Evidence map›Paper›PMID 26768431›Full record

ArticlePrevention science : the official journal of the Society for Prevention Research2016

Derivation and Evaluation of a Risk-Scoring Tool to Predict Participant Attrition in a Lifestyle Intervention Project.

Luohua Jiang, Jing Yang, Haixiao Huang, Ann Johnson, Edward J Dill, Janette Beals, Spero M Manson, Yvette Roubideaux, Special Diabetes Program for Indians Diabetes Prevention Demonstration Project

Open access · greenAbstract readMulticenter Study
In one paragraph

Article in Prevention science : the official journal of the Society for Prevention Research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.6field-weighted citation impact, top 23% 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

7 citing papers in PubMed, 9 citations in OpenAlex.

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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

9 authors at 4 institutions in 1 country.

Luohua JiangDepartment of Epidemiology, School of Medicine, University of California Irvine, 205B Irvine Hall, Irvine, CA, 92697-7550, USA. lhjiang@uci.edu.
Jing YangDepartment of Epidemiology and Biostatistics, School of Rural Public Health, Texas A&M Health Science Center, College Station, TX, USA.
Haixiao HuangCenters for American Indian and Alaska Native Health, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
Ann JohnsonCenters for American Indian and Alaska Native Health, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
Edward J DillDepartment of Psychology, University of Colorado Denver, Denver, CO, USA.
Janette BealsCenters for American Indian and Alaska Native Health, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
Spero M MansonCenters for American Indian and Alaska Native Health, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
Yvette RoubideauxElson S. Floyd College of Medicine, Washington State University, Spokane, WA, USA.
Special Diabetes Program for Indians Diabetes Prevention Demonstration Project
Colorado School of Public Health · USTexas A&M Health Science Center · USUniversity of California, Irvine · USWashington State University Spokane · US

Funding

TRANSLATIONAL RESEARCH COREP30DK092923 · NIDDK · UNIVERSITY OF COLORADO DENVER · PI Angela Gwen Brega · 2011 to 2026
$10.2M
NIDDK NIH HHS 1P30DK092923NIDDK NIH HHS P30 DK092923PHS HHS HHSI242200400049C
6 · The paper itself

Abstract

Participant attrition in clinical trials and community-based interventions is a serious, common, and costly problem. In order to develop a simple predictive scoring system that can quantify the risk of participant attrition in a lifestyle intervention project, we analyzed data from the Special Diabetes Program for Indians Diabetes Prevention Program (SDPI-DP), an evidence-based lifestyle intervention to prevent diabetes in 36 American Indian and Alaska Native communities. SDPI-DP participants were randomly divided into a derivation cohort (n = 1600) and a validation cohort (n = 801). Logistic regressions were used to develop a scoring system from the derivation cohort. The discriminatory power and calibration properties of the system were assessed using the validation cohort. Seven independent factors predicted program attrition: gender, age, household income, comorbidity, chronic pain, site's user population size, and average age of site staff. Six factors predicted long-term attrition: gender, age, marital status, chronic pain, site's user population size, and average age of site staff. Each model exhibited moderate to fair discriminatory power (C statistic in the validation set: 0.70 for program attrition, and 0.66 for long-term attrition) and excellent calibration. The resulting scoring system offers a low-technology approach to identify participants at elevated risk for attrition in future similar behavioral modification intervention projects, which may inform appropriate allocation of retention resources. This approach also serves as a model for other efforts to prevent participant attrition.

Indexed as

Life StyleAdolescentAdultFemaleHumansMaleMiddle AgedPsychologyRisk AssessmentYoung AdultLifestyle modificationsMulti-site studyRetentionRisk prediction modelsWeight loss program

Identifiers

PMID26768431
PMCPMC5532883
OpenAlexW2237541985

What OpenQuestion holds

Textmetadata
LicenceTDM
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.