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      Effect of a Popular Web Drama Video Series on HIV and Other Sexually Transmitted Infection Testing Among Gay, Bisexual, and Other Men Who Have Sex With Men in Singapore: Community-Based, Pragmatic, Randomized Controlled Trial


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          Gay, bisexual, and other men who have sex with men (GBMSM) are at disproportionately higher risk of acquiring HIV and other sexually transmitted infections (STI). While HIV/STI testing rates among GBMSM are increasing worldwide, they remain suboptimal in a variety of settings. While many studies have attempted to evaluate the efficacy of a variety of community-based campaigns, including peer and reminder-based interventions on HIV/STI testing, however few have attempted to do so for a web drama series.


          This study evaluates the effectiveness of a popular web drama video series developed by a community-based organization in Singapore for GBMSM on HIV and other STI testing behaviors.


          The study is a pragmatic, randomized controlled trial to evaluate a popular web drama video series developed by a community-based organization in Singapore for GBMSM. A total of 300 HIV-negative, GBMSM men in Singapore aged 18 to 29 years old were recruited and block-randomized into the intervention (n=150) and control arms (n=150). Primary outcomes included changes in self-reported intention to test for, actual testing for, and regularity of testing for HIV, syphilis, chlamydia or gonorrhea, while secondary outcomes include changes in a variety of other knowledge-based and psychosocial measures at the end of the study period.


          Overall, 83.3% (125/150) of participants in the intervention arm completed the proof of completion survey, compared to 88.7% (133/150) in the control arm. We found improvements in self-reporting as a regular (at least yearly) tester for HIV (15.9% difference, 95% CI, 3.2% to 28.6%; P=.02), as well as chlamydia or gonorrhea (15.5% difference, 95% CI, 4.2% to 26.9%; P=.009), indicating that the intervention had positively impacted these outcomes compared to the control condition. We also found improvements in participants’ intentions to test for HIV (16.6% difference, 95% CI, 4.3% to 28.9%; P=.009), syphilis (14.8% difference, 95% CI, 3.2% to 26.4%; P=.01), as well as chlamydia or gonorrhea (15.4% difference, 95% CI, 4.2% to 26.6%; P=.008), in the next 3 months, indicating that the intervention was effective in positively impacting intention for HIV and other STI testing among participants.


          There are clear benefits for promoting intentions to test regularly and prospectively on a broad scale through this intervention. This intervention also has potential to reach GBMSM who may not have access to conventional HIV and other STI prevention messaging, which have typically been implemented at sex-on-premises venues, bars, clubs, and in sexual health settings frequented by GBMSM. When coupled with community or population-wide structural interventions, the overall impact on testing will likely be significant.

          Trial Registration

          ClinicalTrials.gov NCT04021953; https://clinicaltrials.gov/ct2/show/NCT04021953

          International Registered Report Identifier (IRRID)


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          Most cited references43

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          Measuring community connectedness among diverse sexual minority populations.

          Theory and research agree that connectedness to the lesbian, gay, bisexual, and transgender (LGBT) community is an important construct to account for in understanding issues related to health and well-being among gay and bisexual men. However, the measurement of this construct among lesbian and bisexual women or racial and ethnic minority individuals has not yet been adequately investigated. This study examined the reliability and validity of an existing measure of connectedness to the LGBT Community among a diverse group of sexual minority individuals in New York City, and whether differences in connectedness existed across gender and race or ethnicity. Scores on the measure demonstrated both internal consistency and construct stability across subgroups defined by gender and race or ethnicity. The subgroups did not differ in their mean levels of connectedness, and scores on the measure demonstrated factorial, convergent, and discriminant validity, both generally and within each of the subgroups. Inconsistencies were observed with regard to which scores on the measure demonstrated predictive validity in their associations with indicators of mental health and well-being. The scale is a useful tool for researchers and practitioners interested in understanding the role of community connectedness in the lives of diverse populations of sexual minority individuals.
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            Videos to influence: a systematic review of effectiveness of video-based education in modifying health behaviors.

