{"doi":"10.1111/jrh.12903","title":"Rural health research in the 21st century: A commentary on challenges and the role of digital technology","abstract":"Rural health research, fundamental to US public health, has faced significant challenges including inconsistencies in defining rural areas, methodological constraints in studying dispersed populations, and complex social and cultural factors.1, 2 This commentary reexamines these enduring issues and proposes innovative solutions leveraging digital technologies. While acknowledging the potential of these technological approaches, we also address barriers to digital equity in rural settings and suggest practical strategies to overcome them. Defining “rural” poses significant challenges.1, 2 Current classification methods typically consider population density, proximity to urban centers, and infrastructure availability. However, these approaches often lead to inconsistencies.1, 3 The US Census, for instance, identifies urban areas based on population density, with non-urban areas classified as rural.1 This method, while systematic, often overlooks crucial factors like commuting patterns, employment nature, land use, and access to essential services—including internet connectivity and advanced medical care. Online tools have emerged to address these limitations by incorporating multiple definitions of rurality. The Rural Health Information Hub's “Am I Rural?” tool exemplifies this approach, integrating seven distinct definitions including data from the US Census, Rural-Urban Commuting Areas, and Federal Office of Rural Health Policy classifications.4 This tool also considers federal grant eligibility and health care professional shortages, providing a more comprehensive assessment of rural status. The “Am I Rural?” tool illustrates how technological advancements can enhance rural area definition precision.4 By employing a multifaceted approach, these tools enable more accurate representations of rurality in health research. Consequently, this can inform policy decisions and resource allocation more effectively, ultimately benefiting rural communities' health and wellness. Smaller population size, low population density, and limited access to transportation often pose methodological challenges for rural participant recruitment and retention, particularly if in-person data collection is required.2, 5 Additionally, research questions or scales that are urban-normative (i.e., urban lifestyles or values are viewed as the default/ideal) may alienate respondents, leading to reduced response rates and questionable validity.2 Dissemination of rural research findings is often more challenging due to confidentiality concerns in smaller communities.6, 7 To address these challenges, researchers are increasingly turning to innovative digital approaches. For instance, Vos et al.8 created a standalone page on a popular social media platform resulting in successful engagement and recruitment of rural participants. This low-cost, accessible method was particularly impactful when researchers’ community engagement was highlighted. Once recruited, real-time interactions via text messages or Zoom, or data collection reminders via mobile applications (“apps”) offer personal, timely, and tailored communications. Rural residents feel positively about personal technology, including apps and wearables, and view technology as a means of bridging resource gaps.9, 10 Health assessment and intervention tools designed for urban populations may be adapted for rural participants using community-based participatory research (CBPR). CBPR, where community members and key informants actively collaborate with researchers, has long been used in rural communities. However, integrating CBPR with health informatics research has shown distinct benefits, including increased recruitment of diverse populations, improved internal validity, and more rapid translation of research into action.11 CBPR has also proven helpful in identifying best practices in dissemination of research findings in small communities.12 Research participants have identified helpful digital tools includin","journal":"The Journal of Rural Health","year":2024,"id":439435,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":10,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9595,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2024-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1250767,"name":"Jasmine Rubio","orcid":null,"position":1,"is_corresponding":false},{"id":1250768,"name":"Israel Palencia","orcid":null,"position":2,"is_corresponding":false},{"id":1142460,"name":"Laronda Hollimon","orcid":null,"position":3,"is_corresponding":false},{"id":1250769,"name":"Dunia Mejia","orcid":null,"position":4,"is_corresponding":false},{"id":414511,"name":"Azizi Seixas","orcid":"0000-0003-0843-2679","position":5,"is_corresponding":false},{"id":794896,"name":"Mairead Moloney","orcid":"0000-0001-6598-9401","position":0,"is_corresponding":true}],"reference_count":24,"raw_metadata":null,"created_at":"2026-07-19T02:00:47.992543Z","pmid":"39682077","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}