Personal health technologies in employee health promotion

Usage activity, usefulness, and health-related outcomes in a 1-year randomized controlled trial

Elina M. Mattila (Corresponding Author), Anna-Leena Orsama, Aino Ahtinen, L. Hopsu, T. Leino, Korhonen

Research output: Contribution to journalArticleScientificpeer-review

31 Citations (Scopus)

Abstract

Background: Common risk factors such as obesity, poor nutrition, physical inactivity, stress, and sleep deprivation threaten the wellness and work ability of employees. Personal health technologies may help improve engagement in health promotion programs and maintenance of their effect.

Objective: This study investigated personal health technologies in supporting employee health promotion targeting multiple behavioral health risks. We studied the relations of usage activity to demographic and physiological characteristics, health-related outcomes (weight, aerobic fitness, blood pressure and cholesterol), and the perceived usefulness of technologies in wellness management.

Methods: We conducted a subgroup analysis of the technology group (114 subjects, 33 males, average age 45 years, average BMI 27.1 kg/m2) of a 3-arm randomized controlled trial (N=352). The trial was organized to study the efficacy of a face-to-face group intervention supported by technologies, including Web services, mobile applications, and personal monitoring devices. Technology usage was investigated based on log files and questionnaires. The associations between sustained usage of Web and mobile technologies and demographic and physiological characteristics were analyzed by comparing the baseline data of sustained and non-sustained users. The associations between sustained usage and changes in health-related outcomes were studied by repeated analysis of variance, using data measured by baseline and end questionnaires, and anthropometric and laboratory measurements. The experienced usability, usefulness, motivation, and barriers to using technologies were investigated by 4 questionnaires and 2 interviews.

Results: 111 subjects (97.4%) used technologies at some point of the study, and 33 (29.9%) were classified as sustained users of Web or mobile technologies. Simple technologies, weight scales and pedometer, attracted the most users. The sustained users were slightly older 47 years (95% CI 44 to 49) versus 44 years (95% CI 42 to 45), P=.034 and had poorer aerobic fitness at baseline (mean difference in maximal metabolic equivalent 1.0, 95% Cl 0.39 to 1.39; P=.013) than non-sustained users. They succeeded better in weight management: their weight decreased -1.2 kg (95% CI -2.38 to -0.01) versus +0.6 kg (95% CI -0.095 to 1.27), P=.006; body fat percentage -0.9%-units (95% CI -1.64 to -0.09) versus +0.3%-units (95% CI -0.28 to 0.73), P=.014; and waist circumference -1.4 cm (95% CI -2.60 to -0.20) versus +0.7 cm (95% CI -0.21 to 1.66), P=.01. They also participated in intervention meetings more actively: median 4 meetings (interquartile range; IQR 4–5) versus 4 meetings (IQR 3–4), P=.009. The key factors in usefulness were: simplicity, integration into daily life, and clear feedback on progress.

Conclusions: Despite active initial usage, less than 30% of subjects continued using Web or mobile technologies throughout the study. Sustained users achieved better weight-related outcomes than non-sustained users. High non-usage attrition and modest outcomes cast doubt on the potential of technologies to support interventions.
Original languageEnglish
Article numbere16
JournalJMIR Mhealth and Uhealth
Volume1
Issue number2
DOIs
Publication statusPublished - 2013
MoE publication typeA1 Journal article-refereed

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Biomedical Technology
Occupational Health
Health Promotion
Randomized Controlled Trials
Technology
Health
Weights and Measures
Demography
Mobile Applications
Metabolic Equivalent
Aptitude
Sleep Deprivation
Waist Circumference
Adipose Tissue
Motivation
Analysis of Variance
Obesity
Cholesterol
Maintenance
Interviews

Keywords

  • device
  • health promotion
  • health technology
  • internet
  • intervention
  • mobile phones
  • risk factors

