Evidence map›Paper›PMID 33284122›Full record

ArticleJMIR cancer2020

Evaluation of a Remote Symptom Assessment and Management (SAM) System for People Receiving Adjuvant Chemotherapy for Breast or Colorectal Cancer: Mixed Methods Study.

Lisa Whitehead, Laura Emery, Deborah Kirk, Diane Twigg, Deborah Brown, Joanna Dewar

Open access · goldAbstract read
In one paragraph

Article in JMIR cancer, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
0.4field-weighted citation impact, top 35% 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

4 citing papers in PubMed, 1 synthesis or guideline pooled it, 9 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Strategies to promote the dissemination of psychosocial digital health resources for those affected by cancer: scoping review.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2026
    Article
  4. Review
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

6 authors at 2 institutions in 1 country.

Lisa WhiteheadEdith Cowan University, Joondalup, Australia.ORCID https://orcid.org/0000-0002-6395-0279
Laura EmeryEdith Cowan University, Joondalup, Australia.ORCID https://orcid.org/0000-0002-3015-5463
Deborah KirkEdith Cowan University, Joondalup, Australia.ORCID https://orcid.org/0000-0003-2992-3389
Diane TwiggEdith Cowan University, Joondalup, Australia.ORCID https://orcid.org/0000-0002-4694-4555
Deborah BrownSir Charles Gairdner Hospital, Perth, Australia.ORCID https://orcid.org/0000-0001-6621-4333
Joanna DewarSir Charles Gairdner Hospital, Perth, Australia.ORCID https://orcid.org/0000-0002-1755-7097
Edith Cowan University · AUSir Charles Gairdner Hospital · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe Symptom Assessment and Management (SAM) program is a structured, online, nurse-supported intervention to support symptom self-management in people receiving adjuvant chemotherapy post surgery for breast or colorectal cancer.

objectiveThe objective of this study was to describe the development, implementation strategy, and evaluation of the SAM system.

methodsThe development of the SAM program involved 3 phases. In phase 1, the web app was developed through consultation with consumers and clinicians and of the literature to ensure that the system was evidence-based and reflected the realities of receiving treatment and supporting patients through treatment. In phase 2, 7 participants recorded the severity of 6 symptoms daily over the course of 1 cycle of chemotherapy. In phase 3, 17 participants recorded their symptoms daily over the course of 3 cycles of chemotherapy. Once symptoms were recorded, participants received immediate feedback on the severity of their symptoms and self-management recommendations, which could include seeking immediate medical attention. Data on quality of life, symptom burden, anxiety and depression, distress, and self-efficacy were collected during treatment; participants' perceptions of the SAM program were evaluated following participation via interview.

resultsThe outcomes of the SAM project include the development of a system that is reliable and easy to use and navigate. Participants reported benefits related to using the SAM program that included feeling more in control of managing their symptoms and feeling reassured. Engagement with the system on a daily basis was variable, with some participants completing the symptom tracker daily and others engaging some of the time. The feedback from all participants was that the system was easy to navigate and the information was relevant and supportive.

conclusionsThe SAM program has the potential to enhance the management of symptoms for people receiving chemotherapy treatment. The system creates an accurate repository of symptoms that can be accessed easily and highlight patterns in symptom experience. These can be shared with clinicians, with patient permission, to inform and support treatment plans. The potential to predict the risk of developing severe symptoms can be developed to anticipate the need for care and support. Further considerations on how to increase engagement with the system, the value of the system for people diagnosed with other tumor types and treatment regimes, and the incorporation of the system into everyday clinical practice are needed.

Indexed as

breast cancercancercolorectal cancerdevelopmentevaluationimplementationinterventionmonitoringonline interventionself-managementsymptomsymptom management

Identifiers

PMID33284122
PMCPMC7752534
OpenAlexW3097639377

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.