Review
Abstract
Background: Ecological momentary assessment (EMA) is pivotal in longitudinal health research in youth, but potential bias associated with nonparticipation, omitted reports, or dropout threatens its clinical validity. Previous meta-analytic evidence is inconsistent regarding specific determinants of missing data.
Objective: This meta-analysis aimed to update and expand upon previous research by examining key participation metrics—acceptance, compliance, and retention—in youth EMA studies. In addition, it sought to identify potential moderators among sample and design characteristics, with the goal of better understanding and mitigating the impact of missing data.
Methods: We used a bibliographic database search to identify EMA studies involving children and adolescents published from 2001 to November 2023. Eligible studies used mobile-delivered EMA protocols in samples with an average age up to 18 years. We conducted separate meta-analyses for acceptance, compliance, and retention rates, and performed meta-regressions to address sample and design characteristics. Furthermore, we extracted and pooled sample-level effect sizes related to correlates of response compliance. Risk of publication bias was assessed using funnel plots, regression tests, and sensitivity analyses targeting inflated compliance rates.
Results: We identified 285 samples, including 17,441 participants aged 5 to 17.96 years (mean age 14.22, SD 2.24 years; mean percentage of female participants 55.7%). Pooled estimates were 67.27% (k=88, 95% CI 62.39-71.96) for acceptance, 71.97% (k=216, 95% CI 69.83-74.11) for compliance, and 96.57% (k=169, 95% CI 95.42-97.56) for retention. Despite overall poor moderation of participation metrics, acceptance rates decreased as the number of EMA items increased (log-transformed b=−0.115, SE 0.036; 95% CI −0.185 to −0.045; P=.001; R2=19.98), compliance rates declined by 0.8% per year of publication (SE 0.25, 95% CI −1.3 to −0.3; P=.002; R2=4.17), and retention rates dropped with increasing study duration (log-transformed b=−0.061, SE 0.015; 95% CI −0.091 to 0.032; P<.001; R2=10.06). The benefits of monetary incentives on response compliance diminished as the proportion of female participants increased (b=−0.002, SE 0.001; 95% CI −0.003 to −0.001; P=.003; R2=9.47). Within-sample analyses showed a small but significant effect indicating higher compliance in girls compared to boys (k=25; g=0.18; 95% CI 0.06-0.31; P=.003), but no significant age-related effects were found (k=14; z score=0.05; 95% CI −0.01 to 0.16).
Conclusions: Despite a 5-fold increase in included effect sizes compared to the initial review, the variability in rates of missing data that one can expect based on specific sample and design characteristics remains substantial. The inconsistency in identifying robust moderators highlights the need for greater attention to missing data and its impact on study results. To eradicate any health-related bias in EMA studies, researchers should collectively increase transparent reporting practices, intensify primary methodological research, and involve participants’ perspectives on missing data.
Trial Registration: PROSPERO CRD42022376948; https://www.crd.york.ac.uk/PROSPERO/view/CRD42022376948
doi:10.2196/65710
Keywords
Introduction
Background
Contemporary longitudinal health research focusing on youth increasingly uses the collection of self-reports, which are prompted multiple times per day as participants navigate their daily lives. These techniques are collectively known as ecological momentary assessment (EMA), the experience sampling methodology (ESM), and ambulatory assessment (AA), the latter also encompassing data passively collected via sensors []. Initially developed as an ecologically valid instrument to study adolescent development and well-being [], EMA has evolved into a tool for approaching real-time processes by recording momentary snapshots of participants’ daily real-world environments. Today, it is considered as the method of choice for state-of-the-art multivariate modeling frameworks investigating health behaviors [] and psychopathology [,], with affect dynamics being a major area of innovation []. The success of EMA in health research stems from its ability to meet the demands of personalized precision medicine, which requires large amounts of data per person and scalable data collection methods []. Despite its widely recognized benefits in capturing subjective time-series data as participants go about their daily lives, the technical requirement for young participants to complete multiple self-evaluations throughout the day poses significant challenges.
The Importance of Missing Data in EMA Research
One of the critical challenges in EMA studies is to achieve high acceptance, compliance, and retention rates. The acceptance rate, also known as the participation or enrollment rate, represents the percentage of approached individuals who consent to enroll in the study. Throughout this paper, we use the term acceptance rate because this term was initially introduced in the discussion of an earlier meta-analysis on missing data in EMA research []. Response compliance, defined as the proportion of completed self-evaluations relative to the maximum possible within the study protocol, is expressed as a percentage and represents the inverse of missing data on the prompt level [,]. Retention, the opposite of dropout, denotes the percentage of participants who remain engaged throughout the study duration, regardless of their inclusion in subsequent analysis.
Together, these participation metrics capture different forms of missing data at various stages of a study protocol. Nonacceptance (ie, refusing to enroll when invited) results in the absence of an entire time series for a given individual. Compliance rates, which are often reported as sample averages, reflect the proportion of data collected over time from participants who do enroll. Failed retention (ie, dropout) leads to an unplanned truncation of the time series.
When researchers focus solely on data quantity, they may opt to oversample, if unrecruited participants (nonacceptance), missing momentary measures (low compliance), or truncated time series (dropout) do not contain systematically different information. However, if any of these forms of missingness is tied to the underlying phenomena of interest (eg, stress reactivity), these metrics can signal substantial risks to a study’s validity by introducing self-selection bias. This bias may occur when only certain types of participants, perhaps those more resilient or less burdened by the demands of daily assessments, enroll and remain engaged []. Consequently, the observed data may no longer represent the intended spectrum of real-life experiences and obscure the underlying phenomena of interest [], compromising the validity of the research findings.
However, researchers can still investigate clinically relevant selection bias in cases of noncompliance and dropout through missing data analyses, for instance by associating baseline symptom severity with dropout or by correlating compliance rates with the clinical constructs of interest []. If refusal to participate occurs before any screening, missing data analysis becomes more complex [], making nonacceptance the most obscure form of unobserved data in practice.
Furthermore, setting up an EMA study requires balancing the need for sufficient data points with the practicalities and burden of the method []. Therefore, understanding how different aspects of the EMA design and participant characteristics influence participation metrics is crucial. By leveraging this knowledge, researchers can tailor EMA studies to enhance acceptability and engagement among youth, thereby mitigating risks of selection bias and enhancing the integrity of the research findings.
Prior Meta-Analytic Findings
The first meta-analysis on missing data in EMA youth research was conducted by Wen et al [], focusing on EMA delivered via mobile devices. Their systematic literature search and selection process identified 42 studies published up to March 2016. From these, 36 studies reported compliance rates, yielding a pooled estimate of 78.3%. Surprisingly, the tested design factors (ie, study duration, assessment frequency, adjunctive use of wearables, and incentivization strategy) and participant characteristics (ie, age, gender, and clinical status) did not significantly moderate the overall compliance rate []. However, subgroup analyses indicated that higher assessment frequencies led to higher compliance rates in clinical groups; the opposite was true for nonclinical groups, but no such effect was observed for study length.
Researchers conducted further meta-analyses and pooled sample studies, synthesizing data from several hundred studies, either in adult populations [,] or without age restrictions (ie, age-inclusive) [-]. These studies reported similar overall compliance estimates and noted substantial heterogeneity between studies. Such findings on the impact of design factors as the number of EMA items, sampling schedule, and study duration on response rates have been mixed. While individual studies have found that planning more days with EMA [], higher prompt frequency [], and longer surveys [] correlated with lower compliance rates, these effects have not been consistently replicated in other studies [,,,]. Similarly, sample characteristics, such as age [], gender [], and clinical status [] showed significant moderation of compliance rates in individual meta-analyses but not across multiple studies. Moreover, 2 meta-analyses found no significant moderators among sample characteristics [,]. Financial incentives emerged as a relatively consistent moderator, showing benefits for compliance in 3 meta-analyses [,,], although 2 others found no effect [,].
Retention rates have been synthesized in fewer meta-analyses [,,], noting lower retention for psychotic samples [] and higher retention in intervention studies and those with compliance-contingent incentivization []. However, the largest meta-analysis so far found no evidence for any candidate moderator [].
The existing synthesis of evidence holds limited relevance for contemporary EMA research in youth. Much of the data derives from adult studies, the findings of which may not translate directly to youth populations due to developmental differences in motivational systems and responses to incentives [-]. Cross-disciplinary research suggests that youth’s motivation and engagement benefit from playful visual design and gamification [-], as well as from parental involvement []. However, these design enhancements have not yet been subject to meta-analytic synthesis. Furthermore, the rapid expansion of EMA research into diverse populations and technical advancements over the past 7 years necessitates an updated review and meta-analysis that incorporate these evolving design strategies.
This Review and Meta-Analysis Update
We conducted this meta-analysis update following expert consensus guidelines [] and began with consultations with the first author of the initial review to identify significant extensions. Our objectives were to (1) revise the literature search and inclusion process from the prior meta-analysis in youth populations [] to search for previously undetected samples; (2) provide a cumulative meta-analytic update of all available participation metrics, including acceptance and retention rates; and (3) test novel moderators, such as the implementation of gamification and parental involvement. The methodological approaches described in subsequent sections were informed by a careful review of prior work [,-] to address generic biases in meta-analyses [] and biases specific to EMA literature, such as inflated compliance rates.
Methods
Registration and Reporting
This meta-analysis update was registered in PROSPERO (CRD42022376948) in 2022. Reporting of this paper adheres to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 ( contains the PRISMA checklist [].
Literature Search
The research strategy combined 2 concepts—youth as the population and EMA as the intervention. The following bibliographic databases were searched by a medical librarian (JR-A): MEDLINE ALL Ovid, Embase, APA PsycInfo Ovid, CINAHL with Full Text EBSCO, Web of Science Core Collection, and the Cochrane Library Wiley. The search strategies were designed to identify studies using EMA or related methodologies in youth populations. Search equations were adapted for each database to retrieve semantic descriptions of EMA data collection that did not necessarily use prominent key terms related to EMA, ESM, and AA (refer to [-,-] for further details). The databases were searched from 2001 to November 2023. The searches were performed without language restriction. The final search strategies were peer reviewed by another information specialist. provides details regarding the search syntax (field labels, Boolean, and proximity operators), keywords (free text words), and index terms (subject headings) used for each database.
The backward citation search was carried out (JR-A) on a selection of 19 review articles of interest (literature review or systematic reviews), using Citationchaser []. In total, 16 reviews [,-] were found with the database search and 3 [,,] others were known to the research team. While these reviews targeted studies explicitly labeled as EMA, ESM, or AA protocols, their scope included often broader populations beyond youth.
To improve the comprehensiveness of our search strategy, we also examined the included studies from 4 compliance-focused meta-analyses within the backward sources [,-]. While some overlap was anticipated due to methodological similarities, the degree of overlap was limited for various reasons, including differing inclusion criteria. Additional hand-screening of review tables and supplementary data was conducted as bibliographic details in large meta-analytic datasets are often omitted from main articles.
Inclusion and Exclusion Criteria
On the basis of a widely accepted working definition of EMA methodology [], we included surveys collected more than once per day in the natural environment via remote mobile technology and were actively responded to by participants. Eligibility was further defined by a hierarchical list of 12 criteria defining the type of research, sampling characteristics, longitudinal design parameters, the setting, and the modalities of data collection. All eligibility criteria were clarified regarding indications of inclusion versus exclusion (
Textbox 1).
Of note, we accepted publications in any language based on the multilingual composition of the review team and the availability of translation software. Furthermore, study quality was not considered as an a priori criteria of eligibility because there is no well-established consensus on specific criteria of quality in this data collection framework. However, the exclusion criteria in this study limit excessive heterogeneity in data collection methodologies. Furthermore, some design characteristics were excluded that are known to be prone to bias, such as the risk of recall bias that arises in paper-pencil formats of EMA that allow backfilling of missed responses. Compared to the initial review [], we adopted a more inclusive definition of youth [] and included samples with an average age of 18 years. Blinded pairs of raters (KD and students) assessed eligibility based on titles, abstracts, and full texts through incremental working packages, resolving disagreements with one supervisor (ie, either JG or SU).
Inclusion criteria
- Type of publication: report of primary empirical research
- Sample characteristics: human participants; samples of multiple participants; youth (ie, mean age ≤18 years)
- Longitudinal design: time-series data (ie, consecutive assessments across multiple consecutive days); momentary assessments (ie, prompt frequency ≥1 per d on average)
- Setting of data collection: free-living environment (eg, unrestricted daily life and routine clinical settings)
- Modalities of data collection: active-subjective self-reports (adjunctive use of sensors allowed); first-person self-report by youth; automated ecological momentary assessment delivery (eg, prompting tactile surveys and speaking interview bot); structured format (ie, repetition of a fixed catalog of items); digitized mobile data capture
Exclusion criteria
- Type of publication: other article types (eg, reviews, comments, letters to the editors, and conference abstracts)
- Sample characteristics: samples of nonhuman origin, for example, animals; single-case studies; adults (ie, mean age >18 years)
- Longitudinal design: no time series (eg, cross-sectional, pre-post, and panel designs); low-frequent designs (eg, daily-diary or weekly designs)
- Setting of data collection: simulated environments (ie, experimental control of events and environment, eg, Trier-Stress-Test)
- Modalities of data collection: exclusive use of passive-objective data (eg, wearable sensors and phone use logs); parent report or other-person-report; personal phone interviews; free formats (eg, personal diaries) or permanent free choice among formats (eg, item response, free-format report, or sensor-based sampling); paper-pencil format
Data Extraction
To identify unique samples from multiple publications, we detected coauthorship networks which we disentangled by progressively matching information on study identifiers (eg, funding and institutional review board numbers), country, year, and sample size. Studies with distinct groups and sufficient information on participant flow or response compliance were extracted at the group level (refer to Sample identification in [,,-,-]). We extracted information on (1) sample characteristics (eg, age and clinical status); (2) participant flow; (3) general study design; (4) EMA design (eg, study length and prompt frequency); (5) EMA questionnaires; (6) technical implementation of EMA; (7) compliance rates and correlates thereof; and (8) incentivization strategies and participant care. To facilitate reliable extraction, we extended the basic operationalizations of acceptance, compliance, and retention rates provided in the Introduction section of this paper to accommodate deviating but compatible reporting practices in the literature. The detailed operationalizations of all variables are provided in the sections Extraction of Included Variables and Harmonization of Reported Compliance Rates in . Similar to previous large-scale analyses in the field [,], we adapted the extraction process to accommodate the high number of studies and variables to practicable workloads. Following training on 10.1% (26/258) of studies, extractors (KD, VR, and 4 master’s-level students) conducted single extractions reviewed by KD and VR, with modifications logged for regular meetings.
Risk of Bias
In line with previous reviews [,], we did not conduct formal assessments of study quality or risk of bias as per PRISMA guidelines, for two main reasons. First, we considered participation metrics to be minimally affected by publication bias or practices such as p-hacking, because they are rarely the primary outcome of interest. Second, the field lacks a standardized definition of the quality of conducting an EMA study, which cannot be replaced by checklists for reporting an EMA study [,]. Thus, we approached assessment of publication bias [] by visual inspection of funnel plot asymmetry and regression tests with sample size as the predictor [,,]. In addition, we addressed inflated compliance rates from studies reporting compliance only for participants who entered analyses because they met a certain compliance threshold (eg, 70%) []. Therefore, we extracted relevant information to quantify the associated weight of effect sizes and to compare inflated versus uninflated compliance rates [].
Statistical Analyses
Preprocessing steps involved harmonizing reported information on response compliance as the number of completed over the planned EMA surveys to fractions from 0 to 1 (refer to Harmonization of Compliance Metrics in ). For studies reporting central tendency and spread in quantiles, we estimated the arithmetic mean and the SD performing the maximum likelihood approach [] using the R (R Foundation for Statistical Computing) package estmeansd []. Subsequently, we imputed missing SDs using a meta-regression model with squared compliance rate as a predictor [] (refer to Imputation of Missing Sampling Variances in ). We applied the arcsine transformation to acceptance and retention rates to obtain robust variances and to accommodate samples with 100% values [] (refer to Statistical Analyses in for respective equations).
We used random-effects models to obtain pooled overall estimates for acceptance, compliance, and retention. The exploration of heterogeneity was conducted via the Q test []. We identified influential samples by Cook distance larger than the median plus 6 times the IQR of their distribution. Similarly, standardized residuals larger than the 100×(1−0.05/(2×k))th percentile of a standard normal distribution indicated outliers [].
Expecting widespread missingness across reported variables, we conducted separate meta-regressions with single predictors. On the basis of power simulations adapted from previous work [], we required predictor variables to provide at least 40 effect sizes and at least 10 effect sizes per category, targeting a statistical power of 80% for realistic effect sizes at an α level restricted to 0.005 for multiple testing (refer to Power Analyses for Meta-Regressions in for further details). Where appropriate, we combined 2 or more categories to allow for examination of candidate predictors (refer to Extraction of Included Variables in ). The categorical and continuous predictors included in this study are provided in Textbox 2.
