It comes as something ofa surprise to reflect that the New York Review ofBooks is now over twenty years old. Even people of my generation (that is, old enough to remember the revolutionary 196os but not young enough to have taken a very exciting part in them) think of the paper as eternally youthful. In fact, it has gone through years of relatively quiet life, yet, as always in a competitive journalistic market, it is the controversies that attract the interest of the reader and to which the history (especially an admittedly impressionistic survey that tries to include something of the intellectual context in which a journal has operated) must give some attention. Not all the attacks which the New York Review has attracted, both early in its career and more recently, are worth more than a brief summary. What do we now make, for example, of Richard Kostelanetz's forthright accusation that 'The New York Review was from its origins destined to publicize Random House's (and especially [Jason] Epstein's) books and writers'?1 Well, simply that, even if the statistics bear out the charge (and Kostelanetz provides some suggestive evidence to support it, at least with respect to some early issues), there is nothing surprising in a market economy about a publisher trying to push his books through the pages of a journal edited by his friends. True, the New York Review has not had room to review more than around fifteen books in each issue and there could be a bias in the selection of

http://www.jstor.org/stable/pdfplus/3507774.pdf

The New York Review of Books

Background: In recent years, cyberculture has informally reported a phenomenon named the 1% rule, or 90-9-1 principle, which seeks to explain participatory patterns and network effects within Internet communities. The rule states that 90% of actors observe and do not participate, 9% contribute sparingly, and 1% of actors create the vast majority of new content. This 90%, 9%, and 1% are also known as Lurkers, Contributors, and Superusers, respectively. To date, very little empirical research has been conducted to verify the 1% rule. Objective: The 1% rule is widely accepted in digital marketing. Our goal was to determine if the 1% rule applies to moderated Digital Health Social Networks (DHSNs) designed to facilitate behavior change. Methods: To help gain insight into participatory patterns, descriptive data were extracted from four long-standing DHSNs: the AlcoholHelpCenter, DepressionCenter, PanicCenter, and StopSmokingCenter sites. Results: During the study period, 63,990 actors created 578,349 posts. Less than 25% of actors made one or more posts. The applicability of the 1% rule was confirmed as Lurkers, Contributors, and Superusers accounted for a weighted average of 1.3% (n=4668), 24.0% (n=88,732), and 74.7% (n=276,034) of content. Conclusions: The 1% rule was consistent across the four DHSNs. As social network sustainability requires fresh content and timely interactions, these results are important for organizations actively promoting and managing Internet communities. Superusers generate the vast majority of traffic and create value, so their recruitment and retention is imperative for long-term success. Although Lurkers may benefit from observing interactions between Superusers and Contributors, they generate limited or no network value. The results of this study indicate that DHSNs may be optimized to produce network effects, positive externalities, and bandwagon effects. Further research in the development and expansion of DHSNs is required. [J Med Internet Res 2014;16(2):e33]

The 1% Rule in Four Digital Health Social Networks: An Observational Study

A key core competency for medical students, residents, fellows, and practicing physicians is “lifelong learning.” Scholarly works such as Anatomy of an Epidemic represent a prime reason that we master this competency. A main stated purpose of the book is to challenge the reader to think about the biological base of mental illness and to come to conclusions about the author’s assertion that there is a hidden epidemic that has been caused by rather than successfully treated through biological agents, eg, psychotropic medications and electroconvulsive therapy. The author succeeds by this well-written and easily understood work to force the reader to take a new look at the cherished tenets of our profession and how they developed. This is accomplished through predominantly negative anecdotes of the destructive power of biological treatments and what appear to be carefully selected citations that explain how the prescribing of medication results in fostering the often irreversible chronicity of the more severe psychiatric disorders and the negative adverse effects of current and past psychotropics. The book is divided into 5 parts: The Epidemic, The Science of Psychiatric Drugs, Outcomes, Explication of a Delusion, and Solutions. The work is comprehensive, but this review will focus on the argument as it pertains to the pediatric population. Under Outcomes, the chapter “The Epidemic Spreads to Children” considers, among other topics, “The Rise of ADHD” (attention-deficit/ hyperactivity disorder), “Stimulants Flunk Out,” “Tallying up the Harm” (of stimulant medications), “Creating the Bipolar Child,” and “The Disability Numbers.” As is done throughout the book, the challenge is raised as to the established biological basis of psychiatric disorders and the conclusion drawn that no evidence exists for such a concept. The author seems to ignore the past decade of neuroimaging results that clearly demonstrate, for example, the differences between children and adolescents with ADHD and those without as well as comparisons in those treated with stimulant medications and those who are treatment naive. Moreover, the cost-benefit ratio of stimulants is asserted to be heavily weighed to their detrimental effects without reference to significant epidemiologic data to the contrary. There is similarly no reference to the documented biological underpinnings of clinically depressed or at risk individuals and the well-designed though limited studies of the comparison treatments for pediatric depression. The book fails to take into account current thinking on the interaction between biological vulnerability and the environment for the basis of psychiatric disorders that dates back to George Engel’s biopsychosocial model of disease1 and models, eg, Akiskal and McKinney’s,2 for melancholia taught to medical students and psychiatry residents. Overall, Anatomy of an Epidemic is a well-, but highly selectively, referenced, useful polemic that provides a comprehensive but biased and dated effort to explain the rise of mental illness in our society to the level of an “epidemic” of pain and suffering. It is must reading for mental health professionals because it exposes us to a different perspective on one of the cornerstones of modern psychiatry and forces us to appreciate how patients and their families can get skewed views of psychotropic medications and their acceptability to society. It is unfortunate that key advances to understanding the more severe or prevalent psychiatric disorders are omitted. Being aware of the spurious arguments that provide the base for such negative and potentially destructive views will allow readers a greater sympathy for those fearful of psychotropic medications and foster motivation to maintain familiarity with advances in the field as the best way to deal with such an attack in a thoughtful and nondefensive response to anxious questions concerning safety, efficacy, and effectiveness.

