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Mobile-based ecological momentary assessment and intervention: bibliometric analysis

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SUBMITTER: Yin H

PROVIDER: S-EPMC10925651 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature

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Project description:Valid, reliable behavioral data and contextually meaningful interventions are necessary for improved health outcomes. Ecological Momentary Assessment and Intervention (EMAI), which collects data as behaviors occur to deliver real-time interventions, may be more accurate and reliable than retrospective methods. The rapid expansion of mobile technologies in low-and-middle-income countries allows for unprecedented remote data collection and intervention opportunities. However, no previous studies have trialed EMAI in sub-Saharan Africa. We assessed EMAI acceptability and feasibility, including participant retention and response rate, in a prospective, parallel group, randomized pilot trial in Rakai, Uganda comparing behavioral outcomes among adults submitting ecological momentary assessments (EMA) versus EMAI. After training, participants submitted EMA data on five nutrition and health risk behaviors over a 90-day period using a smartphone-based application utilizing prompt-based, participant-initiated, and geospatial coordinate data collection, with study coordinator support and incentives for >50% completion. Included behaviors and associated EMAI-arm intervention messages were selected to pilot a range of EMAI applications. Acceptability was measured on questionnaires. We estimated the association between high response rate and participant characteristics and conducted thematic analysis characterizing participant experiences. Study completion was 48/50 participants. Median prompt response rate was 66.5% (IQR: 60.0%-78.6%). Prior smartphone app use at baseline (aPR 3.76, 95%CI: 1.16-12.17, p = 0.03) and being in the intervention arm (aPR 2.55, 95% CI: 1.01-6.44, p = 0.05) were significantly associated with the top response rate quartile (response to >78.6% of prompts). All participants submitted self-initiated reports, covering all behaviors of interest, including potentially sensitive behaviors. Inconsistent phone charging was the most reported feasibility challenge. In this pilot, EMAI was acceptable and feasible. Response rates were good; additional strategies to improve compliance should be investigated. EMAI using mobile technologies may support improved behavioral data collection and intervention approaches in low and middle-income settings. This approach should be tested in larger studies.

Project description:As mobile devices have become a central part of our daily lives, they are also becoming increasingly important in research. In the medical context, for example, smartphones are used to collect ecologically valid and longitudinal data using Ecological Momentary Assessment (EMA), which is mostly implemented through questionnaires delivered via smart notifications. This type of data collection is intended to capture a patient's condition on a moment-to-moment and longer-term basis. To collect more objective and contextual data and to understand patients even better, researchers can not only use patients' input via EMA, but also use sensors as part of the Mobile Crowdsensing (MCS) approach. In this paper, we examine how researchers have embraced the topic of MCS in the context of EMA through a systematic literature review. This PRISMA-guided review is based on the databases PubMed, Web of Science, and EBSCOhost. It is shown through the results that both EMA research in general and the use of sensors in EMA research are steadily increasing. In addition, most of the studies reviewed used mobile apps to deliver EMA to participants, used a fixed-time prompting strategy, and used signal-contingent or interval-contingent self-assessment as sampling/assessment strategies. The most commonly used sensors in EMA studies are the accelerometer and GPS. In most studies, these sensors are used for simple data collection, but sensor data are also commonly used to verify study participant responses and, less commonly, to trigger EMA prompts. Security and privacy aspects are addressed in only a subset of mHealth EMA publications. Moreover, we found that EMA adherence was negatively correlated with the total number of prompts and was higher in studies using a microinteraction-based EMA (μEMA) approach as well as in studies utilizing sensors. Overall, we envision that the potential of the technological capabilities of smartphones and sensors could be better exploited in future, more automated approaches.

