fa اثر تعاملی پیچیدگی و تکرار اندازه‌گیری بر شبکه‌‌های ارتباطی: مطالعه‌ای با رویکرد فرا ابعادی چند سطحی روان شناسی شناختی پژوهشي اصیل Research <p dir="rtl" style="line-height:1.3800000000000001; text-align:justify"><span style="font-size:11pt"><span style="line-height:150%"><span style="direction:rtl"><span style="unicode-bidi:embed"><span style="font-family:Arial,sans-serif"><b><span lang="FA" style="font-size:12.0pt"><span style="line-height:150%"><span b="" nazanin="" style="font-family:">مقدمه:</span></span></span></b> <span lang="FA" style="font-size:12.0pt"><span style="line-height:150%"><span b="" nazanin="" style="font-family:">بر اساس چارچوب فراابعادی چندسطحی (</span></span></span><span dir="LTR" lang="EN" style="line-height:150%"><span new="" roman="" style="font-family:" times="">HDML</span></span><span lang="FA" style="font-size:12.0pt"><span style="line-height:150%"><span b="" nazanin="" style="font-family:">)، پیچیدگی یک بُعد تحلیلی کلیدی است که پایداری و پویایی پاسخ‌دهی ارتباطی قراردادی (</span></span></span><span dir="LTR" lang="EN" style="line-height:150%"><span new="" roman="" style="font-family:" times="">AARR</span></span><span lang="FA" style="font-size:12.0pt"><span style="line-height:150%"><span b="" nazanin="" style="font-family:">) را شکل می‌دهد. این مطالعه با هدف بررسی تعامل نظام‌مند پیچیدگی ساختاری و تکرار سنجش بر کارایی و صحت </span></span></span><span dir="LTR" lang="EN" style="line-height:150%"><span new="" roman="" style="font-family:" times="">AARR</span></span> <span lang="FA" style="font-size:12.0pt"><span style="line-height:150%"><span b="" nazanin="" style="font-family:">طراحی شد.</span></span></span><span dir="LTR" lang="EN" style="line-height:150%"><span style="font-family:"Times New Roman",serif"></span></span></span></span></span></span></span><br> <span style="font-size:11pt"><span style="line-height:150%"><span style="direction:rtl"><span style="unicode-bidi:embed"><span style="font-family:Arial,sans-serif"><b><span lang="FA" style="font-size:12.0pt"><span style="line-height:150%"><span b="" nazanin="" style="font-family:">روش‌:</span></span></span></b><span lang="FA" style="font-size:12.0pt"><span style="line-height:150%"><span b="" nazanin="" style="font-family:"> در یک طرح بین گروهی، ۶۰ شرکت‌کننده در دو گروه ۳۰ نفره قرار گرفتند. با کنترل تعامل محرک‌ها، فضای بالینی شبیه‌سازی شد. این شامل ۳۲ مرحله آموزش و آزمون با محرک‌های نمادین جدید (مانند &quot;</span></span></span><span dir="LTR" lang="EN" style="line-height:150%"><span new="" roman="" style="font-family:" times="">)))</span></span><span lang="FA" style="font-size:12.0pt"><span style="line-height:150%"><span b="" nazanin="" style="font-family:">&quot; و &quot;</span></span></span><span dir="LTR" lang="EN" style="line-height:150%"><span new="" roman="" style="font-family:" times="">!!!</span></span><span lang="FA" style="font-size:12.0pt"><span style="line-height:150%"><span b="" nazanin="" style="font-family:">&quot;) و نشانگرهای بافتاری (</span></span></span><span dir="LTR" lang="EN" style="line-height:150%"><span new="" roman="" style="font-family:" times="">OST, UNR, ALB</span></span><span lang="FA" style="font-size:12.0pt"><span style="line-height:150%"><span b="" nazanin="" style="font-family:">) بود. پیچیدگی (پایین، بالا) به‌عنوان یک عامل بین گروهی دستکاری شد و عملکرد در دو نقطه سنجش متوالی (نوبت اول و نوبت دوم) اندازه‌گیری گردید. داده‌ها با استفاده از مدل‌های خطی تعمیم‌یافته آمیخته (</span></span></span><span dir="LTR" lang="EN" style="line-height:150%"><span new="" roman="" style="font-family:" times="">GLMM</span></span><span lang="FA" style="font-size:12.0pt"><span style="line-height:150%"><span b="" nazanin="" style="font-family:">) تحلیل شدند.