Using a smartphone application to capture daily work activities: a longitudinal pilot study in a farming population.
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| Title: | Using a smartphone application to capture daily work activities: a longitudinal pilot study in a farming population. |
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| Authors: | Josse, Pabitra R1 pabitra.josse@nih.gov, Locke, Sarah J1, Bowles, Heather R2, Wolff-Hughes, Dana L3, Sauve, Jean-François4, Andreotti, Gabriella1, Moon, Jon5, Hofmann, Jonathan N1, Freeman, Laura E Beane1, Friesen, Melissa C1 |
| Source: | Annals of Work Exposures & Health. Aug2023, Vol. 67 Issue 7, p895-906. 12p. |
| Subjects: | Work environment, Pilot projects, Mobile apps, Smartphones, Occupational exposure, Descriptive statistics, Research funding, Motion capture (Human mechanics), Agricultural laborers, Digital video, Longitudinal method, Horticulture |
| Abstract: | Objectives Smartphones 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. Methods We 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. Results Of 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). Conclusions Our 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. [ABSTRACT FROM AUTHOR] |
| Copyright of Annals of Work Exposures & Health is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
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| Header | DbId: egs DbLabel: Engineering Source An: 170020768 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Using a smartphone application to capture daily work activities: a longitudinal pilot study in a farming population. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Josse%2C+Pabitra+R%22">Josse, Pabitra R</searchLink><relatesTo>1</relatesTo><i> pabitra.josse@nih.gov</i><br /><searchLink fieldCode="AR" term="%22Locke%2C+Sarah+J%22">Locke, Sarah J</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Bowles%2C+Heather+R%22">Bowles, Heather R</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Wolff-Hughes%2C+Dana+L%22">Wolff-Hughes, Dana L</searchLink><relatesTo>3</relatesTo><br /><searchLink fieldCode="AR" term="%22Sauve%2C+Jean-François%22">Sauve, Jean-François</searchLink><relatesTo>4</relatesTo><br /><searchLink fieldCode="AR" term="%22Andreotti%2C+Gabriella%22">Andreotti, Gabriella</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Moon%2C+Jon%22">Moon, Jon</searchLink><relatesTo>5</relatesTo><br /><searchLink fieldCode="AR" term="%22Hofmann%2C+Jonathan+N%22">Hofmann, Jonathan N</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Freeman%2C+Laura+E+Beane%22">Freeman, Laura E Beane</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Friesen%2C+Melissa+C%22">Friesen, Melissa C</searchLink><relatesTo>1</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Annals+of+Work+Exposures+%26+Health%22">Annals of Work Exposures & Health</searchLink>. Aug2023, Vol. 67 Issue 7, p895-906. 12p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Work+environment%22">Work environment</searchLink><br /><searchLink fieldCode="DE" term="%22Pilot+projects%22">Pilot projects</searchLink><br /><searchLink fieldCode="DE" term="%22Mobile+apps%22">Mobile apps</searchLink><br /><searchLink fieldCode="DE" term="%22Smartphones%22">Smartphones</searchLink><br /><searchLink fieldCode="DE" term="%22Occupational+exposure%22">Occupational exposure</searchLink><br /><searchLink fieldCode="DE" term="%22Descriptive+statistics%22">Descriptive statistics</searchLink><br /><searchLink fieldCode="DE" term="%22Research+funding%22">Research funding</searchLink><br /><searchLink fieldCode="DE" term="%22Motion+capture+%28Human+mechanics%29%22">Motion capture (Human mechanics)</searchLink><br /><searchLink fieldCode="DE" term="%22Agricultural+laborers%22">Agricultural laborers</searchLink><br /><searchLink fieldCode="DE" term="%22Digital+video%22">Digital video</searchLink><br /><searchLink fieldCode="DE" term="%22Longitudinal+method%22">Longitudinal method</searchLink><br /><searchLink fieldCode="DE" term="%22Horticulture%22">Horticulture</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Objectives Smartphones 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. Methods We 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. Results Of 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). Conclusions Our 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. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Annals of Work Exposures & Health is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1093/annweh/wxad034 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 12 StartPage: 895 Subjects: – SubjectFull: Work environment Type: general – SubjectFull: Pilot projects Type: general – SubjectFull: Mobile apps Type: general – SubjectFull: Smartphones Type: general – SubjectFull: Occupational exposure Type: general – SubjectFull: Descriptive statistics Type: general – SubjectFull: Research funding Type: general – SubjectFull: Motion capture (Human mechanics) Type: general – SubjectFull: Agricultural laborers Type: general – SubjectFull: Digital video Type: general – SubjectFull: Longitudinal method Type: general – SubjectFull: Horticulture Type: general Titles: – TitleFull: Using a smartphone application to capture daily work activities: a longitudinal pilot study in a farming population. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Josse, Pabitra R – PersonEntity: Name: NameFull: Locke, Sarah J – PersonEntity: Name: NameFull: Bowles, Heather R – PersonEntity: Name: NameFull: Wolff-Hughes, Dana L – PersonEntity: Name: NameFull: Sauve, Jean-François – PersonEntity: Name: NameFull: Andreotti, Gabriella – PersonEntity: Name: NameFull: Moon, Jon – PersonEntity: Name: NameFull: Hofmann, Jonathan N – PersonEntity: Name: NameFull: Freeman, Laura E Beane – PersonEntity: Name: NameFull: Friesen, Melissa C IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 08 Text: Aug2023 Type: published Y: 2023 Identifiers: – Type: issn-print Value: 23987308 Numbering: – Type: volume Value: 67 – Type: issue Value: 7 Titles: – TitleFull: Annals of Work Exposures & Health Type: main |
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