Evidence map›Paper›PMID 36406185›Full record

ArticleHealth and technology2022

Revisiting agency and medical health technology: actor network theory and breast cancer survivors' perspectives on an adherence tool.

Mark L Cabling, Fabrizio Drago, Jeanine Turner, Alejandra Hurtado-de-Mendoza, Vanessa B Sheppard

Open access · bronzeAbstract read
In one paragraph

Article in Health and technology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.7field-weighted citation impact, top 30% 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

2 citing papers in PubMed, 5 citations in OpenAlex.

  1. Review
  2. Article
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

5 authors at 3 institutions in 1 country.

Mark L CablingLombardi Comprehensive Cancer Center, Georgetown University Medical Center, 3300 Whitehaven Street, NW, Ste. 4100, 20007 Washington DC, USA.ORCID 0000-0003-2450-0512
Fabrizio DragoDepartment of Biostatistics and Epidemiology, Rutgers School of Public Health, 683 Hoes Lane West, Piscataway, NJ 08854 USA.
Jeanine TurnerCommunication, Culture & Technology Program, Graduate School of Arts and Sciences, Georgetown University Car Barn, Suite 311, 3520 Prospect Street, Washington DC , N.W. 20057 USA.
Alejandra Hurtado-de-MendozaLombardi Comprehensive Cancer Center, Georgetown University Medical Center, 3300 Whitehaven Street, NW, Ste. 4100, 20007 Washington DC, USA.
Vanessa B SheppardMassey Cancer Center, School of Medicine, Virginia Commonwealth University, 401 College Street, Box 980037, Richmond, VA 23298-0037 USA.
Georgetown University · USRutgers, The State University of New Jersey · USVirginia Commonwealth University · US

Funding

PREDICTORS OF ADJUVANT ENDOCRINE THERAPY ADHERENCE IN WOMEN WITH BREAST CANCERR01CA154848 · NCI · GEORGETOWN UNIVERSITY · PI SHEPPARD, VANESSA B · 2011 to 2015
$2.5M
NCI NIH HHS R01 CA154848
6 · The paper itself

Abstract

Purpose: Optimal treatment adherence is critical in the management of breast cancer patients/survivors taking hormonal therapy. However, lack of adherence is common. Many technologies have been developed to encourage medication intake, such as reminders on phones or digital pills, with varying degrees of success. Methods: To explore the role of technology in medical adherence requires a framework that considers all complexities of technology, from software to the end user's beliefs. Actor Network Theory (ANT) defines technology based on its technical, social, and abstract components. We conducted three focus groups, which we analyzed using a thematic analysis to determine topics in breast cancer survivors' discussions of these technologies. We also conducted a deductive content analysis using ANT concepts as codes. Results: In discussing the use of technology to improve medical adherence, participants had an empowering view of technology (48.8%) a neutral one (41.5%) or a disempowering view (9.8%). When it comes to their medication adherence, breast cancer survivors taking hormonal therapy perceived technology as something on which they could assert agency while their own agency dictated their adherence behaviors. Conclusions: In line with a non-technologically deterministic view of medical technologies, this finding shows that technology can be both constraining and enabling, depending on the specific context of human use. This networked understanding of technology in terms of social dynamics has relevant implications in designing interventions that use technology to improve adherence.

Indexed as

Actor Network TheoryAdherenceBreast CancerHormonal therapyMedical Technology

Identifiers

PMID36406185
PMCPMC9660207
OpenAlexW4309047570

What OpenQuestion holds

Textmetadata
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.