</span></span></span><span dir="LTR" lang="EN" style="line-height:150%"><span style="font-family:"Times New Roman",serif"></span></span></span></span></span></span></span><br> <span style="font-size:11pt"><span style="line-height:150%"><span style="direction:rtl"><span style="unicode-bidi:embed"><span style="font-family:Arial,sans-serif"><b><span lang="FA" style="font-size:12.0pt"><span style="line-height:150%"><span b="" nazanin="" style="font-family:">یافته‌ها:</span></span></span></b><span lang="FA" style="font-size:12.0pt"><span style="line-height:150%"><span b="" nazanin="" style="font-family:"> برای زمان پاسخ، یک اثر تعامل معنادار بین نقطه سنجش و پیچیدگی مشاهده شد (۰.۲۶۰ = </span></span></span><span dir="LTR" lang="EN" style="line-height:150%"><span new="" roman="" style="font-family:" times="">&beta;،۰.۰۱ ></span></span> <span dir="LTR" lang="EN" style="line-height:150%"><span new="" roman="" style="font-family:" times="">p</span></span><span lang="FA" style="font-size:12.0pt"><span style="line-height:150%"><span b="" nazanin="" style="font-family:">). تحلیل شیب‌های ساده یک الگوی تقاطعی را نشان داد: در شرایط پیچیدگی پایین، زمان پاسخ از نوبت اول به نوبت دوم افزایش یافت (۳.۸۹ به ۴.۲۸ میلی‌ثانیه). در شرایط پیچیدگی بالا، زمان پاسخ کاهش یافت (۴.۱۲ به ۳.۴۹ میلی‌ثانیه). برای دقت، تنها اثر اصلی معنادار مربوط به نقطه سنجش بود (۱.۲۴۳- = </span></span></span><span dir="LTR" lang="EN" style="line-height:150%"><span new="" roman="" style="font-family:" times="">&beta;، OR = ۰.۲۸۸، ۰.۰۱ > p</span></span><span lang="FA" style="font-size:12.0pt"><span style="line-height:150%"><span b="" nazanin="" style="font-family:">). اثر تعامل برای دقت معنادار نبود (۰.۲۹۱ = </span></span></span><span dir="LTR" lang="EN" style="line-height:150%"><span new="" roman="" style="font-family:" times="">p</span></span><span lang="FA" style="font-size:12.0pt"><span style="line-height:150%"><span b="" nazanin="" style="font-family:">).</span></span></span><span dir="LTR" lang="EN" style="line-height:150%"><span style="font-family:"Times New Roman",serif"></span></span></span></span></span></span></span><br> <span style="font-size:11pt"><span style="line-height:150%"><span style="direction:rtl"><span style="unicode-bidi:embed"><span style="font-family:Arial,sans-serif"><b><span lang="FA" style="font-size:12.0pt"><span style="line-height:150%"><span b="" nazanin="" style="font-family:">نتیجه‌گیری:</span></span></span></b><span lang="FA" style="font-size:12.0pt"><span style="line-height:150%"><span b="" nazanin="" style="font-family:"> یافته‌ها نشان می‌دهند که پیچیدگی ساختاری شبکه، الگوی تغییر کارایی پردازش در طول زمان را به‌طور کیفی تعدیل می‌کند. این الگوی تقاطعی با مفروضات چارچوب </span></span></span><span dir="LTR" lang="EN" style="line-height:150%"><span new="" roman="" style="font-family:" times="">HDML</span></span> <span lang="FA" style="font-size:12.0pt"><span style="line-height:150%"><span b="" nazanin="" style="font-family:">در مورد پیچیدگی همخوانی دارد.</span></span></span><span dir="LTR" lang="EN" style="line-height:150%"><span style="font-family:"Times New Roman",serif"></span></span></span></span></span></span></span></p> <p style="line-height:1.7999999999999998; text-align:justify"><span style="font-size:12pt; font-variant-numeric:normal; font-variant-east-asian:normal; font-variant-alternates:normal; font-variant-position:normal; font-variant-emoji:normal; white-space-collapse:preserve"><span new="" roman="" style="font-family:" times=""><span style="color:#000000"><span style="font-weight:700">Introduction:</span></span></span></span><span style="font-size:12pt; font-variant-numeric:normal; font-variant-east-asian:normal; font-variant-alternates:normal; font-variant-position:normal; font-variant-emoji:normal; white-space-collapse:preserve"><span new="" roman="" style="font-family:" times=""><span style="color:#000000"> Relational Frame Theory (RFT) posits derived relational responding (AARR) as the foundation of language and cognition. The Hyperdimensional, Multilevel (HDML) framework operationalizes complexity as a key dimension influencing AARR. This study examined the interaction between task complexity and repeated measurement on AARR performance within a dynamic paradigm.