Geolocation Patterns, Wi-Fi Connectivity Rates, and Psychiatric Symptoms Among Urban Homeless Youth: Mixed Methods Study Using Self-report and Smartphone Data

JMIR Formative Research, Год журнала: 2023, Номер 7, С. e45309 - e45309

Опубликована: Март 6, 2023

Despite significant research done on youth experiencing homelessness, few studies have examined movement patterns and digital habits in this population. Examining these behaviors may provide useful data to design new health intervention models for homelessness. Specifically, passive collection (data collected without extra steps a user) insights into lived experience user needs putting an additional burden homelessness inform design.The objective of study was explore mobile phone Wi-Fi usage GPS location among Additionally, we further the relationship between as correlated with depression posttraumatic stress disorder (PTSD) symptoms.A total 35 adolescent young adult participants were recruited from general community that included installing sensor acquisition app (Purple Robot) up 6 months. Of participants, 19 had sufficient conduct analyses. At baseline, completed self-reported measures (Patient Health Questionnaire-9 [PHQ-9]) PTSD (PTSD Checklist DSM-5 [PCL-5]). Behavioral features developed extracted data.Almost all (18/19, 95%) used private networks most their noncellular connectivity. Greater associated higher PCL-5 score (P=.006). entropy, representing amount variability time spent across identified clusters, also severity both (P=.007) PHQ-9 (P=.045) scores.Location demonstrated associations symptoms, while only symptom severity. While be conducted establish consistency findings, they suggest offer could tailor interventions.

Язык: Английский

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The Relation between passively collected GPS features and depressive symptoms: A systematic review and meta-analysis. (Preprint)

Опубликована: Сен. 11, 2023

The objective, unobtrusively collected GPS features (eg, homestay and distance) from everyday devices like smartphones may offer a promising augmentation to current assessment tools for depression. However, date, there is no systematic meta-analytical evidence on the associations between This study aimed investigate between-person within-person correlations mobility activity depressive symptoms, critically review quality potential publication bias in field. We searched MEDLINE, PsycINFO, Embase, CENTRAL, ACM, IEEE Xplore, PubMed, Web of Science identify eligible articles focusing depression December 6, 2022, March 24, 2023. Inclusion exclusion criteria were applied 2-stage inclusion process conducted by 2 independent reviewers (YT JK). To be eligible, studies needed report wearable-based variables total symptoms measured with validated questionnaire. Studies underage persons other mental health disorders excluded. Between- analyzed using random effects models. Study was determined comparing against STROBE (Strengthening Reporting Observational Epidemiology) guidelines. Publication investigated Egger test funnel plots. A k=19 involving N=2930 participants included analysis. mean age 38.42 (SD 18.96) years 59.64% 22.99%) being female. Significant identified: distance (<i>r</i>=–0.25, 95% CI –0.29 –0.21), normalized entropy (<i>r</i>–0.17, –0.04), location variance –0.26 (<i>r</i>=–0.13, –0.23 number clusters (<i>r</i>=–0.11, –0.18 –0.03), (<i>r</i>=0.10, 0.00 0.19). reporting within-correlations (k=3) too heterogeneous conduct meta-analysis. deficiency research standards all followed exploratory observational designs, but referenced or fully adhered international guidelines (STROBE). 79% (k=15) underpowered detect small correlation (<i>r</i>=.20). Results showed bias. Our results provide Hence, diagnostics benefit adding as an integral part future expert tools. confirmatory further are needed. In addition, methodological needs improve. OSF Registeries cwder; https://osf.io/cwder