Project description:BackgroundHealthy behaviors are crucial for maintaining a person's health and well-being. The effects of health behavior interventions are mediated by individual and contextual factors that vary over time. Recently emerging smartphone-based ecological momentary interventions (EMIs) can use real-time user reports (ecological momentary assessments [EMAs]) to trigger appropriate support when needed in daily life.ObjectiveThis systematic review aims to assess the characteristics of smartphone-delivered EMIs using self-reported EMAs in relation to their effects on health behaviors, user engagement, and user perspectives.MethodsWe searched MEDLINE, Embase, PsycINFO, and CINAHL in June 2019 and updated the search in March 2020. We included experimental studies that incorporated EMIs based on EMAs delivered through smartphone apps to promote health behaviors in any health domain. Studies were independently screened. The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines were followed. We performed a narrative synthesis of intervention effects, user perspectives and engagement, and intervention design and characteristics. Quality appraisal was conducted for all included studies.ResultsWe included 19 papers describing 17 unique studies and comprising 652 participants. Most studies were quasi-experimental (13/17, 76%), had small sample sizes, and great heterogeneity in intervention designs and measurements. EMIs were most popular in the mental health domain (8/17, 47%), followed by substance abuse (3/17, 18%), diet, weight loss, physical activity (4/17, 24%), and smoking (2/17, 12%). Of the 17 studies, the 4 (24%) included randomized controlled trials reported nonstatistically significant effects on health behaviors, and 4 (24%) quasi-experimental studies reported statistically significant pre-post improvements in self-reported primary outcomes, namely depressive (P<.001) and psychotic symptoms (P=.03), drinking frequency (P<.001), and eating patterns (P=.01). EMA was commonly used to capture subjective experiences as well as behaviors, whereas sensors were rarely used. Generally, users perceived EMIs to be helpful. Common suggestions for improvement included enhancing personalization, multimedia and interactive capabilities (eg, voice recording), and lowering the EMA reporting burden. EMI and EMA components were rarely reported and were not described in a standardized manner across studies, hampering progress in this field. A reporting checklist was developed to facilitate the interpretation and comparison of findings and enhance the transparency and replicability of future studies using EMAs and EMIs.ConclusionsThe use of smartphone-delivered EMIs using self-reported EMAs to promote behavior change is an emerging area of research, with few studies evaluating efficacy. Such interventions could present an opportunity to enhance health but need further assessment in larger participant cohorts and well-designed evaluations following reporting checklists. Future research should explore combining self-reported EMAs of subjective experiences with objective data passively collected via sensors to promote personalization while minimizing user burden, as well as explore different EMA data collection methods (eg, chatbots).Trial registrationPROSPERO CRD42019138739; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=138739.

Project description:BackgroundNew methods for assessing diet in research are being developed to address the limitations of traditional dietary assessment methods. Mobile device-assisted ecological momentary diet assessment (mEMDA) is a new dietary assessment method that has not yet been optimized and has the potential to minimize recall biases and participant burden while maximizing ecological validity. There have been limited efforts to characterize the use of mEMDA in behavioral research settings.ObjectiveThe aims of this study were to summarize mEMDA protocols used in research to date, to characterize key aspects of these assessment approaches, and to discuss the advantages and disadvantages of mEMDA compared with the traditional dietary assessment methods as well as implications for future mEMDA research.MethodsStudies that used mobile devices and described mEMDA protocols to assess dietary intake were included. Data were extracted according to Preferred Reporting of Systematic Reviews and Meta-Analyses and Cochrane guidelines and then synthesized narratively.ResultsThe review included 20 studies with unique mEMDA protocols. Of these, 50% (10/20) used participant-initiated reports of intake at eating events (event-contingent mEMDA), and 50% (10/20) used researcher-initiated prompts requesting that participants report recent dietary intake (signal-contingent mEMDA). A majority of the study protocols (60%, 12/20) enabled participants to use mobile phones to report dietary data. Event-contingent mEMDA protocols most commonly assessed diet in real time, used dietary records for data collection (60%, 6/10), and provided estimates of energy and nutrient intake (60%, 6/10). All signal-contingent mEMDA protocols used a near real-time recall approach with unannounced (ie, random) abbreviated diet surveys. Most signal-contingent protocols (70%, 7/10) assessed the frequency with which (targeted) foods or food groups were consumed. Relatively few (30%, 6/20) studies compared mEMDA with the traditional dietary assessment methods.ConclusionsThis review demonstrates that mEMDA has the potential to reduce participant burden and recall bias, thus advancing the field beyond current dietary assessment methods while maximizing ecological validity.