Cite this

@article{87acfc4c0a694e5bb7c93b5c87617f8b,
title = "Personal health technologies in employee health promotion: Usage activity, usefulness, and health-related outcomes in a 1-year randomized controlled trial",
abstract = "Background: Common risk factors such as obesity, poor nutrition, physical inactivity, stress, and sleep deprivation threaten the wellness and work ability of employees. Personal health technologies may help improve engagement in health promotion programs and maintenance of their effect.Objective: This study investigated personal health technologies in supporting employee health promotion targeting multiple behavioral health risks. We studied the relations of usage activity to demographic and physiological characteristics, health-related outcomes (weight, aerobic fitness, blood pressure and cholesterol), and the perceived usefulness of technologies in wellness management.Methods: We conducted a subgroup analysis of the technology group (114 subjects, 33 males, average age 45 years, average BMI 27.1 kg/m2) of a 3-arm randomized controlled trial (N=352). The trial was organized to study the efficacy of a face-to-face group intervention supported by technologies, including Web services, mobile applications, and personal monitoring devices. Technology usage was investigated based on log files and questionnaires. The associations between sustained usage of Web and mobile technologies and demographic and physiological characteristics were analyzed by comparing the baseline data of sustained and non-sustained users. The associations between sustained usage and changes in health-related outcomes were studied by repeated analysis of variance, using data measured by baseline and end questionnaires, and anthropometric and laboratory measurements. The experienced usability, usefulness, motivation, and barriers to using technologies were investigated by 4 questionnaires and 2 interviews.Results: 111 subjects (97.4{\%}) used technologies at some point of the study, and 33 (29.9{\%}) were classified as sustained users of Web or mobile technologies. Simple technologies, weight scales and pedometer, attracted the most users. The sustained users were slightly older 47 years (95{\%} CI 44 to 49) versus 44 years (95{\%} CI 42 to 45), P=.034 and had poorer aerobic fitness at baseline (mean difference in maximal metabolic equivalent 1.0, 95{\%} Cl 0.39 to 1.39; P=.013) than non-sustained users. They succeeded better in weight management: their weight decreased -1.2 kg (95{\%} CI -2.38 to -0.01) versus +0.6 kg (95{\%} CI -0.095 to 1.27), P=.006; body fat percentage -0.9{\%}-units (95{\%} CI -1.64 to -0.09) versus +0.3{\%}-units (95{\%} CI -0.28 to 0.73), P=.014; and waist circumference -1.4 cm (95{\%} CI -2.60 to -0.20) versus +0.7 cm (95{\%} CI -0.21 to 1.66), P=.01. They also participated in intervention meetings more actively: median 4 meetings (interquartile range; IQR 4–5) versus 4 meetings (IQR 3–4), P=.009. The key factors in usefulness were: simplicity, integration into daily life, and clear feedback on progress.Conclusions: Despite active initial usage, less than 30{\%} of subjects continued using Web or mobile technologies throughout the study. Sustained users achieved better weight-related outcomes than non-sustained users. High non-usage attrition and modest outcomes cast doubt on the potential of technologies to support interventions.",
keywords = "device, health promotion, health technology, internet, intervention, mobile phones, risk factors",
author = "Mattila, {Elina M.} and Anna-Leena Orsama and Aino Ahtinen and L. Hopsu and T. Leino and Korhonen",
year = "2013",
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language = "English",
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Personal health technologies in employee health promotion : Usage activity, usefulness, and health-related outcomes in a 1-year randomized controlled trial. / Mattila, Elina M. (Corresponding Author); Orsama, Anna-Leena; Ahtinen, Aino; Hopsu, L.; Leino, T.; Korhonen.

In: JMIR Mhealth and Uhealth, Vol. 1, No. 2, e16, 2013.

Research output: Contribution to journalArticleScientificpeer-review

TY - JOUR

T1 - Personal health technologies in employee health promotion

T2 - Usage activity, usefulness, and health-related outcomes in a 1-year randomized controlled trial

AU - Mattila, Elina M.

AU - Orsama, Anna-Leena

AU - Ahtinen, Aino

AU - Hopsu, L.

AU - Leino, T.

