Evidence map›Paper›PMID 35346358›Full record

ArticleAddiction science & clinical practice2022

Automated Reinforcement Management System (ARMS): focused phase I provider feedback.

Crystal L Smith, Nicole M Rodin, Julie Y Hwang, André Q C Miguel, Kim Johnson, Michael G McDonell, Sterling M McPherson

Open access · goldAbstract read
In one paragraph

Article in Addiction science & clinical practice, 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
0.3field-weighted citation impact, top 43% 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, 2 citations in OpenAlex.

  1. Article
  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

7 authors at 2 institutions in 1 country.

Crystal L SmithElson S. Floyd College of Medicine, Washington State University, PO Box 1495, Spokane, WA, 99210-1495, USA. crystal.lederhos@wsu.edu.ORCID 0000-0002-5095-2822
Nicole M RodinElson S. Floyd College of Medicine, Washington State University, PO Box 1495, Spokane, WA, 99210-1495, USA.
Julie Y HwangElson S. Floyd College of Medicine, Washington State University, PO Box 1495, Spokane, WA, 99210-1495, USA.
André Q C MiguelElson S. Floyd College of Medicine, Washington State University, PO Box 1495, Spokane, WA, 99210-1495, USA.
Kim JohnsonManaged Health Connections, Spokane, WA, USA.
Michael G McDonellElson S. Floyd College of Medicine, Washington State University, PO Box 1495, Spokane, WA, 99210-1495, USA.
Sterling M McPhersonElson S. Floyd College of Medicine, Washington State University, PO Box 1495, Spokane, WA, 99210-1495, USA.
Washington State University Spokane · USCommunity Connections · US

Funding

Automated Contingency Management System for Reduction of Alcohol UseR41AA026793 · NIAAA · MANAGED HEALTH CONNECTIONS, LLC · PI JOHNSON, RON KIMBERLY, MCDONELL, MICHAEL G · 2018 to 2018
$216k
NIAAA NIH HHS R41 AA026793
6 · The paper itself

Abstract

backgroundAlcohol use increases risk for morbidity and mortality and is associated with over 3 million annual deaths worldwide. Contingency Management (CM) is one of the most effective interventions for substance use disorders, and has recently been coupled with technologies to promote novel treatments for alcohol use disorders (AUD). Leveraging these technological advances, we are developing the Automated Reinforcement Management System (ARMS), an integrated CM system designed to enable CM treatment as a component of a digital therapeutic or adjunct therapy remotely to anyone with a smartphone.

objectiveTo collect detailed provider feedback on ARMS and determine the need for modifications to make the system most feasible, acceptable, and useful to providers.

methodsSeven providers completed one-hour structured interviews/focus groups wherein we described the ARMS system and its application to clinical care. Providers viewed screen shots of the ARMS provider facing and patient facing systems. Providers gave feedback on their current AUD treatment practices, preferences for the functionality and appearance of the system, preferences for receipt of information on their patients, why they and their patients would or would not use the system, suggestions for improvement, and the proposed intervention overall. To analyze the qualitative data gathered, we used a qualitative descriptive approach with content analysis methods.

resultsThe overarching theme of Individualized Treatment emerged throughout the interviews. This sentiment supports use of ARMS, as it is intended to supplement provider communication and intervention as an adjunctive and customizable tool with the ability to reach rural patients, not a stand-alone option. Themes of Accountability and Objective Assessment arose during discussions of why people would use the system. Themes within provider obstacles included, Information Overload and Clinical Relevance, and in patient obstacles, Sustained Engagement and Security Concerns. Two themes emerged regarding suggestions for improvement: Increasing Accessibility and Bi-directional Communication. DISCUSSION: Themes from provider input are being used to modify ARMS to make it more user friendly, time saving, and relevant to treatment of AUD. If successful, ARMS will provide effective, individualized-digital therapeutic for those needing adjunctive treatment or those living in rural remote areas needing better connected care.

Indexed as

AlcoholismAlcohol DrinkingCommunicationFeedbackFocus GroupsHumansAlcohol use disorderContingency managementDigital therapeuticNovel treatment

Identifiers

PMID35346358
PMCPMC8962143
OpenAlexW4221107672

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.