View source for Summary Statistics

{| class="wikitable sortable"
!Domain
!Variable Name
!Description of Variable 
|'''Description of What it Measures'''
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|[[Passive Data|GPS]]
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|Time  spent at home
|Time  spent at home over the course of a day.
|Home  is the most frequently visited significant location for a person between the  hours of 8pm and 8am each day over the course of follow up. Measured in  minutes.
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|Distance  travelled
|Total  distance travelled over the course of a day.
|Measures  in meters.
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|Radius  of gyration
|Average  radius that a person travels from their center over the course of a day.
|After  converting GPS to xy coordinates, a person's centroid is determined by  averaging the xy coordinates for each place visited over the course of a day,  with weights proportional to the amount of time spent in the location. Next,  the radius of gyration is calculated using a weighted average of the distance  between each place and the centroid, where weights are measured in the same  way. Measured in meters.
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|Maximum  diameter
|Largest  distance between any two places that a person visited in a day.
|Measured  in meters.
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|Maximum  distance from home
|Largest  distance between any places that a person visited in a day and their home.
|Measured  in meters.
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|Number  of significant locations
|Number  of significant visited at any point over the course of a day.
|Significant  locations are determined using K-means clustering on locations that a patient  visits over the course of follow up. Set K=K+1 and repeat clustering until  two significant locations are within 100 meters of one another. Then use the  results from the previous step (K-1) as the total number of significant  locations.
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|Average  flight length
|Average  of the length of all flights (straight line movement) that took place over  the course of a day.
|GPS  is converted into a sequence of flights (straight line movement) and pauses  (time spent stationary).  The average  length of flights (in meters) of the day is reported.
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|Standard  deviation of flight length
|Standard  deviation of the length of all flights (straight line movement) that took  place over the course of a day.
|GPS  is converted into a sequence of flights (straight line movement) and pauses  (time spent stationary). The standard deviation of flights (in meters) of the  day is reported.
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|Average  flight duration
|Average  of the duration of all flights (straight line movement) that took place over  the course of a day.
|GPS  is converted into a sequence of flights (straight line movement) and pauses  (time spent stationary). The average duration of flights (in seconds) over  the course of a day is reported.
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|Standard  deviation of flight duration
|Standard  deviation of the duration of all flights (straight line movement) that took  place over the course of a day.
|GPS  is converted into a sequence of flights (straight line movement) and pauses  (time spent stationary). The standard deviation of duration of flights (in  seconds) over the course of a day is reported.
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|Fraction  of the day spent stationary
|Fraction  of the day spent not moving.
|GPS  is converted into a sequence of flights (straight line movement) and pauses  (time spent stationary). The fraction of the day in a pause is reported.
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|Significant  location entropy
|Entropy  measure based on the proportion of time spent at significant locations over  the course of a day.
|Letting  p_i be the proportion of the day spent at significant location I, significant  location entropy is calculated as -\sum_{i} p_i\log(p_i), where the sum  occurs over all non-zero p_i for that day.
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|Minutes  of GPS data missing
|Number  of minutes of GPS data missing over the course of a day.
|Measured  in minutes.
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|Physical  circadian rhythm
|A  continuous measurement of routine in the interval [0,1] that scores a day  with 0 if there was a complete break from routine and 1 if the person  followed the exact same routine as have in every other day of follow up.
|For  a detailed description of how this measure is calculated, see Canzian and  Musolesi's 2015 paper in the Proceedings of the 2015 ACM International Joint  Conference on Pervasive and Ubiquitous Computing, titled "Trajectories  of depression: unobtrusive monitoring of depressive states by means of  smartphone mobility traces analysis." Their procedure was followed using  30-min increments as a bin size.
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|Physical  circadian rhythm stratified
|A  continuous measurement of routine in the interval [0,1] that scores a day  with 0 if there was a complete break from routine and 1 if the person  followed the exact same routine as have in every other day of follow up.
|Calculated  in the same way as Physical circadian rhythm, except the procedure is  repeated separately for weekends and weekdays.
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|[[Passive Data|Texts]]
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|Number  of outgoing texts
|The  total number of texts sent by the subject.
|Measured  in counts.
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|Total  outgoing text length
|The  total number of characters texted by the subject.
|Measured  in characters.
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|Texting  out-degree
|The  total number of unique subjects to which the subject sent texts.
|Measured  in unique counts.
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|Number  of incoming texts
|The  total number of texts received by the subject.
|Measured  in counts.
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|Total  incoming text length
|The  total number of characters of text received by the subject.
|Measured  in characters.
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|Texting  in-degree
|The  total of unique individuals who texted to the subject.
|Measured  in unique counts.
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|Texting  reciprocity
|The  total number of times a text is received or sent to a unique person and day  without response.
|The  reciprocity of incoming texts is the number of texts sent from a unique  individual to the subject, which is next followed up on the same day with at  least one more text sent from that same individual without a response from  the subject. The reciprocity of outgoing texts is the number of texts  received by the subject from a unique individual, which is next followed up  on the same day with at least one more text sent by the subject to that same  individual without a response from that individual. Texting reciprocity is  the sum of these totals.