</span></span></span></p> <p style="line-height:1.2; text-align:justify; margin-top:19px; margin-bottom:19px"><span style="font-size:12pt; font-variant-numeric:normal; font-variant-east-asian:normal; font-variant-alternates:normal; font-variant-position:normal; font-variant-emoji:normal; white-space-collapse:preserve"><span new="" roman="" style="font-family:" times=""><span style="color:#000000"><span style="font-weight:700">Methods:</span></span></span></span><span style="font-size:12pt; font-variant-numeric:normal; font-variant-east-asian:normal; font-variant-alternates:normal; font-variant-position:normal; font-variant-emoji:normal; white-space-collapse:preserve"><span new="" roman="" style="font-family:" times=""><span style="color:#000000"> Sixty participants were tested using the clinical simulation paradigm, including symbolic stimuli (e.g., &quot;</span></span></span><span style="font-size:12pt; font-variant-numeric:normal; font-variant-east-asian:normal; font-variant-alternates:normal; font-variant-position:normal; font-variant-emoji:normal; white-space-collapse:preserve"><span new="" roman="" style="font-family:" times=""><span style="color:#000000"><span style="font-weight:700">)))</span></span></span></span><span style="font-size:12pt; font-variant-numeric:normal; font-variant-east-asian:normal; font-variant-alternates:normal; font-variant-position:normal; font-variant-emoji:normal; white-space-collapse:preserve"><span new="" roman="" style="font-family:" times=""><span style="color:#000000">&quot; and &quot;</span></span></span><span style="font-size:12pt; font-variant-numeric:normal; font-variant-east-asian:normal; font-variant-alternates:normal; font-variant-position:normal; font-variant-emoji:normal; white-space-collapse:preserve"><span new="" roman="" style="font-family:" times=""><span style="color:#000000"><span style="font-weight:700">!!!</span></span></span></span><span style="font-size:12pt; font-variant-numeric:normal; font-variant-east-asian:normal; font-variant-alternates:normal; font-variant-position:normal; font-variant-emoji:normal; white-space-collapse:preserve"><span new="" roman="" style="font-family:" times=""><span style="color:#000000">&quot;) and contextual cues (</span></span></span><span style="font-size:12pt; font-variant-numeric:normal; font-variant-east-asian:normal; font-variant-alternates:normal; font-variant-position:normal; font-variant-emoji:normal; white-space-collapse:preserve"><span new="" roman="" style="font-family:" times=""><span style="color:#000000"><span style="font-weight:700">OST</span></span></span></span><span style="font-size:12pt; font-variant-numeric:normal; font-variant-east-asian:normal; font-variant-alternates:normal; font-variant-position:normal; font-variant-emoji:normal; white-space-collapse:preserve"><span new="" roman="" style="font-family:" times=""><span style="color:#000000">, </span></span></span><span style="font-size:12pt; font-variant-numeric:normal; font-variant-east-asian:normal; font-variant-alternates:normal; font-variant-position:normal; font-variant-emoji:normal; white-space-collapse:preserve"><span new="" roman="" style="font-family:" times=""><span style="color:#000000"><span style="font-weight:700">UNR</span></span></span></span><span style="font-size:12pt; font-variant-numeric:normal; font-variant-east-asian:normal; font-variant-alternates:normal; font-variant-position:normal; font-variant-emoji:normal; white-space-collapse:preserve"><span new="" roman="" style="font-family:" times=""><span style="color:#000000">, </span></span></span><span