Evidence map›Paper›PMID 28651151›Full record

Trial reportDrug and alcohol dependence2017

Assessment methods and schedules for collecting daily process data on substance use related health behaviors: A randomized control study.

Anne Buu, Lynn S Massey, Maureen A Walton, James A Cranford, Marc A Zimmerman, Rebecca M Cunningham

Abstract readRandomized Controlled Trial
In one paragraph

Trial report in Drug and alcohol dependence, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Translating strategies for promoting engagement in mobile health: A proof-of-concept microrandomized trial.Health psychology : official journal of the Division of Health Psychology, American Psychological Association · 2021
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  6. Validating E-Cigarette Dependence Scales Based on Dynamic Patterns of Vaping Behaviors.Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco · 2021
    Article
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  13. Addressing Key Gaps in Existing Longitudinal Research and Establishing a Pathway Forward for Firearm Violence Prevention Research.Journal of clinical child and adolescent psychology : the official journal for the Society of Clinical Child and Adolescent Psychology, American Psychological Association, Division 53
    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

6 authors.

Anne BuuDepartment of Health Behavior and Biological Sciences, University of Michigan, 400 North Ingalls, Ann Arbor, MI 48109, USA. Electronic address: buu@umich.edu.
Lynn S MasseyAddiction Research Center, Department of Psychiatry, University of Michigan, 4250 Plymouth Road, Ann Arbor, MI 48109, USA. Electronic address: lsmassey@med.umich.edu.
Maureen A WaltonAddiction Research Center, Department of Psychiatry, University of Michigan, 4250 Plymouth Road, Ann Arbor, MI 48109, USA. Electronic address: waltonma@umich.edu.
James A CranfordAddiction Research Center, Department of Psychiatry, University of Michigan, 4250 Plymouth Road, Ann Arbor, MI 48109, USA. Electronic address: jcranfor@med.umich.edu.
Marc A ZimmermanDepartment of Health Behavior and Health Education, University of Michigan, 1415 Washington Heights, Ann Arbor, MI 481099, USA. Electronic address: marcz@umich.edu.
Rebecca M CunninghamDepartment of Emergency Medicine, University of Michigan, 2800 Plymouth Rd, Bldg 10-G080, Ann Arbor, MI 48109, USA. Electronic address: stroh@med.umich.edu.

Funding

Measurement and Methodology for Daily Patterns of Drug Use and Related BehaviorsR01DA035183 · NIDA · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI BUU, YUH-PEY ANNE, CUNNINGHAM, REBECCA M. · 2013 to 2017
$2.6M
NIDA NIH HHS R01 DA035183
6 · The paper itself

Abstract

backgroundInteractive voice response (IVR) and short message service (SMS) systems have been used to collect daily process data on substance use. Yet, their relative compliance, use patterns, and user experiences are unknown. Furthermore, recent studies presented the potential of a hybrid weekly protocol requiring recall of behaviors in past week right after the weekend, in order to reduce the concerns about low compliance and measurement reactivity associated with daily data collection and also provide high quality data on the peak of use.

methodsThis study randomized substance users to four (2×2) assessment groups with different combinations of assessment methods (IVR or SMS) and schedules (daily or weekly). The compliance rates and use patterns during the experimental period of 90days and user experiences reported after the period were compared across the groups.

resultsWhen IVR was assigned, the weekly schedule generated a higher compliance rate than the daily schedule. When SMS was used, however, the assessment schedule did not have an effect on compliance. While both the daily and weekly surveys via IVR can be completed within a short time, the weekly survey administered via SMS took much longer than its daily counterpart. Such an increased time consumption may offset the benefit of a less frequent assessment schedule.

conclusionsIVR is a better choice for delivering the hybrid protocol of weekly collection of daily process data because of its higher compliance rate, shorter duration, and lower likelihood of interruption during data collection.

Indexed as

Health BehaviorAdolescentAdultData AccuracyFemaleHumansPatient ComplianceProcess Assessment, Health CareSubstance-Related DisordersSurveys and QuestionnairesText MessagingYoung AdultComplianceDaily processincentiveInteractive voice responseShort message serviceUse patterns

Identifiers

PMID28651151
PMCPMC5548619

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.