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|Texting  responsiveness
|The  mean time before sending a text after a text is received.
|Measured  in hours.
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|[[Passive Data|Calls]]
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|Number  of outgoing calls
|The  total number of outgoing calls initiated by the subject.
|Measured  in counts.
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|Total  outgoing call duration
|The total amount of time spent on calls  initiated by the subject.
|Measured  in minutes.
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|Call  out-degree
|The  total number of unique calls initiated by the subject.
|Measured  in unique counts.
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|Number  of incoming calls
|The  total number of calls received by the subject.
|Measured  in counts.
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|Total  incoming call durations
|The total amount of time spent on calls  received by the subject.
|Measured  in minutes.
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|Call  in-degree
|The  total number of unique calls received by the subject.
|Measured  in unique counts.
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|Call  reciprocity
|The  total number of times a call is received or sent to a unique person and day  without response.
|The  reciprocity of incoming calls is the number of calls sent from a unique  individual to the subject, which is next followed up on the same day with at  least one more call sent from that same individual without a response from  the subject. The reciprocity of outgoing calls is the number of calls  received by the subject from a unique individual, which is next followed up  on the same day with at least one more call sent by the subject to that same  individual without a response from that individual. Call reciprocity is the  sum of these totals.
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|Call  responsiveness
|The  mean time before initiating a call after receiving a call.
|Measured  in hours.
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|[[Passive Data|Accelerometer]]
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|Accelerometer  coverage fraction
|Fraction  of a participant's follow-up time during which accelerometer measurements  have been recorded.
|Follow-up  time is divided into windows of uniform length (e.g. minutes or hours).  The fraction of windows with more than a  set minimum number of accelerometer measurements is reported.
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|Accelerometer  univariate summaries
|A  single accelerometer observation consists of three measurements, one for each  axis of the device.  A univariate  summary combines these measurements into a single interpretable number.  Univariate summaries include the Signal  Magnitude Area (SMA), the Vector Magnitude (VM), and the Sum of Amplitudes  (SA).
|<nowiki>Given  an accelerometer observation (x, y, z), the univariate summaries are  calculated as SMA = |x| + |y| + |z|, VM = (x</nowiki><sup>2</sup> + y<sup>2</sup> + z<sup>2</sup>)<sup>1/2</sup>, and SA = x + y + z.   The unit for each of these summaries is meters-per-second-squared (m/s<sup>2</sup>).
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|Accelerometer  signal variability
|A  measure of the variability of consecutive accelerometer measurements during a  given time window.
|For  the given window of accelerometer observations, univariate summaries are  computed and the corresponding sample variance is reported.
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|Acceleration  direction (Device orientation)
|An  estimate of the direction (x, y, z) in which the phone is accelerating during  a given time window, with respect to the phone's frame of reference.  In many circumstances (e.g. when the phone  is at rest), this direction is directly upward in the Earth's frame of  reference.
|For  accelerometer observations {(x<sub>i</sub>, y<sub>i</sub>, z<sub>i</sub>)} from the given time window, the normalized vector of  (median{x<sub>i</sub>},  median{y<sub>i</sub>},  median{z<sub>i</sub>})  is reported.
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|Device  proximity classification
|A  binary classifciation corresponding to whether the phone is  "on-person" or "off-person" during a window of time.  A phone is considered "on-person"  if the user is carrying it (e.g. in a pocket or handbag) or if the user is  physically interacting with it (e.g. making a phone call or playing a game)  at any point during the window; otherwise the phone is considered  "off-person."
|The  given window of observations is classified as "on-person" when the  accelerometer signal variability exceeds the variability that is expected  from sensor noise.  The window is  classified as "off-person" when the signal variability may be  attributed to sensor noise alone.
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|[[Passive Data|Power State or OS]]
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|Total  screen events
|The  total number of times the screen has been turned on during a given  observation window.
|A  record of times when the phone screen has been turned on or off is obtained  from the phone's operating system.  A  "screen event" occurs when the screen is turned on and subsequently  turned off; the number of such events during the given window is reported.
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|Total  unlock events
|The  total number of times the phone has been unlocked during a given observation  window.
|A  record of times when the phone has been unlocked is obtained from the phone's  operating system; the number of such events during the given window is  reported
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|Total  power events
|The  total number of discreet periods that the phone has been connected to a power  supply during a given observation window.
|A  record of times when the phone has been connected or disconnected from a  power source is obtained from the phone's operating system.  A "power event" occurs when the  phone is connected and subsequently disconntected; the number of such events  during the given window is reported.
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|Multiple Domains
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|Sleep  onset time
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|A  longitudinal model computes the distribution of sleep onset timing per day  according to a parametric model. This model is then combined with daily  activity data to compute the most likely time for that day's sleeping onset.
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|Awake  onset time
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|A  longitudinal model computes the distribution of awaking onset timing per day  according to a parametric model. This model is then combined with daily  activity data to compute the most likely time for that day's waking onset.
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|Sleep  duration
|The  total amount of time estimated to be asleep.
|The  sleep awake time subtracted by the sleep onset time.
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