Tablet-based screening of depressive symptoms in quito, ecuador: efficiency in primary care.
Michelle GrunauerDavid SchrockEric E FabaraGabriela JimenezAimee MillerZongshan LaiAmy KilbourneMelvin G McInnisPublished in: International journal of family medicine (2014)
Depression is a frequent yet overlooked occurrence in primary health care clinics worldwide. Depression and related health screening instruments are available but are rarely used consistently. The availability of technologically based instruments in the assessments offers novel approaches for gathering, storing, and assessing data that includes self-reported symptom severity from the patients themselves as well as clinician recorded information. In a suburban primary health care clinic in Quito, Ecuador, we tested the feasibility and utility of computer tablet-based assessments to evaluate clinic attendees for depression symptoms with the goal of developing effective screening and monitoring tools in the primary care clinics. We assessed individuals using the 9-item Patient Health Questionnaire, the Quick Inventory of Depressive Symptoms-Self-Report, the 12-item General Health Questionnaire, the Clinical Global Impression Severity, and a DSM-IV checklist of symptoms. We found that 20% of individuals had a PHQ9 of 8 or greater. There was good correlation between the symptom severity assessments. We conclude that the tablet-based PHQ9 is an excellent and efficient method of screening for depression in attendees at primary health care clinics and that one in five people should be assessed further for depressive illness and possible intervention.
Keyphrases
- primary care
- depressive symptoms
- sleep quality
- healthcare
- psychometric properties
- public health
- social support
- end stage renal disease
- health information
- patient reported
- chronic kidney disease
- randomized controlled trial
- general practice
- risk assessment
- ejection fraction
- patient reported outcomes
- health promotion
- cross sectional
- newly diagnosed
- deep learning
- bipolar disorder
- peritoneal dialysis
- physical activity
- climate change
- artificial intelligence