We performed logarithmic or exponential transformation of continuous predictors with excessive positive or negative skew above 3.0, respectively. Additional meta-regressions with multiple predictors tested interactions between major participant characteristics (ie, age, gender, and clinical status) and parameters of protocol intensity (ie, number of EMA days, prompt frequency, and number of items), as well as monetary incentives.
We conducted additional random-effects models on within-study correlates of response compliance and between-person comparisons, if at least 10 effect sizes were available for subsequent evaluation of funnel plot asymmetry []. All models were fitted using restricted maximum likelihood estimation techniques with the metafor [] package in R, version 4.3.0 []. Statistical code, materials, and datasets are available via the research compendium [] hosted by the Open Science Framework.
Categorical predictors
- clinical status (2 levels; clinical vs healthy)
- diagnostic domains (2 levels; somatic vs psychiatric)
- treatment status (2 levels; none vs pre-, peri-, or posttreatment setting)
- treatment setting (2 levels; inpatients vs outpatients)
- assessment of symptoms (yes or no)
- signaling schedule (2 levels; fixed vs random)
- enhancement of ecological momentary assessment (EMA) material (2 levels; none or not reported vs visual elements or gamification)
- adjunctive passive recordings (yes or no)
- compliance reinforcement (yes or no)
- training of participants in responding to EMA surveys (yes or no)
- participant care (2 levels; none or remote availability vs active strategies)
- parent involvement (4 levels; no parent involvement, providing sporadic assessments, assisting child EMA, and parallel parent EMA)
Continuous predictors
- mean sample age (in years)
- percentage of female participants (other sex or gender identities were not considered due to infrequent reporting)
- percentage of White participants
- number of days with EMA
- prompt frequency (ie, number of planned surveys per day)
- response duration
- maximum number of items within a single EMA
- amount of monetary incentivization (in US $)
- year of publication
Results
Literature Search and Selection
Results of the literature search and selection process are quantified in the extended PRISMA 2020 [] flow diagram (
Figure 1) with regard to all exclusion criteria (Textbox 1). During the initial title-abstract screening of 4172 records, we excluded 2492 (59.7%) records. We were able to obtain all full texts of the remaining 1680 (40.3%) records. Full-text assessment resulted in the exclusion of roughly two-thirds (n=1139, 67.8%) versus one-third considered eligible for extraction (n=541, 32.2%).
The additional search strategy based on targeted backward citation chasing and screening of published meta-analytic datasets led to title-abstract screening of 669 newly identified records. However, 534 (79.8%) records did not qualify for full-text screening and 5 of the remaining 135 (21.2%) could not be retrieved due to ambiguous bibliographic information. Full-text screening excluded the majority (n=125, 96.2%) of these records contributing only 5 newly identified study reports to the overall included 586 study reports (refer to for alphabetical reference list, and [,,-] for interrater reliability).
Following further deduplication of multiple publications on identical studies, we identified 258 distinct studies covering 285 independent samples [,,-]. With respect to the eligibility criteria of the initial review, our revised search strategy identified 31 additional samples for the initial review period (ie, 2001 to 2016).
Descriptive Summary
The selected studies collectively included 17,441 participants (mean percentage of female participants 55.7%; mean percentage of White participants 60.1%), with average ages spanning from 5 to 17.96 years (mean age 14.22, SD 2.24 years; refer to 
Table 1). Most of the samples were recruited from the United States (169/285, 59.3%). Regarding clinical profiles, 136 (47.7%) samples were recruited from general populations without specific attention to clinical status, 97 (34%) samples met specific diagnostic requirements (eg, via disorder-specific expert interviews []), 8 (2.8%) samples consisted of individuals at risk of developing a condition (eg, according to familial incidence []), and 29 (10.2%) samples qualified as having no disorders (eg, via extensive diagnostic interviews [,]; refer to Table S2 in for complete diagnostic breakdown).
The average prompt frequency was 4.9 per day (SD 5.3 per d, median 4; range 1-57.4) over an average of 18.1 days (SD 28.6 d, median 10; range 1-274). Prompt frequency and number of assessment days showed a negative and statistically significant correlation (r=–0.40, 95% CI −0.50 to −0.29; t256=−6.94; P<.001; Figures S1-S3 in ). The number of items in the EMA questionnaires was reported for slightly over half the investigated samples (154/285, 54%) among which the individual numbers varied widely, with an average of 19.3 items (SD 23.65, median 15; range 1-248). The presented EMA material involved visual design enhancements or elements of gamification in 38 (13.3%) samples. Monetary compensation was noted in 136 (47.7%) samples with an average amount of US $111.4 (SD US $144.5; median 75, range 5-905). The extracted variables can be explored via an interactive shiny app [].
| Characteristic | Study level (K=258), k (%) | Sample level (K=285), k (%) | ||
| General characteristics | ||||
| Year of earliest publication | ||||
| 2001-2009 | 14 (5.4) | 15 (5.3) | ||
| 2010-2019 | 116 (45) | 128 (44.9) | ||
| ≥2020 | 128 (49.6) | 142 (49.8) | ||
| Sample size (n) at enrollment | ||||
| 3-49 | 64 (24.8) | 69 (24.2) | ||
| 50-99 | 36 (14) | 39 (13.7) | ||
| ≥100 | 51 (19.8) | 53 (18.6) | ||
| Not reported | 107 (41.5) | 124 (43.5) | ||
| Sample characteristics | ||||
| Mean sample age (y) | ||||
| 5-12 | 67 (26) | 74 (26) | ||
| ≥13 | 189 (73.3) | 208 (73) | ||
| Not reported | 2 (0.8) | 3 (1.1) | ||
| Gender (% girls) | ||||
| 0-49 | 84 (32.6) | 92 (32.3) | ||
| ≥50 | 165 (64) | 183 (64.2) | ||
| Not reported | 9 (3.5) | 10 (3.5) | ||
| Clinical status | ||||
| Clinical | 83 (32.2) | 97 (34) | ||
| At risk | 7 (2.7) | 8 (2.8) | ||
| Healthy | 20 (7.8) | 29 (10.2) | ||
| Convenience | 124 (48.1) | 136 (47.7) | ||
| Mixed | 24 (9.3) | 15 (5.3) | ||
| Design characteristics | ||||
| Number of EMAadays | ||||
| 1-9 | 117 (45.3) | 131 (46) | ||
| 10-28 | 108 (41.9) | 119 (41.8) | ||
| ≥29 | 28 (10.9) | 29 (10.2) | ||
| Not reported | 5 (1.9) | 6 (2.1) | ||
| Prompt frequency (per d) | ||||
| 1-4 | 159 (61.6) | 172 (60.4) | ||
| ≥5 | 77 (29.8) | 87 (30.5) | ||
| Not reported | 22 (8.5) | 26 (9.1) | ||
| Sampling scheme | ||||
| Fixed sampling | 92 (35.7) | 99 (34.7) | ||
| Random or semirandom sampling | 125 (48.4) | 140 (49.1) | ||
| Not reported | 41 (15.9) | 46 (16.1) | ||
| Number of items | ||||
| 1-19 | 75 (29.1) | 82 (28.8) | ||
| 20-39 | 33 (12.8) | 38 (13.3) | ||
| ≥40 | 11 (4.3) | 11 (3.9) | ||
| Not reported | 139 (53.9) | 154 (54) | ||
| Enhancement of EMA material | ||||
| Gamification | 20 (7.8) | 22 (7.7) | ||
| Visual elements | 13 (5) | 16 (5.6) | ||
| None or not reported | 225 (87.2) | 247 (86.7) | ||
| Type of incentivization | ||||
| Monetary | 116 (45) | 125 (43.9) | ||
| Nonmonetary | 5 (1.9) | 5 (1.8) | ||
| Both | 11 (4.3) | 11 (3.9) | ||
| Not reported | 126 (48.8) | 144 (50.5) | ||
| Monetary incentive (US $) | ||||
| 5-99 | 71 (27.5) | 77 (27) | ||
| ≥100 | 50 (19.4) | 52 (18.2) | ||
| Not reported | 137 (53.1) | 156 (54.7) | ||
| Providing feedback | ||||
| No or not reported | 237 (91.9) | 264 (92.6) | ||
| Feedback | 21 (8.1) | 21 (7.4) | ||
| EMA training | ||||
| Individually; face-to-face | 101 (39.1) | 116 (40.7) | ||
| Grouped sessions | 18 (7) | 21 (7.4) | ||
| Remotely (print or online) | 20 (7.8) | 22 (7.7) | ||
| Multiple | 4 (1.6) | 5 (1.8) | ||
| Not reported | 115 (44.6) | 121 (42.5) | ||
| Parent involvement | ||||
| No involvement | 201 (77.9) | 222 (77.9) | ||
| Some parent reports | 15 (5.8) | 18 (6.3) | ||
| Parents assist child EMA | 21 (8.1) | 23 (8.1) | ||
| Parallel parent EMA | 20 (7.8) | 22 (7.7) | ||
| Outcome characteristics | ||||
| Acceptance rate (%) | ||||
| 21-39 | 12 (4.7) | 13 (4.6) | ||
| 40-79 | 47 (18.2) | 54 (18.9) | ||
| ≥80 | 21 (8.1) | 21 (7.4) | ||
| Not reported | 178 (69) | 197 (69.1) | ||
| Retention rate (%) | ||||
| 34-39 | 2 (0.8) | 2 (0.7) | ||
| 40-79 | 12 (4.7) | 12 (4.2) | ||
| ≥80 | 137 (53.1) | 147 (51.6) | ||
| Not reported | 107 (41.5) | 124 (43.5) | ||
| Mean compliance rate (%) | ||||
| 1-39 | 9 (3.5) | 9 (3.2) | ||
| 40-79 | 121 (46.9) | 135 (47.4) | ||
| ≥80 | 78 (30.2) | 85 (29.8) | ||
| Not reported | 50 (19.4) | 56 (19.6) | ||
aEMA: ecological momentary assessment.
Meta-Analyses of Acceptance, Compliance, and Retention Rates
In our meta-analysis, acceptance rates were available for 30.9% (88/285) of samples, compliance rates for 216 (75.8%) samples, and retention rates for 161 (56.5%) samples (refer to Figures S4 and S5 in , for detailed patterns of missingness and distributions, respectively). After removal of 1 influential sample [] that did not relate to the planned moderator analyses (refer to Influential Samples in ), we noted an average acceptance rate of 67.27% (95% CI 62.39-71.96, 95% prediction interval [PI] 22.99-97.84), an average compliance rate of 71.97% (95% CI 69.83-74.11, 95% PI 41.14-102.8), and an average retention rate of 96.57% (95% CI 95.42-95.42, 95% PI 74.46-100; refer to Figure S7 in for caterpillar plots). Q tests indicated that the underlying true effects were heterogeneous (Ps<.001). According to fit indexes, the low proportion of samples nested within studies did not support 3-level models (refer to Table S3 in ). Regression tests for funnel plot asymmetry were statistically significant for acceptance (P<.001), and compliance (P=.002), but not for retention (P=.15; Figure S8 in ). Visual inspection suggested lack of large sample sizes (ie, high precision) at the upper bounds of participation metrics. However, this asymmetry may be artifactual due to an inherent association of sample size and the difficulty of maintaining engagement in all participants when conducting large-scale projects. The regression test results remained robust when removing 1 sample with an outstanding sample size [] (Ps≤.044).
Meta-Regression Analyses
Among candidate moderators (refer to 
Figure 2 and Table S4 in ), only a higher number of items in EMA surveys robustly predicted lower acceptance rates (41/285, 14.4%; b=−0.115, SE 0.036; 95% CI −0.185 to −0.045; P=.001; R2=19.98; Figure S9 in ). To illustrate predictions from this log-transformed predictor, doubling the number of items of an EMA survey from 20 to 40 items would predict a 7.91% decline in acceptance from 60.95% (95% CI 54.6-67.11; 95% PI 23.31-92.2) to 53.04% (95% CI 44.29-61.69; 95% PI 16.58-87.69). A negative effect of female participation was not significant at the restricted α level of .005 (P=.02). For compliance, response duration (P=.009), participant training (P=.009), and parallel parent EMA (P=.007) showed positive associations with compliance, but these effects did not survive our restricted significance criterion. However, compliance rates declined significantly by 0.8% per year of publication (216/285, 75.8%; SE 0.25; 95% CI −1.3 to −.3; P=.002; R2=4.17; Figure S9 in ). Retention showed a robust negative association with the number of assessment days (158/285, 55.4%; b=−0.061, SE 0.015; 95% CI −0.091 to −0.032; P<.001; R2=10.06; Figure S9 in ). Accordingly, doubling the planned number of assessment days from 14 to 28 corresponds to a reduction in retention of approximately 1.76% from 96.02% (95% CI 94.79-97.09; 95% PI 73.72-100) to 94.26% in 28 days (95% CI 92.3-95.94; 95% PI 69.94-100).
We detected no significant difference between samples with reportedly inflated compliance rates and uninflated compliance rates (P=.85). Further sensitivity analyses of meta-regressions based exclusively on uninflated rates resulted in a substantial loss of precision, with none of the described effects surviving the restricted α level (refer to Figure S10 in ). Higher-order meta-regression models revealed that the percentage of female participants and the log-transformed amount of monetary incentives interacted significantly, showing decreasing benefits of monetary incentives with higher female participation (103/285, 36.1%; b=−0.002, SE 0.001; 95% CI −0.003 to −0.001; P=.003; R2=9.47; Table S5 in ).
Meta-Analyses of Within-Study Correlates of Compliance
The results of missing data analyses regarding sample and design characteristics were available in 52 (20.2%) studies, and 42 (16.3%) provided at least 1 effect size. We performed meta-analysis for differences by gender (25/285, 8.8%), and age (14/285, 4.9%), but not for baseline symptom severity (9/285, 3.2%), ethnicity (5/285, 1.8%), and clinical status (5/285, 1.8%). Contrary to the meta-regression findings, pooled gender differences showed a small significant effect with higher compliance found in girls (g=0.18, SE 0.06; 95% CI 0.06-0.31; P=.003; 
Figure 3). The pooled correlation between age and response compliance remained small and did not reach significance (z score=0.05, 95% CI −0.01 to 0.16; 
Figure 4). Neither regression tests nor visual inspection indicated funnel plot asymmetry, and we detected no influential samples (refer to Figure S11 in ). However, the present pooled effects ignored 23 narrative findings, with 10 and 11 null effects described for gender and age, respectively.
Discussion
Principal Findings
Aiming for a complete capture of EMA research conducted in youth, this meta-analysis provides a comprehensive cumulative update marking a 5-fold increase in the total number of included compliance rates compared to the initial review []. In addition, it includes the first youth-specific analysis of acceptance and retention and investigates a fine-grained set of sample and design characteristics as potential moderators of missing data.
Our meta-analysis of acceptance rates is also the first of its kind among the wider EMA literature. The negative association between the number of items and acceptance warrants further explanation. At first glance, it may seem puzzling that survey volume would deter individuals who have not yet experienced the burden of completing an EMA. Here, we outline several considerations that might explain this result but require deeper empirical investigation. First, even if the exact number of items was not explicitly disclosed in all studies, potential participants could have inferred from general study descriptions (eg, the time anticipated to respond to one survey), presented training material, or the collaborator’s attitude about the study’s demands that the protocol involved a substantial number of questions. Although we cannot determine these commonly unreported factors of communication using meta-analysis, an experimental study documented the negative effect of described protocol intensity, including the time required to respond to an EMA prompt and on the willingness of adult crowd-workers to participate in hypothetical studies []. While this finding substantially supports the assumption that anticipated burden influences the acceptance rate, such experimental research is still lacking in youth. Moreover, we did not observe similar effects for study length and prompt frequency.
Second, the negative relationship between survey volume and acceptance might also reflect broader study characteristics. For instance, the larger-scale studies in our meta-analysis tended to have both more survey items as indicated by the strongest correlation found between the study variables (r=.53, refer to Figure S2 in ) and lower acceptance rates (refer to Figure S8 in ). This suggests that broader study design strategies beyond item count alone may be at play linking more intense EMA surveys and high outreach of invitations, with less efficient recruitment. For instance, planning an EMA study with long questionnaires and less targeted recruitment can be described as an opportunistic or unselective design strategy. Specifically, large-scale invitations may involve less-engaging formats (eg, flyers vs individual recruitment by clinician). The intention to maximize the number of collected variables and participants without concentrating on specific target phenomena or a specific target population might then come at the cost of low acceptance. However, this does not unavoidably translate into a threat of validity for specific research paradigms, such as epidemiological phenotyping studies that also control representativeness in their recruitment. Unfortunately, only 14.4% (41/285) of the studies included in our meta-analysis reported both the number of items and the acceptance rate, which limited our ability to isolate the direct effect of survey volume from other confounding variables. Future research should more systematically assess how adolescents learn about the scope and intensity of EMA protocols to clarify how perceived burden may deter participation. Until then, researchers can involve youth from the target population as young partners to inquire about their hypothetical acceptance of invitation to enroll across varying numbers of items. Further pilot testing can examine whether shorter, more targeted surveys will even promote data quality, for instance by minimizing careless response behavior.
