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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 郭柏秀 | zh_TW |
| dc.contributor.advisor | Po-Hsiu Kuo | en |
| dc.contributor.author | 張嵐婷 | zh_TW |
| dc.contributor.author | Lan-Ting Chang | en |
| dc.date.accessioned | 2024-02-23T16:13:37Z | - |
| dc.date.available | 2024-02-24 | - |
| dc.date.copyright | 2024-02-23 | - |
| dc.date.issued | 2024 | - |
| dc.date.submitted | 2024-02-06 | - |
| dc.identifier.citation | Marneros, A. (2006). Mood disorders: epidemiology and natural history. Psychiatry, 5(4), 119-122.
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Z., Lee, E. E., Yoon, H. K., Wing, D., Depp, C. A., & Eyler, L. T. (2019). Inaccuracy between subjective reports and objective measures of sleep duration and clinical correlates in bipolar disorder. J Affect Disord, 250, 226-230. https://doi.org/10.1016/j.jad.2019.03.014 Ritter, P. S., Sauer, C., Pfeiffer, S., Bauer, M., & Pfennig, A. (2016). Comparison of Subjective and Objective Sleep Estimations in Patients with Bipolar Disorder and Healthy Control Subjects. Sleep Disord, 2016, 4031535. https://doi.org/10.1155/2016/4031535 Ihler, H. M., Meyrel, M., Hennion, V., Maruani, J., Gross, G., Geoffroy, P. A., Lagerberg, T. V., Melle, I., Bellivier, F., Scott, J., & Etain, B. (2020). Misperception of sleep in bipolar disorder: an exploratory study using questionnaire versus actigraphy. Int J Bipolar Disord, 8(1), 34. https://doi.org/10.1186/s40345-020-00198-x Minaeva, O., Booij, S. H., Lamers, F., Antypa, N., Schoevers, R. A., Wichers, M., & Riese, H. (2020). Level and timing of physical activity during normal daily life in depressed and non-depressed individuals. Transl Psychiatry, 10(1), 259. https://doi.org/10.1038/s41398-020-00952-w Difrancesco, S., Riese, H., Merikangas, K. R., Shou, H., Zipunnikov, V., Antypa, N., van Hemert, A. M., Schoevers, R. A., Penninx, B., & Lamers, F. (2021). Sociodemographic, Health and Lifestyle, Sampling, and Mental Health Determinants of 24-Hour Motor Activity Patterns: Observational Study. J Med Internet Res, 23(2), e20700. https://doi.org/10.2196/20700 Sera, F., Griffiths, L. J., Dezateux, C., Geraci, M., & Cortina-Borja, M. (2017). Using functional data analysis to understand daily activity levels and patterns in primary school-aged children: Cross-sectional analysis of a UK-wide study. PLoS One, 12(11), e0187677. https://doi.org/10.1371/journal.pone.0187677 Hamilton, M. (1960). A rating scale for depression. Journal of neurology, neurosurgery, and psychiatry, 23(1), 56. Young, R. C., Biggs, J. T., Ziegler, V. E., & Meyer, D. A. (1978). A rating scale for mania: reliability, validity and sensitivity. The British journal of psychiatry, 133(5), 429-435. Beck, A. T., Steer, R. A., & Brown, G. (1996). Beck depression inventory–II. Psychological assessment. Buysse, D. J., Reynolds III, C. F., Monk, T. H., Berman, S. R., & Kupfer, D. J. (1989). The Pittsburgh Sleep Quality Index: a new instrument for psychiatric practice and research. Psychiatry research, 28(2), 193-213. Fischer, D., Klerman, E. B., & Phillips, A. J. K. (2021). Measuring sleep regularity: theoretical properties and practical usage of existing metrics. Sleep, 44(10). https://doi.org/10.1093/sleep/zsab103 Armitage, R., Trivedi, M., Hoffmann, R., & Rush, A. J. (1997). Relationship between objective and subjective sleep measures in depressed patients and healthy controls. Depression and Anxiety, 5(2), 97-102. https://doi.org/10.1002/(sici)1520-6394(1997)5:2<97::Aid-da6>3.0.Co;2-2 Tsuchiyama, K., Nagayama, H., Kudo, K., Kojima, K., & Yamada, K. (2003). Discrepancy between subjective and objective sleep in patients with depression. Psychiatry Clin Neurosci, 57(3), 259-264. https://doi.org/10.1046/j.1440-1819.2003.01114.x Xiao, Q., Lu, J., Zeitzer, J. M., Matthews, C. E., Saint-Maurice, P. F., & Bauer, C. (2022). Rest-activity profiles among US adults in a nationally representative sample: a functional principal component analysis. International Journal of Behavioral Nutrition and Physical Activity, 19(1), 32. Ramsay, J. O., Silverman, B. W., and SpringerLink. 2005. Functional data analysis. In Springer series in statistics. New York New York, NY: Springer Springer New York. Wold, S., Esbensen, K., & Geladi, P. (1987). Principal component analysis. Chemometrics and intelligent laboratory systems, 2(1-3), 37-52. | - |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/91836 | - |
