Cargando…

Changing Behavioral Lifestyle Risk Factors Related to Cognitive Decline in Later Life Using a Self-Motivated eHealth Intervention in Dutch Adults

BACKGROUND: Our labor force is aging, but aged workers are not yet coached on how to stay cognitively fit for the job. OBJECTIVE: In this study, we tested whether a self-motivated, complex eHealth intervention could improve multiple health-related behaviors that are associated with cognitive aging a...

Descripción completa

Detalles Bibliográficos
Autores principales: Aalbers, Teun, Qin, Li, Baars, Maria AE, de Lange, Annet, Kessels, Roy PC, Olde Rikkert, Marcel GM
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4930530/
https://www.ncbi.nlm.nih.gov/pubmed/27317506
http://dx.doi.org/10.2196/jmir.5269
_version_ 1782440754489065472
author Aalbers, Teun
Qin, Li
Baars, Maria AE
de Lange, Annet
Kessels, Roy PC
Olde Rikkert, Marcel GM
author_facet Aalbers, Teun
Qin, Li
Baars, Maria AE
de Lange, Annet
Kessels, Roy PC
Olde Rikkert, Marcel GM
author_sort Aalbers, Teun
collection PubMed
description BACKGROUND: Our labor force is aging, but aged workers are not yet coached on how to stay cognitively fit for the job. OBJECTIVE: In this study, we tested whether a self-motivated, complex eHealth intervention could improve multiple health-related behaviors that are associated with cognitive aging among working Dutch adults. METHODS: This quasi-experimental prospective study with a pre-post design was conducted with employees of Dutch medium to large companies. All employees with Internet access, a good understanding of the Dutch language, and who provided digital informed consent were eligible to participate. In total, 2972 participants (2110/2972, 71.11% females) with a mean (standard deviation, SD) age of 51.8 (SD 12.9) years were recruited; 2305 became active users of the intervention, and 173 completed the 1-year follow-up. This self-motivated eHealth lifestyle intervention stimulates participants to set personally relevant, monthly health behavior change goals using Goal Attainment Scaling and to realize these goals by implementing behavior change techniques grounded in behavior change theory. The primary outcomes were the goal-setting success rate and the change in overall lifestyle score from baseline to the 1-year follow-up; the score was based on physical activity, diet, smoking, alcohol, sleep, and stress scores. The secondary outcomes were the changes in body weight, body mass index, specific lifestyle characteristics, and website usage. RESULTS: A total of 1212 participants set 2620 behavior change goals; 392 participants assessed 1089 (1089/2288, 47.59%) goals and successfully achieved 422 (422/1089, 38.75%) of these goals. Among the goal-setting participants in follow-up, this led to a +0.81-point improvement (95% CI 0.49-1.13, P<.001) in overall lifestyle (d=0.32) and weight loss of 0.62 kg (95% CI −1.16 to −0.07, P=.03). These participants also showed significant improvement in 8 out of 11 specific lifestyle components. CONCLUSIONS: Among an adult Dutch population, this eHealth intervention resulted in lifestyle changes in behavioral risk factors associated with cognitive decline, and these improvements lasted over the period of 1 year. Given the general aging of our workforce, this eHealth intervention opens new avenues for the widespread use of cost-effective self-motivated prevention programs aimed at prevention of early-stage cognitive decline and more self-management of their risk factors. TRIAL REGISTRATION: Nederlands Trial Register: NTR4144; http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=4144 (Archived by WebCite at http://www.webcitation.org/6cZzwZSg3).
format Online
Article
Text
id pubmed-4930530
institution National Center for Biotechnology Information
language English
publishDate 2016
publisher JMIR Publications
record_format MEDLINE/PubMed
spelling pubmed-49305302016-07-18 Changing Behavioral Lifestyle Risk Factors Related to Cognitive Decline in Later Life Using a Self-Motivated eHealth Intervention in Dutch Adults Aalbers, Teun Qin, Li Baars, Maria AE de Lange, Annet Kessels, Roy PC Olde Rikkert, Marcel GM J Med Internet Res Original Paper BACKGROUND: Our labor force is aging, but aged workers are not yet coached on how to stay cognitively fit for the job. OBJECTIVE: In this study, we tested whether a self-motivated, complex eHealth intervention could improve multiple health-related behaviors that are associated with cognitive aging among working Dutch adults. METHODS: This quasi-experimental prospective study with a pre-post design was conducted with employees of Dutch medium to large companies. All employees with Internet access, a good understanding of the Dutch language, and who provided digital