基于性别的青少年在智能语音助手中的隐私保护行为异质性：多组PLS-SEM的实证研究
Gender-Based Heterogeneity in Youth Privacy-Protective Behavior for Smart Voice Assistants: Evidence from Multigroup PLS-SEM
AI总结：
本文研究性别如何影响青少年在智能语音助手生态系统中的隐私决策，通过多组PLS-SEM分析发现性别在隐私路径中存在调节作用，揭示了性别对隐私保护行为的影响差异。
摘要：
本文探讨性别如何塑造青少年在智能语音助手（SVA）生态系统中的隐私决策。利用469名加拿大16-24岁青少年的调查数据，应用多组偏最小二乘结构方程模型，比较男性（N=241）和女性（N=174）（总N=415）在五个隐私构念上的差异：感知隐私风险（PPR）、感知隐私益处（PPBf）、算法透明度和信任（ATT）、隐私自我效能（PSE）和隐私保护行为（PPB）。结果提供了性别异质性的探索性证据。PPR对PPB的直接效应在男性中更强（男性：η=0.424；女性：η=0.233；p<0.1），而ATT通过PSE对PPB的间接效应在女性中更强（女性：η=0.229；男性：η=0.132；p<0.1）。非二元（N=15）和不愿回答者（N=39）的描述性分析显示，其信任度较低，感知风险较高，提示未来研究需使用充分powered的性别多样化样本。总体而言，研究结果提供了性别可能调节关键隐私路径的探索性证据，支持更有效的透明度和控制干预措施，以应对青少年SVA使用。
英文摘要：
This paper investigates how gender shapes privacy decision-making in youth smart voice assistant (SVA) ecosystems. Using survey data from 469 Canadian youths aged 16-24, we apply multigroup Partial Least Squares Structural Equation Modeling to compare males (N=241) and females (N=174) (total N = 415) across five privacy constructs: Perceived Privacy Risks (PPR), Perceived Privacy Benefits (PPBf), Algorithmic Transparency and Trust (ATT), Privacy Self-Efficacy (PSE), and Privacy Protective Behavior (PPB). Results provide exploratory evidence of gender heterogeneity in selected pathways. The direct effect of PPR on PPB is stronger for males (Male: \b{eta} = 0.424; Female: \b{eta} = 0.233; p < 0.1), while the indirect effect of ATT on PPB via PSE is stronger for females (Female: \b{eta} = 0.229; Male: \b{eta} = 0.132; p < 0.1). Descriptive analysis of non-binary (N=15) and prefer-not-to-say participants (N=39) shows lower trust and higher perceived risk than the binary groups, motivating future work with adequately powered gender-diverse samples. Overall, the findings provide exploratory evidence that gender may moderate key privacy pathways, supporting more responsive transparency and control interventions for youth SVA use.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