| dc.description.abstract | 在情緒疾患中，躁鬱症和重鬱症是最常見的類型，並伴隨有症狀發作。即使在情緒穩定期間，患者仍可能經歷殘留症狀。其中，睡眠障礙和活動變化相對容易測量。除了用於睡眠評估的主觀問卷外，腕動計（Actigraphy）提供了一種測量睡眠、活動和光照暴露的客觀方法。以往的研究顯示，主觀問卷的結果可能受到當前情緒症狀嚴重度、年齡和認知功能等因素的影響，這表明客觀與主觀睡眠評估之間可能存在差異。此外，許多關於日常活動的研究都著重於平均活動量，因而可能忽略了24小時周期內的重要資訊。使用函數主成分分析（Functional Principal Component Analysis）可以更好地理解日常活動的變化我們的研究旨在探討躁鬱症和重鬱症患者以及健康對照組在主觀和客觀睡眠測量之間的差異，以及使用函數主成分分析了解三組的日常活動量。我們共招募了350名參與者（包括145名重鬱症患者、111名躁鬱症患者和94名健康對照組），進行訪談，並連續7天佩戴腕動計與記錄睡眠日誌。研究發現在三組參與者之間的總睡眠時間和入睡潛伏期的主客觀測量中存在差異。此外，函數主成分分析也證明是可以有效區分病例組和健康對照組。 | zh_TW |
| dc.description.abstract | In this study, we examined sleep disturbances and daily activity variations in mood disorders, focusing on bipolar disorder (BD) and major depressive disorder (MDD) compared to healthy controls (HC). Our objective was to investigate differences between objective and subjective sleep measurements and to capture daily activity patterns using functional principal component analysis (fPCA). The study enrolled 350 participants (145 MDD, 111 BD, and 94 HC), who completed interviews, wore actigraphy devices for 7 days, and maintained sleep diaries. We found significant differences in total sleep time and sleep latency between objective and subjective measurements across the three groups. Moreover, fPCA effectively distinguished between case and HC groups, highlighting its utility in analyzing daily motor activity. This research underscores the potential differences in sleep assessments and emphasizes the need for objective measurements in understanding sleep and activity patterns in mood disorders. | en |
| dc.description.provenance | Submitted by admin ntu (admin@lib.ntu.edu.tw) on 2024-02-23T16:13:37Z No. of bitstreams: 0 | en |
| dc.description.provenance | Made available in DSpace on 2024-02-23T16:13:37Z (GMT). No. of bitstreams: 0 | en |
| dc.description.tableofcontents | 誌謝 i
中文摘要 ii ABSTRACT iii Chapter 1 Introduction 1 Chapter 2 Materials & Methods 5 2.1 Participants 5 2.2 Assessment and definition of the seasons 6 2.3 Assessment of demographic and clinical factors 6 2.4 Assessment of sleep parameters from subjective tools 7 2.5 Assessment of sleep measurements from an objective tool 7 2.6 Assessment of nonparametric and Cosinor analysis in activity patterns 8 2.7 Functional Principal Component Analysis (fPCA) in activity patterns 9 2.8 Statistical analysis 10 Chapter 3 Results 11 3.1 The distribution of demographic, clinical in three groups 11 3.2 The distribution of sleep variables in three groups 11 3.3 Differences between objective and subjective sleep variables in three groups 12 3.4 The association of demographic, season, and clinical variables with differences between actigraphy and sleep diary (△sleep variables) 13 3.5 Nonparametric and Cosinor analyses in three groups 14 3.6 Functional principal component analysis (fPCA) 14 3.7 Logistic regression to distinguish diagnosis groups 16 Chapter 4 Discussion 18 4.1 Compared the sleep latency differences measured by actigraphy and PSQI 18 4.2 Compared the total sleep time differences measured by actigraphy and sleep diary 19 4.3 Compared the results of different methods in activity patterns 20 4.4 Strengths and limitations 22 Chapter 5 Conclusion 24 Tables 25 Table 1 Demographic and clinical variables in three groups 25 Table 1 Demographic and clinical variables in three groups (Continued) 26 Table 2-a Sleep variables in three groups (presented in number of