style="font-size:12pt; font-variant-numeric:normal; font-variant-east-asian:normal; font-variant-alternates:normal; font-variant-position:normal; font-variant-emoji:normal; white-space-collapse:preserve"><span new="" roman="" style="font-family:" times=""><span style="color:#000000"><span style="font-weight:700">ALB</span></span></span></span><span style="font-size:12pt; font-variant-numeric:normal; font-variant-east-asian:normal; font-variant-alternates:normal; font-variant-position:normal; font-variant-emoji:normal; white-space-collapse:preserve"><span new="" roman="" style="font-family:" times=""><span style="color:#000000">), in a between-subjects design. Task complexity (Low vs. High) was manipulated, and performance was assessed across two consecutive measurement points (Set1, Set2). Data from 5,077 trials were analyzed using Generalized Linear Mixed Models (GLMM) with Gamma and Binomial distributions in SPSS.</span></span></span></p> <p style="line-height:1.2; text-align:justify; margin-top:19px; margin-bottom:19px"><span style="font-size:12pt; font-variant-numeric:normal; font-variant-east-asian:normal; font-variant-alternates:normal; font-variant-position:normal; font-variant-emoji:normal; white-space-collapse:preserve"><span new="" roman="" style="font-family:" times=""><span style="color:#000000"><span style="font-weight:700">Results:</span></span></span></span><span style="font-size:12pt; font-variant-numeric:normal; font-variant-east-asian:normal; font-variant-alternates:normal; font-variant-position:normal; font-variant-emoji:normal; white-space-collapse:preserve"><span new="" roman="" style="font-family:" times=""><span style="color:#000000"> For response time (RT), a significant Measurement Point &times; Complexity interaction was observed (&beta; = 0.260, p < .001). Simple slopes analysis revealed a crossover pattern: RT increased from Set1 to Set2 in low-complexity trials (3.89 ms to 4.28 ms) and decreased in high-complexity trials (4.12 ms to 3.49 ms). For accuracy, only the main effect of Measurement Point was significant (&beta; = -1.243, OR = 0.288, p < .001), indicating a general decline at the second measurement. The main effect of Complexity (p = .837) and the interaction (p = .291) were not significant for accuracy.</span></span></span></p> <span style="font-size:12pt; font-variant-numeric:normal; font-variant-east-asian:normal; font-variant-alternates:normal; font-variant-position:normal; font-variant-emoji:normal; white-space-collapse:preserve"><span new="" roman="" style="font-family:" times=""><span style="color:#000000"><span style="font-weight:700">Conclusion:</span></span></span></span><span style="font-size:12pt; font-variant-numeric:normal; font-variant-east-asian:normal; font-variant-alternates:normal; font-variant-position:normal; font-variant-emoji:normal; white-space-collapse:preserve"><span new="" roman="" style="font-family:" times=""><span style="color:#000000"> The crossover interaction for RT indicates that task complexity moderates the effect of repeated measurement on processing efficiency. These findings support the HDML perspective, suggesting that complexity shapes cognitive demand and adaptive potential, and that simple versus complex relational tasks engage distinct adaptive processes over time.</span></span></span> نظریه چارچوب ارتباطی، پاسخ‌دهی ارتباطی قراردادی، چارچوب فراابعادی چندسطحی، پیچیدگی RFT, Relational Frame Theory, HDML, Hyper-Dimensional Multi Level, Complexity, AARR 0 0 http://icssjournal.ir/browse.php?a_code=A-10-2132-1&slc_lang=fa&sid=1 alireza jamaloo علیرضا جمالو Alirezajamalu@gmail.com 100319475328460019713 100319475328460019713 No Kharazmi University دانشگاه خوارزمی Jafar Hasani جعفر حسنی Hasanimehr57@khu.ac.ir 100319475328460019714 100319475328460019714 Yes Kharazmi University دانشگاه خوارزمی Shahram Mohammadkhani شهرام محمدخانی Mohammadkhani@khu.ac.ir 100319475328460019715 100319475328460019715 No Kharazmi University دانشگاه خوارزمی