Project description:IntroductionDigital health interventions are an effective way to treat depression, but it is still largely unclear how patients' individual symptoms evolve dynamically during such treatments. Data-driven forecasts of depressive symptoms would allow to greatly improve the personalisation of treatments. In current forecasting approaches, models are often trained on an entire population, resulting in a general model that works overall, but does not translate well to each individual in clinically heterogeneous, real-world populations. Model fairness across patient subgroups is also frequently overlooked. Personalised models tailored to the individual patient may therefore be promising.MethodsWe investigate different personalisation strategies using transfer learning, subgroup models, as well as subject-dependent standardisation on a newly-collected, longitudinal dataset of depression patients undergoing treatment with a digital intervention ( N=65 patients recruited). Both passive mobile sensor data as well as ecological momentary assessments were available for modelling. We evaluated the models' ability to predict symptoms of depression (Patient Health Questionnaire-2; PHQ-2) at the end of each day, and to forecast symptoms of the next day.ResultsIn our experiments, we achieve a best mean-absolute-error (MAE) of 0.801 (25% improvement) for predicting PHQ-2 values at the end of the day with subject-dependent standardisation compared to a non-personalised baseline ( MAE=1.062 ). For one day ahead-forecasting, we can improve the baseline of 1.539 by 12% to a MAE of 1.349 using a transfer learning approach with shared common layers. In addition, personalisation leads to fairer models at group-level.DiscussionOur results suggest that personalisation using subject-dependent standardisation and transfer learning can improve predictions and forecasts, respectively, of depressive symptoms in participants of a digital depression intervention. We discuss technical and clinical limitations of this approach, avenues for future investigations, and how personalised machine learning architectures may be implemented to improve existing digital interventions for depression.

Project description:BackgroundMemory and learning deficits are among the most impactful and longest-lasting symptoms experienced by people with chronic traumatic brain injury (TBI). Despite the persistence of post-TBI memory deficits and their implications for community reintegration, memory rehabilitation is restricted to short-term care within structured therapy sessions. Technology shows promise to extend memory rehabilitation into daily life and to increase the number and contextual diversity of learning opportunities. Ecological momentary assessment and intervention frameworks leverage mobile phone technology to assess and support individuals' behaviors across contexts and have shown benefits in other chronic conditions. However, few studies have used regular outreach via text messaging for adults with chronic TBI, and none have done so to assess and support memory.ObjectiveThis study aimed to develop and test the usability of memory ecological momentary intervention (MEMI), a text message-based assessment and intervention tool for memory in daily life. MEMI is designed to introduce new information, cue retrieval of the information, and assess learning across time and contexts. We tested MEMI via an iterative, user-centered design process to ready it for a future trial.MethodsWe developed MEMI by leveraging automated text messages for prompts using a REDCap (Research Electronic Data Capture)/Twilio interface linking to the Gorilla web-based behavioral experimental platform. We recruited 14 adults with chronic, moderate-severe TBI from the Vanderbilt Brain Injury Patient Registry to participate in 3 rounds of usability testing: one round of ThinkAloud sessions using the platform and providing real-time feedback to an experimenter (n=4) and 2 rounds of real-world usability testing in which participants used MEMI in their daily lives for a week and provided feedback (n=5/round). We analyzed engagement and quantitative and qualitative user feedback to assess MEMI's usability and acceptability.ResultsParticipants were highly engaged with MEMI, completing an average of 11.8 out of 12 (98%) possible sessions. They rated MEMI as highly usable, with scores on the System Usability Scale across all rounds equivalent to an A+ on a standardized scale. In semistructured interviews, they stated that MEMI was simple and easy to use, that daily retrieval sessions were not burdensome, and that they perceived MEMI as helpful for memory. We identified a few small issues (eg, instruction wording) and made improvements between usability testing rounds.ConclusionsTesting MEMI with adults with chronic TBI revealed that this technology is highly usable and favorably rated for this population. We incorporated feedback regarding users' preferences and plan to test the efficacy of this tool in a future clinical trial.

