Possible Application of Ecological Momentary Assessment to Older Adults’ Daily Depressive Mood: Integrative Literature Review
Bibliographic record
Abstract
BACKGROUND: Ecological momentary assessment is a method of investigating individuals' real-time experiences, behaviors, and moods in their natural environment over time. Despite its general usability and clinical value for evaluating daily depressive mood, there are several methodological challenges when applying ecological momentary assessment to older adults. OBJECTIVE: The aims of this integrative literature review were to examine possible uses of the ecological momentary assessment methodology with older adults and to suggest strategies to increase the feasibility of its application in geriatric depression research and practice. METHODS: We searched 4 electronic databases (MEDLINE, CINAHL, PsycINFO, and EMBASE) and gray literature; we also hand searched the retrieved articles' references. We limited all database searches to articles published in peer-reviewed journals from 2009 to 2019. Search terms were "ecological momentary assessment," "smartphone assessment," "real time assessment," "electronic daily diary," "mHealth momentary assessment," "mobile-based app," and "experience sampling method," combined with the relevant terms of depression. We included any studies that enrolled older adults even as a subgroup and that reported depressive mood at least once a day for more than 2 days. RESULTS: Of the 38 studies that met the inclusion criteria, only 1 study enrolled adults aged 65 years or older as the entire sample; the remainder of the reviewed studies used mixed samples of both younger and older adults. Most of the analyzed studies (18/38, 47%) were quantitative, exploratory (descriptive, correlational, and predictive), and cohort in design. Ecological momentary assessment was used to describe the fluctuating pattern of participants' depressive moods primarily and to examine the correlation between mood patterns and other health outcomes as a concurrent symptom. We found 3 key methodological issues: (1) heterogeneity in study design and protocol, (2) issues with definitions of dropout and adherence, and (3) variation in how depressive symptoms were measured with ecological momentary assessment. Some studies (8/38, 21%) examined the age difference of participants with respect to dropout or poor compliance rate. Detailed participant burden was reported, such as technical problems, aging-related health problems, or discomfort while using the device. CONCLUSIONS: Ecological momentary assessment has been used for comprehensive assessment of multiple mental health indicators in relation to depressive mood. Our findings provide methodological considerations for further studies that may be implemented using ecological momentary assessment to assess daily depressive mood in older adults. Conducting more feasibility studies focusing on older adults with standardized data collection protocols and mixed-methods research is required to reflect users' experiences. Further telepsychiatric evaluation and diagnosis based on ecological momentary assessment data should involve standardized and sophisticated strategies to maximize the potential of ecological momentary assessment for older adults with depression in the community setting.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".