Evidence map›Paper›PMID 42785736›Full record

ArticleJMIR formative research2026

Patient Experiences With a Symptom Monitoring and Self-Referral Program for Specialty Palliative Care After Lung Cancer Diagnosis: Qualitative Study.

Julia L Agne, Alice A Gaughan, Laura J Rush, Jennifer L Eramo, Anneliese Sinclair, Madison M Grogan, Jessica S Merlin, Jack Stevens, Robert M Cronin, Tasleem J Padamsee and 2 more

Abstract read
In one paragraph

Article in JMIR formative research, 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

12 authors.

Julia L AgneSection of Palliative and Pain Research (SPARC), Division of Palliative Medicine, The Ohio State University Wexner Medical Center, Columbus, OH, United States.ORCID 0000-0002-9967-0818
Alice A GaughanCenter for the Advancement of Team Science, Analytics, and Systems Thinking in Health Services and Implementation Science Research (CATALYST), College of Medicine, The Ohio State University, Columbus, OH, United States.ORCID 0000-0001-9109-3473
Laura J RushCollege of Medicine, The Ohio State University, Columbus, OH, United States.ORCID 0000-0003-3859-6885
Jennifer L EramoCollege of Medicine, The Ohio State University, Columbus, OH, United States.ORCID 0000-0002-2436-2247
Anneliese SinclairCenter for the Advancement of Team Science, Analytics, and Systems Thinking in Health Services and Implementation Science Research (CATALYST), College of Medicine, The Ohio State University, Columbus, OH, United States.ORCID 0009-0004-2254-8293
Madison M GroganDivision of Medical Oncology, Department of Internal Medicine, The Ohio State University Comprehensive Cancer Center - Arthur G. James Cancer Hospital and Richard J. Solove Research Institute, Columbus, OH, United States.ORCID 0009-0000-1517-4829
Jessica S MerlinSection of Palliative and Pain Research (SPARC), Division of Palliative Medicine, The Ohio State University Wexner Medical Center, Columbus, OH, United States.ORCID 0000-0003-3207-4875
Jack StevensDepartment of Pediatrics, The Ohio State University, Columbus, OH, United States.ORCID 0000-0001-6586-1918
Robert M CroninDepartment of Internal Medicine, The Ohio State University Wexner Medical Center, Columbus, OH, United States.ORCID 0000-0003-1916-6521
Tasleem J PadamseeDivision of Health Services Management and Policy, College of Public Health, The Ohio State University, Columbus, OH, United States.ORCID 0000-0001-6644-8084
Carolyn J PresleyDivision of Medical Oncology, Department of Internal Medicine, The Ohio State University Comprehensive Cancer Center - Arthur G. James Cancer Hospital and Richard J. Solove Research Institute, Columbus, OH, United States.ORCID 0000-0002-2607-5639
Ann Scheck McAlearneyCenter for the Advancement of Team Science, Analytics, and Systems Thinking in Health Services and Implementation Science Research (CATALYST), College of Medicine, The Ohio State University, Columbus, OH, United States.ORCID 0000-0001-9107-5419

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPalliative care improves patients' health-related quality of life (HRQoL) by delivering specialty-level management for cancer symptoms. Digital symptom monitoring programs (SMPs) improve patients' HRQoL through early symptom identification during cancer care. Through complementary approaches, SMPs and palliative care align with symptom management theory by linking the patient-reported symptom experience with clinician recommendations for symptom management to improve health outcomes for patients with serious illness. While both SMPs and palliative care reduce health care use and improve survival through detection and treatment of cancer symptoms, few studies have attempted to integrate palliative care into SMPs for cancer symptom management.

objectiveThis study aimed to assess patients' perspectives about the feasibility and acceptability of an SMP with a prompted palliative care self-referral option (Symptom Monitoring Program Linked to Electronic Referrals [SyMPLER]) via a mobile health (mHealth) app during lung cancer treatment.

methodsThis is a single-institution qualitative study of patients newly diagnosed with lung cancer who were enrolled in a single-arm feasibility pilot of an mHealth app that facilitates on-demand reporting of cancer-related symptoms and prompts patients to self-refer to palliative care for symptom management. Interview participants were purposively sampled based on high (≥3 uses) vs low (0-2 uses) engagement with the app during the first 3 months of access to the SMP. Questions focused on program feasibility and acceptability as well as perceptions of the 5 components of the SMP intervention (introduction to palliative care, reminders, symptom reporting, palliative care self-referral, and oncology team callback). Interviews were conducted from May 2024 to May 2025 by telephone, recorded, transcribed, and analyzed using thematic analysis.

resultsA total of 31 patients were interviewed; 21 had high and 10 had low app engagement. Participants were mostly White (n=29, 93.5%), female (n=21, 67.7%), and aged 60 years or older (n=19, 61.3%). In high and low engagement groups, participants voiced willingness and ability to report symptoms through the app and self-refer to palliative care if needed for symptom management. Feasibility barriers differed by group, with high-engagement participants noting forgetting to use the app for symptom reporting, while low-engagement participants cited low symptom burden, technology concerns, and time constraints as reasons for limited use of the SMP. Participants described uncertainty about when or why to request palliative care as a major barrier to self-referral.

conclusionsParticipants' perspectives on the feasibility and acceptability of SyMPLER differed by their level of engagement with the SMP app. Participants in both groups voiced acceptance of the option to self-refer to palliative care, although feasibility was limited by low uptake of palliative care self-referral. Participants suggested improvements to educational outreach, digital accessibility, customizable reminders, and recommendations for help-seeking behaviors based on symptom scoring thresholds to improve patient engagement with iterations of this SMP intervention.

Indexed as

Lung NeoplasmsPalliative CareReferral and ConsultationSymptom AssessmentAdultAgedAged, 80 and overFeasibility StudiesFemaleHumansMaleMiddle AgedQualitative ResearchQuality of LifeRemote Patient MonitoringSymptom BurdencancermHealthmobile healthpalliative carequalitativeremote symptom monitoringself-referralsymptom monitoring program

Identifiers

PMID42785736
PMCPMC13650458

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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.