MétaCan
Menu
Back to cohort
Record W2898246453 · doi:10.2196/12112

Investigating Health Risk Environments in Housing Programs for Young Adults: Protocol for a Geographically Explicit Ecological Momentary Assessment Study

2018· article· en· W2898246453 on OpenAlexvenueno aff
Benjamin F. Henwood, Brian Redline, Eldin Dzubur, Danielle R. Madden, Harmony Rhoades, Genevieve F. Dunton, Eric Rice, Sara Semborski, Qu Tang, Stephen Intille

Bibliographic record

VenueJMIR Research Protocols · 2018
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsnot available
FundersNational Institute of Mental Health
KeywordsGeospatial analysisQualitative researchContext (archaeology)PsychologyAffect (linguistics)Qualitative propertymHealthPhoneGerontologyApplied psychologyEnvironmental healthMedicinePsychological interventionGeographyPsychiatryComputer science

Abstract

fetched live from OpenAlex

BACKGROUND: Young adults who experience homelessness are exposed to environments that contribute to risk behavior. However, few studies have examined how access to housing may affect the health risk behaviors of young adults experiencing homelessness. OBJECTIVE: This paper describes the Log My Life study that uses an innovative, mixed-methods approach based on geographically explicit ecological momentary assessment (EMA) through cell phone technology to understand the risk environment of young adults who have either enrolled in housing programs or are currently homeless. METHODS: For the quantitative arm, study participants age 18-27 respond to momentary surveys via a smartphone app that collects geospatial information repeatedly during a 1-week period. Both EMAs (up to 8 per day) and daily diaries are prompted to explore within-day and daily variations in emotional affect, context, and health risk behavior, while also capturing infrequent risk behaviors such as sex in exchange for goods or services. For the qualitative arm, a purposive subsample of participants who indicated engaging in risky behaviors are asked to complete an in-depth qualitative interview using an interactive, personalized geospatial map rendering of EMA responses. RESULTS: Recruitment began in June of 2017. To date, 170 participants enrolled in the study. Compliance with EMA and daily diary surveys was generally high. In-depth qualitative follow-ups have been conducted with 15 participants. We expect to recruit 50 additional participants and complete analyses by September of 2019. CONCLUSIONS: Mixing the quantitative and qualitative arms in this study will provide a more complete understanding of differences in risk environments between homeless and housed young adults. Furthermore, this approach can improve recall bias and enhance ecological validity. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/12112.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.029
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.058
Threshold uncertainty score0.195

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0290.019
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0050.004
Bibliometrics0.0030.002
Science and technology studies0.0050.002
Scholarly communication0.0020.002
Open science0.0030.003
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0580.017

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.376
GPT teacher head0.644
Teacher spread0.268 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreProtocol

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations13
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueJMIR Research ProtocolsSame topicHomelessness and Social IssuesFrench-language works237,207