کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
8691139 1581348 2017 32 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Insomnia heterogeneity: Characteristics to consider for data-driven multivariate subtyping
ترجمه فارسی عنوان
ناهمگونی بی خوابی: ویژگی هایی که برای زیرتایوی چند متغیره تحت هدایت داده قرار می گیرند
کلمات کلیدی
بیخوابی، زیرمجموعه، فنوتیپ، اینترنت، پرسشنامه ها، صفات، رویدادهای زندگی، روش چند متغیره، تجزیه و تحلیل کلاس خوش آمدید، تاریخچه بیماری،
موضوعات مرتبط
علوم زیستی و بیوفناوری علم عصب شناسی عصب شناسی
چکیده انگلیسی
Meta-analyses and systematic reviews have reported surprisingly few consistent insomnia-characteristics with respect to cognitions, mood, traits, history of life events and family history. One interpretation of this limited consistency is that different subtypes of insomnia exist, each with its own specific multivariate profile of characteristics. Because previously unrecognized subtypes will be differentially represented in individual studies and dilute effect sizes of subtype-dependent characteristics of importance, they are unlikely to be reported consistently in individual studies, let alone in meta-analyses. This review therefore aims to complement meta-analyses by listing previously reported psychometric characteristics of insomnia, irrespective of the degree of consistency over studies. The review clearly indicates that characteristics of insomnia may not be limited to sleep. Reports suggest that at least some individuals with insomnia may deviate from people without sleep complaints with respect to demographics, mental and physical health, childhood trauma, life events, fatigue, sleepiness, hyperarousal, hyperactivity, other sleep disorders, lifetime sleep history, chronotype, depression, anxiety, mood, quality of life, personality, happiness, worry, rumination, self-consciousness, sensitivity, dysfunctional beliefs, self-conscious emotion regulation, coping, nocturnal mentation, wake resting-state mentation, physical activity, food intake, temperature perception and hedonic evaluation. The value of this list of characteristics is that 1) internet has now made it feasible to asses them all in a large sample of people suffering from insomnia, and 2) statistical methods like latent class analysis and community detection can utilize them for a truly bottom-up data-driven search for subtypes. The supplement to this review provides a blueprint of this multivariate approach as implemented in the Sleep registry platform (www.sleepregistry.nl), that allows for bottom-up subtyping and fosters cross-cultural comparison and worldwide collaboration on insomnia subtype finding - and beyond.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Sleep Medicine Reviews - Volume 36, December 2017, Pages 71-81
نویسندگان
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