Pooling all available information on response compliance, the cumulative estimate of the compliance rate decreased by approximately 6% compared to the result of the previous meta-analysis (71.94% vs 78.26%) []. This difference mirrors the general downward trend of 0.8% per publication year, which also aligns with the previously reported, yet steeper, yearly decline of 3.1% in health-related adult EMA research []. In line with the same adult meta-analysis, we found no indication that reportedly inflated compliance rates were systematically higher than those that were uninflated. Nonetheless, without knowing the respective raw compliance rates, we inevitably overestimate the pooled rate. For instance, if the raw compliance rates scored on average 10% below their reported value, their accumulated meta-analytic weight of 21% would pull the pooled estimate down to 69.84%.
Consistent with the initial review [], sample, design characteristics, and reporting practices did not reduce unexplained heterogeneity among compliance rates, except for the significant interaction of smaller benefits of monetary incentivization with higher female participation. If we assume lower baseline compliance in boys compared to girls, as indicated by our within-sample finding, this interaction may open a door for practical intervention. Researchers may involve youth from the target population as young partners to attenuate this gender gap in compliance by calibrating monetary incentives to reach equal engagement of boys and girls. At the same time, this interpretation is incoherent with the lack of an equivocal main effect of gender at the between-study level.
In contrast, the balance of female and male gender could also act as an outcome of the proposed monetary incentives at recruitment. From this perspective, incentivization plans may be tailored to balance gender proportions in conditions that are less prevalent in boys (eg, nonsuicidal self-injury) or to control for general self-selection bias of youth identifying as male in mental health research [].
Of note, the conditions of receiving monetary incentives may be of relevance as well. Other authors cautioned for potential negative effects of conditioning financial rewards to tightly to expected compliance rates [], hypothesizing that this strategy could draw on the motivation to respond to several prompts above the required minimum. Negative reactivity on the incentivization strategy may also interfere with data quality, if participants prioritize providing the required number of responses rather than engaging in active reflection of their current mental states.
At the same time, we caution against overemphasizing this finding which remains limited in explanation of heterogeneity, modest practical effect size, the strong assumption of baseline gender balance in the recruited population, and the lack of interaction with clinical variables. In addition, this finding may be subject to the ecologic fallacy that arises in meta-analysis when summary statistics act as observations []. For instance, the varying proportion of females may be confounded by other sample-level characteristics, such as the disorder (eg, anorexia nervosa vs attention-deficit/hyperactivity disorder) that can explain the gender composition as well as sensitivity to external rewards and the resulting response compliance. Conversely, within-study effects overcome this limitation by directly comparing girls’ and boys’ response compliance. However, only 8.8% of all included studies quantified gender differences and potential moderators, such as the incentivization strategy was not even available, as it is usually fixed for all participants within the same study. Nonetheless, the finding of girls being more compliant aligns with previous pooled within-study results in adolescents []. Looking ahead, research should explore how incentives and number of items interact with sex and gender diversity in clinical samples to further refine compliance strategies, thereby enhancing study design and ensuring more representative, high-quality data.
This meta-analysis provides the first youth-specific synthesis of retention rates, which were close to full retention (96.57%). The number of assessment days was the only factor associated with lower retention, yet the expected loss of participants over time was surprisingly low, predicting average retention rates above 90% for up to 100 days of EMA collection. While publication bias toward optimal retention rates was not evident in funnel plot asymmetry, we underline that our synthesis of retention rates lacks nearly half of all evidence due to poor reporting of participant flow in the literature. Finally, no interactions of the number of assessment days and clinical variables were found, which suggests that individual clinical burden does not necessarily translate to sensitivity to experienced burden in EMA studies.
How Do We Deal With Heterogeneity?
In line with previous meta-analyses [,-], substantial heterogeneity in compliance rates persists in the literature and is also present in acceptance and retention rates. Moreover, the robustly significant moderators explain only a limited amount of heterogeneity (highest R2=20%). Accordingly, we found no indication that nonparticipation, omitted responses, or dropouts are selectively linked to clinical characteristics, though small cell frequencies across diagnostic categories hindered further in-depth analysis of specific diseases []. However, this does not imply that participation metrics from EMA research manifest randomly and irrespective of the researchers’ attempts to prevent missing data. On the contrary, the reported prediction intervals, as well as the extensive spread of compliance rates in recent years (refer to Figure S9 in ), suggest that EMA protocols can successfully minimize loss of data, even in disadvantageous configurations with many EMA items, a high proportion of male participants, and low financial incentives.
The persistence of statistical heterogeneity may also reflect that researchers continuously tackle the barriers of EMA research in the field. For example, a recent study applied EMA in such marginalized minority groups as asylum-seeking children [], while other EMA protocols were scaled to public implementation [], where any app-store user could become a participant but would receive only minimal participant care [,]. Although such pioneering work may suffer from more missing data, it is not necessarily poorly conducted regarding the valuable insights it offers. Specific implementations of EMA will need to address specific sources of bias (eg, language barriers). We underline that preparing an EMA protocol implies a deliberate process of adapting the recommendations [,] to the needs of the target group and, in the best case, involves the latter as young partners to identify systematic challenges in recruitment and data collection [].
However, this perspective on heterogeneity challenges the interpretation of cumulative meta-analytic estimates as benchmarks for individual data collections, as many citing authors did with the initial meta-analysis in youth []. Given that incomplete reporting in journal articles undermines many of the present findings, one may question if the published journal article offers an adequate source of information for meta-analyzing the complex determinants of missing data. As a consequence, future meta-analytic endeavors may consider such alternative data collection methods [] as purely survey-based inquiry from EMA researchers identified via a systematic literature search []. Meta-analytic synthesis may also follow a more selective approach by focusing on effect sizes from experimental primary methods research. However, seminal demonstrations of well-conducted experimental research on important EMA design parameters, such as prompt frequency and number of items, do not yet provide consistent effects and are primarily available from adult student populations [,].
To help researchers build adequate expectations for future EMA studies based on this work, we strongly recommend filtering the dataset [] to studies that relate to the individual design and population of interest. Finally, we provide a web-based shiny app [] that facilitates this task through an easy-to-use interface.
Limitations
Several limitations exist in this meta-analysis. We did not search for unpublished studies or trial registries, nor did we contact authors for additional data, which could have filled gaps in the reported information. Our inclusion of diverse EMA study designs may have introduced excessive heterogeneity, affecting the clarity of effect sizes, and we assumed the accuracy of reported data without verification. While conventional approaches to study quality and risk of bias assessment do not apply to this meta-analysis on descriptive participation metrics, a consensual definition of quality in EMA data collection could improve confidence. Finally, our penalty for multiple testing could have obscured genuine effects, particularly interactions.
Recommendations for Transparent EMA Study Reporting
This meta-analysis is not the first to highlight the unfortunate lack of reporting transparency in EMA study reports [,,]. As transparent research practices continue to gain traction, we would like to remind readers—especially those less familiar with open science—that several EMA-specific reporting guidelines and checklists have been available for years [,,]. Indeed, these guidelines informed much of our own data extraction.
Our large-scale review of the youth EMA literature also revealed that the typical journal article format and word-limit constraints often restrict the level of methodological detail one can feasibly include. However, such limitations need not pose a dead end. Multiple formats allow for full disclosure of methods outside the main text, including preregistrations, registered reports, and supplemental materials. Ideally, authors can preregister or prepare a registered report of their detailed EMA protocols before data collection, following established templates []. Similarly, researchers drafting manuscripts (including protocol papers) can consider adding a “detailed EMA protocol” section to the supplemental materials. Existing reporting guidelines [,,] can be directly integrated as tables, with each cell describing design elements rather than pointing to page numbers.
We further encourage authors to provide in-depth missing data analyses, including correlates of all participation metrics. Variables reflecting target phenomena or constructs should be examined for potential associations with missingness at both the participant (eg, baseline depression predicting compliance) and the momentary level (eg, perceived stress predicting next moment missingness). Again, supplemental materials offer an ideal space for these additional analyses. Researchers who have already published their main findings could consider releasing a dedicated paper that focuses on feasibility, data availability, and data quality, with instructive examples available (eg, []).
All these formats supported our data extraction process in this meta-analysis.
Conclusions
Overall, this meta-analysis marks a significant advance in the synthesis of health research using EMA in youth populations. Consistent with previous large-scale meta-analyses, heterogeneity among participation metrics remained largely unaffected by the tested moderators. However, underreporting, especially of within-study correlates of missing data, undermined this investigation. To address the limitations identified in this and other studies, future research should focus on improving reporting transparency, expanding methodological research, and involving young partners to enhance study design and data integrity.
Specifically, the strategic integration of participant perspectives may involve young partners in the identification of research priorities, recruitment strategies, and strategies for preventing missing data. A participatory design process can also tailor monetary and nonmonetary incentives to match participant preferences. Further confidence in the protocol can be gained by conducting a preliminary pilot phase to identify and address missing data patterns, to optimize compliance, and minimize attrition. This participatory approach further allows calibrating specific design parameters, such as the use of gamification or parent involvement. Neither of both emerged as significant (P>.06) predictor of participation metrics across studies, though tailoring these factors to the participants’ lived experience may promote data quantity and quality in specific target populations and settings. These measures, paired with transparent reporting practices, will help in reducing missing data and boost the clinical utility of EMA studies in diverse youth populations.
Acknowledgments
The authors want to thank Assel Aitkulova, Fabienne Crousaz, Sophie Berthod, and Talia Petter for their extraordinary help in literature screening and data extraction. Posters on the meta-analytic project were presented at the following meetings: the Society for Ambulatory Assessment Annual Conference (online), June 14 to June 16, 2022, Missouri, United States; the 19th International Congress of the European Society for Child and Adolescent Psychiatry, June 19 to June 21, 2022, Maastricht, The Netherlands; and the Annual Meeting of the Society for the Improvement of Psychological Sciences, June 22 to June 24, 2023, Padua, Italy. The authors extend their thanks to the many authors who made their detailed methods readily available for this study.
Data Availability
The datasets generated and analyzed during this study are available in the Open Science Repository []. This includes bibliographic data of all screened records, the respective reasons for exclusions, as well as the meta-analytic dataset that was used for statistical analyses.
Authors' Contributions
KD, CKW, SU, KJP, and JG conceptualized the study. JR-A revised, conducted, and updated the systematic literature search. KD contributed to piloting the literature and organizing the literature selection and extraction methods. KD, VR, SU, and JG organized and contributed to the selection and extraction procedures as detailed in the Methods section. KD wrote the manuscript of the study, supervised by SU, JG, and KJP. All authors reviewed the final manuscript. KD programmed the interactive web app illustrating the meta-analytic dataset.
Conflicts of Interest
CKW is a medical writer at Edwards Life Sciences. The other authors declare having no conflicts of interest.
References
- Trull TJ, Ebner-Priemer UW. Ambulatory assessment in psychopathology research: a review of recommended reporting guidelines and current practices. J Abnorm Psychol. Jan 2020;129(1):56-63. [CrossRef] [Medline]
- Csikszentmihalyi M, Larson R. Being Adolescent: Conflict And Growth In The Teenage Years. New York, NY. Basic Books; 1984.
- Chevance G, Perski O, Hekler E. Innovative methods for observing and changing complex health behaviors: four propositions. Transl Behav Med. Mar 16, 2021;11(2):676-685. [FREE Full text] [CrossRef] [Medline]
- Hamaker EL, Wichers M. No time like the present: discovering the hidden dynamics in intensive longitudinal data. Curr Dir Psychol Sci. Feb 08, 2017;26(1):10-15. [CrossRef]
- Bringmann LF, Albers C, Bockting C, Borsboom D, Ceulemans E, Cramer A, et al. Psychopathological networks: theory, methods and practice. Behav Res Ther. Feb 2022;149:104011. [FREE Full text] [CrossRef] [Medline]
- Houben M, Van Den Noortgate W, Kuppens P. The relation between short-term emotion dynamics and psychological well-being: a meta-analysis. Psychol Bull. Jul 2015;141(4):901-930. [CrossRef] [Medline]
- Verhagen S, van Os J, Delespaul P. Ecological momentary assessment and other digital technologies for capturing daily life in mental health. In: Stein DJ, Fineberg NA, Chamberlain SR, editors. Mental Health in a Digital World. New York, NY. Academic Press; 2022:81-108.
- Vachon H, Viechtbauer W, Rintala A, Myin-Germeys I. Compliance and retention with the experience sampling method over the continuum of severe mental disorders: meta-analysis and recommendations. J Med Internet Res. Dec 06, 2019;21(12):e14475. [FREE Full text] [CrossRef] [Medline]
- van Roekel E, Keijsers L, Chung JM. A review of current ambulatory assessment studies in adolescent samples and practical recommendations. J Res Adolesc. Sep 17, 2019;29(3):560-577. [FREE Full text] [CrossRef] [Medline]
- Smith LH. Selection mechanisms and their consequences: understanding and addressing selection bias. Curr Epidemiol Rep. Aug 09, 2020;7(4):179-189. [CrossRef]
- Boone-Heinonen J, Guilkey DK, Evenson KR, Gordon-Larsen P. Residential self-selection bias in the estimation of built environment effects on physical activity between adolescence and young adulthood. Int J Behav Nutr Phys Act. Oct 04, 2010;7(1):70. [FREE Full text] [CrossRef] [Medline]
- Naim R, Shaughnessy S, Smith A, Karalunas SL, Kircanski K, Brotman MA. Real-time assessment of positive and negative affective fluctuations and mood lability in a transdiagnostic sample of youth. Depress Anxiety. Dec 2022;39(12):870-880. [FREE Full text] [CrossRef] [Medline]
- Gray L, Gorman E, White IR, Katikireddi SV, McCartney G, Rutherford L, et al. Correcting for non-participation bias in health surveys using record-linkage, synthetic observations and pattern mixture modelling. Stat Methods Med Res. Apr 11, 2020;29(4):1212-1226. [FREE Full text] [CrossRef] [Medline]
- Dejonckheere E, Erbas Y. Designing an experience sampling study. In: Myin-Germeys I, Kuppens P, editors. The Open Handbook of Experience Sampling Methodology: A Step-By-Step Guide to Designing, Conducting, and Analyzing ESM Studies. 2nd edition. Leuven, Belgium. Center for Research on Experience Sampling and Ambulatory Methods; 2022.
