title: Associations between observed in-home behaviors and self-reported low mood in community-dwelling older adults.
abstract: OBJECTIVE
  To ascertain the association between self-report of low mood and unobtrusively measured behaviors (walking speed, time out of residence, frequency of room transitions, and computer use) in community-dwelling older adults using novel monitoring technologies.
  
  
  METHODS
  Longitudinal cohort study of older adults whose homes were outfitted with activity sensors. Participants completed Internet-based weekly health questionnaires with questions about mood.
  
  
  METHODS
  Apartments and homes of older adults living in the Portland, Oregon, metropolitan area.
  
  
  METHODS
  Adults, average age 84, followed for an average of 3.7 years (n = 157).
  
  
  METHODS
  Mood was assessed according to self-report each week. Walking speed, time spent out of residence, and room transitions were estimated using data from sensors; computer use was measured by timing actual use. The association between global or weekly low mood and the four behavior measures was ascertained, adjusting for baseline characteristics.
  
  
  RESULTS
  Eighteen thousand nine hundred sixty weekly observations of mood were analyzed; 2.6% involved low mood. Individuals who reported low mood more often had no average differences in any behavior parameters from those who reported low mood less often. During weeks when they reported low mood, participants spent significantly less time out of residence and on the computer but showed no change in walking speed or room transitions.
  
  
  CONCLUSIONS
  Low mood in these community-dwelling older adults involved going out of the house less and using the computer less but no consistent changes in movements. Technologies to monitor in-home behavior may have potential for research and clinical care.
authors.affiliation: Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, Washington; Geriatric Research Education and Clinical Center, Seattle Veterans Affairs Medical Center, Seattle, Washington.
authors.forename: Stephen M
authors.initials: SM
authors.lastname: Thielke
authors.forename: Nora C
authors.initials: NC
authors.lastname: Mattek
authors.forename: Tamara L
authors.initials: TL
authors.lastname: Hayes
authors.forename: Hiroko H
authors.initials: HH
authors.lastname: Dodge
authors.forename: Ana R
authors.initials: AR
authors.lastname: Quiñones
authors.forename: Daniel
authors.initials: D
authors.lastname: Austin
authors.forename: Johanna
authors.initials: J
authors.lastname: Petersen
authors.forename: Jeffrey A
authors.initials: JA
authors.lastname: Kaye
mesh_terms: D000203:Activities of Daily Living; D000339:Affect / Q000502:physiology*; D000369:Aged, 80 and over; D005260:Female; D005500:Follow-Up Studies; D015577:Geriatric Assessment / Q000379:methods*; D006801:Humans; D008297:Male; D008991:Monitoring, Physiologic / Q000295:instrumentation*; D009043:Motor Activity / Q000502:physiology; D009922:Oregon; D012111:Residence Characteristics; D012189:Retrospective Studies; D012307:Risk Factors; D040242:Risk Reduction Behavior; D057566:Self Report; D011795:Surveys and Questionnaires; D016138:Walking / Q000502:physiology*
keywords: behaviors; monitoring; mood; psychomotor; sensors; technologies