Possible Application of Ecological Momentary Assessment to Older Adults' Daily Depressive Mood: Integrative Literature Review

Dynamic influence of mood on subjective cognitive complaints in mild cognitive impairment: A time series network analysis approach

OBJECTIVES

Subjective cognitive complaints (SCC) are common and clinically relevant in mild cognitive impairment (MCI) but are intertwined with mood states. Using Ecological Momentary Assessment (EMA) of SCC and network analyses we sought to uncover the links between mood and SCC and how these links may vary by the presence or absence of MCI.

DESIGN

We used EMA to collect intensive longitudinal data. In addition to analyzing the data at an aggregate level to estimate between-person associations of affect and SCC variables, we used time series analyses to estimate contemporaneous and time-lagged relations between the variables.

SETTING

EMA survey and mobile cognitive testing in subjects' natural environments.

PARTICIPANTS

The sample included 100 participants, 48 with Normal Cognition (NC), and 52 with MCI.

MEASUREMENTS

Participants completed 30-day EMA protocols in which surveys sampling SCC and moods were delivered 3 times per day.

RESULTS

The association between SCC (as measured by EMA) and standard in-lab measures of SCC was significant in MCI, but not in NC. Despite no average level differences in severity of SCC, there was a strong association between negative affect (as measured by EMA) with SCC in NCs compared to MCI.

CONCLUSIONS

EMA maybe a useful and valid approach to measuring SCCs in MCI. Network analyses indicated that negative affect was linked with later SCCs. This finding was strong in persons with NC than in persons with MCI. The basis of the attenuated association between negative affect and SCCs in MCI deserves further study.

Ecological momentary assessment in prolonged grief research: Feasibility, acceptability, and measurement reactivity

Ecological momentary assessment (EMA) is a method of data collection that entails prompting individuals to report their experiences (e.g., thoughts, feelings, and behaviors) in real time over the course of their day-to-day lives. By providing rich information about how these experiences unfold over time within an individual, EMA has the potential to substantially advance our understanding of grief. However, there is uncertainty about how bereaved adults will respond to EMA, especially among those with high prolonged grief symptom severity. Accordingly, we evaluated the feasibility and acceptability of an EMA protocol in bereaved adults with low and high prolonged grief severity. Participants completed six 12-item EMA surveys per day on their smartphones for 17 days. Adherence was high (mean survey completion = 90%, median = 96%), and only 6% of participants withdrew. Adherence remained high in those with high prolonged grief symptom severity (mean = 86%; median = 96%). On average, participants reported agreement that survey frequency and length were acceptable. There was no evidence for systematic worsening of symptoms during EMA data collection. Together, these findings suggest that EMA is feasible, acceptable, and safe for bereaved adults, including those with high prolonged grief symptom severity.

Multiple Roads to Success: A Latent Class Analysis on Successful Ageing Among Hong Kong Near-Centenarians and Centenarians (NCC)

Notwithstanding the oldest-old cohort being the fastest-growing population in most ageing societies, characterizing successful ageing in adults of advanced age, such as nonagenarians and centenarians, remains challenging. This study investigated the successful ageing subphenotypes using the data from Hong Kong Centenarian Study 2. Between April 2021 and September 2022, 146 family caregivers of community-dwelling older adults aged 95 or above were interviewed by phone. Latent class analysis identified three classes-Overall Frail (46.6%) with poor mobility, cognitive and functional health, Nonambulant (37.0%) but good functional health, and Robust (16.4%) with overall good health-from 11 indicators based on caregivers' reports. Although we found a low prevalence of fulfillment of all indicators of successful ageing, our findings will help care professionals appreciate the heterogeneity underlying partial successful ageing in this vulnerable cohort for segmented and targeted healthy longevity interventions.

Mobile-based ecological momentary assessment and intervention: bibliometric analysis

Objective

The aim of this article was to review existing documents in the field of mobile-based EMA and EMI, provide an overview of current hot topics, and predict future development trends.

Methods

We conducted a bibliometric study on mobile-based EMA and EMI publications that were collected from the Web of Science Core Collection database. Biblioshiny and CiteSpace were utilized to analyze scientific productions, leading sources, authors, affiliations, documents, research hot topics, keywords, and trend topics.

Results

A total of 2222 documents related to EMA and EMI published between 1992 and 2023 were retrieved. In recent years, scholarly publications have generally increased in mobile-based EMA and EMI research, particularly in the last decade. JMIR mHealth and uHealth (n=86), as well as JMIR (n=73), showed the highest number of publications. The United States (n=1038), Germany (n=218) and Netherlands (n=175) were leading countries. Regarding keyword co-occurrence and trend topics analysis, mental health, health behaviors, and feasibility were hot topics in mobile-based EMA and EMI research. Future research trends included using EMA for tailoring EMI, just-in-time adaptive interventions (JITAI), and digital phenotyping.