- Wen CK, Schneider S, Stone AA, Spruijt-Metz D. Compliance with mobile ecological momentary assessment protocols in children and adolescents: a systematic review and meta-analysis. J Med Internet Res. Apr 26, 2017;19(4):e132. [FREE Full text] [CrossRef] [Medline]
- Perski O, Keller J, Kale D, Asare BY, Schneider V, Powell D, et al. Understanding health behaviours in context: a systematic review and meta-analysis of ecological momentary assessment studies of five key health behaviours. Health Psychol Rev. Dec 15, 2022;16(4):576-601. [FREE Full text] [CrossRef] [Medline]
- Ottenstein C, Werner L. Compliance in ambulatory assessment studies: investigating study and sample characteristics as predictors. Assessment. Dec 20, 2022;29(8):1765-1776. [FREE Full text] [CrossRef] [Medline]
- Jones A, Remmerswaal D, Verveer I, Robinson E, Franken IH, Wen CK, et al. Compliance with ecological momentary assessment protocols in substance users: a meta-analysis. Addiction. Apr 21, 2019;114(4):609-619. [FREE Full text] [CrossRef] [Medline]
- Wrzus C, Neubauer AB. Ecological momentary assessment: a meta-analysis on designs, samples, and compliance across research fields. Assessment. Apr 11, 2023;30(3):825-846. [FREE Full text] [CrossRef] [Medline]
- Morren M, van Dulmen S, Ouwerkerk J, Bensing J. Compliance with momentary pain measurement using electronic diaries: a systematic review. Eur J Pain. Apr 2009;13(4):354-365. [CrossRef] [Medline]
- Ono M, Schneider S, Junghaenel DU, Stone AA. What affects the completion of ecological momentary assessments in chronic pain research? An individual patient data meta-analysis. J Med Internet Res. Feb 05, 2019;21(2):e11398. [FREE Full text] [CrossRef] [Medline]
- Understanding motivation: building the brain architecture that supports learning, health, and community participation: working paper no. 14. National Scientific Council of the Developing Child. 2018. URL: https://pediatrics.developingchild. harvard.edu/wp-content/uploads/2021/12/wp14_reward_motivation_121118_FINAL.pdf [accessed 2024-03-25]
- Galvan A. Adolescent development of the reward system. Front Hum Neurosci. 2010;4:6. [FREE Full text] [CrossRef] [Medline]
- Krach S, Paulus FM, Bodden M, Kircher T. The rewarding nature of social interactions. Front Behav Neurosci. 2010;4:22. [FREE Full text] [CrossRef] [Medline]
- Bittner J, Shipper J. Motivational effects and age differences of gamification in product advertising. J Consum Mark. 2014;31(5):391-400. [CrossRef]
- Dietvorst E, Aukes MA, Legerstee JS, Vreeker A, Hrehovcsik MM, Keijsers L, et al. A smartphone serious game for adolescents (Grow It! app): development, feasibility, and acceptance study. JMIR Form Res. Mar 03, 2022;6(3):e29832. [FREE Full text] [CrossRef] [Medline]
- Sailer M, Homner L. The gamification of learning: a meta-analysis. Educ Psychol Rev. Aug 15, 2019;32(1):77-112. [CrossRef]
- Fan W, Williams CM. The effects of parental involvement on students’ academic self‐efficacy, engagement and intrinsic motivation. Educ Psychol. Dec 11, 2009;30(1):53-74. [CrossRef]
- Garner P, Hopewell S, Chandler J, MacLehose H, Schünemann HJ, Akl EA, et al. Panel for updating guidance for systematic reviews (PUGs). When and how to update systematic reviews: consensus and checklist. BMJ. Jul 20, 2016;354:i3507. [FREE Full text] [CrossRef] [Medline]
- Geissbühler M, Hincapié CA, Aghlmandi S, Zwahlen M, Jüni P, da Costa BR. Most published meta-regression analyses based on aggregate data suffer from methodological pitfalls: a meta-epidemiological study. BMC Med Res Methodol. Jun 15, 2021;21(1):123. [FREE Full text] [CrossRef] [Medline]
- Sarkis-Onofre R, Catalá-López F, Aromataris E, Lockwood C. How to properly use the PRISMA statement. Syst Rev. Apr 19, 2021;10(1):117. [FREE Full text] [CrossRef] [Medline]
- Liao Y, Skelton K, Dunton G, Bruening M. A systematic review of methods and procedures used in ecological momentary assessments of diet and physical activity research in youth: an adapted STROBE checklist for reporting EMA studies (CREMAS). J Med Internet Res. Jun 21, 2016;18(6):e151. [FREE Full text] [CrossRef] [Medline]
- Bourke M, Hilland TA, Craike M. Domain specific association between physical activity and affect in adolescents' daily lives: an ecological momentary assessment study. Psychol Health. Mar 27, 2023;38(3):369-388. [CrossRef] [Medline]
- Baltasar-Tello I, Miguélez-Fernández C, Peñuelas-Calvo I, Carballo JJ. Ecological momentary assessment and mood disorders in children and adolescents: a systematic review. Curr Psychiatry Rep. Aug 01, 2018;20(8):66. [CrossRef] [Medline]
- Bourke M, Hilland TA, Craike M. A systematic review of the within-person association between physical activity and affect in children's and adolescents' daily lives. Psychol Sport Exerc. Jan 2021;52:101825. [CrossRef]
- Dubad M, Winsper C, Meyer C, Livanou M, Marwaha S. A systematic review of the psychometric properties, usability and clinical impacts of mobile mood-monitoring applications in young people. Psychol Med. Jun 23, 2017;48(2):208-228. [CrossRef]
- Duvenage M, Uink BN, Zimmer-Gembeck MJ, Barber BL, Donovan CL, Modecki KL. Ambulatory assessment of adolescent coping: it's a complicated process. J Res Adolesc. Sep 2019;29(3):578-594. [CrossRef] [Medline]
- Heron K, Everhart R, McHale S, Smyth J. Using mobile-technology-based ecological momentary assessment (EMA) methods with youth: a systematic review and recommendations. J Pediatr Psychol. Nov 01, 2017;42(10):1087-1107. [CrossRef] [Medline]
- Mason TB, Do B, Wang S, Dunton GF. Ecological momentary assessment of eating and dietary intake behaviors in children and adolescents: a systematic review of the literature. Appetite. Jan 01, 2020;144:104465. [FREE Full text] [CrossRef] [Medline]
- Miguelez-Fernandez C, de Leon SJ, Baltasar-Tello I, Peñuelas-Calvo I, Barrigon ML, Capdevila AS, et al. Evaluating attention-deficit/hyperactivity disorder using ecological momentary assessment: a systematic review. Atten Defic Hyperact Disord. Dec 2018;10(4):247-265. [CrossRef] [Medline]
- Mölsä ME, Lax M, Korhonen J, Gumpel TP, Söderberg P. The experience sampling method in monitoring social interactions among children and adolescents in school: a systematic literature review. Front Psychol. Apr 4, 2022;13:844698. [FREE Full text] [CrossRef] [Medline]
- Reitsema AM, Jeronimus BF, van Dijk M, de Jonge P. Emotion dynamics in children and adolescents: a meta-analytic and descriptive review. Emotion. Mar 2022;22(2):374-396. [CrossRef] [Medline]
- Romanzini CL, Romanzini M, Batista MB, Barbosa CC, Shigaki GB, Dunton G, et al. Methodology used in ecological momentary assessment studies about sedentary behavior in children, adolescents, and adults: systematic review using the checklist for reporting ecological momentary assessment studies. J Med Internet Res. May 15, 2019;21(5):e11967. [FREE Full text] [CrossRef] [Medline]
- Sequeira L, Perrotta S, LaGrassa J, Merikangas K, Kreindler D, Kundur D, et al. Mobile and wearable technology for monitoring depressive symptoms in children and adolescents: a scoping review. J Affect Disord. Mar 15, 2020;265:314-324. [CrossRef] [Medline]
- Thunnissen MR, Aan Het Rot M, van den Hoofdakker BJ, Nauta MH. Youth psychopathology in daily life: systematically reviewed characteristics and potentials of ecological momentary assessment applications. Child Psychiatry Hum Dev. Dec 01, 2022;53(6):1129-1147. [FREE Full text] [CrossRef] [Medline]
- Urben S, Constanty L, Lepage C, Rosselet Amoussou J, Durussel J, Turri F, et al. The added value of a micro-level ecological approach when mapping self-regulatory control processes and externalizing symptoms during adolescence: a systematic review. Eur Child Adolesc Psychiatry. Dec 16, 2023;32(12):2387-2397. [FREE Full text] [CrossRef] [Medline]
- van Dalen M, Snijders A, Dietvorst E, Bracké K, Nijhof SL, Keijsers L, et al. Applications of the experience sampling method (ESM) in paediatric healthcare: a systematic review. Pediatr Res. Mar 07, 2024;95(4):887-900. [FREE Full text] [CrossRef] [Medline]
- Haddaway NR, Grainger MJ, Gray CT. Citationchaser: a tool for transparent and efficient forward and backward citation chasing in systematic searching. Res Synth Methods. Jul 2022;13(4):533-545. [CrossRef] [Medline]
- Myin-Germeys I. Experience sampling methods, an introduction. In: Myin-Germeys I, Kuppens P, editors. The Open Handbook of Experience Sampling Methodology: A Step-By-Step Guide to Designing, Conducting, and Analyzing ESM Studies. 2nd edition. Leuven, Belgium. Center for Research on Experience Sampling and Ambulatory Methods; 2023:7-19.
- Youth social entrepreneurship and the 2030 agenda. United Nations. URL: https://www.un.org/development/desa/youth/wp-content/uploads/sites/21/2020/05/WYR-2020-Executive-Summary-REV.pdf [accessed 2024-04-29]
- Cai S, Zhou J, Pan J. Estimating the sample mean and standard deviation from order statistics and sample size in meta-analysis. Stat Methods Med Res. Dec 20, 2021;30(12):2701-2719. [CrossRef] [Medline]
- Gambarota F, Altoè G. Understanding meta-analysis through data simulation with applications to power analysis. Adv Methods Pract Psychol Sci. Feb 13, 2024;7(1):25. [CrossRef]
- American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders (DSM-5-TR). 5th edition. Washington, DC. American Psychiatric Association Publishing; 2022.
- International classification of diseases eleventh revision (ICD-11). World Health Organization. URL: https://www.who.int/news/item/11-02-2022-icd-11-2022-release [accessed 2024-04-29]
- Jensen FF, Håkansson KE, Overgaard Nielsen B, Weinreich UM, Ulrik CS. Self-reported vs. objectively assessed adherence to inhaled corticosteroids in asthma. Asthma Res Pract. May 31, 2021;7(1):7. [FREE Full text] [CrossRef] [Medline]
- Exchange rates (indicator). Organisation for Economic Co-operation and Development. URL: https://www.oecd.org/en/data/indicators/exchange-rates.html [accessed 2024-04-29]
- Logullo P, MacCarthy A, Kirtley S, Collins GS. Reporting guideline checklists are not quality evaluation forms: they are guidance for writing. Health Sci Rep. Jun 03, 2020;3(2):e165. [FREE Full text] [CrossRef] [Medline]
- Carter EC, Schönbrodt FD, Gervais WM, Hilgard J. Correcting for bias in psychology: a comparison of meta-analytic methods. Adv Methods Pract Psychol Sci. Jun 13, 2019;2(2):115-144. [CrossRef]
- Macaskill P, Walter SD, Irwig L. A comparison of methods to detect publication bias in meta-analysis. Stat Med. Feb 28, 2001;20(4):641-654. [CrossRef] [Medline]
- Viechtbauer W. Conducting meta-analyses in R with the metafor package. J Stat Soft. 2010;36(3):1-48. [CrossRef]
- McGrath S, Zhao X, Steele R, Benedetti A. estmeansd: Estimating the sample mean and standard deviation from commonly reported quantiles in meta-analysis. Cran R. URL: https://CRAN.R-project.org/package=estmeansd [accessed 2024-04-29]
- Cochran WG. Some methods for strengthening the common χ 2 tests. Biometrics. Dec 1954;10(4):417. [CrossRef]
- Viechtbauer W, Cheung MW. Outlier and influence diagnostics for meta-analysis. Res Synth Methods. Apr 04, 2010;1(2):112-125. [CrossRef] [Medline]
- Page MJ, Higgins JP, Sterne JA. Assessing risk of bias due to missing results in a synthesis. In: Higgins JP, Thomas J, Chandler J, Cumpston M, Li T, Page MJ, et al, editors. Cochrane Handbook for Systematic Reviews of Interventions. London, UK. The Cochrane Collaboration; 2019.
- R Core Team. R: a language and environment for statistical computing. R Foundation. URL: https://www.R-project.org/ [accessed 2024-04-29]
- Drexl K, Urben S, Glaus J. Youth ecological momentary assessment meta-analysis (YEMAMA) update. Open Science Framework. URL: https://osf.io/8nkeu/ [accessed 2024-04-29]
- Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ. Mar 29, 2021;372:n71. [FREE Full text] [CrossRef] [Medline]
- Tutelman PR, Chambers CT, Stinson JN, Parker JA, Barwick M, Witteman HO, et al. The implementation effectiveness of a freely available pediatric cancer pain assessment app: a pilot implementation study. JMIR Cancer. Dec 21, 2018;4(2):e10280. [FREE Full text] [CrossRef] [Medline]
- Holton N. Eudaimonia and engagement in the classroom: using experience sampling in an exploratory study of well-being in high school students. Michigan State University. 2017. URL: https://d.lib.msu.edu/etd/4023 [accessed 2024-04-29]
- Buhr L, Moschko T, Eppinger Ruiz de Zarate A, Schwarz U, Kühnhausen J, Gawrilow C. The association of self-reported ADHD symptoms and sleep in daily life of a general population sample of school children: an inter- and intraindividual perspective. Brain Sci. Mar 25, 2022;12(4):440. [FREE Full text] [CrossRef] [Medline]
- Bentley KH, Millner AJ, Bear A, Follet L, Fortgang RG, Zuromski KL, et al. Intervening on high-risk responses during ecological momentary assessment of suicidal thoughts: is there an effect on study data? Psychol Assess. Jan 2024;36(1):66-80. [CrossRef] [Medline]
- Bakshi N, Smith ME, Ross D, Krishnamurti L. Novel metrics in the longitudinal evaluation of pain data in sickle cell disease. Clin J Pain. Jun 2017;33(6):517-527. [CrossRef] [Medline]
- Zuzama N, Roman-Juan J, Fiol-Veny A, Balle M. The use of rumination and reappraisal in adolescents daily life: links to affect and emotion regulation style. Child Psychiatry Hum Dev. Jun 17, 2023;54(3):837-848. [FREE Full text] [CrossRef] [Medline]
- Zurbriggen CLA, Venetz M, Hinni C. The quality of experience of students with and without special educational needs in everyday life and when relating to peers. Eur J Spec Needs Educ. Jan 24, 2018;33(2):205-220. [CrossRef]
- Xu S, Wang Z, Woods K. Multitasking and dual motivational systems: a dynamic longitudinal study. Hum Commun Res. 2019;45(4):371-394. [CrossRef]
- Wronski M, Hohnemann C, Bernardoni F, Bahnsen K, Doose A, Arold D, et al. Explicating the role of amygdala substructure alterations in the link between hypoleptinemia and rumination in anorexia nervosa. Acta Psychiatr Scand. Oct 08, 2023;148(4):368-381. [CrossRef] [Medline]
- Wilson TK, Riley A, Khetarpal SK, Abernathy P, Booth J, Culyba AJ. Exploring the impact of racism on black youth: a multidimensional examination of discriminatory experiences across place and time. J Adolesc Health. Feb 2023;72(2):246-253. [FREE Full text] [CrossRef] [Medline]
- Williams V, Romano C, Clark M, Korver D, Williams N, Goss D, et al. Psychometric evaluation of an electronic asthma symptom diary for young children. J Patient Rep Outcomes. Oct 30, 2023;7(1):105. [FREE Full text] [CrossRef] [Medline]
- Wieczorek LL, Mueller S, Lüdtke O, Wagner J. What makes for a pleasant social experience in adolescence? The role of perceived social interaction behavior in associations between personality traits and momentary social satisfaction. Eur J Pers. May 21, 2021;36(5):787-808. [CrossRef]
- Wieczorek LL, Bleckmann E, Brandt ND, Wagner J. Gloomy and out of control? Consequences of the COVID-19 pandemic on momentary optimism in daily lives of adolescents. Curr Psychol. Jun 25, 2022;43(14):13089-13099. [CrossRef]
- Wiebe DJ, Storey EP, Orchinik JE, Grady MF, Leddy JJ, Willer BS, et al. Measuring recovery with ecological momentary assessment in a randomized trial of exercise after sport-related concussion. Clin J Sport Med. 2022;32(4):345-353. [CrossRef]
- Whalen CK, Odgers CL, Reed PL, Henker B. Dissecting daily distress in mothers of children with ADHD: an electronic diary study. J Fam Psychol. Jun 2011;25(3):402-411. [CrossRef] [Medline]
- Weinstein SM, Mermelstein RJ, Hedeker D, Hankin BL, Flay BR. The time-varying influences of peer and family support on adolescent daily positive and negative affect. J Clin Child Adolesc Psychol. Sep 07, 2006;35(3):420-430. [FREE Full text] [CrossRef] [Medline]