            This systematic review examines the effectiveness of videos in modifying health behaviors. We searched PubMed (1975-2012), PsycINFO (1975-2012), EMBASE (1975-2012), and CINAHL (1983-2012) for controlled clinical trials that examined the effectiveness of video interventions in changing health behaviors. Twenty-eight studies comprised of 12,703 subjects were included in the systematic review. Video interventions were variably effective for modifying health behaviors depending on the target behaviors to be influenced. Video interventions appear to be effective in breast self-examination, prostate cancer screening, sunscreen adherence, self-care in patients with heart failure, HIV testing, treatment adherence, and female condom use. However, videos have not shown to be effective in influencing addiction behaviors when they are not tailored. Compared to loss-framing, gain-framed messages may be more effective in promoting certain types of health behavior change. Also, video modeling may facilitate learning of new behaviors and can be an important consideration in future video interventions.
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              Is Open Access

              The earth is flat (p > 0.05): significance thresholds and the crisis of unreplicable research

              The widespread use of ‘statistical significance’ as a license for making a claim of a scientific finding leads to considerable distortion of the scientific process (according to the American Statistical Association). We review why degrading p-values into ‘significant’ and ‘nonsignificant’ contributes to making studies irreproducible, or to making them seem irreproducible. A major problem is that we tend to take small p-values at face value, but mistrust results with larger p-values. In either case, p-values tell little about reliability of research, because they are hardly replicable even if an alternative hypothesis is true. Also significance (p ≤ 0.05) is hardly replicable: at a good statistical power of 80%, two studies will be ‘conflicting’, meaning that one is significant and the other is not, in one third of the cases if there is a true effect. A replication can therefore not be interpreted as having failed only because it is nonsignificant. Many apparent replication failures may thus reflect faulty judgment based on significance thresholds rather than a crisis of unreplicable research. Reliable conclusions on replicability and practical importance of a finding can only be drawn using cumulative evidence from multiple independent studies. However, applying significance thresholds makes cumulative knowledge unreliable. One reason is that with anything but ideal statistical power, significant effect sizes will be biased upwards. Interpreting inflated significant results while ignoring nonsignificant results will thus lead to wrong conclusions. But current incentives to hunt for significance lead to selective reporting and to publication bias against nonsignificant findings. Data dredging, p-hacking, and publication bias should be addressed by removing fixed significance thresholds. Consistent with the recommendations of the late Ronald Fisher, p-values should be interpreted as graded measures of the strength of evidence against the null hypothesis. Also larger p-values offer some evidence against the null hypothesis, and they cannot be interpreted as supporting the null hypothesis, falsely concluding that ‘there is no effect’. Information on possible true effect sizes that are compatible with the data must be obtained from the point estimate, e.g., from a sample average, and from the interval estimate, such as a confidence interval. We review how confusion about interpretation of larger p-values can be traced back to historical disputes among the founders of modern statistics. We further discuss potential arguments against removing significance thresholds, for example that decision rules should rather be more stringent, that sample sizes could decrease, or that p-values should better be completely abandoned. We conclude that whatever method of statistical inference we use, dichotomous threshold thinking must give way to non-automated informed judgment.

                Author and article information

                J Med Internet Res
                J Med Internet Res
                Journal of Medical Internet Research
                JMIR Publications (Toronto, Canada )
                May 2022
                6 May 2022
                : 24
                : 5
                : e31401
                [1 ] Saw Swee Hock School of Public Health National University of Singapore and National University Health System Singapore Singapore
                [2 ] University of North Carolina Project–China Guangzhou China
                [3 ] Action for AIDS Singapore Singapore Singapore
                [4 ] Department of Sexually Transmitted Infections Control Clinic National Skin Centre Singapore Singapore
                [5 ] National Skin Centre Singapore Singapore
                [6 ] Behavioral, Epidemiological and Clinical Sciences FHI 360 Durham, NC United States
                [7 ] National Centre for Infectious Diseases Singapore Singapore
                Author notes
                Corresponding Author: Rayner Kay Jin Tan rayner.tan@ 123456u.nus.edu
                Author information
                ©Rayner Kay Jin Tan, Wee Ling Koh, Daniel Le, Sumita Banerjee, Martin Tze-Wei Chio, Roy Kum Wah Chan, Christina Misa Wong, Bee Choo Tai, Mee Lian Wong, Alex R Cook, Mark I-Cheng Chen, Chen Seong Wong. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 06.05.2022.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.

                : 20 June 2021
                : 4 January 2022
                : 9 March 2022
                : 9 April 2022
                Original Paper
                Original Paper

                hiv,sti,testing,health promotion,ehealth,mhealth
                hiv, sti, testing, health promotion, ehealth, mhealth


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