Cited by 105Mobile Health and mHealth ApplicationsICT in Developing CommunitiesTechnology Adoption and User Behaviour

The Technology Acceptance Model for Resource-Limited Settings (TAM-RLS): A Novel Framework for Mobile Health Interventions Targeted to Low-Literacy End-Users in Resource-Limited Settings

Open access
Campbell, Jeffrey I., Aturinda, Isaac, Mwesigwa, Evans, Burns, Bridget, Santorino, Data, Haberer, Jessica E., Bangsberg, David R., Holden, Richard J. +2 more·2017·AIDS and Behavior

Abstract

Although mobile health (mHealth) technologies have shown promise in improving clinical care in resource-limited settings (RLS), they are infrequently brought to scale. One limitation to the success of many mHealth interventions is inattention to end-user acceptability, which is an important predictor of technology adoption. We conducted in-depth interviews with 43 people living with HIV in rural Uganda who had participated in a clinical trial of a short messaging system (SMS)-based intervention designed to prompt return to clinic after an abnormal laboratory test. Interviews focused on established features of technology acceptance models, including perceived ease of use and perceived usefulness, and included open-ended questions to gain insight into unexplored issues related to the intervention's acceptability. We used conventional (inductive) and direct content analysis to derive categories describing use behaviors and acceptability. Interviews guided development of a proposed conceptual framework, the technology acceptance model for resource-limited settings (TAM-RLS). This framework incorporates both classic technology acceptance model categories as well as novel factors affecting use in this setting. Participants described how SMS message language, phone characteristics, and experience with similar technologies contributed to the system's ease of use. Perceived usefulness was shaped by the perception that the system led to augmented HIV care services and improved access to social support from family and colleagues. Emergent themes specifically related to mHealth acceptance among PLWH in Uganda included (1) the importance of confidentiality, disclosure, and stigma, and (2) the barriers and facilitators downstream from the intervention that impacted achievement of the system's target outcome. The TAM-RLS is a proposed model of mHealth technology acceptance based upon end-user experiences in rural Uganda. Although the proposed model requires validation, the TAM-RLS may serve as a useful tool to guide design and implementation of mHealth interventions.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1007/s10461-017-1765-y

Cites

54 of 54 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Authors
Campbell, J. I., Aturinda, I., Mwesigwa, E., Burns, B., Santorino, D., Haberer, J. E., Bangsberg, D. R., Holden, R. J., Ware, N. C., & Siedner, M. J.
Affiliations
  • Boston Medical Center (US)
  • Mbarara University of Science and Technology (UG)
  • Massachusetts General Hospital (US)
  • Harvard University (US)
  • Portland State University (US)
  • Indiana University Indianapolis (US)
Corresponding author
Siedner, Mark J.
Venue
AIDS and Behavior
Published
2017-04-18
Volume
21
Issue
11
Pages
3129-3140
ISSN
  • 1090-7165 (ISSN-L)
  • 1573-3254
OpenAlex
W2606947362
Cited by
105
References
54
Citations by year
2026: 10 · 2025: 8 · 2024: 14 · 2023: 14 · 2022: 11 · 2021: 14 · 2020: 21 · 2019: 5 · 2018: 8
FWCI
15.01
Type
journal article
Language
en
Open access
Locations
  • AIDS and Behavior (publishedVersion)
  • PubMed (publishedVersion)
  • Europe PMC (PubMed Central) (acceptedVersion)
  • PubMed Central (acceptedVersion)
  • PDXScholar (Portland State University) (submittedVersion)
  • Purdue University Indianapolis (Indiana University) (submittedVersion)
Funders
  • National Institutes of Health (R24 TW007988, T32 AI007433, K23 MH099916)
  • Harvard Global Health Insitute
Topics
  • Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
  • Physical Sciences › Computer Science › Information Systems › ICT in Developing Communities
  • Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
Keywords
technology acceptance model, mobile health, resource-limited settings, low-literacy users, people living with HIV, text messaging intervention, perceived ease of use, perceived usefulness, confidentiality, HIV stigma, disclosure, rural Uganda, conceptual framework
MeSH terms
Literacy, Ambulatory Care Facilities, Confidentiality, Female, Health Resources, Humans, Interviews as Topic, Patient Acceptance of Health Care, Perception, Rural Population, Uganda, HIV Infections, Telemedicine, Biomedical Technology, Disclosure

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review