Evidence map›Paper›PMID 42502521›Full record

ArticleCureus2026

Public Information-Seeking Behavior in Primary Care: A National Case Study of Türkiye.

Muhammed Inan, Cenk Aypak

Abstract read
In one paragraph

Article in Cureus, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Muhammed InanDepartment of Family Medicine, University of Health Sciences Ankara Etlik City Hospital, Ankara, TUR.
Cenk AypakDepartment of Family Medicine, University of Health Sciences Ankara Etlik City Hospital, Ankara, TUR.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective This study utilizes digital epidemiology to examine public engagement with family medicine in Türkiye, aiming to inform strategies for optimizing primary care delivery and reducing health disparities. Method This observational study analyzed public interest in family medicine in Türkiye using Google Trends data between January 2018 and April 2025, following the STROBE guidelines. A total of 56 keywords were selected based on expert consensus and search volume assessment, excluding redundant or low-volume queries. Statistical analyses, including Mann-Kendall (MK) trend tests, one-way analysis of variance (ANOVA), and OLS regression, were conducted using Python (v3.12; Python Software Foundation, Delaware, USA). To control for type I error across multiple comparisons, all p-values were adjusted using the Benjamini-Hochberg false discovery rate (FDR) procedure. Practical significance was further evaluated using Eta-squared (η²) and Cohen's d effect sizes, and model robustness was verified via regression diagnostics (Durbin-Watson and Shapiro-Wilk tests). Results Long-term interest in family medicine services demonstrated significant growth, with "what is a family physician?" (τ = 0.759, pFDR < 0.001) and "family health center" (τ = 0.558, pFDR < 0.001) emerging as the most prominent upward trends. Seasonal analysis revealed significant variation for "family physician" (η² = 0.232, pFDR = 0.003), with peaks in winter and fall, aligning with respiratory illness cycles. Impact analysis of the COVID-19 pandemic confirmed a sustained transition to digital platforms, particularly for the "Central Physician Appointment System" (new-normal Cohen's d = 5.05, pFDR < 0.001). Regionally, while metropolitan centers dominated general appointment searches, specific healthcare needs were highlighted by unique regional patterns, such as the high search intensity for "family physician on-call" in Ordu. Conclusion Although public interest in family medicine has steadily increased, significantly accelerated by the pandemic's shift to digital platforms, information gaps regarding the scope of services remain. Furthermore, geographic disparities in search behavior point to a potential "digital shadow" in rural areas, suggesting localized informational deficits. These digital footprints provide hypothesis-generating insights that health administrators may consider as supplementary tools for regional planning and guiding digital literacy initiatives in underserved regions.

Indexed as

family medicinegoogle trendshealth status disparitiessearch enginetelemedicine

Identifiers

PMID42502521
PMCPMC13401469

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.