- Webb CA, Swords CM, Murray L, Hilt LM. App-based mindfulness training for adolescent rumination: predictors of immediate and cumulative benefit. Mindfulness (N Y). Oct 09, 2021;12(10):2498-2509. [FREE Full text] [CrossRef] [Medline]
- Webb C, Swords C, Lawrence H, Hilt L. Which adolescents are well-suited to app-based mindfulness training? A randomized clinical trial and data-driven approach for personalized recommendations. J Consult Clin Psychol. Sep 2022;90(9):655-669. [FREE Full text] [CrossRef] [Medline]
- Warren CM, Pentz MA. The feasibility and acceptability of assessing inhibitory control and working memory among adolescents via an ecological momentary assessment approach. Child Neuropsychol. Nov 18, 2019;25(8):1022-1034. [FREE Full text] [CrossRef] [Medline]
- Warnick JL, Westen SC, Albanese-O'Neill A, Filipp SL, Schatz D, Haller MJ, et al. Use of ecological momentary assessment to measure self-monitoring of blood glucose adherence in youth with type 1 diabetes. Diabetes Spectr. Aug 2020;33(3):280-289. [FREE Full text] [CrossRef] [Medline]
- Wang Y, Cham H, Aladin M, Yip T. Parental cultural socialization and adolescent private regard: exploring mediating pathways through daily experiences. Child Dev. Jan 11, 2019;90(1):e19-e36. [FREE Full text] [CrossRef] [Medline]
- Walsh RJ, van Buuren M, Hollarek M, Sijtsma H, Lee NC, Krabbendam L. Social contexts, momentary mood and affective variability in early adolescence: an exploratory ecological momentary assessment study. J Early Adolesc. Feb 28, 2023;44(1):59-95. [CrossRef]
- Waldron KA, Lewis MA, Fairlie AM, Litt DM, Zhou Z, Bryant D. Daily-level associations between alcohol use cognitions and normative perceptions among adolescents: an intensive longitudinal study. Addict Behav. Aug 2023;143:107697. [CrossRef] [Medline]
- Vilaysack B, Cordier R, Doma K, Chen Y. Capturing everyday experiences of typically developing children aged five to seven years: a feasibility study of experience sampling methodology. Aust Occup Ther J. Dec 10, 2016;63(6):424-433. [CrossRef] [Medline]
- van Woudenberg TJ, Bevelander KE, Burk WJ, Buijzen M. The reciprocal effects of physical activity and happiness in adolescents. Int J Behav Nutr Phys Act. Nov 19, 2020;17(1):147. [FREE Full text] [CrossRef] [Medline]
- van Roekel E, Goossens L, Verhagen M, Wouters S, Engels RC, Scholte RH. Loneliness, Affect, and Adolescents' Appraisals of Company: An Experience Sampling Method Study. J Res Adolesc. Jun 21, 2013;24(2):350-363. [CrossRef]
- Van Oort C, Tupper SM, Rosenberg AM, Farthing JP, Baxter-Jones AD. Safety and feasibility of a home-based six week resistance training program in juvenile idiopathic arthritis. Pediatr Rheumatol Online J. Dec 20, 2013;11(1):46. [FREE Full text] [CrossRef] [Medline]
- Van Liefferinge D, Sonuga-Barke E, Danckaerts M, Fayn K, Van Broeck N, van der Oord S. Measuring child and adolescent emotional lability: how do questionnaire-based ratings relate to experienced and observed emotion in everyday life and experimental settings? Int J Methods Psychiatr Res. Sep 30, 2018;27(3):e1720. [FREE Full text] [CrossRef] [Medline]
- van der Kaap-Deeder J, Bülow A, Waterschoot J, Truyen I, Keijsers L. A moment of autonomy support brightens adolescents' mood: autonomy support, psychological control and adolescent affect in everyday life. Child Dev. 2023;94(6):1659-1671. [CrossRef] [Medline]
- Valrie C, Kilpatrick R, Alston K, Trout K, Redding-Lallinger R, Sisler I, et al. Investigating the sleep-pain relationship in youth with sickle cell utilizing mHealth technology. J Pediatr Psychol. Apr 01, 2019;44(3):323-332. [FREE Full text] [CrossRef] [Medline]
- Turri F, Jones A, Constanty L, Ranjbar S, Drexl K, Miano G, et al. Self-regulatory control processes in youths: a temporal network analysis approach. JCPP Adv. Mar 30, 2024;4(1):e12200. [FREE Full text] [CrossRef] [Medline]
- Turner AL, Brokamp C, Wolfe C, Reponen T, Ryan PH. Impact of personal, subhourly exposure to ultrafine particles on respiratory health in adolescents with asthma. Ann Am Thorac Soc. Sep 2022;19(9):1516-1524. [FREE Full text] [CrossRef] [Medline]
- Treloar Padovano H, Janssen T, Emery NN, Carpenter RW, Miranda R. Risk-taking propensity, affect, and alcohol craving in adolescents' daily lives. Subst Use Misuse. Jul 15, 2019;54(13):2218-2228. [FREE Full text] [CrossRef] [Medline]
- Tkaczyk M, Lacko D, Elavsky S, Tancoš M, Smahel D. Are smartphones detrimental to adolescent sleep? An electronic diary study of evening smartphone use and sleep. Comput Human Behav. Dec 2023;149:107946. [CrossRef]
- Thomassin K, Morelen D, Suveg C. Emotion reporting using electronic diaries reduces anxiety symptoms in girls with emotion dysregulation. J Contemp Psychother. Jan 17, 2012;42(4):207-213. [CrossRef]
- Tasian GE, Ross M, Song L, Audrain-McGovern J, Wiebe D, Warner SG, et al. Ecological momentary assessment of factors associated with water intake among adolescents with kidney stone disease. J Urol. Mar 2019;201(3):606-614. [FREE Full text] [CrossRef] [Medline]
- Talić I, Scherer R, Marsh HW, Greiff S, Möller J, Niepel C. Uncovering everyday dynamics in students’ perceptions of instructional quality with experience sampling. Learn Instr. Oct 2022;81:101594. [CrossRef]
- Swendeman D, Sumstine S, Brink A, Mindry D, Medich M, Russell M. Smartphone self-monitoring by young adolescents and parents to assess and improve family functioning: qualitative feasibility study. JMIR Form Res. Jun 23, 2020;4(6):e15777. [FREE Full text] [CrossRef] [Medline]
- Sweenie R, Cushing CC, Fleming KK, Prabhakaran S, Fedele DA. Daily adherence variability and psychosocial differences in adolescents with asthma: a pilot study. J Behav Med. Feb 06, 2022;45(1):148-158. [CrossRef] [Medline]
- Sufrinko A, Howie E, Charek D, Elbin R, Collins M, Kontos A. Mobile ecological momentary assessment of postconcussion symptoms and recovery outcomes. J Head Trauma Rehabil. 2019;34(6):E40-E48. [CrossRef] [Medline]
- Streb J, Keis O, Lau M, Hille K, Spitzer M, Sosic-Vasic Z. Emotional engagement in kindergarten and school children: a self-determination theory perspective. Trends Neurosci Educ. Dec 2015;4(4):102-107. [CrossRef]
- Streb J, Kammer T, Spitzer M, Hille K. Extremely reduced motion in front of screens: investigating real-world physical activity of adolescents by accelerometry and electronic diary. PLoS One. May 8, 2015;10(5):e0126722. [FREE Full text] [CrossRef] [Medline]
- Stinson JN, Stevens BJ, Feldman BM, Streiner D, McGrath PJ, Dupuis A, et al. Construct validity of a multidimensional electronic pain diary for adolescents with arthritis. Pain. Jun 2008;136(3):281-292. [CrossRef] [Medline]
- Stinson JN, Jibb LA, Nguyen C, Nathan PC, Maloney AM, Dupuis LL, et al. Construct validity and reliability of a real-time multidimensional smartphone app to assess pain in children and adolescents with cancer. Pain. Dec 2015;156(12):2607-2615. [CrossRef] [Medline]
- Stinson JN, Jibb LA, Nguyen C, Nathan PC, Maloney AM, Dupuis LL, et al. Development and testing of a multidimensional iPhone pain assessment application for adolescents with cancer. J Med Internet Res. Mar 08, 2013;15(3):e51. [FREE Full text] [CrossRef] [Medline]
- Starr LR, Hershenberg R, Shaw ZA, Li YI, Santee AC. The perils of murky emotions: emotion differentiation moderates the prospective relationship between naturalistic stress exposure and adolescent depression. Emotion. Sep 2020;20(6):927-938. [FREE Full text] [CrossRef] [Medline]
- Sokolovsky AW, Mermelstein RJ, Hedeker D. Factors predicting compliance to ecological momentary assessment among adolescent smokers. Nicotine Tob Res. Mar 2014;16(3):351-358. [FREE Full text] [CrossRef] [Medline]
- Smith AR, Jones EL, Subar AR, Do QB, Kircanski K, Leibenluft E, et al. The role of anxiety and gender in anticipation and avoidance of naturalistic anxiety-provoking experiences during adolescence: an ecological momentary assessment study. JCPP Adv. Sep 22, 2022;2(3):e12084. [FREE Full text] [CrossRef] [Medline]
- Smelror RE, Bless JJ, Hugdahl K, Agartz I. Feasibility and acceptability of using a mobile phone app for characterizing auditory verbal hallucinations in adolescents with early-onset psychosis: exploratory study. JMIR Form Res. May 14, 2019;3(2):e13882. [FREE Full text] [CrossRef] [Medline]
- Slot E, Vulperhorst J, Bronkhorst L, van der Rijst R, Wubbels T, Akkerman S. Mechanisms of interest sustainment. Learn Cult Soc Interact. Mar 2020;24:100356. [CrossRef]
- Skimina E, Karaś D, Topolewska-Siedzik E, Kłym-Guba M, Ponikiewska K, Rogoza R, et al. A categorization of behaviors reported in experience sampling studies. Soc Psychol Bull. Jul 31, 2020;15(2):1-33. [CrossRef]
- Siebers T, Beyens I, Pouwels JL, Valkenburg PM. Explaining variation in adolescents' social media-related distraction: the role of social connectivity and disconnectivity factors. Curr Psychol. Nov 24, 2022;42(34):1-14. [FREE Full text] [CrossRef] [Medline]
- Shiyko MP, Perkins S, Caldwell L. Feasibility and adherence paradigm to ecological momentary assessments in urban minority youth. Psychol Assess. Jul 2017;29(7):926-934. [FREE Full text] [CrossRef] [Medline]
- Shelton N, Douglass S, Garcia RL, Yip T, Trail TE. Feeling (Mis)understood and intergroup friendships in interracial interactions. Pers Soc Psychol Bull. Sep 20, 2014;40(9):1193-1204. [FREE Full text] [CrossRef] [Medline]
- Shamblen SR, Abadi MH, Thompson KT, García-Ramírez G, Richard BO. Changes in the patterns and characteristics of youth ENDS use over time. Int J Environ Res Public Health. Jul 01, 2022;19(13):8120. [FREE Full text] [CrossRef] [Medline]
- Segovia-Siapco G, Sabaté J. Using personal mobile phones to assess dietary intake in free-living adolescents: comparison of face-to-face versus telephone training. JMIR Mhealth Uhealth. Jul 29, 2016;4(3):e91. [FREE Full text] [CrossRef] [Medline]
- Schwartz-Mette RA, Duell N, Lawrence HR, Balkind EG. COVID-19 distress impacts adolescents' depressive symptoms, NSSI, and suicide risk in the rural, northeast US. J Clin Child Adolesc Psychol. Sep 03, 2023;52(5):702-715. [CrossRef] [Medline]
- Schurman JV, Friesen CA. Identifying potential pediatric chronic abdominal pain triggers using ecological momentary assessment. Clin Pract Pediatr Psychol. Jun 01, 2015;3(2):131-141. [CrossRef]
- Schneider-Worthington CR, Smith KE, Roemmich JN, Salvy S. External food cue responsiveness and emotional eating in adolescents: a multimethod study. Appetite. Jan 01, 2022;168:105789. [FREE Full text] [CrossRef] [Medline]
- Schneider B, Chen I, Bradford L, Bartz K. Intervention initiatives to raise young people's interest and participation in STEM. Front Psychol. Nov 18, 2022;13:960327. [FREE Full text] [CrossRef] [Medline]
- Schmutz C, Bürgler A, Ashta N, Soenksen J, Bou Karim Y, Shen C, et al. Personal radiofrequency electromagnetic field exposure of adolescents in the Greater London area in the SCAMP cohort and the association with restrictions on permitted use of mobile communication technologies at school and at home. Environ Res. Sep 2022;212(Pt B):113252. [FREE Full text] [CrossRef] [Medline]
- Schmidt A, Dirk J, Schmiedek F. The importance of peer relatedness at school for affective well‐being in children: between‐ and within‐person associations. Soc Dev. Jun 06, 2019;28(4):873-892. [CrossRef]
- Schmidt A, Neubauer AB, Dirk J, Schmiedek F. The bright and the dark side of peer relationships: differential effects of relatedness satisfaction and frustration at school on affective well-being in children's daily lives. Dev Psychol. Aug 2020;56(8):1532-1546. [CrossRef] [Medline]
- Scharf DM, Martino SC, Setodji CM, Staplefoote BL, Shadel WG. Middle and high school students' exposure to alcohol- and smoking-related media: a pilot study using ecological momentary assessment. Psychol Addict Behav. Dec 2013;27(4):1201-1206. [FREE Full text] [CrossRef] [Medline]
- Schappo C, Garanhani RR, Cordeiro ME, Oppitz LR, Schneider N, Tanaka OM, et al. Assessment of awake bruxism and oral mucosa indentation in adolescents. J Oral Rehabil. Aug 27, 2023;50(8):671-678. [CrossRef] [Medline]
- Salvy S, Bowker J, Roemmich J, Romero N, Kieffer E, Paluch R, et al. Peer influence on children's physical activity: an experience sampling study. J Pediatr Psychol. 2008;33(1):39-49. [FREE Full text] [CrossRef] [Medline]
- Salmela-Aro K, Moeller J, Schneider B, Spicer J, Lavonen J. Integrating the light and dark sides of student engagement using person-oriented and situation-specific approaches. Learn Instr. Jun 2016;43:61-70. [CrossRef]
- Salamon R, Husky MM, Swendsen JD. Self-esteem and emotional well-being of students in academic difficulty: a study in daily life. J Thér Comport Cogn. Mar 2013;23(1):24-30. [CrossRef]
- Saarikallio SH, Randall WM, Baltazar M. Music listening for supporting adolescents' sense of agency in daily life. Front Psychol. Jan 8, 2019;10:2911. [FREE Full text] [CrossRef] [Medline]
- Russell MA, Wang L, Odgers CL. Witnessing substance use increases same-day antisocial behavior among at-risk adolescents: Gene-environment interaction in a 30-day ecological momentary assessment study. Dev Psychopathol. Nov 09, 2016;28(4pt2):1441-1456. [FREE Full text] [CrossRef] [Medline]
- Rusby JC, Westling E, Crowley R, Mills KL, Light JM. Associations between marijuana use and anxious mood lability during adolescence. Addict Behav. May 2019;92:89-94. [FREE Full text] [CrossRef] [Medline]
- Rusby JC, Westling E, Crowley R, Light JM. Concurrent and predictive associations between early adolescent perceptions of peer affiliates and mood states collected in real time via ecological momentary assessment methodology. Psychol Assess. Mar 2013;25(1):47-60. [FREE Full text] [CrossRef] [Medline]
- Rumbold J, Fletcher D, Daniels K. An experience sampling study of organizational stress processes and future playing time in professional sport. J Sports Sci. Mar 28, 2020;38(5):559-567. [CrossRef] [Medline]
- Ross K, Martin T, Chen E, Miller GE. Social encounters in daily life and 2-year changes in metabolic risk factors in young women. Dev Psychopathol. Aug 15, 2011;23(3):897-906. [FREE Full text] [CrossRef] [Medline]
- Rosen PJ, Factor PI. Emotional impulsivity and emotional and behavioral difficulties among children with ADHD: an ecological momentary assessment study. J Atten Disord. Sep 19, 2015;19(9):779-793. [CrossRef] [Medline]
- Rosen PJ, Epstein JN, Van Orden G. I know it when I quantify it: ecological momentary assessment and recurrence quantification analysis of emotion dysregulation in children with ADHD. Atten Defic Hyperact Disord. Sep 22, 2013;5(3):283-294. [FREE Full text] [CrossRef] [Medline]
- Rönkä A, Sevón E, Räikkönen E, Hintikka T. Manuscript: you have a message from illi! the mobile diary in researching children’s daily experiences. Child Ind Res. Mar 29, 2016;10(2):505-523. [CrossRef]
- Rodman AM, Vidal Bustamante CM, Dennison MJ, Flournoy JC, Coppersmith DD, Nook EC, et al. A year in the social life of a teenager: within-person fluctuations in stress, phone communication, and anxiety and depression. Clin Psychol Sci. Sep 01, 2021;9(5):791-809. [FREE Full text] [CrossRef] [Medline]
- Roberts ME, Keller-Hamilton B, Hinton A, Browning CR, Slater MD, Xi W, et al. The magnitude and impact of tobacco marketing exposure in adolescents' day-to-day lives: an ecological momentary assessment (EMA) study. Addict Behav. Jan 2019;88:144-149. [FREE Full text] [CrossRef] [Medline]
- Riddell M, Gal R, Bergford S, Patton S, Clements M, Calhoun P, et al. The acute effects of real-world physical activity on glycemia in adolescents with type 1 diabetes: the type 1 diabetes exercise initiative pediatric (T1DEXIP) study. Diabetes Care. Jan 01, 2024;47(1):132-139. [CrossRef] [Medline]
