29 research outputs found

    An Observational Analysis of ‘Me Too’ Narratives from YouTube

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    The ‘me too’ movement originated to help survivors of sexual violence by providing resources and building a community of advocates to exemplify the magnitude of sexual violence victimization. This movement gained momentum via Twitter due to the viral hashtag—#metoo. YouTube is often used as a means of expression in younger generations, thus sexual violence survivors began using the platform as a way to disseminate ‘me too’ narratives. Therefore, this study aimed to examine how sexual violence narratives resulting from the ‘me too’ movement are being told on YouTube and understand the components of the narratives related to self-blaming mindsets. Based on predetermined search criteria, researchers identified and screened YouTube videos of people sharing ‘me too’ narratives, and developed themes and codes (e.g., type of violence, perpetrator characteristics). Descriptive statistics and a logistic regression were conducted using demographic, experience, and attitudinal data to predict self-blaming mindsets. Sixty-two YouTube videos were included, consisting of 96 individual ‘me too’ stories. The sample was mostly female, and perpetrators were predominately strangers. The model explained 19.3% of the variance in self-blaming attitudes. Odds of self-blaming rose 4.589 times for those who experienced sexual harassment, and 6.109 times for those who experienced rape. If the perpetrator was not mentioned in the video, odds of self-blaming dropped by 89.4%. This study suggests self-blaming beliefs are prominent among victims, even when they have the space to share their story. Overall, our findings support the continued need for further education and support for victims

    Time to Switch to Second-line Antiretroviral Therapy in Children With Human Immunodeficiency Virus in Europe and Thailand.

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    Background: Data on durability of first-line antiretroviral therapy (ART) in children with human immunodeficiency virus (HIV) are limited. We assessed time to switch to second-line therapy in 16 European countries and Thailand. Methods: Children aged <18 years initiating combination ART (≄2 nucleoside reverse transcriptase inhibitors [NRTIs] plus nonnucleoside reverse transcriptase inhibitor [NNRTI] or boosted protease inhibitor [PI]) were included. Switch to second-line was defined as (i) change across drug class (PI to NNRTI or vice versa) or within PI class plus change of ≄1 NRTI; (ii) change from single to dual PI; or (iii) addition of a new drug class. Cumulative incidence of switch was calculated with death and loss to follow-up as competing risks. Results: Of 3668 children included, median age at ART initiation was 6.1 (interquartile range (IQR), 1.7-10.5) years. Initial regimens were 32% PI based, 34% nevirapine (NVP) based, and 33% efavirenz based. Median duration of follow-up was 5.4 (IQR, 2.9-8.3) years. Cumulative incidence of switch at 5 years was 21% (95% confidence interval, 20%-23%), with significant regional variations. Median time to switch was 30 (IQR, 16-58) months; two-thirds of switches were related to treatment failure. In multivariable analysis, older age, severe immunosuppression and higher viral load (VL) at ART start, and NVP-based initial regimens were associated with increased risk of switch. Conclusions: One in 5 children switched to a second-line regimen by 5 years of ART, with two-thirds failure related. Advanced HIV, older age, and NVP-based regimens were associated with increased risk of switch
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