Prevalence Rates of Mental Disorders in Chilean Prisons

PMCID: PMC371883

Protocol for the saMS trial (supportive adjustment for multiple sclerosis): a randomized controlled trial comparing cognitive behavioral therapy to supportive listening for adjustment to multiple sclerosis

BackgroundMultiple Sclerosis (MS) is an incurable, chronic, potentially progressive and unpredictable disease of the central nervous system. The disease produces a range of unpleasant and debilitating symptoms, which can have a profound impact including disrupting activities of daily living, employment, income, relationships, social and leisure activities, and life goals. Adjusting to the illness is therefore particularly challenging. This trial tests the effectiveness of a cognitive behavioural intervention compared to supportive listening to assist adjustment in the early stages of MS.MethodsThis is a two arm randomized multi-centre parallel group controlled trial. 122 consenting participants who meet eligibility criteria will be randomly allocated to receive either Cognitive Behavioral Therapy or Supportive Listening. Eight one hour sessions of therapy (delivered over a period of 10 weeks) will be delivered by general nurses trained in both treatments. Self-report questionnaire data will be collected at baseline (0 weeks), mid-therapy (week 5 of therapy), post-therapy (15 weeks) and at six months (26 weeks) and twelve months (52 weeks) follow-up. Primary outcomes are distress and MS-related social and role impairment at twelve month follow-up. Analysis will also consider predictors and mechanisms of change during therapy. In-depth interviews to examine participants’ experiences of the interventions will be conducted with a purposively sampled sub-set of the trial participants. An economic analysis will also take place. DiscussionThis trial is distinctive in its aims in that it aids adjustment to MS in a broad sense. It is not a treatment specifically for depression. Use of nurses as therapists makes the interventions potentially viable in terms of being rolled out in the NHS. The trial benefits from incorporating patient input in the development and evaluation stages. The trial will provide important information about the efficacy, cost-effectiveness and acceptability of the interventions as well as mechanisms of psychosocial adjustment.Trial registrationCurrent Controlled Trials ISRCTN91377356<br/

Changes in the Provision of Institutionalized Mental Health Care in Post-Communist Countries

PMCID: PMC3371010This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

Alcohol-related blackouts among college students: impact of low level of response to alcohol, ethnicity, sex, and environmental characteristics

Objective: To explore how a genetically-influenced characteristic (the level of response to alcohol [LR]), ethnicity, and sex relate to environmental and attitudinal characteristics (peer drinking [PEER], drinking to cope [COPE], and alcohol expectancies [EXPECT]) regarding future alcohol-related blackouts (ARBs). Methods: Structural equation models (SEMs) were used to evaluate how baseline variables related to ARB patterns in 462 college students over 55 weeks. Data were extracted from a longitudinal study of heavy drinking and its consequences at a U.S. university. Results: In the SEM analysis, female sex and Asian ethnicity directly predicted future ARBs (beta weights 0.10 and -0.11, respectively), while all other variables had indirect impacts on ARBs through alcohol quantities (beta weights ~ 0.23 for European American ethnicity and low LR, 0.21 for cannabis use and COPE, and 0.44 for PEER). Alcohol quantities then related to ARBs with beta = 0.44. The SEM explained 23% of the variance. Conclusion: These data may be useful in identifying college students who are more likely to experience future ARBs over a 1-year period. They enhance our understanding of whether the relationships of predictors to ARBs are direct or mediated through baseline drinking patterns, information that may be useful in prevention strategies for ARBs

The Cytoplasmic Location of Chicken Mx Is Not the Determining Factor for Its Lack of Antiviral Activity

Chicken Mx belongs to the Mx family of interferon-induced dynamin-like GTPases, which in some species possess potent antiviral properties. Conflicting data exist for the antiviral capability of chicken Mx. Reports of anti-influenza activity of alleles encoding an Asn631 polymorphism have not been supported by subsequent studies. The normal cytoplasmic localisation of chicken Mx may influence its antiviral capacity. Here we report further studies to determine the antiviral potential of chicken Mx against Newcastle disease virus (NDV), an economically important cytoplasmic RNA virus of chickens, and Thogoto virus, an orthomyxovirus known to be exquisitely sensitive to the cytoplasmic MxA protein from humans. We also report the consequences of re-locating chicken Mx to the nucleus.Chicken Mx was tested in virus infection assays using NDV. Neither the Asn631 nor Ser631 Mx alleles (when transfected into 293T cells) showed inhibition of virus-directed gene expression when the cells were subsequently infected with NDV. Human MxA however did show significant inhibition of NDV-directed gene expression. Chicken Mx failed to inhibit a Thogoto virus (THOV) minireplicon system in which the cytoplasmic human MxA protein showed potent and specific inhibition. Relocalisation of chicken Mx to the nucleus was achieved by inserting the Simian Virus 40 large T antigen nuclear localisation sequence (SV40 NLS) at the N-terminus of chicken Mx. Nuclear re-localised chicken Mx did not inhibit influenza (A/PR/8/34) gene expression during virus infection in cell culture or influenza polymerase activity in A/PR/8/34 or A/Turkey/50-92/91 minireplicon systems.The chicken Mx protein (Asn631) lacks inhibitory effects against THOV and NDV, and is unable to suppress influenza replication when artificially re-localised to the cell nucleus. Thus, the natural cytoplasmic localisation of the chicken Mx protein does not account for its lack of antiviral activity

Queer In AI: A Case Study in Community-Led Participatory AI

Queerness and queer people face an uncertain future in the face of ever more widely deployed and invasive artificial intelligence (AI). These technologies have caused numerous harms to queer people, including privacy violations, censoring and downranking queer content, exposing queer people and spaces to harassment by making them hypervisible, deadnaming and outing queer people. More broadly, they have violated core tenets of queerness by classifying and controlling queer identities. In response to this, the queer community in AI has organized Queer in AI, a global, decentralized, volunteer-run grassroots organization that employs intersectional and community-led participatory design to build an inclusive and equitable AI future. In this paper, we present Queer in AI as a case study for community-led participatory design in AI. We examine how participatory design and intersectional tenets started and shaped this community’s programs over the years. We discuss different challenges that emerged in the process, look at ways this organization has fallen short of operationalizing participatory and intersectional principles, and then assess the organization’s impact. Queer in AI provides important lessons and insights for practitioners and theorists of participatory methods broadly through its rejection of hierarchy in favor of decentralization, success at building aid and programs by and for the queer community, and effort to change actors and institutions outside of the queer community. Finally, we theorize how communities like Queer in AI contribute to the participatory design in AI more broadly by fostering cultures of participation in AI, welcoming and empowering marginalized participants, critiquing poor or exploitative participatory practices, and bringing participation to institutions outside of individual research projects. Queer in AI’s work serves as a case study of grassroots activism and participatory methods within AI, demonstrating the potential of community-led participatory methods and intersectional praxis, while also providing challenges, case studies, and nuanced insights to researchers developing and using participatory methods