participants) 27 Table 2-a Sleep variables in three groups (presented in number of participants) (Continued) 28 Table 2-b Sleep variables in three groups (presented in number of person-day) 29 Table 3 The association of demographic, season, and clinical variables with differences between actigraphy and sleep diary 30 Table 4 The distribution of nonparametric and Cosinor analyses in three groups 31 Table 5 Logistic regression to distinguish diagnosis group with demographic, current mood status and fPC score 32 Figures 33 Figure 1. Flow chart of this study 33 Figure 2. Mean physical activity functions in 350 participants and 3 groups using activity data with 7 days’ average 34 Figure 3. fPC1-4 in 350 participants using activity data with 7 days’ average 35 References 36 Supplementary materials 39 Supplementary Table 1 Demographic and clinical variables in participants who had repeated measured times across different seasons 39 Supplementary Table 2-a Sleep variables in participants who had repeated measured times across different seasons (number in each group included repeated times) 40 Supplementary Table 2-b Sleep variables in participants who had repeated measured times across different seasons (number in each group included repeated times) (continued) 41 Supplementary Table 3 The association of demographic, season, and clinical variables with differences between actigraphy and sleep diary in participants who had repeated measured times across different seasons 42 Supplementary Table 4 Logistic regression to distinguish diagnosis group with demographic, current mood status and fPC score for 93 participants with repeated data across 4 seasons 43 Supplementary Table 5 The distribution of sleep variables among 350 participants in their measured season (presented in number of person-day) 44 Supplementary Figure 1 fPC1-4 in 350 participants with 5-day daily activity data 45 Supplementary Figure 2 Mean physical activity functions across 4 seasons in 350 participants 46 Supplementary Figure 3-a Overall and four-season average daily activity levels for 93 participants with repeated data across 4 seasons 47 Supplementary Figure 3-b Mean physical activity functions for 93 participants categorized into 3 groups 48 Supplementary Figure 3-c fPC1-4 in 93 participants with repeated data across 4 seasons 49 Supplementary Figure 4 Correlation plot of activity parameters 50 Supplementary Figure 5 fPC1-4 of 350 participants in employment and unemployment status 51 Supplementary Figure 6 The scatter plot between fPC scores in 350 participants 52 | - |
| dc.language.iso | en | - |
| dc.subject | 睡眠 | zh_TW |
| dc.subject | 函數主成分分析 | zh_TW |
| dc.subject | 情緒疾患 | zh_TW |
| dc.subject | 腕動計 | zh_TW |
| dc.subject | 活動量 | zh_TW |
| dc.subject | Sleep | en |
| dc.subject | Activity | en |
| dc.subject | Actigraphy | en |
| dc.subject | Functional principal component analysis | en |
| dc.subject | Mood disorders | en |
| dc.title | 探討日常活動模式及主客觀睡眠測量差異與情緒疾患的關係 | zh_TW |
| dc.title | Investigating Daily Motor Activity Patterns and the Differences Between Subjective and Objective Measurements of Sleep Parameters in Mood Disorders | en |
| dc.type | Thesis | - |
| dc.date.schoolyear | 112-1 | - |
| dc.description.degree | 碩士 | - |
| dc.contributor.oralexamcommittee | 陳錫中;蕭朱杏;李文宗 | zh_TW |
| dc.contributor.oralexamcommittee | Hsi-Chung Chen;Chu-Hsing Hsiao;Wen-Chung Lee | en |
| dc.subject.keyword | 情緒疾患,睡眠,腕動計,活動量,函數主成分分析, | zh_TW |
| dc.subject.keyword | Mood disorders,Sleep,Actigraphy,Activity,Functional principal component analysis, | en |
| dc.relation.page | 52 | - |
| dc.identifier.doi | 10.6342/NTU202400616 | - |
| dc.rights.note | 同意授權(限校園內公開) | - |
| dc.date.accepted | 2024-02-06 | - |
| dc.contributor.author-college | 公共衛生學院 | - |
| dc.contributor.author-dept | 流行病學與預防醫學研究所 | - |
| dc.date.embargo-lift | 2029-02-06 | - |
| 顯示於系所單位： | 流行病學與預防醫學研究所 | |
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