Conclusion

This bibliometric study on mobile-based EMA and EMI is a valuable resource for understanding the field's evolution and future trends. Our analysis indicates that EMA and EMI have great potential in health behaviors and mental health, but implementation should consider feasibility and reactivity issues carefully. Emerging trends include EMA-tailored EMI, JITAI, and digital phenotyping. In the future, strengthening multidisciplinary cooperation will be necessary to promote the continued development of the field.

Compliance with ecological momentary assessment programmes in the elderly: a systematic review and meta-analysis

OBJECTIVE

Ecological momentary assessment (EMA) refers to the repeated sampling of information about an individual's symptoms and behaviours, enabling the capture of ecologically meaningful real-time information in a timely manner. Compliance with EMA is critical in determining the validity of an assessment. However, there is limited evidence related to how the elderly comply with EMA programmes or the factors that are associated with compliance.

DESIGN

Systematic review and meta-analysis.

DATA SOURCES

PubMed, Embase, the Cochrane Library and Web of Science were searched up to 17 July 2022.

ELIGIBILITY CRITERIA

We included observational studies on EMA in the elderly reported in English.

DATA EXTRACTION AND SYNTHESIS

Two investigators independently performed screening and data extraction. Discrepancies were resolved by discussion or a third investigator. A systematic review was carried out to characterise the basic characteristics of the participants and EMA programmes. Random-effects meta-analysis was conducted to assess overall compliance and to explore factors associated with differences in compliance among the elderly.

RESULTS

A total of 20 studies with 2047 participants were included in the systematic review and meta-analysis. Meta-analysis showed that the combined compliance rate was 86.41% (95% CI: 77.38% to 92.20%; I²=96.4%; p<0.001). Subgroup analysis revealed high levels of heterogeneity in terms of the methods used to assess population classification, assessment method and assessment frequency, although these may not be the sources of heterogeneity. Meta-regression analysis showed that population classification and assessment period might have a significant impact on heterogeneity (p<0.05). Egger's test indicated significant publication bias (p<0.001).

CONCLUSIONS

Compliance with EMA programmes is high in the elderly. It is recommended that scholars design reasonable EMA programmes according to the health status of the elderly in the future.

A nurse-led mHealth intervention to alleviate depressive symptoms in older adults living alone in the community: A quasi-experimental study

BACKGROUND

The prevalence of geriatric depression has increased worldwide, becoming a major contributor to the burden of health care costs. Geriatric depression is difficult to detect in daily life because of its atypical presentation for each person. Therefore, there is an emerging need to develop personalised mHealth interventions for older adults with depression based on data from an ecological momentary assessment.

OBJECTIVE

To develop and evaluate the effect of a nurse-led mHealth intervention of geriatric depression in older adults living alone.

DESIGN

A quasi-experimental research design was used, and the study followed the transparent reporting of evaluations with a nonrandomised design statement.

SETTING

The nurse-led mHealth intervention was developed and evaluated in a community senior centre in Seoul, Korea.

PARTICIPANTS

Sixty-four older adults living alone with depressive symptoms were recruited between 1 October 2018 and 1 October 2019.

METHODS

Study participants were randomly assigned to the intervention or control groups by drawing lots. In the intervention group, nurses repeatedly assessed older adults' depressive symptoms using an ecological momentary assessment via a mobile tablet. The intervention consisted of weekly sessions, which included (1) standardised mHealth device training, (2) a nurse-led mHealth programme, and (3) art activities. The control group received care as usual. Intra- and inter-group differences were evaluated using paired t-tests and analysis of covariance was used to assess subjective depression symptoms. A linear mixed-model was used to analyse the relationship between groups and momentary scores over time.

RESULTS

The average age of the final sample was 76.2 years (SD = 6.06), 63.6 % (28/44) of whom were female. Compared with the control group (n = 23), the intervention group (n = 21) showed a decreased depression score (t = 4.041, p = .027). There was no statistical difference between the intervention and control groups based on traditional scales and the ecological momentary assessment. However, our data from the ecological momentary assessment captures clear fluctuating patterns across the days during the study, which traditional scales could not measure.

CONCLUSIONS

Most of the older adults successfully participated in a nurse-led mHealth intervention that included multiple components of a non-pharmacological approach to address depression. Mental health nurses should perform critical roles to personalise mHealth activities considering the older adult's autonomy and supportive decision-making, specifically when using high-technological intervention. Future research should maximise the methodological and clinical advantage of an ecological momentary assessment of geriatric depression.