Project description:BackgroundAn extraordinary increase in mobile phone ownership has revolutionized the opportunities to use mobile health approaches in lower- and middle-income countries (LMICs). Ecological momentary assessment and intervention (EMAI) uses mobile technology to gather data and deliver timely, personalized behavior change interventions in an individual's natural setting. To our knowledge, there have been no previous trials of EMAI in sub-Saharan Africa.ObjectiveTo advance the evidence base for mobile health (mHealth) interventions in LMICs, we conduct a pilot randomized trial to assess the feasibility of EMAI and establish estimates of the potential effect of EMAI on a range of health-related behaviors in Rakai, Uganda.MethodsThis prospective, parallel-group, randomized pilot trial compared health behaviors between adult participants submitting ecological momentary assessment (EMA) data and receiving behaviorally responsive interventional health messaging (EMAI) with those submitting EMA data alone. Using a fully automated mobile phone app, participants submitted daily reports on 5 different health behaviors (fruit consumption, vegetable consumption, alcohol intake, cigarette smoking, and condomless sex with a non-long-term partner) during a 30-day period before randomization (P1). Participants were then block randomized to the control arm, continuing EMA reporting through exit, or the intervention arm, EMA reporting and behavioral health messaging receipt. Participants exited after 90 days of follow-up, divided into study periods 2 (P2: randomization + 29 days) and 3 (P3: 30 days postrandomization to exit). We used descriptive statistics to assess the feasibility of EMAI through the completeness of data and differences in reported behaviors between periods and study arms.ResultsThe study included 48 participants (24 per arm; 23/48, 48% women; median age 31 years). EMA data collection was feasible, with 85.5% (3777/4418) of the combined days reporting behavioral data. There was a decrease in the mean proportion of days when alcohol was consumed in both arms over time (control: P1, 9.6% of days to P2, 4.3% of days; intervention: P1, 7.2% of days to P3, 2.4% of days). Decreases in sex with a non-long-term partner without a condom were also reported in both arms (P1 to P3 control: 1.9% of days to 1% of days; intervention: 6.6% of days to 1.3% of days). An increase in vegetable consumption was found in the intervention (vegetable: 65.6% of days to 76.6% of days) but not in the control arm. Between arms, there was a significant difference in the change in reported vegetable consumption between P1 and P3 (control: 8% decrease in the mean proportion of days vegetables consumed; intervention: 11.1% increase; P=.01).ConclusionsPreliminary estimates suggest that EMAI may be a promising strategy for promoting behavior change across a range of behaviors. Larger trials examining the effectiveness of EMAI in LMICs are warranted.Trial registrationClinicalTrials.gov NCT04375423; https://www.clinicaltrials.gov/ct2/show/NCT04375423.

Project description:BackgroundMobile device-based ecological momentary assessment (mobile-EMA) is increasingly used to collect participants' data in real-time and in context. Although EMA offers methodological advantages, these advantages can be diminished by participant noncompliance. However, evidence on how well participants comply with mobile-EMA protocols and how study design factors associated with participant compliance is limited, especially in the youth literature.ObjectiveTo systematically and meta-analytically examine youth's compliance to mobile-EMA protocols and moderators of participant compliance in clinical and nonclinical settings.MethodsStudies using mobile devices to collect EMA data among youth (age ≤18 years old) were identified. A systematic review was conducted to describe the characteristics of mobile-EMA protocols and author-reported factors associated with compliance. Random effects meta-analyses were conducted to estimate the overall compliance across studies and to explore factors associated with differences in youths' compliance.ResultsThis review included 42 unique studies that assessed behaviors, subjective experiences, and contextual information. Mobile phones were used as the primary mode of EMA data collection in 48% (20/42) of the reviewed studies. In total, 12% (5/42) of the studies used wearable devices in addition to the EMA data collection platforms. About half of the studies (62%, 24/42) recruited youth from nonclinical settings. Most (98%, 41/42) studies used a time-based sampling protocol. Among these studies, most (95%, 39/41) prompted youth 2-9 times daily, for a study length ranging from 2-42 days. Sampling frequency and study length did not differ between studies with participants from clinical versus nonclinical settings. Most (88%, 36/41) studies with a time-based sampling protocol defined compliance as the proportion of prompts to which participants responded. In these studies, the weighted average compliance rate was 78.3%. The average compliance rates were not different between studies with clinical (76.9%) and nonclinical (79.2%; P=.29) and studies that used only a mobile-EMA platform (77.4%) and mobile platform plus additional wearable devices (73.0%, P=.36). Among clinical studies, the mean compliance rate was significantly lower in studies that prompted participants 2-3 times (73.5%) or 4-5 times (66.9%) compared with studies with a higher sampling frequency (6+ times: 89.3%). Among nonclinical studies, a higher average compliance rate was observed in studies that prompted participants 2-3 times daily (91.7%) compared with those that prompted participants more frequently (4-5 times: 77.4%; 6+ times: 75.0%). The reported compliance rates did not differ by duration of EMA period among studies from either clinical or nonclinical settings.ConclusionsThe compliance rate among mobile-EMA studies in youth is moderate but suboptimal. Study design may affect protocol compliance differently between clinical and nonclinical participants; including additional wearable devices did not affect participant compliance. A more consistent compliance-related result reporting practices can facilitate understanding and improvement of participant compliance with EMA data collection among youth.

