Co-variation of depressive mood and locomotor dynamics evaluated by ecological momentary assessment in healthy humans
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{"title"=>"Co-Variation of Depressive Mood and Locomotor Dynamics Evaluated by Ecological Momentary Assessment in Healthy Humans", "type"=>"journal", "authors"=>[{"first_name"=>"Jinhyuk", "last_name"=>"Kim", "scopus_author_id"=>"55557315100"}, {"first_name"=>"Toru", "last_name"=>"Nakamura", "scopus_author_id"=>"56719931700"}, {"first_name"=>"Hiroe", "last_name"=>"Kikuchi", "scopus_author_id"=>"25925119400"}, {"first_name"=>"Tsukasa", "last_name"=>"Sasaki", "scopus_author_id"=>"55629396800"}, {"first_name"=>"Yoshiharu", "last_name"=>"Yamamoto", "scopus_author_id"=>"8890139400"}], "year"=>2013, "source"=>"PLoS ONE", "identifiers"=>{"doi"=>"10.1371/journal.pone.0074979", "sgr"=>"84884182458", "issn"=>"19326203", "pui"=>"369822297", "pmid"=>"24058642", "scopus"=>"2-s2.0-84884182458"}, "id"=>"978ef1ce-7066-38f6-abdd-013628535df0", "abstract"=>"Computerized ecological momentary assessment (EMA) is widely accepted as a \"gold standard\" method for capturing momentary symptoms repeatedly experienced in daily life. Although many studies have addressed the within-individual temporal variations in momentary symptoms compared with simultaneously measured external criteria, their concurrent associations, specifically with continuous physiological measures, have not been rigorously examined. Therefore, in the present study, we first examined the variations in momentary symptoms by validating the associations among self-reported symptoms measured simultaneously (depressive mood, anxious mood, and fatigue) and then investigated covariant properties between the symptoms (especially, depressive mood) and local statistics of locomotor activity as the external objective criteria obtained continuously. Healthy subjects (N = 85) from three different populations (adolescents, undergraduates, and office workers) wore a watch-type computer device equipped with EMA software for recording the momentary symptoms experienced by the subjects. Locomotor activity data were also continuously obtained by using an actigraph built into the device. Multilevel modeling analysis confirmed convergent associations by showing positive correlations among momentary symptoms. The increased intermittency of locomotor activity, characterized by a combination of reduced activity with occasional bursts, appeared concurrently with the worsening of depressive mood. Further, this association remained statistically unchanged across groups regardless of group differences in age, lifestyle, and occupation. These results indicate that the temporal variations in the momentary symptoms are not random but reflect the underlying changes in psychophysiological variables in daily life. In addition, our findings on the concurrent changes in depressive mood and locomotor activity may contribute to the continuous estimation of changes in depressive mood and early detection of depressive disorders.", "link"=>"http://www.mendeley.com/research/covariation-depressive-mood-locomotor-dynamics-evaluated-ecological-momentary-assessment-healthy-hum", "reader_count"=>52, "reader_count_by_academic_status"=>{"Unspecified"=>2, "Professor > Associate Professor"=>1, "Librarian"=>1, "Researcher"=>12, "Student > Doctoral Student"=>5, "Student > Ph. D. Student"=>13, "Student > Postgraduate"=>3, "Student > Master"=>8, "Other"=>3, "Student > Bachelor"=>3, "Professor"=>1}, "reader_count_by_user_role"=>{"Unspecified"=>2, "Professor > Associate Professor"=>1, "Librarian"=>1, "Researcher"=>12, "Student > Doctoral Student"=>5, "Student > Ph. D. Student"=>13, "Student > Postgraduate"=>3, "Student > Master"=>8, "Other"=>3, "Student > Bachelor"=>3, "Professor"=>1}, "reader_count_by_subject_area"=>{"Unspecified"=>7, "Agricultural and Biological Sciences"=>1, "Business, Management and Accounting"=>1, "Computer Science"=>8, "Decision Sciences"=>1, "Engineering"=>1, "Nursing and Health Professions"=>2, "Medicine and Dentistry"=>7, "Neuroscience"=>2, "Sports and Recreations"=>1, "Physics and Astronomy"=>2, "Psychology"=>15, "Social Sciences"=>4}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>7}, "Social Sciences"=>{"Social Sciences"=>4}, "Decision Sciences"=>{"Decision Sciences"=>1}, "Sports and Recreations"=>{"Sports and Recreations"=>1}, "Physics and Astronomy"=>{"Physics and Astronomy"=>2}, "Psychology"=>{"Psychology"=>15}, "Unspecified"=>{"Unspecified"=>7}, "Engineering"=>{"Engineering"=>1}, "Neuroscience"=>{"Neuroscience"=>2}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>1}, "Computer Science"=>{"Computer Science"=>8}, "Business, Management and Accounting"=>{"Business, Management and Accounting"=>1}, "Nursing and Health Professions"=>{"Nursing and Health Professions"=>2}}, "reader_count_by_country"=>{"United States"=>1, "Japan"=>1, "Ukraine"=>1, "Italy"=>1, "Germany"=>1}, "group_count"=>12}