REGISTRATION

Clinical Research Information Service number KCT0005073.

Feasibility, usability and clinical value of intensive longitudinal diary assessments in older persons with cognitive impairment and depressive symptoms

OBJECTIVES

To evaluate the feasibility, usability and clinical value of daily diary assessments combined with actigraphy in older persons with cognitive impairment.

METHODS

For 63 days, patients ≥60 years with cognitive impairments filled out a daily diary (including standardized questionnaires and cognitive test battery), and wore an actiwatch (sleep). After the study, participants and clinicians received personal feedback about patterns and daily triggers of depressive symptoms, sleep and cognitive performance. We assessed feasibility (participation rate, compliance and subjective burden), usability (variability and floor- or ceiling effects) and clinical value for patients and their clinicians (questionnaires).

RESULTS

Of 96 eligible patients, 13 agreed to participate (13.5%). One patient dropped out after 2 days, another after 37 days, and another did not complete the cognitive test battery. Compliance rate was high (6.7-10% missing values). Subjective burden was relatively low. Time-series data showed sufficient variability and no floor- or ceiling effects, except for one relevant ceiling effect on the One Back task. The personal feedback report was considered insightful by 4 out of 11 participants and 5 out of 7 clinicians.

CONCLUSION

Daily assessments are suitable for a minority of cognitively impaired older persons, but is helpful to increase insight into their symptoms.

Digital phenotyping in depression diagnostics: Integrating psychiatric and engineering perspectives

Depression is a serious medical condition and is a leading cause of disability worldwide. Current depression diagnostics and assessment has significant limitations due to heterogeneity of clinical presentations, lack of objective assessments, and assessments that rely on patients' perceptions, memory, and recall. Digital phenotyping (DP), especially assessments conducted using mobile health technologies, has the potential to greatly improve accuracy of depression diagnostics by generating objectively measurable endophenotypes. DP includes two primary sources of digital data generated using ecological momentary assessments (EMA), assessments conducted in real-time, in subjects' natural environment. This includes active EMA, data that require active input by the subject, and passive EMA or passive sensing, data passively and automatically collected from subjects' personal digital devices. The raw data is then analyzed using machine learning algorithms to identify behavioral patterns that correlate with patients' clinical status. Preliminary investigations have also shown that linguistic and behavioral clues from social media data and data extracted from the electronic medical records can be used to predict depression status. These other sources of data and recent advances in telepsychiatry can further enhance DP of the depressed patients. Success of DP endeavors depends on critical contributions from both psychiatric and engineering disciplines. The current review integrates important perspectives from both disciplines and discusses parameters for successful interdisciplinary collaborations. A clinically-relevant model for incorporating DP in clinical setting is presented. This model, based on investigations conducted by our group, delineates development of a depression prediction system and its integration in clinical setting to enhance depression diagnostics and inform the clinical decision making process. Benefits, challenges, and opportunities pertaining to clinical integration of DP of depression diagnostics are discussed from interdisciplinary perspectives.

Ecological Momentary Assessment of Depression in People With Advanced Dementia: Longitudinal Pilot Study

Background

Barriers to assessing depression in advanced dementia include the presence of informant and patient recall biases. Ecological momentary assessment provides an improved approach for mood assessment by collecting observations in intervals throughout the day, decreasing recall bias, and increasing ecological validity.

Objective

This study aims to evaluate the feasibility, reliability, and validity of the modified 4-item Cornell Scale for Depression in Dementia for Momentary Assessment (mCSDD4-MA) tool to assess depression in patients with advanced dementia.

Methods

A intensive longitudinal pilot study design was used. A total of 12 participants with advanced dementia were enrolled from an inpatient psychogeriatric unit. Participants were assessed using clinical depression assessments at admission and discharge. Research staff recorded observations four times a day for 6 weeks on phones with access to the mCSDD4-MA tool. Descriptive data related to feasibility were reported (ie, completion rates). Statistical models were used to examine the interrater reliability and construct and predictive validity of the data.

Results

Overall, 1923 observations were completed, representing 55.06% (1923/3496) of all rating opportunities with 2 raters and 66.01% (1923/2913) with at least one rater. Moderate interrater reliability was demonstrated for all items, except for lack of interest. Moderate correlations were observed between observers and patient-reported outcomes, where observers reported fewer symptoms relative to participants’ self-reports. Several items were associated with and able to predict depression.

Conclusions

The mCSDD4-MA tool was feasible to use, and most items in the tool showed moderate reliability and validity for assessing depression in dementia. Repeated and real-time depression assessment in advanced dementia holds promise for the identification of clinical depression and depressive symptoms.