Project description:BackgroundIndividuals can experience difficulties pursuing their goals amid multiple competing priorities in their environment. Effective goal dynamics require flexible and generalizable pursuit skills. Supporting successful goal pursuit requires a perpetually adapting intervention responsive to internal states.ObjectiveThe purpose of this study was to (1) develop a flexible intervention that can adapt to an individual's changing short to medium-term goals and be applied to their daily life and (2) examine the feasibility and acceptability of the just-in-time adaptive intervention for goal pursuit.MethodsThis study involved 3 iterations to test and systematically enhance all aspects of the intervention. During the pilot phase, 73 participants engaged in an ecological momentary assessment (EMA) over 1 month. After week 1, they attended an intervention training session and received just-in-time intervention prompts during the following 3 weeks. The training employed the Capability, Opportunity, Motivation, and Behavior (COM-B) framework for goal setting, along with mental contrasting with implementation intentions (MCII). Subsequent prompts, triggered by variability in goal pursuit, guided the participants to engage in MCII in relation to their current goal. We evaluated feasibility and acceptability, efficacy, and individual change processes by combining intensive (single-case experimental design) and extensive methods.ResultsThe results suggest that the digital intervention was feasible and acceptable to participants. Compliance with the intervention was high (n=63, 86%). The participants endorsed high acceptability ratings relating to both the study procedures and the intervention. All participants (N=73, 100%) demonstrated significant improvements in goal pursuit with an average difference of 0.495 units in the outcome (P<.001). The results of the dynamic network modeling suggest that self-monitoring behavior (EMA) and implementing the MCII strategy may aid in goal reprioritization, where goal pursuit itself is a driver of further goal pursuit.ConclusionsThis pilot study demonstrated the feasibility and acceptability of a just-in-time adaptive intervention among a nonclinical adult sample. This intervention used self-monitoring of behavior, the COM-B framework, and MCII strategies to improve dynamic goal pursuit. It was delivered via an Ecological Momentary Intervention (EMI) procedure. Future research should consider the utility of this approach as an additional intervention element within psychological interventions to improve goal pursuit. Sustaining goal pursuit throughout interventions is central to their effectiveness and warrants further evaluation.

Project description:BackgroundRecent prevalence data indicates that Pacific Islanders living in the United States have disproportionately high smoking rates when compared to the general populace. However, little is known about the factors contributing to tobacco use in this at-risk population. Moreover, few studies have attempted to determine these factors utilizing technology-based assessment techniques.ObjectiveThe objective was to develop a customized Internet-based Ecological Momentary Assessment (EMA) system capable of measuring cigarette use among Pacific Islanders in Southern California. This system integrated the ubiquity of text messaging, the ease of use associated with mobile phone apps, the enhanced functionality offered by Internet-based Cell phone-optimized Assessment Techniques (ICAT), and the high survey completion rates exhibited by EMA studies that used electronic diaries. These features were tested in a feasibility study designed to assess whether Pacific Islanders would respond to this method of measurement and whether the data gathered would lead to novel insights regarding the intrapersonal, social, and ecological factors associated with cigarette use.Methods20 young adult smokers in Southern California who self-identified as Pacific Islanders were recruited by 5 community-based organizations to take part in a 7-day EMA study. Participants selected six consecutive two-hour time blocks per day during which they would be willing to receive a text message linking them to an online survey formatted for Web-enabled mobile phones. Both automated reminders and community coaches were used to facilitate survey completion.Results720 surveys were completed from 840 survey time blocks, representing a completion rate of 86%. After adjusting for gender, age, and nicotine dependence, feeling happy (P=<.001) or wanting a cigarette while drinking alcohol (P=<.001) were positively associated with cigarette use. Being at home (P=.02) or being around people who are not smoking (P=.01) were negatively associated with cigarette use.ConclusionsThe results of the feasibility study indicate that customized systems can be used to conduct technology-based assessments of tobacco use among Pacific Islanders. Such systems can foster high levels of survey completion and may lead to novel insights for future research and interventions.

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Mobile-based ecological momentary assessment and intervention: bibliometric analysis

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