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Can phone sensors flag how depressed someone is?

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In 28 adults carrying a sensor phone for 2 weeks, less regular GPS movement and more phone use tracked higher PHQ-9 scores; normalized entropy classified any vs no depressive symptoms at 86.5% accuracy.

Source

Mobile Phone Sensor Correlates of Depressive Symptom Severity in Daily-Life Behavior: An Exploratory Study

Saeb S, Zhang M, Karr CJ, et al. · Journal of medical Internet research · 2015

doi.org/10.2196/jmir.4273Read the full paper ↗355 citationscc by

Study at a glance

Design
Cross-sectional — 2-week exploratory sensor study: community adults carried Purple Robot; PHQ-9 at baseline correlated with GPS/usage features
N
N=28 · 40 recruited; 28 with sufficient sensor data (18 GPS, 21 phone usage); 12 excluded for <50% data coverage
Population
US community adults (19–58 years; 20 women, 8 men in the analyzed set) recruited via Craigslist
Outcome
Correlation of GPS/phone-usage features with PHQ-9 severity; classification of PHQ-9 ≥5 vs <5

Structured fields used in claim comparison tables when every cited study has a complete layer.

What they did

Recruited 40 community adults to carry Purple Robot for 2 weeks (GPS every 5 minutes; screen on/off). Baseline PHQ-9 was correlated with GPS features (circadian movement, normalized entropy, location variance) and phone-usage duration/frequency in the 28 people with enough data.

What they found

Circadian movement r=−.63 (P=.005), normalized entropy and location variance each r=−.58 (P=.012). Usage duration r=.54 (P=.011) and frequency r=.52 (P=.015). A normalized-entropy classifier of PHQ-9 ≥5 vs <5 reached 86.5% accuracy; PHQ-9 regression error was 23.5%.

The limits

What it doesn't show

n=28 with a one-time self-report PHQ-9 cannot diagnose clinical depression or prove sensors should replace interviews; 12/40 lacked usable data, so selection bias is possible.

Key terms

PHQ-9
Patient Health Questionnaire-9; self-report depressive-symptom score from 0–27; ≥5 marked any symptoms here.
Circadian movement
How strongly GPS traces follow a 24-hour rhythm; lower values tracked higher PHQ-9 (r=−.63).
Normalized entropy
How evenly time is split across location clusters (0–1); lower values meant sticking to fewer places and tracked depression.
Location variance
Log of GPS latitude+longitude variance; a mobility marker independent of which places were visited.
Purple Robot
Android sensing app that sampled GPS every 5 minutes and logged screen-on usage.
NRMSD
Normalized root-mean-square deviation; percent error when estimating PHQ-9 from a sensor feature (23.5% here).

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Analyzed n was:

Common questions

How many people were analyzed?

28 of 40 recruits (18 GPS, 21 usage).

What PHQ-9 split was used?

≥5 vs <5; 14 people in each group among the 28.

Best GPS correlation?

Circadian movement r=−.63, P=.005.

Classification accuracy?

86.5% using normalized entropy.

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