Scopus | Further Information

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Figshare

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  • {"files"=>["https://ndownloader.figshare.com/files/1204100"], "description"=>"<p>The estimate of the model coefficient of the predictor: (a) Mean (γ<sub>10</sub>) and (c) Detrended skewness (γ<sub>20</sub>) of the best-fitting model for depressive mood scores (Depressive mood scores<sub><i>ij</i></sub> = γ<sub>00</sub> + γ<sub>10</sub> (Mean<sub><i>ij</i></sub>) + γ<sub>20</sub> (Detrended skewness<sub><i>ij</i></sub>) + ζ<sub>0i</sub> + ζ<sub>1i</sub> (Mean<sub><i>ij</i></sub>) + ε<sub><i>ij</i></sub>) as a function of the location. In panels (a) and (c), the size of the time frame was fixed at 60 min. The same is shown in panels (b) and (d), except for the dependency on the size of the time frame. For evaluation, the location of the time frame was fixed at 0 min; thus, the frame was centered around the EMA recordings. Error bars indicate standard error of the coefficients. The asterisk and dagger indicate significant cases at the 0.05 and 0.10, respectively.</p>", "links"=>[], "tags"=>["best-fitting", "coefficients", "depressive"], "article_id"=>799137, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Jinhyuk Kim", "Toru Nakamura", "Hiroe Kikuchi", "Tsukasa Sasaki", "Yoshiharu Yamamoto"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0074979.g002"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Dependency_of_best_fitting_model_coefficients_for_depressive_mood_on_different_time_frames_/799137", "title"=>"Dependency of best-fitting model coefficients for depressive mood on different time frames.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-09-13 01:47:56"}
  • {"files"=>["https://ndownloader.figshare.com/files/1204107"], "description"=>"<p>Filled circles indicate depressive mood scores (y-axis on the left side) recorded by ecological momentary assessment (EMA) over seven consecutive days. The inset in the upper left represents the watch-type activity monitor equipped with EMA software. The locomotor activity measured simultaneously (zero-crossing counts within every 1 min time interval) is also shown (y-axis on the right side). The periods shaded in gray are times during which the subject was sleeping or had taken off the device.</p>", "links"=>[], "tags"=>["depressive", "locomotor"], "article_id"=>799144, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Jinhyuk Kim", "Toru Nakamura", "Hiroe Kikuchi", "Tsukasa Sasaki", "Yoshiharu Yamamoto"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0074979.g003"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Fluctuation_of_depressive_mood_and_locomotor_activity_in_an_office_worker_/799144", "title"=>"Fluctuation of depressive mood and locomotor activity in an office worker.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-09-13 01:47:56"}

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