AU - Korhonen, null

PY - 2013

Y1 - 2013

N2 - Background: Common risk factors such as obesity, poor nutrition, physical inactivity, stress, and sleep deprivation threaten the wellness and work ability of employees. Personal health technologies may help improve engagement in health promotion programs and maintenance of their effect.Objective: This study investigated personal health technologies in supporting employee health promotion targeting multiple behavioral health risks. We studied the relations of usage activity to demographic and physiological characteristics, health-related outcomes (weight, aerobic fitness, blood pressure and cholesterol), and the perceived usefulness of technologies in wellness management.Methods: We conducted a subgroup analysis of the technology group (114 subjects, 33 males, average age 45 years, average BMI 27.1 kg/m2) of a 3-arm randomized controlled trial (N=352). The trial was organized to study the efficacy of a face-to-face group intervention supported by technologies, including Web services, mobile applications, and personal monitoring devices. Technology usage was investigated based on log files and questionnaires. The associations between sustained usage of Web and mobile technologies and demographic and physiological characteristics were analyzed by comparing the baseline data of sustained and non-sustained users. The associations between sustained usage and changes in health-related outcomes were studied by repeated analysis of variance, using data measured by baseline and end questionnaires, and anthropometric and laboratory measurements. The experienced usability, usefulness, motivation, and barriers to using technologies were investigated by 4 questionnaires and 2 interviews.Results: 111 subjects (97.4%) used technologies at some point of the study, and 33 (29.9%) were classified as sustained users of Web or mobile technologies. Simple technologies, weight scales and pedometer, attracted the most users. The sustained users were slightly older 47 years (95% CI 44 to 49) versus 44 years (95% CI 42 to 45), P=.034 and had poorer aerobic fitness at baseline (mean difference in maximal metabolic equivalent 1.0, 95% Cl 0.39 to 1.39; P=.013) than non-sustained users. They succeeded better in weight management: their weight decreased -1.2 kg (95% CI -2.38 to -0.01) versus +0.6 kg (95% CI -0.095 to 1.27), P=.006; body fat percentage -0.9%-units (95% CI -1.64 to -0.09) versus +0.3%-units (95% CI -0.28 to 0.73), P=.014; and waist circumference -1.4 cm (95% CI -2.60 to -0.20) versus +0.7 cm (95% CI -0.21 to 1.66), P=.01. They also participated in intervention meetings more actively: median 4 meetings (interquartile range; IQR 4–5) versus 4 meetings (IQR 3–4), P=.009. The key factors in usefulness were: simplicity, integration into daily life, and clear feedback on progress.Conclusions: Despite active initial usage, less than 30% of subjects continued using Web or mobile technologies throughout the study. Sustained users achieved better weight-related outcomes than non-sustained users. High non-usage attrition and modest outcomes cast doubt on the potential of technologies to support interventions.

AB - Background: Common risk factors such as obesity, poor nutrition, physical inactivity, stress, and sleep deprivation threaten the wellness and work ability of employees. Personal health technologies may help improve engagement in health promotion programs and maintenance of their effect.Objective: This study investigated personal health technologies in supporting employee health promotion targeting multiple behavioral health risks. We studied the relations of usage activity to demographic and physiological characteristics, health-related outcomes (weight, aerobic fitness, blood pressure and cholesterol), and the perceived usefulness of technologies in wellness management.Methods: We conducted a subgroup analysis of the technology group (114 subjects, 33 males, average age 45 years, average BMI 27.1 kg/m2) of a 3-arm randomized controlled trial (N=352). The trial was organized to study the efficacy of a face-to-face group intervention supported by technologies, including Web services, mobile applications, and personal monitoring devices. Technology usage was investigated based on log files and questionnaires. The associations between sustained usage of Web and mobile technologies and demographic and physiological characteristics were analyzed by comparing the baseline data of sustained and non-sustained users. The associations between sustained usage and changes in health-related outcomes were studied by repeated analysis of variance, using data measured by baseline and end questionnaires, and anthropometric and laboratory measurements. The experienced usability, usefulness, motivation, and barriers to using technologies were investigated by 4 questionnaires and 2 interviews.Results: 111 subjects (97.4%) used technologies at some point of the study, and 33 (29.9%) were classified as sustained users of Web or mobile technologies. Simple technologies, weight scales and pedometer, attracted the most users. The sustained users were slightly older 47 years (95% CI 44 to 49) versus 44 years (95% CI 42 to 45), P=.034 and had poorer aerobic fitness at baseline (mean difference in maximal metabolic equivalent 1.0, 95% Cl 0.39 to 1.39; P=.013) than non-sustained users. They succeeded better in weight management: their weight decreased -1.2 kg (95% CI -2.38 to -0.01) versus +0.6 kg (95% CI -0.095 to 1.27), P=.006; body fat percentage -0.9%-units (95% CI -1.64 to -0.09) versus +0.3%-units (95% CI -0.28 to 0.73), P=.014; and waist circumference -1.4 cm (95% CI -2.60 to -0.20) versus +0.7 cm (95% CI -0.21 to 1.66), P=.01. They also participated in intervention meetings more actively: median 4 meetings (interquartile range; IQR 4–5) versus 4 meetings (IQR 3–4), P=.009. The key factors in usefulness were: simplicity, integration into daily life, and clear feedback on progress.Conclusions: Despite active initial usage, less than 30% of subjects continued using Web or mobile technologies throughout the study. Sustained users achieved better weight-related outcomes than non-sustained users. High non-usage attrition and modest outcomes cast doubt on the potential of technologies to support interventions.

KW - device

KW - health promotion

KW - health technology

KW - internet

KW - intervention

KW - mobile phones

KW - risk factors

U2 - 10.2196/mhealth.2557

DO - 10.2196/mhealth.2557

M3 - Article

VL - 1

JO - JMIR Mhealth and Uhealth

JF - JMIR Mhealth and Uhealth

SN - 2291-5222

IS - 2

M1 - e16

ER -