- Rhee H, Belyea MJ, Sterling M, Bocko MF. Evaluating the validity of an automated device for asthma monitoring for adolescents: correlational design. J Med Internet Res. Oct 16, 2015;17(10):e234. [FREE Full text] [CrossRef] [Medline]
- Rende R, Slomkowski C, Floro J, Jamner L. Capturing rule breaking behavior between siblings in real time and everyday settings. Eur J Dev Sci. 2009;3(2):150-160. [CrossRef]
- Reid SC, Kauer SD, Dudgeon P, Sanci LA, Shrier LA, Patton GC. A mobile phone program to track young people's experiences of mood, stress and coping. Development and testing of the mobiletype program. Soc Psychiatry Psychiatr Epidemiol. Jun 2009;44(6):501-507. [CrossRef] [Medline]
- Rauschenberg C, van Os J, Cremers D, Goedhart M, Schieveld JN, Reininghaus U. Stress sensitivity as a putative mechanism linking childhood trauma and psychopathology in youth's daily life. Acta Psychiatr Scand. Oct 2017;136(4):373-388. [CrossRef] [Medline]
- Ranzenhofer LM, Engel SG, Crosby RD, Haigney M, Tanofsky-Kraff M. A pilot study of attachment style and emotional experience in adolescent girls with loss of control eating. Adv Eat Disord. Sep 06, 2016;4(3):250-263. [CrossRef]
- Rahdar A, Galván A. The cognitive and neurobiological effects of daily stress in adolescents. Neuroimage. May 15, 2014;92:267-273. [CrossRef] [Medline]
- Rah MJ, Walline JJ, Lynn Mitchell G, Zadnik K. Comparison of the experience sampling method and questionnaires to assess visual activities in pre-teen and adolescent children. Ophthalmic Physiol Opt. Sep 11, 2006;26(5):483-489. [CrossRef] [Medline]
- Rabbitts JA, Zhou C, Narayanan A, Palermo TM. Longitudinal and temporal associations between daily pain and sleep patterns after major pediatric surgery. J Pain. Jun 2017;18(6):656-663. [FREE Full text] [CrossRef] [Medline]
- Rabbitts JA, Holley AL, Karlson CW, Palermo TM. Bidirectional associations between pain and physical activity in adolescents. Clin J Pain. Mar 2014;30(3):251-258. [FREE Full text] [CrossRef] [Medline]
- Psihogios AM, Li Y, Ahmed A, Huang J, Kersun LS, Schwartz LA, et al. Daily text message assessments of 6-mercaptopurine adherence and its proximal contexts in adolescents and young adults with leukemia: a pilot study. Pediatr Blood Cancer. Feb 2021;68(2):e28767. [FREE Full text] [CrossRef] [Medline]
- Pramana G, Parmanto B, Kendall PC, Silk JS. The SmartCAT: an m-health platform for ecological momentary intervention in child anxiety treatment. Telemed J E Health. May 2014;20(5):419-427. [FREE Full text] [CrossRef] [Medline]
- Pöysä S, Vasalampi K, Muotka J, Lerkkanen M, Poikkeus A, Nurmi J. Variation in situation-specific engagement among lower secondary school students. Learn. Instr. Feb 2018;53:64-73. [CrossRef]
- Pihet S, De Ridder J, Suter M. Ecological Momentary Assessment (EMA) goes to jail: capturing daily antisocial behavior in its context, a feasibility and reliability study in incarcerated juvenile offenders. Eur J Psychol Assess. Mar 2017;33(2):87-96. [CrossRef]
- Parker MN, Tanofsky-Kraff M, Crosby RD, Byrne ME, LeMay-Russell S, Swanson TN, et al. Food cravings and loss-of-control eating in youth: associations with gonadal hormone concentrations. Int J Eat Disord. Aug 04, 2021;54(8):1426-1437. [FREE Full text] [CrossRef] [Medline]
- Owens J, Sangal RB, Sutton VK, Bakken R, Allen AJ, Kelsey D. Subjective and objective measures of sleep in children with attention-deficit/hyperactivity disorder. Sleep Med. Apr 2009;10(4):446-456. [CrossRef] [Medline]
- Ortega-Williams A, Booth JM, Fussell-Ware DJ, Lawrence YJ, Pearl D, Chapman N, et al. Using ecological momentary assessments to understand black youths' experiences of racism, stress, and safety. J Res Adolesc. Mar 03, 2022;32(1):270-289. [FREE Full text] [CrossRef] [Medline]
- Nugent NR, Armey M, Boker S, Brick L, Knopik V, McGeary JE, et al. Adolescents hospitalised for suicidality: biomarkers, social and affective predictors: a cohort study. BMJ Open. Oct 03, 2022;12(10):e056063. [FREE Full text] [CrossRef] [Medline]
- Nollen NL, Mayo MS, Carlson SE, Rapoff MA, Goggin KJ, Ellerbeck EF. Mobile technology for obesity prevention: a randomized pilot study in racial- and ethnic-minority girls. Am J Prev Med. Apr 2014;46(4):404-408. [FREE Full text] [CrossRef] [Medline]
- Noël C, Armiento C, Péfoyo AK, Klein R, Bédard M, Scharf D. Adolescent exposure to cannabis marketing following recreational cannabis legalization in Canada: a pilot study using ecological momentary assessment. Addict Behav Rep. Dec 2021;14:100383. [FREE Full text] [CrossRef] [Medline]
- Nock MK, Prinstein MJ, Sterba SK. Revealing the form and function of self-injurious thoughts and behaviors: a real-time ecological assessment study among adolescents and young adults. Psychol Violence. Aug 2010;1(S):36-52. [CrossRef]
- Nock MK, Prinstein MJ, Sterba SK. Revealing the form and function of self-injurious thoughts and behaviors: a real-time ecological assessment study among adolescents and young adults. J Abnorm Psychol. Nov 2009;118(4):816-827. [FREE Full text] [CrossRef] [Medline]
- Niestroj SC, Steden S, Boecker M, Brodkin ES, Konrad K. The development and validation of the first German open scale of social information processing. Psychopathology. Aug 31, 2023;56(1-2):52-63. [CrossRef] [Medline]
- Neubauer AB, Kramer AC, Schmidt A, Könen T, Dirk J, Schmiedek F. Reciprocal relations of subjective sleep quality and affective well-being in late childhood. Dev Psychol. Aug 2021;57(8):1372-1386. [CrossRef] [Medline]
- Nereim C, Bickham D, Rich M. Exploring use patterns and racial and ethnic differences in real time affective states during social media use among a clinical sample of adolescents with depression: prospective cohort study. JMIR Form Res. May 12, 2022;6(5):e30900. [FREE Full text] [CrossRef] [Medline]
- Nap-van der Vlist MM, Houtveen J, Dalmeijer GW, Grootenhuis MA, van der Ent CK, van Grotel M, et al. Internet and smartphone-based ecological momentary assessment and personalized advice (PROfeel) in adolescents with chronic conditions: a feasibility study. Internet Interv. Sep 2021;25:100395. [FREE Full text] [CrossRef] [Medline]
- Naim R, Smith A, Chue A, Grassie H, Linke J, Dombek K, et al. Using ecological momentary assessment to enhance irritability phenotyping in a transdiagnostic sample of youth. Dev Psychopathol. Dec 07, 2021;33(5):1734-1746. [CrossRef]
- Murray DW, Ridenour TA, Swingler MM, Morgan A, Hegarty-Craver M. Feasibility of combining biosensor and ecological momentary assessment to measure stress experiences among economically disadvantaged adolescents. Stress Health. Aug 24, 2023;39(3):684-689. [CrossRef] [Medline]
- Mulvaney SA, Vaala S, Hood KK, Lybarger C, Carroll R, Williams L, et al. Mobile momentary assessment and biobehavioral feedback for adolescents with type 1 diabetes: feasibility and engagement patterns. Diabetes Technol Ther. Jul 2018;20(7):465-474. [FREE Full text] [CrossRef] [Medline]
- Mulvaney SA, Rothman RL, Dietrich MS, Wallston KA, Grove E, Elasy TA, et al. Using mobile phones to measure adolescent diabetes adherence. Health Psychol. Jan 2012;31(1):43-50. [FREE Full text] [CrossRef] [Medline]
- Müller LR, Gossmann K, Schmid RF, Rosner R, Unterhitzenberger J. A pilot study on ecological momentary assessment in asylum-seeking children and adolescents resettled to Germany: Investigating compliance, post-migration factors, and the relation between daily mood, sleep patterns, and mental health. PLoS One. Feb 1, 2021;16(2):e0246069. [FREE Full text] [CrossRef] [Medline]
- Moeller J, Ivcevic Z, Brackett MA, White AE. Mixed emotions: network analyses of intra-individual co-occurrences within and across situations. Emotion. Dec 2018;18(8):1106-1121. [CrossRef] [Medline]
- Minich M, Zhao Q, Eickhoff J, Moreno MA. In the mood for music: listening to music and other smartphone uses improve adolescent mood. Cyberpsychol Behav Soc Netw. Nov 01, 2023;26(11):869-873. [CrossRef] [Medline]
- Milojevich HM, Stickel D, Swingler MM, Zhang X, Terrell J, Sheridan MA, et al. Building an ecological momentary assessment smartphone app for 4- to 10-year-old children: a pilot study. PLoS One. Aug 30, 2023;18(8):e0290148. [FREE Full text] [CrossRef] [Medline]
- Mikalsen IB, Nassehi D, Øymar K. Vortex whistle and smart phone application for peak flow recordings in asthmatic children: a feasibility study. Telemed J E Health. Nov 2019;25(11):1077-1082. [FREE Full text] [CrossRef] [Medline]
- Michel C, Lerch S, Büetiger JR, Flückiger R, Cavelti M, Koenig J, et al. An ecological momentary assessment study of age effects on perceptive and non-perceptive clinical high-risk symptoms of psychosis. Eur Child Adolesc Psychiatry. Oct 18, 2023;32(10):1841-1852. [FREE Full text] [CrossRef] [Medline]
- Messer LH, Vigers T, Pyle L, Fivekiller E, Wadwa RP, Hernandez TL, et al. Novel predictors of daily fluctuations in glycemia and self-management in adolescents and young adults with type 1 diabetes. Diabet Med. Sep 07, 2022;39(9):e14910. [CrossRef] [Medline]
- Mereish EH, Treloar Padovano H, Parlette B, Miranda R. Momentary associations among minority stress, craving, affect, and nicotine use among sexual minority youth. J Clin Child Adolesc Psychol. Jul 27, 2022;51(6):877-891. [FREE Full text] [CrossRef] [Medline]
- Mennis J, Mason M, Ambrus A. Urban greenspace is associated with reduced psychological stress among adolescents: a geographic ecological momentary assessment (GEMA) analysis of activity space. Landsc Urban Plan. Jun 2018;174:1-9. [FREE Full text] [CrossRef] [Medline]
- Mazereel V, Vansteelandt K, Menne-Lothmann C, Decoster J, Derom C, Thiery E, et al. The complex and dynamic interplay between self-esteem, belongingness and physical activity in daily life: an experience sampling study in adolescence and young adulthood. Ment Health Phys Act. Oct 2021;21:100413. [CrossRef]
- Mayne SL, DiFiore G, Hannan C, Nwokeji U, Tam V, Filograna C, et al. Feasibility and acceptability of mobile methods to assess home and neighborhood environments related to adolescent sleep. Sleep Health. Jun 2023;9(3):331-338. [FREE Full text] [CrossRef] [Medline]
- Mason M, Mennis J, Way T, Floyd Campbell L. Real-time readiness to quit and peer smoking within a text message intervention for adolescent smokers: modeling mechanisms of change. J Subst Abuse Treat. Dec 2015;59:67-73. [CrossRef] [Medline]
- Maskevich S, Shen L, Drummond SP, Bei B. What time do you plan to sleep tonight? An intense longitudinal study of adolescent daily sleep self-regulation via planning and its associations with sleep opportunity. J Child Psychol Psychiatry. Aug 22, 2022;63(8):900-911. [CrossRef] [Medline]
- Martin AJ, Papworth B, Ginns P, Malmberg L, Collie RJ, Calvo RA. Real-time motivation and engagement during a month at school: every moment of every day for every student matters. Learn Individ Differ. Feb 2015;38:26-35. [CrossRef]
- Martin AJ, Mansour M, Malmberg L. What factors influence students’ real-time motivation and engagement? An experience sampling study of high school students using mobile technology. Educ Psychol. Feb 09, 2019;40(9):1113-1135. [CrossRef]
- Malmberg L, Walls TA, Martin AJ, Little TD, Lim WH. Primary school students' learning experiences of, and self-beliefs about competence, effort, and difficulty: random effects models. Learn Individ Differ. Dec 2013;28:54-65. [CrossRef]
- Magallón-Neri E, Kirchner-Nebot T, Forns-Santacana M, Calderón C, Planellas I. Ecological momentary assessment with smartphones for measuring mental health problems in adolescents. World J Psychiatry. Sep 22, 2016;6(3):303-310. [FREE Full text] [CrossRef] [Medline]
- Loukomies A, Juuti K, Lavonen J. Investigating situational interest in primary science lessons. Int J Sci Educ. Jan 06, 2016;37(18):3015-3037. [CrossRef]
- Lipperman-Kreda S, Mair C, Gruenewald PJ. Ecological momentary assessments of night-time drinking among California adolescents: bases for informing night-time preventive interventions. Addiction. Dec 05, 2021;116(12):3408-3421. [FREE Full text] [CrossRef] [Medline]
- Lionarons JM, Delespaul PA, Hellebrekers DM, Broen MP, Klinkenberg S, Faber CG, et al. Use of the experience sampling method in adolescents with Duchenne muscular dystrophy: a feasibility study. Eur Child Adolesc Psychiatry. Jul 01, 2024;33(7):2281-2290. [CrossRef] [Medline]
- Limberger MF, Schmiedek F, Santangelo PS, Reichert M, Wieland LM, Berhe O, et al. Assessing affect in adolescents with e-diaries: multilevel confirmatory factor analyses of different factor models. Front Psychol. Jun 23, 2023;14:1061229. [FREE Full text] [CrossRef] [Medline]
- Lewandowski L, Rieger B, Smyth J, Perry L, Gathje R. Measuring post-concussion symptoms in adolescents: feasibility of ecological momentary assessment. Arch Clin Neuropsychol. Dec 04, 2009;24(8):791-796. [CrossRef] [Medline]
- Letkiewicz AM, Funkhouser CJ, Umemoto A, Trivedi E, Sritharan A, Zhang E, et al. Neurophysiological responses to emotional faces predict dynamic fluctuations in affect in adolescents. Psychophysiology. Apr 31, 2024;61(4):e14476. [CrossRef] [Medline]
- Lennarz HK, Lichtwarck-Aschoff A, Finkenauer C, Granic I. Jealousy in adolescents' daily lives: how does it relate to interpersonal context and well-being? J Adolesc. Jan 16, 2017;54(1):18-31. [CrossRef] [Medline]
- Lekkas D, Gyorda JA, Jacobson NC. A machine learning investigation into the temporal dynamics of physical activity-mediated emotional regulation in adolescents with anorexia nervosa and healthy controls. Eur Eat Disord Rev. Jan 25, 2023;31(1):147-165. [FREE Full text] [CrossRef] [Medline]
- Lee M, Bong M. Patterns of motivation and learning during test-preparation of Korean adolescents: an experience sampling approach. Educ Psychol. Dec 16, 2021;42(2):200-221. [CrossRef]
- Lavonen J, Ávalos B, Upadyaya K, Araneda S, Juuti K, Cumsille P, et al. Upper secondary students’ situational interest in physics learning in Finland and Chile. Int J Sci Educ. Oct 28, 2021;43(16):2577-2596. [CrossRef]
- Laakso M, Fagerlund Å, Pesonen A, Figueiredo RA, Eriksson JG. The impact of the positive education program flourishing students on early adolescents’ daily positive and negative emotions using the experience sampling method. J Early Adolesc. May 30, 2022;43(4):385-417. [CrossRef]
- Kudinova A, Brick LA, Barthelemy C, MacPherson HA, Jenkins G, DeYoung L, et al. Sex and age moderate the trajectory of guilt among children and adolescents with and without recent suicidal ideation. Cogn Emot. May 25, 2022;36(3):512-526. [FREE Full text] [CrossRef] [Medline]
- Kubiak T, Vögele C, Siering M, Schiel R, Weber H. Daily hassles and emotional eating in obese adolescents under restricted dietary conditions--the role of ruminative thinking. Appetite. Jul 2008;51(1):206-209. [CrossRef] [Medline]
- Kracht CL, Beyl RA, Maher JP, Katzmarzyk PT, Staiano AE. Adolescents' sedentary time, affect, and contextual factors: an ecological momentary assessment study. Int J Behav Nutr Phys Act. Apr 15, 2021;18(1):53. [FREE Full text] [CrossRef] [Medline]
- Kovac M, Mosner M, Miller S, Hanna EK, Dichter GS. Experience sampling of positive affect in adolescents with autism: feasibility and preliminary findings. Res Autism Spectr Disord. Sep 2016;29-30:57-65. [FREE Full text] [CrossRef] [Medline]
- Kolar DR, Hammerle F, Jenetzky E, Huss M, Bürger A. Aversive tension in female adolescents with Anorexia Nervosa: a controlled ecological momentary assessment using smartphones. BMC Psychiatry. Apr 12, 2016;16(1):97. [FREE Full text] [CrossRef] [Medline]
- Koenig J, Klier J, Parzer P, Santangelo P, Resch F, Ebner-Priemer U, et al. High-frequency ecological momentary assessment of emotional and interpersonal states preceding and following self-injury in female adolescents. Eur Child Adolesc Psychiatry. Aug 2021;30(8):1299-1308. [FREE Full text] [CrossRef] [Medline]
