eHealth recruitment challenges

Little is known about effective eHealth recruitment methods. This paper presents recruitment challenges associated with enrolling African-American girls aged 8–10 years in an eHealth obesity prevention program, their effect on the recruitment plan, and potential implications for eHealth research.Although the initial recruitment strategy was literature-informed, it failed to enroll the desired number of girls within a reasonable time period. Therefore, the recruitment strategy was reformulated to incorporate principles of social marketing and traditional marketing techniques. The resulting plan included both targeted, highly specific strategies (e.g., selected churches), and more broad-based approaches (e.g., media exposure, mass mailings, radio advertisements).The revised plan enabled recruitment goals to be attained. Media appeared to be particularly effective at reaching the intended audience. Future research should identify the most effective recruitment strategies for reaching potential eHealth audiences.     

A bivariate normal example where the locally most powerful and distantly most powerful test statistics are beaten everywhere from a median p-value standpoint

In the bivariate normal, n=2 case, when testing H₀:μ_x=μ_y=0,σ² _x=σ² _y=1, ρ=0 vs. H₁:μ_x=μ_y=0,σ² _x=σ² _y=1, 0<ρ<1, it is shown that the median p-values given by the locally most powerful test and the distantly most powerful test are both beaten everywhere by the median of a third test.     

The collected works of john w. tukey

We describe novel, analytical, data-analysis, and Monte-Carlo-simulation studies of strongly heteroscedastic data of both small and wide range.Many different types of heteroscedasticity and fixed or variable weighting are incorporated through error-variance models.Attention is given to parameter bias determinations, evaluations of their significances, and to new ways to correct for bias.The error-variance models allow for both additive and independent power-law errors, and the power exponent is shown to be able to be well determined for typical physicalsciences data by the rapidly-converging, general-purpose, extended-least-squares program we use.The fitting and error-variance models are applied to both low-and high-heteroscedasticity situations, including single-response data from radioactive decay.Monte-Carlo simulations of data with similar parameters are used to evaluate the analytical models developed and the various minimization methods em-ployed, such as extended and generalized least squares.Logarithmic and inversion transformations are investigated in detail, and it is shown analytically and by simulations that exponential data with constant percentage errors can be logarithmically transformed to allow a simple parameter-bias-removal procedure.A more-general bias-reduction approach combining direct and inversion fitting is also developed.Distributions of fitting-model and error-variance-model parameters are shown to be typically non-normal, thus invalidating the usual estimates of parameter bias and precision.Errors in conventional confidence-interval estimates are quantified by comparison with accurate simulation results.     

Disabled or differently-enabled? Dyslexic identities in online forum postings

This study presents a novel exploration into how people with dyslexia construct personal identities within anonymous, unsolicited, postings to an online discussion forum. An interpretational phenomenological analysis suggested three key identities: learning-disabled, differently-enabled and societally-disabled. These are discussed in terms of the extent to which they draw differentially on a discourse of disability as opposed to one of individual difference. The identities are to an extent malleable and overlapping according to context. Postings suggested overall that while some contributors constructed themselves as differently-enabled and celebrated dyslexia-related abilities, others sensed themselves having a disabled identity imposed upon them. Dyslexia is perceived as negatively construed within a society which promotes literacy and cognitive acuity as essential aspects of educational and social competence and where learning differences are poorly tolerated. In addition, this study highlights the potential of online forum contributions in the study of social influences in under-researched groups.     

Citing history

ABSTRACT

Although rarely considered within the existing scholarship on social movements, even a cursory analysis of protest activity suggests that movements regularly invoke historical citations (whether consciously or not) while working to clarify aims and mobilize constituencies. In order to make sense of this process, and to account for the variations that arise among the different citation modalities favored by movements on opposite ends of the political spectrum, I draw upon the theoretical contributions of Marxist cultural critic Walter Benjamin and, in particular, on his exploration of ‘wish images’ and ‘dialectical images,’ their attributes, and their interrelationship. According to Benjamin, such images summoned the past either to project visions of future happiness (as with the wish image) or to deposit the witness before a moment of decisive, present-tense reckoning. After outlining the role of historical citation in social movements and in the broader cultural field through which these movements find expression, I analyze two recent protest events – the ‘Unite the Right’ rally in Charlottesville, VA, in which wish images were actively deployed, and the 2017 Women’s Strike in New York City, where a dialectical image arose from the constellated nodes of the march’s route – to consider the relationship between citation modality and protest outcome. Following from this analysis, and in keeping with the unapologetically partisan nature of my investigation, I conclude by advancing some strategic recommendations for movements seeking – as Benjamin once enjoined – to ‘improve our position in the struggle against Fascism.’