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Record W4392306925 · doi:10.1177/21501319241233198

Access to MAT: Participants’ Experiences With Transportation, Non-Emergency Transportation, and Telehealth

2024· review· en· W4392306925 on OpenAlex
Jennifer Boyd, Martha Carter, Adam Baus

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Primary Care & Community Health · 2024
Typereview
Languageen
FieldMedicine
TopicOpioid Use Disorder Treatment
Canadian institutionsnot available
FundersWest Virginia Higher Education Policy CommissionClaude Worthington Benedum FoundationPew Charitable Trusts
KeywordsTelehealthMedicineContext (archaeology)MedicaidQuarter (Canadian coin)Family medicineNursingMedical emergencyTelemedicineHealth careGeography

Abstract

fetched live from OpenAlex

INTRODUCTION: Access to medication assisted treatment (MAT) for opioid use disorder (OUD) in the United States is a significant challenge for many individuals attempting to recover and improve their lives. Access to treatment is especially challenging in rural areas characterized by lack of programs, few prescribers, and transportation barriers. This study aims to better understand the roles that transportation, Medicaid-funded non-emergency medical transportation (NEMT), and telehealth play in facilitating access to MAT in West Virginia (WV). METHODS: We developed this survey using an exploratory sequential mixed methods approach following a review of current peer-reviewed literature plus information gained from 3 semi-structured interviews and follow-up discussions with 5 individuals with lived experience in MAT. Survey results from 225 individuals provided rich context on the influence of transportation in enrolling and remaining in treatment, use of NEMT, and experiences using telehealth. Data were collected from February through August 2021. RESULTS: We found that transportation is a significant factor in entering into and remaining in treatment, with 170 (75.9%) respondents agreeing or strongly agreeing that having transportation was a factor in deciding to go into a MAT program, and 176 (71.1%) agreeing or strongly agreeing that having transportation helps them stay in treatment. NEMT was used by one-quarter (n = 52, 25.7%) of respondents. Only 13 (27.1%) noted that they were picked up on time and only 14 (29.2%) noted that it got them to their appointment on time. Two thirds of respondents (n = 134, 66.3%) had participated in MAT services via telehealth video or telephone visits. More preferred in-person visits to telehealth visits but a substantial number either preferred telehealth or reported no preference. However, 18 (13.6%) reported various challenges in using telehealth. CONCLUSIONS: This study confirms that transportation plays a significant role in many people's decisions to enter and remain in treatment for OUD in WV. Additionally, for those who rely on NEMT, services can be unreliable. Finally, findings demonstrate the need for individualized care and options for accessing treatment for OUD in both in-person and telehealth-based modalities. Programs and payers should examine all possible options to ensure access to care and recovery.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.625
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.083
GPT teacher head0.421
Teacher spread0.338 · 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