Evidence map›Paper›PMID 36881466›Full record

ArticleJMIR cancer2023

Using Text Messages and Fotonovelas to Increase Return of Home-Mailed Colorectal Cancer Screening Tests: Mixed Methods Evaluation.

Carly E Levitz, Elena Kuo, Monica Guo, Esmeralda Ruiz, Evelyn Torres-Ozadali, Rena Brar Prayaga, Anne Escaron

Open access · goldAbstract read
In one paragraph

Article in JMIR cancer, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
0.8field-weighted citation impact, top 25% of its field
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

11 citing papers in PubMed, 12 citations in OpenAlex.

  1. Trial
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  8. Review
  9. The Reach of Calls and Text Messages for Mailed FIT Outreach in the PROMPT Stepped-Wedge Colorectal Cancer Screening Trial.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2024
    Article
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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

7 authors at 3 institutions in 1 country.

Carly E Levitz *Center for Community Health and Evaluation, Kaiser Permanente Washington Health Research Institute, Seattle, WA, United States.ORCID https://orcid.org/0000-0003-3094-411X
Elena Kuo *Center for Community Health and Evaluation, Kaiser Permanente Washington Health Research Institute, Seattle, WA, United States.ORCID https://orcid.org/0000-0002-5123-1744
Monica Guo *Institute for Health Equity, AltaMed, Los Angeles, CA, United States.ORCID https://orcid.org/0000-0002-9909-7695
Esmeralda Ruiz *Institute for Health Equity, AltaMed, Los Angeles, CA, United States.ORCID https://orcid.org/0000-0002-2479-3565
Evelyn Torres-Ozadali *Institute for Health Equity, AltaMed, Los Angeles, CA, United States.ORCID https://orcid.org/0000-0002-8458-3754
Rena Brar Prayaga *mPulse Mobile Inc, Encino, CA, United States.ORCID https://orcid.org/0000-0001-9299-9074
Anne Escaron *Institute for Health Equity, AltaMed, Los Angeles, CA, United States.ORCID https://orcid.org/0000-0003-0717-0750
AltaMed · USKaiser Permanente Washington Health Research Institute · UST-Mobile (United States) · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundColorectal cancer (CRC) is currently the second leading cause of cancer-related deaths in the United States; however, it is mostly preventable with appropriate screening and is often treatable when detected at early stages. Many patients enrolled in an urban Federally Qualified Health Center (FQHC) clinic were found to be past due for CRC screening.

objectiveThis study described a quality improvement (QI) project to improve CRC screening rates. This project used bidirectional texting with fotonovela comics and natural language understanding (NLU) to encourage patients to mail fecal immunochemical test (FIT) kits back to the FQHC.

methodsThe FQHC mailed FIT kits to 11,000 unscreened patients in July 2021. Consistent with the usual care, all patients received 2 text messages and a patient navigator call within the first month of mailing. As part of a QI project, 5241 patients who did not return their FIT kit within 3 months, aged 50-75 years, and spoke either English or Spanish were randomized to either usual care (no further intervention) or intervention (4-week texting campaign with a fotonovela comic and remailing kits if requested) groups. The fotonovela was developed to address known barriers to CRC screening. The texting campaign used NLU to respond to patients' texts. A mixed methods evaluation used data from SMS text messages and electronic medical records to understand the impact of the QI project on CRC screening rates. Open-ended text messages were analyzed for themes, and interviews were completed with a convenience sample of patients to understand barriers to screening and impact of the fotonovela.

resultsOf the 2597 participants, 1026 (39.5%) in the intervention group engaged with bidirectional texting. Participating in bidirectional texting was related to language preference (χ

conclusionsTexting using NLU and fotonovela is valuable in increasing CRC screening as observed by the FIT return rate for patients in the intervention group. There were patterns in which patients did not engage bidirectionally; future work should investigate how to ensure that populations are not left out of screening campaigns.

Indexed as

bidirectional textingcancercolorectal cancercolorectal cancer screeningcomicsCRCfecal immunochemical test kitFIT kitfotonovelahealth promotionhealth text messagingparticipationpatient navigationscreeningtexting campaign

Identifiers

PMID36881466
PMCPMC10131942
OpenAlexW4312784796

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.