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Record W4281701140 · doi:10.1136/fmch-2022-001667

Patient experience of residents with restricted primary care access during the COVID-19 pandemic

2022· article· en· W4281701140 on OpenAlexaff
Takuya Aoki, Yasuki Fujinuma, Masato Matsushima

Bibliographic record

VenueFamily Medicine and Community Health · 2022
Typearticle
Languageen
FieldMedicine
TopicTelemedicine and Telehealth Implementation
Canadian institutionsCentre for Family Medicine
FundersJapan Society for the Promotion of Science
KeywordsPrimary careMedicinePandemicCoronavirus disease 2019 (COVID-19)TelemedicineFamily medicinePopulationConfoundingTelehealthHealth careEnvironmental healthInternal medicineDisease

Abstract

fetched live from OpenAlex

OBJECTIVES: To evaluate primary care access for COVID-19 consultation among residents who have a usual source of care (USC) and to examine their associations with patient experience during the pandemic in Japan. DESIGN: Nationwide cross-sectional study. SETTING: Japanese general adult population. PARTICIPANTS: 1004 adult residents who have a USC. MAIN OUTCOME MEASURES: Patient experience assessed by the Japanese version of Primary Care Assessment Tool Short Form (JPCAT-SF). RESULTS: A total of 198 (19.7%) reported restricted primary care access for COVID-19 consultation despite having a USC. After adjustment for possible confounders, restricted primary care access for COVID-19 consultation was negatively associated with the JPCAT-SF total score (adjusted mean difference = -8.61, 95% CI -11.11 to -6.10). In addition, restricted primary care access was significantly associated with a decrease in all JPCAT-SF domain scores. CONCLUSIONS: Approximately one-fifth of adult residents who had a USC reported restricted primary care access for COVID-19 consultation during the pandemic in Japan. Our study also found that restricted primary care access for COVID-19 consultation was negatively associated with a wide range of patient experience including first contact. Material, financial and educational support to primary care facilities, the spread of telemedicine and the application of a patient registration system might be necessary to improve access to primary care during a pandemic.

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)0.000
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.146
GPT teacher head0.428
Teacher spread0.282 · 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 designQualitative
Domainnot available
GenreEmpirical

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

Citations5
Published2022
Admission routes1
Has abstractyes

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