Evidence map›Paper›PMID 37382523›Full record

ArticleAnnals of work exposures and health2023

Using a smartphone application to capture daily work activities: a longitudinal pilot study in a farming population.

Pabitra R Josse, Sarah J Locke, Heather R Bowles, Dana L Wolff-Hughes, Jean-François Sauve, Gabriella Andreotti, Jon Moon, Jonathan N Hofmann, Laura E Beane Freeman, Melissa C Friesen

Erratum issuedAbstract read
In one paragraph

Article in Annals of work exposures and health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Not yet cited in PubMed.

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0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors.

Pabitra R JosseOccupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, United States.ORCID 0000-0003-4506-7682
Sarah J LockeOccupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, United States.
Heather R BowlesBiometry Research Group, Division of Cancer Prevention, National Cancer Institute, Rockville, MD, Unites States.
Dana L Wolff-HughesEpidemiology and Genomics Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, Rockville, MD, United States.
Jean-François SauveInstitut National de Recherche et de Sécurité, Vandoeuvre-lès-Nancy, France.ORCID 0000-0002-4995-4388
Gabriella AndreottiOccupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, United States.ORCID 0000-0002-1096-3324
Jon MoonMEI Research, Edina, MN, United States.
Jonathan N HofmannOccupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, United States.
Laura E Beane FreemanOccupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, United States.
Melissa C FriesenOccupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, United States.ORCID 0000-0002-1695-3282

Funding

STUDIES OF OCCUPATIONAL CANCER--PESTICIDESZ01CP010119 · NCI · DIVISION OF CANCER EPIDEMIOLOGY AND GENETICS · PI ALAVANJA, MICHAEL · 1996 to 2008
$5.0M
Intramural NIH HHS Z01 CP010119
6 · The paper itself

Abstract

objectivesSmartphones are increasingly used to collect real-time information on time-varying exposures. We developed and deployed an application (app) to evaluate the feasibility of using smartphones to collect real-time information on intermittent agricultural activities and to characterize agricultural task variability in a longitudinal study of farmers.

methodsWe recruited 19 male farmers, aged 50-60 years, to report their farming activities on 24 randomly selected days over 6 months using the Life in a Day app. Eligibility criteria include personal use of an iOS or Android smartphone and >4 h of farming activities at least two days per week. We developed a study-specific database of 350 farming tasks that were provided in the app; 152 were linked to questions that were asked when the activity ended. We report eligibility, study compliance, number of activities, duration of activities by day and task, and responses to the follow-up questions.

resultsOf the 143 farmers we reached out to for this study, 16 were not reached by phone or refused to answer eligibility questions, 69 were ineligible (limited smartphone use and/or farming time), 58 met study criteria, and 19 agreed to participate. Refusals were mostly related to uneasiness with the app and/or time commitment (32 of 39). Participation declined gradually over time, with 11 farmers reporting activities through the 24-week study period. We obtained data on 279 days (median 554 min/day; median 18 days per farmer) and 1,321 activities (median 61 min/activity; median 3 activities per day per farmer). The activities were predominantly related to animals (36%), transportation (12%), and equipment (10%). Planting crops and yard work had the longest median durations; short-duration tasks included fueling trucks, collecting/storing eggs, and tree work. Time period-specific variability was observed; for example, crop-related activities were reported for an average of 204 min/day during planting but only 28 min/day during pre-planting and 110 min/day during the growing period. We obtained additional information for 485 (37%) activities; the most frequently asked questions were related to "feed animals" (231 activities) and "operate fuel-powered vehicle (transportation)" (120 activities).

conclusionsOur study demonstrated feasibility and good compliance in collecting longitudinal activity data over 6 months using smartphones in a relatively homogeneous population of farmers. We captured most of the farming day and observed substantial heterogeneity in activities, highlighting the need for individual activity data when characterizing exposure in farmers. We also identified several areas for improvement. In addition, future evaluations should include more diverse populations.

Indexed as

Mobile ApplicationsOccupational ExposureAgricultureAnimalsHumansLongitudinal StudiesMaleMiddle AgedPilot ProjectsSmartphoneexposure assessmentfarmingsmartphone

Identifiers

PMID37382523
PMCPMC10410491

What OpenQuestion holds

Textmetadata
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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.