Язык: Английский

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From smartphone data to clinically relevant predictions: A systematic review of digital phenotyping methods in depression

medRxiv (Cold Spring Harbor Laboratory), Год журнала: 2023, Номер unknown

Опубликована: Окт. 5, 2023

Abstract Background Smartphone-based digital phenotyping enables potentially clinically relevant information to be collected as individuals go about their day. This could improve monitoring and interventions for people with Major Depressive Disorder (MDD). The aim of this systematic review was investigate current features methods used in MDD. Methods We searched PubMed, PsycINFO, Embase, Scopus Web Science (10/11/2023) articles including: (1) MDD population, (2) smartphone-based features, (3) validated ratings. Risk bias assessed using several sources. Studies were compared within analysis goals (correlating depression, predicting symptom severity, diagnosis, mood state/episode, other). Twenty-four studies (9801 participants) included. Results achieved moderate performance. Common themes included challenges from complex missing data (leading a risk bias), lack external validation. Discussion made progress towards relating phenotypes clinical variables, often focusing on time-averaged features. investigating temporal dynamics more directly may beneficial patient monitoring. European Research Council consolidator grant: 101001118, Prospero: CRD42022346264, Open Framework: https://osf.io/s7ay4

Язык: Английский

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Deciphering seasonal depression variations and interplays between weather changes, physical activity, and depression severity in real-world settings: Learnings from RADAR-MDD longitudinal mobile health study

Research Square (Research Square), Год журнала: 2024, Номер unknown

Опубликована: Апрель 19, 2024

Abstract Prior research has shown that changes in seasons and weather can have a significant impact on depression severity. However, findings are inconsistent across populations, the interplay between weather, behavior, not been fully quantified. This study analyzed real-world data from 428 participants (a subset; 68.7% of cohort) RADAR-MDD longitudinal mobile health to investigate seasonal variations (measured through remote validated assessment - PHQ-8) examine potential dynamic changes, physical activity (monitored via wearables), The clustering PHQ-8 scores identified four distinct severity: one stable trend three varying patterns where peaks different seasons. Among these patterns, within had oldest average age (p = 0.002) lowest baseline score 0.003). Mediation analysis assessing indirect effect showed differences among with affective responses weather. Specifically, temperature day length significantly influenced severity, which turn impacted levels < 0.001). For instance, negative correlation severity temperature, 10°C increase led total daily step count rise 655.4, comprised 461.7 steps directly due itself 193.7 because decreased depressive (1.9 decrease PHQ-8). In contrast, for those positive correlation, 262.3-step rise; however, it was offset by 141.3-step increased (2.1 higher temperatures, culminating an insignificant overall 121 steps. These illustrate heterogeneity individuals' underscoring necessity personalized approaches help understand environmental factors effectiveness behavioral treatments.

Язык: Английский

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Evaluating Individual Differences in Emotion Regulation in Response to Sadness Using Digital Phenotyping

Опубликована: Ноя. 5, 2024

Background: The majority of research on emotion regulation processes has been restricted to controlled laboratory settings that use experimental paradigms investigate short-term outcomes. A true understanding requires an unobtrusive, ecologically valid assessment the construct as it occurs in environment. Digital phenotyping is a novel method for evaluating human behavior naturalistic settings. Objective: This study aimed evaluate whether smartphone-based digital data predicts individual differences both in-lab and settings.Methods: During session, unselected university student participants (N = 69) completed self-report questionnaires measuring trait well state affect following baseline period, negative mood induction, recovery period. Smartphone-based were then collected over course 7-day follow-up. Variation global positioning system (GPS) distance mobile power level examined predictors longitudinal variation affect, regulation, depression. Results: Results showed GPS was significantly associated with cognitive reappraisal (b -0.0004, SE 0.0002, p .02) 0. 005, 0.002, .01) time. also time -4.98, 1.72, .005) marginally -29.58, 16.73, .08) Cluster classification analyses accurately classified two clusters high sensitivity (.95 .96 respectively) specificity (.86 .97 respectively). together did not predict current depressive symptoms (ps &gt; .05).Conclusions: Overall, findings provide initial foundational predicting results suggest operationalizations modeling approaches are particularly important factors consider when implementing methodology mental health such regulation.

Язык: Английский

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