informed consent were eligible to participate. In total, 2972 participants (2110/2972, 71.11% females) with a mean (standard deviation, SD) age of 51.8 (SD 12.9) years were recruited; 2305 became active users of the intervention, and 173 completed the 1-year follow-up. This self-motivated eHealth lifestyle intervention stimulates participants to set personally relevant, monthly health behavior change goals using Goal Attainment Scaling and to realize these goals by implementing behavior change techniques grounded in behavior change theory. The primary outcomes were the goal-setting success rate and the change in overall lifestyle score from baseline to the 1-year follow-up; the score was based on physical activity, diet, smoking, alcohol, sleep, and stress scores. The secondary outcomes were the changes in body weight, body mass index, specific lifestyle characteristics, and website usage. RESULTS: A total of 1212 participants set 2620 behavior change goals; 392 participants assessed 1089 (1089/2288, 47.59%) goals and successfully achieved 422 (422/1089, 38.75%) of these goals. Among the goal-setting participants in follow-up, this led to a +0.81-point improvement (95% CI 0.49-1.13, P<.001) in overall lifestyle (d=0.32) and weight loss of 0.62 kg (95% CI −1.16 to −0.07, P=.03). These participants also showed significant improvement in 8 out of 11 specific lifestyle components. CONCLUSIONS: Among an adult Dutch population, this eHealth intervention resulted in lifestyle changes in behavioral risk factors associated with cognitive decline, and these improvements lasted over the period of 1 year. Given the general aging of our workforce, this eHealth intervention opens new avenues for the widespread use of cost-effective self-motivated prevention programs aimed at prevention of early-stage cognitive decline and more self-management of their risk factors. TRIAL REGISTRATION: Nederlands Trial Register: NTR4144; http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=4144 (Archived by WebCite at http://www.webcitation.org/6cZzwZSg3). JMIR Publications 2016-06-17 /pmc/articles/PMC4930530/ /pubmed/27317506 http://dx.doi.org/10.2196/jmir.5269 Text en ©Teun Aalbers, Li Qin, Maria AE Baars, Annet de Lange, Roy PC Kessels, Marcel GM Olde Rikkert. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 17.06.2016. https://creativecommons.org/licenses/by/2.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0/ (https://creativecommons.org/licenses/by/2.0/) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.
spellingShingle Original Paper
Aalbers, Teun
Qin, Li
Baars, Maria AE
de Lange, Annet
Kessels, Roy PC
Olde Rikkert, Marcel GM
Changing Behavioral Lifestyle Risk Factors Related to Cognitive Decline in Later Life Using a Self-Motivated eHealth Intervention in Dutch Adults
title Changing Behavioral Lifestyle Risk Factors Related to Cognitive Decline in Later Life Using a Self-Motivated eHealth Intervention in Dutch Adults
title_full Changing Behavioral Lifestyle Risk Factors Related to Cognitive Decline in Later Life Using a Self-Motivated eHealth Intervention in Dutch Adults
title_fullStr Changing Behavioral Lifestyle Risk Factors Related to Cognitive Decline in Later Life Using a Self-Motivated eHealth Intervention in Dutch Adults
title_full_unstemmed Changing Behavioral Lifestyle Risk Factors Related to Cognitive Decline in Later Life Using a Self-Motivated eHealth Intervention in Dutch Adults
title_short Changing Behavioral Lifestyle Risk Factors Related to Cognitive Decline in Later Life Using a Self-Motivated eHealth Intervention in Dutch Adults
title_sort changing behavioral lifestyle risk factors related to cognitive decline in later life using a self-motivated ehealth intervention in dutch adults
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4930530/
https://www.ncbi.nlm.nih.gov/pubmed/27317506
http://dx.doi.org/10.2196/jmir.5269
work_keys_str_mv AT aalbersteun changingbehaviorallifestyleriskfactorsrelatedtocognitivedeclineinlaterlifeusingaselfmotivatedehealthinterventionindutchadults
AT qinli changingbehaviorallifestyleriskfactorsrelatedtocognitivedeclineinlaterlifeusingaselfmotivatedehealthinterventionindutchadults
AT baarsmariaae changingbehaviorallifestyleriskfactorsrelatedtocognitivedeclineinlaterlifeusingaselfmotivatedehealthinterventionindutchadults
AT delangeannet changingbehaviorallifestyleriskfactorsrelatedtocognitivedeclineinlaterlifeusingaselfmotivatedehealthinterventionindutchadults
AT kesselsroypc changingbehaviorallifestyleriskfactorsrelatedtocognitivedeclineinlaterlifeusingaselfmotivatedehealthinterventionindutchadults
AT olderikkertmarcelgm changingbehaviorallifestyleriskfactorsrelatedtocognitivedeclineinlaterlifeusingaselfmotivatedehealthinterventionindutchadults