Evidence map›Paper›PMID 41199788›Full record

ArticleProceedings of the SIGCHI conference on human factors in computing systems. CHI Conference

T2 Coach: A Qualitative Study of an Automated Health Coach for Diabetes Self-Management.

Elliot G Mitchell, Pooja Desai, Arlene Smaldone, Andrea Cassells, Jonathan N Tobin, David Albers, Matthew Levine, Lena Mamykina

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Proceedings of the SIGCHI conference on human factors in computing systems. CHI Conference. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. 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

8 authors.

Elliot G MitchellGeisinger Health, Danville, Pennsylvania, USA.
Pooja DesaiDepartment of Biomedical Informatics, Columbia University Irving Medical Center, New York, New York, USA.
Arlene SmaldoneSchool of Nursing, Columbia University, New York, New York, USA.
Andrea CassellsClinical Directors Network, New York, New York, USA.
Jonathan N TobinClinical Directors Network (CDN), New York, New York, USA.
David AlbersDepartment of Pediatrics, Section of Informatics and Data Science, University of Colorado Anschutz Medical Center, Aurora, Colorado, USA.
Matthew LevineEric and Wendy Schmidt Center, Broad Institute of MIT and Harvard Cambridge, Massachusetts, USA.
Lena MamykinaDepartment of Biomedical Informatics, Columbia University, New York, New York, USA.

Funding

Training in Biomedical Informatics at Columbia UniversityT15LM007079 · NLM · COLUMBIA UNIV NEW YORK MORNINGSIDE · PI NOEMIE ELHADAD, GEORGE M HRIPCSAK · 1992 to 2026
$28.9M
Dynamically Tailoring Interventions for Problem-Solving in Diabetes Self-Management Using Self-Monitoring Data - a Randomized Controlled Trial.R01DK113189 · NIDDK · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI MAMYKINA, OLENA · 2019 to 2023
$3.3M
NIDDK NIH HHS R01 DK113189NLM NIH HHS T15 LM007079
6 · The paper itself

Abstract

Computational intelligence is increasingly common in interactive systems in many domains, including health. Health coaching with conversational agents (CA) can reach wide populations, but the level of computational intelligence needed for a positive coaching experience is unclear. We conducted a study with sixteen individuals with diabetes and prediabetes who used a CA for health coaching, T2 Coach. Qualitative interviews revealed that participants saw T2 Coach as reliable in helping them stay on track with self-management, appreciated the flexibility in choosing personally meaningful goals and engaging on their own terms, and felt it provided encouragement and even compared it favorably with human coaches. However, they also noted that coaching experience could be improved with more fluid conversations, more tailoring to their personal preferences and lifestyles, and more sensitivity to specific contexts, all of which require more computational intelligence. We discuss implications and design directions for more intelligent coaching CA in health.

Indexed as

chatbotscoachingconversational agentsdiabetesHealthmHealthself-managementself-tracking

Identifiers

PMID41199788
PMCPMC12587852

What OpenQuestion holds

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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.