) in the intervention group vs. \(5.3 \%\) in the control group for sex \((P=.05)\) and \(26 \%\) vs. \(22 \%\) for substance use \((P=.61)\). The proportion of profiles set to "private" at follow-up was \(10.5 \%\) in the intervention group and \(7.4 \%\) in the control group \((P=.45) .\) The proportion of profiles in which any of these three protective changes were made was \(42.1 \%\) in the intervention group and \(29.5 \%\) in the control group \((P=.07)\) a. The quote from the paper references four hypothesis tests. For each test, indicate what hypotheses you think were tested and whether or not the null hypothesis was rejected. b. Based on the information provided by the hypothesis tests, what conclusions can be drawn about the effectiveness of the e-mail intervention?

Step by step solution

01

Identify the hypotheses

The four hypotheses tests in the excerpt are based on: \n1) The decrease of references to sex on social network profiles. \n2) The decrease of references to substance use on social network profiles. \n3) The increase of private profiles on social network sites. \n4) The overall protective changes made in the social network profiles. For each case, the null hypothesis will be that the intervention has no effect, while the alternative hypothesis will be that the intervention has an effect.

02

Decide whether to reject or not reject the null hypotheses

1) For sex references, \(P = 0.05\), so null hypothesis is at the threshold. \n2) For substance use references, \(P = 0.61 \ > 0.05 \), so null hypothesis is not rejected. \n3) For privacy setting, \(P = 0.45 \ > 0.05 \), so null hypothesis is not rejected. \n4) For overall changes, \(P = 0.07 \ > 0.05 \), so null hypothesis is not rejected.

03

Draw conclusions based on the results of the hypothesis tests

From the hypothesis tests, it can be concluded that the intervention had an effect on the decrease of sex references, but does not significantly affect substance use references, privacy settings, or overall protective changes on social network profiles. This suggests there is some evidence that the intervention had an impact, but the impact was limited primarily to references to sex on social network sites.

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Key Concepts

These are the key concepts you need to understand to accurately answer the question.

Null and Alternative Hypotheses

In statistical hypothesis testing, we begin by establishing two opposing statements: the null hypothesis (\(H_0\)) and the alternative hypothesis (\(H_1\) or \( H_a \) ). The null hypothesis typically represents a default position or a state of no effect or no change. From a statistical perspective, when comparing two groups, the assumption under \(H_0\) is that any observed differences are due to random variation rather than a real effect caused by an intervention.

In contrast, the alternative hypothesis stands for what a researcher aims to support — it reflects a genuine effect or a departure from the null condition. For instance, in the exercise dealing with social networking behavior, the null hypothesis for each of the four tests would state that the online intervention has no impact on adolescents’ references to sex, substance use, the privacy setting of their profiles, or any protective changes to their online behavior. In terms of the alternative hypotheses, these would suggest that the intervention successfully influences these behaviors or settings.

P-value Interpretation

A p-value is a fundamental element in hypothesis testing which helps determine the strength of the results in favor of the alternative hypothesis. It is the probability that an effect at least as extreme as the observed effect could have occurred by chance if the null hypothesis were true. A small p-value, generally less than 0.05, is taken as evidence against the null hypothesis, hence suggesting the effect is statistically significant.

In the given exercise, the p-values provided for each hypothesis test dictate whether the null hypothesis can be rejected. For instance, with a p-value of 0.05 for sex references reduction, we are at the conventional cut-off point for considering the result statistically significant, and thus could decide to reject the null hypothesis but with caution. It's important to interpret p-values in context and not just as a strict cut-off. Meanwhile, p-values above 0.05 for substance use references, privacy settings, and overall protective behavior indicate that we do not have sufficient evidence to reject the null hypotheses for these factors.

Intervention Effectiveness

Assessing intervention effectiveness in the social sciences involves measuring the extent to which the intervention produces the expected change in the behavior or condition being targeted. In our example, this would mean evaluating how the email intervention affected adolescents' online behavior.

The results indicated a statistically significant reduction in sex references, which may hint at the intervention’s effectiveness in this particular area. However, the other metrics (references to substance abuse, privacy settings, and overall protective changes) did not show a significant difference. Therefore, one might conclude that while the intervention appears to be somewhat effective at reducing sex references, it may not have been broadly effective across all the measured aspects of social networking behavior. This nuanced view of effectiveness is crucial for researchers to understand which components of an intervention work and which do not.

Social Networking Behavior Research

Research into social networking behavior, particularly among adolescents, is important for understanding how young people represent themselves and interact in the digital space. Facing concerns about privacy and the potential for risky behavior, interventions are often designed to encourage safer online practices. The study in the current exercise investigates this by sending an email cautioning against certain types of online references.

While the intervention affected the display of sexual references, its influence on references to substance use and privacy settings was not significant at a level typically considered persuasive in hypothesis testing. Research in this field requires careful design to isolate the variables at play and to discern not only if an intervention works but also why and how — which behavioral factors are most susceptible to change and which resist intervention.