Anatomy of an Epidemic – Magic Bullets, Psychiatric Drugs, and the Astonishing Rise of Mental Illness in America

The trend towards the use of the Internet for health information purposes is rising. Utilization of various forms of social media has been a key interest in consumer health informatics (CHI). To reveal the information needs of autism-affected users, this study centers on the research of users’ interactions and information sharing within autism communities on social media. It aims to understand how autism-affected users utilize support groups on Facebook by applying natural language process (NLP) techniques to unstructured health data in social media. An interactive visualization method (pyLDAvis) was employed to evaluate produced models and visualize the inter-topic distance maps. The revealed topics (e.g., parenting, education, behavior traits) identify issues that individuals with autism were concerned about on a daily basis and how they addressed such concerns in the form of group communication. In addition to general social support, disease-specific information, collective coping strategies, and emotional support were provided as well by group members based on similar personal experiences. This study concluded that Latent Dirichlet Allocation (LDA) is feasible and appropriated to derive topics (focus) from messages posted to the autism support groups on Facebook. The revealed topics help healthcare professionals (content providers) understand autism from users’ perspectives and provide better patient communications.

Finding Users’ Voice on Social Media: An Investigation of Online Support Groups for Autism-Affected Users on Facebook

Digital Health Social Networks (DHSNs) are common; however, there are few metrics that can be used to identify participation inequality The objective of this study was to investigate whether the Gini coefficient, an economic measure of statistical dispersion traditionally used to measure income inequality, could be employed to measure DHSN inequality Quarterly Gini coefficients were derived from four long-standing DHSNs The combined data set included 625,736 posts that were generated from 15,181 actors over 18,671 days The range of actors (8–2323), posts (29–28,684), and Gini coefficients (015–037) varied Pearson correlations indicated statistically significant associations between number of actors and number of posts (0527–0835, p < 001), and Gini coefficients and number of posts (0342–0725, p < 001) However, the association between Gini coefficient and number of actors was only statistically significant for the addiction networks (0619 and 0276, p < 036) Linear regression models had positive but mixed R2 results (0333–0527) In all four regression models, the association between Gini coefficient and posts was statistically significant (t = 3346–7381, p < 002) However, unlike the Pearson correlations, the association between Gini coefficient and number of actors was only statistically significant in the two mental health networks (t = −4305 and −5934, p < 000) The Gini coefficient is helpful in measuring shifts in DHSN inequality However, as a standalone metric, the Gini coefficient does not indicate optimal numbers or ratios of actors to posts, or effective network engagement Further, mixed-methods research investigating quantitative performance metrics is required

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Employing the Gini coefficient to measure participation inequality in treatment-focused Digital Health Social Networks

Online support groups have shown a strong potential to foster resourceful environments for people living with depression without restrictions of time, space, and stigma. Research has found that users of those groups exchange various types of support. However, due to the scarcity of research, many other aspects of depression online support groups remain inconclusive. In particular, how the support exchange contributes to the everyday lives of users living with depression remains unclear.
To contribute to filing some of the knowledge gaps, the present study explored what kinds of support were requested and provided in a depression online support group. By doing so, this study aimed to examine the roles of the depression online support group in the management of depression.
Mixed methods were employed with a concurrent triangulation strategy. A sample of 980 posts were selected systematically from the support group. Demographic and clinical information of the users who made those posts were recorded. Quantitative and qualitative content analyses were conducted to examine the types of support being exchanged through those posts. Inter-coder reliability was calculated to ensure the consistency of the coding process.
The results indicate that users sought informational support, various types of emotional support and coaching support, and social companionship. Users not only sought listening ears, but also practical advice to cope with the situations they were going through. The group appeared to serve its users as a place to meet others with similar experience; to manage loneliness; to discuss what they could not discuss elsewhere; to "just vent"; to gain advice from multiple perspectives on an issue that had been magnifying the impact of depression; to share the experience with formal care provision systems; to express immediate support needs; to share useful discoveries, accomplishments, and creative ways to manage depression; and to experience the value of helping others. This study supports the idea that depression online support groups have the strong potential to contribute to the everyday lives of people living with depression in a way that is not available elsewhere and in a way that complement to the overall framework of existing care provision systems.%%%%PhD

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Sayaka Sugimoto

Papers

Support Exchange on the Internet: A Content Analysis of an Online Support Group for People Living with Depression