- Koechlin H, Beeckman M, Meier AH, Locher C, Goubert L, Kossowsky J, et al. Association of parental and adolescent emotion-related factors with adolescent chronic pain behaviors. Pain. Jul 01, 2022;163(7):e888-e898. [FREE Full text] [CrossRef] [Medline]
- Klipker K, Wrzus C, Rauers A, Boker SM, Riediger M. Within-person changes in salivary testosterone and physical characteristics of puberty predict boys' daily affect. Horm Behav. Sep 2017;95:22-32. [CrossRef] [Medline]
- Kirshenbaum JS, Coury SM, Colich NL, Manber R, Gotlib IH. Objective and subjective sleep health in adolescence: associations with puberty and affect. J Sleep Res. Jun 13, 2023;32(3):e13805. [FREE Full text] [CrossRef] [Medline]
- King KM, Feil MC, Halvorson MA. Negative urgency is correlated with the use of reflexive and disengagement emotion regulation strategies. Clin Psychol Sci. Aug 08, 2018;6(6):822-834. [CrossRef]
- Kim J, Nakamura T, Kikuchi H, Sasaki T, Yamamoto Y. Co-variation of depressive mood and locomotor dynamics evaluated by ecological momentary assessment in healthy humans. PLoS One. Sep 13, 2013;8(9):e74979. [FREE Full text] [CrossRef] [Medline]
- Kim BH, Ranzenhofer L, Stadterman J, Karvay YG, Burke NL. Food insecurity and eating pathology in adolescents. Int J Environ Res Public Health. Aug 30, 2021;18(17):9155. [FREE Full text] [CrossRef] [Medline]
- Kichline T, Cushing C, Ortega A, Friesen C, Schurman J. Associations between physical activity and chronic pain severity in youth with chronic abdominal pain. Clin J Pain. Jul 2019;35(7):618-624. [CrossRef] [Medline]
- Khor AS, Gray KM, Reid SC, Melvin GA. Feasibility and validity of ecological momentary assessment in adolescents with high-functioning autism and Asperger's disorder. J Adolesc. Jan 2014;37(1):37-46. [CrossRef] [Medline]
- Ketonen EE, Salonen V, Lonka K, Salmela-Aro K. Can you feel the excitement? Physiological correlates of students' self-reported emotions. Br J Educ Psychol. Apr 22, 2023;93 Suppl 1(S1):113-129. [CrossRef] [Medline]
- Kennedy TM, Molina BS, Pedersen SL. Change in adolescents' perceived ADHD symptoms across 17 days of ecological momentary assessment. J Clin Child Adolesc Psychol. Jul 26, 2024;53(3):397-412. [CrossRef] [Medline]
- Kauer SD, Reid SC, Crooke AH, Khor A, Hearps SJ, Jorm AF, et al. Self-monitoring using mobile phones in the early stages of adolescent depression: randomized controlled trial. J Med Internet Res. Jun 25, 2012;14(3):e67. [FREE Full text] [CrossRef] [Medline]
- Karsay K, Matthes J, Schmuck D, Ecklebe S. Messaging, posting, and browsing: a mobile experience sampling study investigating youth’s social media use, affective well-being, and loneliness. Soc Sci Comput Rev. Apr 05, 2022;41(4):1493-1513. [CrossRef]
- Juuti K, Loukomies A, Lavonen J. Interest in dialogic and non-dialogic teacher talk situations in middle school science classroom. Int J of Sci and Math Educ. Nov 26, 2019;18(8):1531-1546. [CrossRef]
- Johnson EI, Swendsen JD. Perceived social status and early adolescents’ responses to negative daily events. J Child Fam Stud. May 6, 2014;24(6):1593-1604. [CrossRef]
- Jibb LA, Stevens BJ, Nathan PC, Seto E, Cafazzo JA, Johnston DL, et al. Implementation and preliminary effectiveness of a real-time pain management smartphone app for adolescents with cancer: a multicenter pilot clinical study. Pediatr Blood Cancer. Oct 2017;64(10):19. [CrossRef] [Medline]
- Jessup G, Bundy AC, Broom A, Hancock N. The social experiences of high school students with visual impairments. J Vis Impair Blind. Jan 01, 2017;111(1):5-19. [CrossRef]
- Jensen M, George MJ, Russell MR, Odgers CL. Young adolescents' digital technology use and mental health symptoms: little evidence of longitudinal or daily linkages. Clin Psychol Sci. Nov 20, 2019;7(6):1416-1433. [FREE Full text] [CrossRef] [Medline]
- Janssen LH, Verkuil B, van Houtum LA, Wever MC, Elzinga BM. Perceptions of parenting in daily life: adolescent-parent differences and associations with adolescent affect. J Youth Adolesc. Dec 04, 2021;50(12):2427-2443. [FREE Full text] [CrossRef] [Medline]
- Janna I, Christopher K, Barbara S, Kalle J, Joseph K, Jari L, et al. Science classroom activities and student situational engagement. Int J Sci Educ. Dec 01, 2018;41(3):316-329. [CrossRef]
- Jacob E, Duran J, Stinson J, Lewis MA, Zeltzer L. Remote monitoring of pain and symptoms using wireless technology in children and adolescents with sickle cell disease. J Am Assoc Nurse Pract. Jan 2013;25(1):42-54. [FREE Full text] [CrossRef] [Medline]
- Hunter JF, Acevedo AM, Gago-Masague S, Kain A, Yun C, Torno L, et al. A pilot study of the preliminary efficacy of pain buddy: a novel intervention for the management of children's cancer-related pain. Pediatr Blood Cancer. Oct 2020;67(10):e28278. [FREE Full text] [CrossRef] [Medline]
- Sew Hoy W, Antoun JS, Lin W, Chandler N, Merriman T, Farella M. Ecological momentary assessment of pain in adolescents undergoing orthodontic treatment using a smartphone app. Semin Orthod. Jun 2018;24(2):209-216. [CrossRef]
- Hoeppner BB, Kahler CW, Gwaltney CJ. Relationship between momentary affect states and self-efficacy in adolescent smokers. Health Psychol. Dec 2014;33(12):1507-1517. [FREE Full text] [CrossRef] [Medline]
- Hennig T, Krkovic K, Lincoln TM. What predicts inattention in adolescents? An experience-sampling study comparing chronotype, subjective, and objective sleep parameters. Sleep Med. Oct 2017;38:58-63. [CrossRef] [Medline]
- Helgeson VS, Lopez LC, Kamarck T. Peer relationships and diabetes: retrospective and ecological momentary assessment approaches. Health Psychol. May 2009;28(3):273-282. [FREE Full text] [CrossRef] [Medline]
- Heathcote LC, Cunningham SJ, Webster SN, Tanna V, Mattke E, Loecher N, et al. Smartphone-based ecological momentary assessment to study "scanxiety" among adolescent and young adult survivors of childhood cancer: a feasibility study. Psychooncology. Aug 25, 2022;31(8):1322-1330. [FREE Full text] [CrossRef] [Medline]
- Hao H, Eckel SP, Hosseini A, Van Vliet ED, Dzubur E, Dunton G, et al. Daily associations of air pollution and pediatric asthma risk using the biomedical REAI-time health evaluation (BREATHE) kit. Int J Environ Res Public Health. Mar 17, 2022;19(6):3578. [FREE Full text] [CrossRef] [Medline]
- Hank P, Baltes-Götz B. The stability of self-esteem variability: a real-time assessment. J Res Pers. Apr 2019;79:143-150. [CrossRef]
- Hamilton JL, Do QB, Choukas-Bradley S, Ladouceur CD, Silk JS. Where it hurts the most: peer interactions on social media and in person are differentially associated with emotional reactivity and sustained affect among adolescent girls. Res Child Adolesc Psychopathol. Feb 27, 2021;49(2):155-167. [FREE Full text] [CrossRef] [Medline]
- Hamilton JL, Chand S, Reinhardt L, Ladouceur CD, Silk JS, Moreno M, et al. Social media use predicts later sleep timing and greater sleep variability: an ecological momentary assessment study of youth at high and low familial risk for depression. J Adolesc. Aug 06, 2020;83(1):122-130. [FREE Full text] [CrossRef] [Medline]
- Gwaltney C, Ivanescu C, Karlsson L, Warholic N, Kjems L, Horn P. Validation of the PRUCISION instruments in pediatric patients with progressive familial intrahepatic cholestasis. Adv Ther. Nov 06, 2022;39(11):5105-5125. [FREE Full text] [CrossRef] [Medline]
- Griffith JM, Hankin BL. Affective benefits of parental engagement with adolescent positive daily life experiences. J Youth Adolesc. Oct 31, 2021;50(10):2036-2051. [CrossRef] [Medline]
- Grenard JL, Stacy AW, Shiffman S, Baraldi AN, MacKinnon DP, Lockhart G, et al. Sweetened drink and snacking cues in adolescents: a study using ecological momentary assessment. Appetite. Aug 2013;67:61-73. [FREE Full text] [CrossRef] [Medline]
- Goldschmidt AB, Smith KE, Crosby RD, Boyd HK, Dougherty E, Engel SG, et al. Ecological momentary assessment of maladaptive eating in children and adolescents with overweight or obesity. Int J Eat Disord. Jun 06, 2018;51(6):549-557. [FREE Full text] [CrossRef] [Medline]
- Goldschmidt AB, Goldstein SP, Schmiedek F, Stalvey E, Irizarry B, Thomas JG. State-level working memory and dysregulated eating in children and adolescents: an exploratory ecological momentary assessment study. Int J Eat Disord. Jan 27, 2024;57(1):93-103. [CrossRef] [Medline]
- Gold BD, Pilmer B, Kierkuś J, Hunt B, Perez MC, Gremse D. Dexlansoprazole for heartburn relief in adolescents with symptomatic, nonerosive gastro-esophageal reflux disease. Dig Dis Sci. Nov 15, 2017;62(11):3059-3068. [FREE Full text] [CrossRef] [Medline]
- Goetz T, Keller MM, Lüdtke O, Nett UE, Lipnevich AA. The dynamics of real-time classroom emotions: appraisals mediate the relation between students’ perceptions of teaching and their emotions. J Educ Psychol. Aug 2020;112(6):1243-1260. [CrossRef]
- Glista D, O'Hagan R, Van Eeckhoutte M, Lai Y, Scollie S. The use of ecological momentary assessment to evaluate real-world aided outcomes with children. Int J Audiol. Apr 24, 2021;60(sup1):S68-S78. [FREE Full text] [CrossRef] [Medline]
- Glenn CR, Kleiman EM, Kearns JC, Santee AC, Esposito EC, Conwell Y, et al. Feasibility and acceptability of ecological momentary assessment with high-risk suicidal adolescents following acute psychiatric care. J Clin Child Adolesc Psychol. Apr 02, 2022;51(1):32-48. [CrossRef] [Medline]
- Gibson F, Aldiss S, Taylor RM, Maguire R, McCann L, Sage M, et al. Utilization of the medical research council evaluation framework in the development of technology for symptom management: the ASyMS-YG study. Cancer Nurs. 2010;33(5):343-352. [CrossRef] [Medline]
- Garcia C, Hardeman RR, Kwon G, Lando-King E, Zhang L, Genis T, et al. Teenagers and texting: use of a youth ecological momentary assessment system in trajectory health research with latina adolescents. JMIR Mhealth Uhealth. Jan 24, 2014;2(1):e3. [FREE Full text] [CrossRef] [Medline]
- Galván A, McGlennen KM. Daily stress increases risky decision-making in adolescents: a preliminary study. Dev Psychobiol. May 19, 2012;54(4):433-440. [CrossRef] [Medline]
- Fuller-Tyszkiewicz M, McCabe M, Skouteris H, Richardson B, Nihill K, Watson B, et al. Does body satisfaction influence self-esteem in adolescents' daily lives? An experience sampling study. J Adolesc. Dec 07, 2015;45(1):11-19. [CrossRef] [Medline]
- Fortier MA, Chung WW, Martinez A, Gago-Masague S, Sender L. Pain buddy: a novel use of m-health in the management of children's cancer pain. Comput Biol Med. Sep 01, 2016;76:202-214. [FREE Full text] [CrossRef] [Medline]
- Fortgang RG, Wang SB, Millner AJ, Reid-Russell A, Beukenhorst AL, Kleiman EM, et al. Increase in suicidal thinking during COVID-19. Clin Psychol Sci. May 15, 2021;9(3):482-488. [FREE Full text] [CrossRef] [Medline]
- Floro JN, Dunton GF, Delfino RJ. Assessing physical activity in children with asthma: convergent validity between accelerometer and electronic diary data. Res Q Exerc Sport. Jun 2009;80(2):153-163. [CrossRef] [Medline]
- Fiedler J, Seiferth C, Eckert T, Woll A, Wunsch K. Sleep quality, valence, energetic arousal, and calmness as predictors of device-based measured physical activity during a three-week mHealth intervention. Ger J Exerc Sport Res. Apr 14, 2022;52(2):237-247. [CrossRef]
- Ferguson K, Gunthert K, Kaidbey JH, Parr M, Visek AJ, Sacheck JM, et al. Behavioral patterns of sugary drink consumption among African American adolescents: a pilot and feasibility study using ecological momentary assessment. Nutrients. May 02, 2023;15(9):2171. [FREE Full text] [CrossRef] [Medline]
- Ewing EL, Xia M, Gunn HE. Affiliative parent-adolescent bedtime and waketime interactions are associated with adolescent sleep. Behav Sleep Med. Mar 03, 2024;22(2):168-178. [CrossRef] [Medline]
- Elovainio M, Kuula L, Halonen R, Pesonen A. Dynamic fluctuations of emotional states in adolescents with delayed sleep phase-a longitudinal network modeling approach. J Affect Disord. Nov 01, 2020;276:467-475. [CrossRef] [Medline]
- El Dahr Y, Perquier F, Moloney M, Woo G, Dobrin-De Grace R, Carvalho D, et al. Feasibility of using research electronic data capture (REDCap) to collect daily experiences of parent-child dyads: ecological momentary assessment study. JMIR Form Res. Nov 09, 2023;7:e42916. [FREE Full text] [CrossRef] [Medline]
- Dzubur E, Huh J, Maher JP, Intille SS, Dunton GF. Response patterns and intra-dyadic factors related to compliance with ecological momentary assessment among mothers and children. Transl Behav Med. Mar 01, 2018;8(2):233-242. [FREE Full text] [CrossRef] [Medline]
- Duvenage M, Correia H, Uink B, Barber BL, Donovan CL, Modecki KL. Technology can sting when reality bites: adolescents’ frequent online coping is ineffective with momentary stress. Comput Human Behav. Jan 2020;102:248-259. [CrossRef]
- Dunton GF, Whalen CK, Jamner LD, Floro JN. Mapping the social and physical contexts of physical activity across adolescence using ecological momentary assessment. Ann Behav Med. Jun 2007;34(2):144-153. [CrossRef]
- Dunton GF, Liao Y, Dzubur E, Leventhal AM, Huh J, Gruenewald T, et al. Investigating within-day and longitudinal effects of maternal stress on children's physical activity, dietary intake, and body composition: Protocol for the MATCH study. Contemp Clin Trials. Jul 2015;43:142-154. [FREE Full text] [CrossRef] [Medline]
- Dunton GF, Kawabata K, Intille S, Wolch J, Pentz MA. Assessing the social and physical contexts of children's leisure-time physical activity: an ecological momentary assessment study. Am J Health Promot. 2012;26(3):135-142. [CrossRef] [Medline]
- Dunton GF, Dzubur E, Intille S. Feasibility and performance test of a real-time sensor-informed context-sensitive ecological momentary assessment to capture physical activity. J Med Internet Res. Jun 01, 2016;18(6):e106. [FREE Full text] [CrossRef] [Medline]
- Dunton G, Dzubur E, Li M, Huh J, Intille S, McConnell R. Momentary assessment of psychosocial stressors, context, and asthma symptoms in Hispanic adolescents. Behav Modif. Jan 05, 2016;40(1-2):257-280. [FREE Full text] [CrossRef] [Medline]
- Doyle C, Werner E, Feng T, Lee S, Altemus M, Isler JR, et al. Pregnancy distress gets under fetal skin: maternal ambulatory assessment and sex differences in prenatal development. Dev Psychobiol. Jul 06, 2015;57(5):607-625. [FREE Full text] [CrossRef] [Medline]
- Domoff SE, Banga CA, Borgen AL, Foley RP, Robinson C, Avery K, et al. Use of passive sensing to quantify adolescent mobile device usage: Feasibility, acceptability, and preliminary validation of the eMoodie application. Hum Behav Emerg Technol. Jan 05, 2021;3(1):63-74. [CrossRef]
- Dietvorst E, Hiemstra M, Maciejewski D, van Roekel E, Bogt TT, Hillegers M, et al. Grumpy or depressed? Disentangling typically developing adolescent mood from prodromal depression using experience sampling methods. J Adolesc. Apr 2021;88:25-35. [FREE Full text] [CrossRef] [Medline]
- Di Giunta L, Lunetti C, Gliozzo G, Rothenberg WA, Lansford JE, Eisenberg N, et al. Negative parenting, adolescents' emotion regulation, self-efficacy in emotion regulation, and psychological adjustment. Int J Environ Res Public Health. Feb 16, 2022;19(4):2251. [FREE Full text] [CrossRef] [Medline]
- Dennis ML, Scott CK, Funk RR, Nicholson L. A pilot study to examine the feasibility and potential effectiveness of using smartphones to provide recovery support for adolescents. Subst Abus. Oct 13, 2015;36(4):486-492. [FREE Full text] [CrossRef] [Medline]
- De France K, Hollenstein T. Emotion regulation strategy use and success during adolescence: assessing the role of context. J Res Adolesc. Jun 29, 2022;32(2):720-736. [CrossRef] [Medline]
