Psychosocial Factors Facilitating Dependence On Anabolic Steroids

调查影响体育运动中对形象和成绩增强药物（IPED）依赖的社会心理因素，特别关注道德脱离（MD;从Bandura的[1991]道德思想和行动的社会认知理论中得出的一系列六种社会心理机制）。在所有三个参与者将通过健身房，体育俱乐部，在线论坛和现有的联系招募。所有参与者将在过去12个月内使用合成代谢类固醇（AS;运动和锻炼参与者中使用最多的IPED），并且年龄在18岁或以上。研究1：纵向研究，旨在确定AS依赖和MD的变化是否介导AS使用变化和AS损害之间的正相关，或者AS依赖和MD的变化是否预示着AS使用的变化。MD和AS依赖的心理测量数据将在18个月内的四个时间点收集，沿着AS使用和AS伤害的数据。将创建匿名在线问卷，以收集每个时间点的数据。调查问卷将通过健身房、体育俱乐部和在线论坛以及过去研究中建立的知名把关人进行传播。研究变量之间的时间关联将使用多级结构方程模型进行检查（参见Stenling et al.，2017).研究2：验证研究开发和验证AS依赖和AS渴望的新措施。将创建每个结构的定义和项目池，并将其发送给专家小组，以确定捕获每个结构的最佳项目，以评估内容有效性。最终确定的项目集将与理论相关变量的测量相结合，以评估新措施的收敛性和判别有效性。包含这些措施的问卷包将由两个样本的AS用户完成，通过在线论坛，健身房，体育俱乐部和既定的看门人招募。AS用户的子样本将被用来评估两个时间点分散4周的AS依赖和AS渴望的最终措施，以检查重测信度。探索性和验证性因素分析将与相关性分析一起使用，以确定最终的项目集及其因素结构（参见Boardley和Kavussanu，2007）。担心下一次剂量、尺寸损失、渴望）。生态瞬时评估将用于在三个12天的时间段内每天三次收集数据;一次在AS周期之前，一次在AS周期中间，一次在AS周期之后（参见Huhn et al. 2016年以阿片类药物依赖为例）。将使用定制的智能手机应用程序收集数据，参与者通过应用程序接收智能手机通知以完成相关的心理测量仪器。研究变量之间的时间关联将使用潜在增长曲线模型进行检查（参见Stenling等人，2017年）。

Investigating psychosocial factors influencing dependency on image and performance enhancing drugs (IPED) in sport and exercise, with a particular focus on moral disengagement (MD; a series of six psychosocial mechanisms drawn from Bandura's [1991] Social Cognitive Theory of Moral Thought and Action).The project includes three studies. Across all three participants will be recruited through gyms, sport clubs, online forums and existing contacts. All participants will have used Anabolic Steroids (AS; the most used IPED amongst sport and exercise participants) during the last 12 months and will be 18 years of age or older. 100-150 participants will be recruited for Study 1, 200-300 for Study 2, and 20-30 for Study 3.Study 1: Longitudinal study aimed at determining whether changes in AS dependence and MD mediate a positive association between changes in AS use and AS harm, or whether changes in AS dependence and MD prelude changes in AS use. Psychometric data on MD and AS dependence will be collected at four time points over an 18-month period, along with data on AS use and AS harm. An anonymous online questionnaire will be created to collect data at each time point. The questionnaire will be disseminated through gyms, sport clubs, and online forums, as well as through known gatekeepers established during past research. Temporal associations among the study variables will be examined using multilevel structural equation modelling (see Stenling et al., 2017).Study 2: Validation study developing and validating new measures for AS dependence and AS craving. Definitions and item pools for each construct will be created and sent to an expert panel to identify the best items to capture each construct, to assess content validity. The finalised item sets will be combined with measures of theoretically associated variables to assess the convergent and discriminant validity of the new measures. Questionnaire packs containing these measures will be completed by two samples of AS users, recruited via online forums, gyms, sports clubs and established gatekeepers. A sub-sample of AS users will be used to assess the final measures of both AS dependence and AS craving over two time points spread 4 weeks apart to examine test-retest reliability. Exploratory and confirmatory factor analysis will be used alongside correlational analyses to determine the final item set and its factor structure (see Boardley and Kavussanu, 2007).Study 3: Longitudinal study investigating associations between changes in MD, mood, AS dependence, and thoughts about AS use (e.g., worries about next dose, loss of size, cravings) during and outside of AS-use cycles. Ecological momentary assessment will be used to collect data three times per day across three 12-day periods; once immediately prior to an AS cycle, once in the middle of an AS cycle, and once immediately following an AS cycle (see Huhn et al., 2016 for an example with opioid dependence). Data will be collected using a bespoke smartphone application, with participants receiving smartphone notifications to complete relevant psychometric instruments via the application. Temporal associations among the study variables will be examined using latent growth-curve modelling (see Stenling et al., 2017).