TY - GEN
T1 - The relationship between clinical, momentary, and sensor-based assessment of depression
AU - Saeb, Sohrab
AU - Zhang, Mi
AU - Kwasny, Mary
AU - Karr, Christopher J.
AU - Kording, Konrad
AU - Mohr, David C.
N1 - Publisher Copyright:
© 2015 ICST.
PY - 2015/12/8
Y1 - 2015/12/8
N2 - The clinical assessment of severity of depressive symptoms is commonly performed with standardized self-report questionnaires, most notably the patient health questionnaire (PHQ-9), which are usually administered in a clinic. These questionnaires evaluate symptoms that are stable over time. Ecological momentary assessment (EMA) methods, on the other hand, acquire patient ratings of symptoms in the context of their lives. Today's smartphones allow us to also obtain objective contextual information, such as the GPS location, that may also be related to depression. Considering clinical PHQ-9 scores as ground truth, an interesting question is to what extent the EMA ratings and contextual sensor data can be used as potential predictors of depression. To answer this question, we obtained PHQ-9 scores from 18 participants with a variety of depressive symptoms in our lab, and then collected their EMA and GPS sensor data using their smartphones over a period of two weeks. We analyzed the relationship between GPS sensor features, EMA ratings, and the PHQ-9 scores. While we found a strong correlation between a number of sensor features extracted from the two-week period and the PHQ-9 scores, the other relationships remained non-significant. Our results suggest that depression is better evaluated using long-term sensor-based measurements than the momentary ratings of mental state or short-term sensor information.
AB - The clinical assessment of severity of depressive symptoms is commonly performed with standardized self-report questionnaires, most notably the patient health questionnaire (PHQ-9), which are usually administered in a clinic. These questionnaires evaluate symptoms that are stable over time. Ecological momentary assessment (EMA) methods, on the other hand, acquire patient ratings of symptoms in the context of their lives. Today's smartphones allow us to also obtain objective contextual information, such as the GPS location, that may also be related to depression. Considering clinical PHQ-9 scores as ground truth, an interesting question is to what extent the EMA ratings and contextual sensor data can be used as potential predictors of depression. To answer this question, we obtained PHQ-9 scores from 18 participants with a variety of depressive symptoms in our lab, and then collected their EMA and GPS sensor data using their smartphones over a period of two weeks. We analyzed the relationship between GPS sensor features, EMA ratings, and the PHQ-9 scores. While we found a strong correlation between a number of sensor features extracted from the two-week period and the PHQ-9 scores, the other relationships remained non-significant. Our results suggest that depression is better evaluated using long-term sensor-based measurements than the momentary ratings of mental state or short-term sensor information.
KW - GPS location
KW - PHQ-9
KW - context sensing
KW - depression
KW - ecological momentary assessment
UR - http://www.scopus.com/inward/record.url?scp=84963746461&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84963746461&partnerID=8YFLogxK
U2 - 10.4108/icst.pervasivehealth.2015.259034
DO - 10.4108/icst.pervasivehealth.2015.259034
M3 - Conference contribution
C2 - 26640739
AN - SCOPUS:84963746461
T3 - Proceedings of the 2015 9th International Conference on Pervasive Computing Technologies for Healthcare, PervasiveHealth 2015
SP - 229
EP - 232
BT - Proceedings of the 2015 9th International Conference on Pervasive Computing Technologies for Healthcare, PervasiveHealth 2015
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 9th International Conference on Pervasive Computing Technologies for Healthcare, PervasiveHealth 2015
Y2 - 20 May 2015 through 23 May 2015
ER -