- De Baere S, Lefevre J, De Martelaer K, Philippaerts R, Seghers J. Temporal patterns of physical activity and sedentary behavior in 10-14 year-old children on weekdays. BMC Public Health. Aug 19, 2015;15(1):791. [FREE Full text] [CrossRef] [Medline]
- Davison BK, Quigg R, Skidmore PML. Pilot testing a photo-based food diary in nine- to twelve- year old- children from Dunedin, New Zealand. Nutrients. Feb 20, 2018;10(2):20. [FREE Full text] [CrossRef] [Medline]
- Dallman AR, Bailliard A, Harrop C. Identifying predictors of momentary negative affect and depression severity in adolescents with autism: an exploratory ecological momentary assessment study. J Autism Dev Disord. Jan 07, 2022;52(1):291-303. [FREE Full text] [CrossRef] [Medline]
- D'Adamo L, Sonnenblick RM, Juarascio AS, Manasse SM. Relations between forms of dietary restraint, restriction, and loss-of-control eating among adolescents seeking weight control: an ecological momentary assessment study. Eat Behav. Aug 2023;50:101791. [CrossRef] [Medline]
- Czyz EK, Koo HJ, Al-Dajani N, Kentopp SD, Jiang A, King CA. Temporal profiles of suicidal thoughts in daily life: results from two mobile-based monitoring studies with high-risk adolescents. J Psychiatr Res. Sep 2022;153:56-63. [FREE Full text] [CrossRef] [Medline]
- Cushing CC, Mitchell TB, Bejarano CM, Walters RW, Crick CJ, Noser AE. Bidirectional associations between psychological states and physical activity in adolescents: a mHealth pilot study. J Pediatr Psychol. Jun 01, 2017;42(5):559-568. [CrossRef] [Medline]
- Cushing C, Kichline T, Blossom J, Friesen C, Schurman J. Tailoring individualized evaluation of pediatric abdominal pain using ecological momentary assessment (EMA): a pilot study testing feasibility and acceptability. Clin J Pain. Nov 2019;35(11):859-868. [CrossRef] [Medline]
- Crooke AH, Reid SC, Kauer SD, McKenzie DP, Hearps SJC, Khor AS, et al. Temporal mood changes associated with different levels of adolescent drinking: using mobile phones and experience sampling methods to explore motivations for adolescent alcohol use. Drug Alcohol Rev. May 24, 2013;32(3):262-268. [CrossRef] [Medline]
- Corwin DJ, Orchinik J, D'Alonzo B, Agarwal AK, Pettijohn KW, Master CL, et al. A randomized trial of incentivization to maximize retention for real-time symptom and activity monitoring using ecological momentary assessment in pediatric concussion. Pediatr Emerg Care. Jul 01, 2023;39(7):488-494. [CrossRef] [Medline]
- Cordier R, Brown N, Chen Y, Wilkes-Gillan S, Falkmer T. Piloting the use of experience sampling method to investigate the everyday social experiences of children with Asperger syndrome/high functioning autism. Dev Neurorehabil. May 19, 2016;19(2):103-110. [CrossRef] [Medline]
- Connelly M, Miller T, Gerry G, Bickel J. Electronic momentary assessment of weather changes as a trigger of headaches in children. Headache. May 23, 2010;50(5):779-789. [CrossRef] [Medline]
- Connelly M, Anthony KK, Sarniak R, Bromberg MH, Gil KM, Schanberg LE. Parent pain responses as predictors of daily activities and mood in children with juvenile idiopathic arthritis: the utility of electronic diaries. J Pain Symptom Manage. Mar 2010;39(3):579-590. [FREE Full text] [CrossRef] [Medline]
- Connelly MA, Boorigie ME. Feasibility of using "SMARTER" methodology for monitoring precipitating conditions of pediatric migraine episodes. Headache. Mar 31, 2021;61(3):500-510. [CrossRef] [Medline]
- Comulada WS, Lightfoot M, Swendeman D, Grella C, Wu N. Compliance to cell phone-based EMA among Latino youth in outpatient treatment. J Ethn Subst Abuse. 2015;14(3):232-250. [FREE Full text] [CrossRef] [Medline]
- Collins RL, Martino SC, Kovalchik SA, Becker KM, Shadel WG, D'Amico EJ. Alcohol advertising exposure among middle school-age youth: an assessment across all media and venues. J Stud Alcohol Drugs. May 2016;77(3):384-392. [FREE Full text] [CrossRef] [Medline]
- Chun SK, Benjamin KS, Mezulis AH. Investigating affective responding to daily positive events among adolescents using ecological momentary assessment. J Early Adolesc. Dec 27, 2021;42(4):542-564. [CrossRef]
- Chin T, Rickard NS, Vella-Brodrick DA. Development and feasibility of a mobile experience sampling application for tracking program implementation in youth well-being programs. Psychol Well Being. Jan 21, 2016;6(1):1. [FREE Full text] [CrossRef] [Medline]
- Cheng C, Brown CR, Venugopalan J, Wang MD. Towards an effective patient health engagement system using cloud-based text messaging technology. IEEE J Transl Eng Health Med. 2020;8:1-7. [CrossRef]
- Chen YR, Ng DY, Tseng M, Bundy A, Cordier R. The impact of coping behaviors on perceived competence and social anxiety in the everyday social engagement of autistic adolescents. Autism. May 29, 2024;28(5):1268-1279. [CrossRef] [Medline]
- Chandler KD, Hodge CJ, McElvaine K, Olschewski EJ, Melton KK, Deboeck P. Challenges of ecological momentary assessments to study family leisure: participants’ perspectives. J Leis Res. Nov 30, 2021;53(1):159-165. [CrossRef]
- Casperson SL, Sieling J, Moon J, Johnson L, Roemmich JN, Whigham L. A mobile phone food record app to digitally capture dietary intake for adolescents in a free-living environment: usability study. JMIR Mhealth Uhealth. Mar 13, 2015;3(1):e30. [FREE Full text] [CrossRef] [Medline]
- Caon M, Prinelli F, Angelini L, Carrino S, Mugellini E, Orte S, et al. PEGASO e-diary: user engagement and dietary behavior change of a mobile food record for adolescents. Front Nutr. Mar 17, 2022;9:727480. [FREE Full text] [CrossRef] [Medline]
- Byrnes HF, Miller BA, Morrison CN, Wiebe DJ, Woychik M, Wiehe SE. Association of environmental indicators with teen alcohol use and problem behavior: teens' observations vs. objectively-measured indicators. Health Place. Jan 2017;43:151-157. [FREE Full text] [CrossRef] [Medline]
- Byrd AL, Vine V, Frigoletto OA, Vanwoerden S, Stepp SD. A multi-method investigation of parental responses to youth emotion: prospective effects on emotion dysregulation and reactive aggression in daily life. Res Child Adolesc Psychopathol. Feb 15, 2022;50(2):117-131. [FREE Full text] [CrossRef] [Medline]
- Bui AA, Hosseini A, Rocchio R, Jacobs N, Ross MK, Okelo S, et al. Biomedical REAl-Time Health Evaluation (BREATHE): toward an mHealth informatics platform. JAMIA Open. Jul 2020;3(2):190-200. [FREE Full text] [CrossRef] [Medline]
- Browning CR, Ford JL, Tarrence J, Kertes DA, Pickler RH, Way BM, et al. Everyday perceptions of safety and racial disparities in hair cortisol concentration. Psychoneuroendocrinology. Jul 2023;153:106088. [FREE Full text] [CrossRef] [Medline]
- Bromberg MH, Connelly M, Anthony KK, Gil KM, Schanberg LE. Self-reported pain and disease symptoms persist in juvenile idiopathic arthritis despite treatment advances: an electronic diary study. Arthritis Rheumatol. Feb 2014;66(2):462-469. [FREE Full text] [CrossRef] [Medline]
- Bray P, Bundy AC, Ryan MM, North KN. Can in-the-moment diary methods measure health-related quality of life in Duchenne muscular dystrophy? Qual Life Res. May 3, 2017;26(5):1145-1152. [CrossRef] [Medline]
- Brannon EE, Cushing CC, Crick CJ, Mitchell TB. The promise of wearable sensors and ecological momentary assessment measures for dynamical systems modeling in adolescents: a feasibility and acceptability study. Transl Behav Med. Dec 27, 2016;6(4):558-565. [FREE Full text] [CrossRef] [Medline]
- Borus JS, Blood E, Volkening LK, Laffel L, Shrier LA. Momentary assessment of social context and glucose monitoring adherence in adolescents with type 1 diabetes. J Adolesc Health. May 2013;52(5):578-583. [FREE Full text] [CrossRef] [Medline]
- Bogaert L, Van der Gucht K, Kuppens P, Kock M, Schreuder MJ, Kuyken W, et al. The effect of universal school-based mindfulness on anhedonia and emotional distress and its underlying mechanisms: a cluster randomised controlled trial via experience sampling in secondary schools. Behav Res Ther. Oct 2023;169:104405. [FREE Full text] [CrossRef] [Medline]
- Boerner KE, Desai U, Luu J, MacLean KE, Munzner T, Foladare H, et al. "Making data the drug": a pragmatic pilot feasibility randomized crossover trial of data visualization as an intervention for pediatric chronic pain. Children (Basel). Aug 07, 2023;10(8):1355. [FREE Full text] [CrossRef] [Medline]
- Björling EA. The momentary relationship between stress and headaches in adolescent girls. Headache. Sep 26, 2009;49(8):1186-1197. [CrossRef] [Medline]
- Bickham DS, Hswen Y, Rich M. Media use and depression: exposure, household rules, and symptoms among young adolescents in the USA. Int J Public Health. Feb 14, 2015;60(2):147-155. [FREE Full text] [CrossRef] [Medline]
- Beymer PN, Rosenberg JM, Schmidt JA, Naftzger NJ. Examining relationships among choice, affect, and engagement in summer STEM programs. J Youth Adolesc. Jun 22, 2018;47(6):1178-1191. [CrossRef] [Medline]
- Bell BM, Alam R, Mondol AS, Ma M, Emi IA, Preum SM, et al. Validity and feasibility of the monitoring and modeling family eating dynamics system to automatically detect in-field family eating behavior: observational study. JMIR Mhealth Uhealth. Feb 18, 2022;10(2):e30211. [FREE Full text] [CrossRef] [Medline]
- Bekman NM, Winward JL, Lau LL, Wagner CC, Brown SA. The impact of adolescent binge drinking and sustained abstinence on affective state. Alcohol Clin Exp Res. Aug 29, 2013;37(8):1432-1439. [FREE Full text] [CrossRef] [Medline]
- Beesdo-Baum K, Voss C, Venz J, Hoyer J, Berwanger J, Kische H, et al. The Behavior and mind health (BeMIND) study: methods, design and baseline sample characteristics of a cohort study among adolescents and young adults. Int J Methods Psychiatr Res. Mar 05, 2020;29(1):e1804. [FREE Full text] [CrossRef] [Medline]
- Balkaya-Ince M, Tahseen M, Umarji O, Schnitker SA. Does Ramadan serve as a naturalistic intervention to promote Muslim American adolescents’ daily virtues? Evidence from a three wave experience sampling study. J Posit Psychol. Feb 17, 2023;19(5):801-816. [CrossRef]
- Balkaya-Ince M, Cheah CS, Kiang L, Tahseen M. Exploring daily mediating pathways of religious identity in the associations between maternal religious socialization and Muslim American adolescents' civic engagement. Dev Psychol. Aug 2020;56(8):1446-1457. [CrossRef] [Medline]
- Babinski DE, Welkie J. Feasibility of ecological momentary assessment of negative emotion in girls with ADHD: a pilot study. Psychol Rep. Aug 27, 2020;123(4):1027-1043. [FREE Full text] [CrossRef] [Medline]
- Armstrong-Carter E, Garrett SL, Nick EA, Prinstein MJ, Telzer EH. Momentary links between adolescents' social media use and social experiences and motivations: individual differences by peer susceptibility. Dev Psychol. Apr 2023;59(4):707-719. [FREE Full text] [CrossRef] [Medline]
- Apple D, Sequiera S. Puberty, parents, and depression: an EMA study in adolescent girls. Psi Chi J Psychol Res. 2020;25(2):130-141. [CrossRef]
- Algheryafi RA, Bevans KB, Hiremath SV, Lai J, Tucker CA. Convergent validity of the patient reported outcome measurement information system-pediatric physical activity instrument (PROMIS-PA) with wearable devices in adolescents. Children (Basel). May 26, 2023;10(6):940. [FREE Full text] [CrossRef] [Medline]
- Alfvén G. SMS pain diary: a method for real-time data capture of recurrent pain in childhood. Acta Paediatr. Jul 2010;99(7):1047-1053. [CrossRef] [Medline]
- Al Ghriwati N, Winter M, Semko J, Merchant TE, Crabtree VM. The feasibility and acceptability of mobile ecological momentary assessment to evaluate sleep, family functioning, and affect in patients with pediatric craniopharyngioma. J Psychosoc Oncol. Aug 03, 2024;42(2):159-174. [CrossRef] [Medline]
- Akkerman DM, Vulperhorst JP, Akkerman SF. A developmental extension to the multidimensional structure of interests. J Educ Psychol. Jan 2020;112(1):183-203. [CrossRef]
- Achterhof R, Kirtley OJ, Schneider M, Lafit G, Hagemann N, Hermans KS, et al. Daily-life social experiences as a potential mediator of the relationship between parenting and psychopathology in adolescence. Front Psychiatry. Aug 5, 2021;12:697127. [FREE Full text] [CrossRef] [Medline]
- Aceves L, Griffin AM, Sulkowski ML, Martinez G, Knapp KS, Bámaca-Colbert MY, et al. The affective lives of doubled-up Latinx youth: influences of school experiences, familism, and ethnic identity exploration. Psychol Sch. Dec 09, 2020;57(12):1878-1895. [FREE Full text] [CrossRef] [Medline]
- Kaufman J, Birmaher B, Brent D, Rao U, Flynn C, Moreci P, et al. Schedule for affective disorders and schizophrenia for school-age children-present and lifetime version (K-SADS-PL): initial reliability and validity data. J Am Acad Child Adolesc Psychiatry. Jul 1997;36(7):980-988. [FREE Full text] [CrossRef] [Medline]
- Drexl K. Youth EMA Meta-Analysis (YEMAMA) Update. Open Science Framework. 2025. URL: https://kdrexl.shinyapps.io/yemama-app/ [accessed 2025-04-25]
- Smyth JM, Jones DR, Wen CK, Materia FT, Schneider S, Stone A. Influence of ecological momentary assessment study design features on reported willingness to participate and perceptions of potential research studies: an experimental study. BMJ Open. Jul 30, 2021;11(7):e049154. [FREE Full text] [CrossRef] [Medline]
- Griffiths KM, Christensen H. Review of randomised controlled trials of Internet interventions for mental disorders and related conditions. Clin Psychol. Feb 03, 2007;10(1):16-29. [CrossRef]
- Murray AL, Xie T. Engaging adolescents in contemporary longitudinal health research: strategies for promoting participation and retention. J Adolesc Health. Jan 2024;74(1):9-17. [FREE Full text] [CrossRef] [Medline]
- Xiao Z, Robertson S, Long E, Flaig R, Kirby L, Romaniuk L, et al. Loneliness in the Digital World: protocol for a co-produced ecological momentary assessment study in adolescents. BMJ Open. Jun 06, 2024;14(6):e087374. [FREE Full text] [CrossRef] [Medline]
- Hardwicke TE, Serghiou S, Janiaud P, Danchev V, Crüwell S, Goodman SN, et al. Calibrating the scientific ecosystem through meta-research. Annu Rev Stat Appl. Mar 09, 2020;7(1):11-37. [CrossRef]
- Meursinge Reynders R, Ladu L, Di Girolamo N. Contacting of authors modified crucial outcomes of systematic reviews but was poorly reported, not systematic, and produced conflicting results. J Clin Epidemiol. Nov 2019;115:64-76. [CrossRef] [Medline]
- Eisele G, Vachon H, Lafit G, Kuppens P, Houben M, Myin-Germeys I, et al. The effects of sampling frequency and questionnaire length on perceived burden, compliance, and careless responding in experience sampling data in a student population. Assessment. Mar 2022;29(2):136-151. [CrossRef] [Medline]
- Hasselhorn K, Ottenstein C, Lischetzke T. The effects of assessment intensity on participant burden, compliance, within-person variance, and within-person relationships in ambulatory assessment. Behav Res Methods. Aug 2022;54(4):1541-1558. [FREE Full text] [CrossRef] [Medline]
- Kirtley OJ, Lafit G, Achterhof R, Hiekkaranta AP, Myin-Germeys I. Making the black box transparent: a template and tutorial for registration of studies using experience-sampling methods. Adv Methods Pract Psychol Sci. Mar 02, 2021;4(1):1-16. [CrossRef]
Abbreviations
| AA: ambulatory assessment |
| EMA: ecological momentary assessment |
| ESM: experience sampling methodology |
| PRISMA: Preferred Reporting Items for Systematic Reviews and Meta-Analyses |
Edited by A Mavragani; submitted 24.08.24; peer-reviewed by J Thrul, F Yang; comments to author 20.10.24; revised version received 17.01.25; accepted 14.02.25; published 30.04.25.
Copyright©Konstantin Drexl, Vanisha Ralisa, Joëlle Rosselet-Amoussou, Cheng K Wen, Sébastien Urben, Kerstin Jessica Plessen, Jennifer Glaus. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 30.04.2025.
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