Elsevier

Maturitas

Volume 113, July 2018, Pages 32-39
Maturitas

Review
eHealth interventions to promote objectively measured physical activity in community-dwelling older people

https://doi.org/10.1016/j.maturitas.2018.04.010Get rights and content

Highlights

  • ā€¢

    eHealth solutions are increasingly applied to deliver interventions for promoting an active lifestyle in older people.

  • ā€¢

    Objective assessment of daily physical activity is essential to reliably evaluate the effectiveness of such interventions.

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    eHealth interventions increased daily step count and time spent on physical activity right after the intervention.

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    Larger studies with longer follow-up are needed for evidence on sustaining long-term physical activity increases.

Abstract

eHealth solutions are increasingly being applied to deliver interventions for promoting an active lifestyle in the general population but also in older people. Objective assessment of daily physical activity (PA) is essential to accurately and reliably evaluate the effectiveness of such interventions. This review presents an overview of eHealth interventions that focus on promoting PA in community-dwelling older people, and discusses the methods used to objectively assess PA, and the effectiveness of the eHealth interventions in increasing PA. The twelve eHealth intervention studies that met our inclusion criteria used a variety of digital solutions, ranging from solely the use of an accelerometer or text messages, to interactive websites with access to (animated) coaches and peer support. Besides evaluating the effectiveness of an intervention on objectively assessed PA, all interventions also included continuous self-monitoring of PA as part of the intervention. Procedures for the collection and analysis of PA data varied across studies; five studies used pedometers to objectively assess PA and seven used tri-axial accelerometers. Main reported outcomes were daily step counts and minutes spent on PA. The current evidence seems to point to a positive short-term effect of increased PA (i.e. right after administering the intervention), but evidence for long-term effects is lacking. Many studies were underpowered to detect any intervention effects, and therefore larger studies with longer follow-up are needed to provide evidence on sustaining the PA increases that follow eHealth interventions in older people.

Introduction

Continuing or commencing an active lifestyle with ageing is associated with health benefits. It is well-documented that higher levels of daily physical activity (PA) are associated with better physical and mental well-being in older people [1], [2], [3]. Adopting an active lifestyle at old age has also shown strong positive effects for older people, such as improved functioning [4], reduced fall risk [5], and improved quality of life[6]. In addition, physical inactivity can boost physical decline as a result of ageing [7]. Given its potential for counteracting or slowing down detrimental outcomes, interventions for promoting an active lifestyle are widely considered in aging populations [8].

Over the past decades, the use of information and communication technology (ICT) to deliver lifestyle interventions has grown exponentially. The use of ICT solutions in healthcare services is often called electronic health or eHealth [9]. eHealth interventions that use electronic devices, such as computers, smartphones or tablets, for promoting an active lifestyle have shown positive results on PA in the general population [10], as well as in older people [9]. eHealth interventions are presumed to have great potential to increase access to interventions, increase compliance, lessen the burden on healthcare staff, and are highly scalable. Moreover, the use of a digital environment allows for delivery of continuous feedback and application of additional behaviour change techniques within the technology [11]. It further facilitates the tailoring of the intervention to the individual [12]. Those aged ā‰„55 years may be more familiar with using electronic devices and wearable technology than previous generations [13], and prior evidence has shown that this generation finds electronic devices promoting PA acceptable [14].

When evaluating the health benefits of lifestyle interventions for older people, it is essential to consider theories underlying the intervention to understand working mechanisms [15]. Besides piloting feasibility of newly developed eHealth interventions in a small sample, evaluating intermediate outcomes related to health, such as PA, is considered crucial to prove effectiveness and establish the causal pathways of long-term health benefits [15]. A recent systematic review showed that eHealth lifestyle interventions are effective in promoting PA in people above 50 years; however, the majority of studies in this review measured PA self-reported by questionnaires [9]. Although questionnaires are inexpensive, quick and easy to administer, they are prone to recall bias, might lead to variable and socially desirable answers and generally do not assess light PA or ordinary activities in daily life [16], [17]. Questionnaires therefore do not provide a very accurate reflection of a personā€™s daily PA. Increased availability of wearable devices, such as pedometers or inertial sensors, allows collection of objective PA data in daily life [18]. Pedometers count steps while walking, whereas inertial sensors collect and store data over longer periods, later analysed to extract multiple features of PA. Inertial sensors, particularly tri-axial accelerometers, have shown better reliability in capturing daily PA than pedometers and uniaxial accelerometers due to their ability to detect light PA [19].

This review presents an overview of recent eHealth interventions for promoting PA in community-dwelling older people with objective measurements of PA (i.e. by pedometer, uni-axial or tri-axial accelerometers). We discuss the eHealth interventions developed for promoting sPA in the older target population, as well as the employed methods to assess PA objectively. Finally, we discuss the effectiveness of the interventions on PA behaviour.

Section snippets

Methods

For this narrative review, we followed the guidelines for database search, selection of studies and data extraction from Cochrane [20]. We searched PubMed (from January 1990 to January 2018) with key search terms and synonyms for ā€œolder peopleā€, ā€œtelemedicineā€, ā€œexerciseā€, ā€œambulatory monitoringā€, and ā€œrandomized trialsā€ (see Supplementary Table 1 for the search syntax). Studies were included in the current review if they: 1) included community-dwelling people with a mean or median age

eHealth interventions for promoting physical activity

Twelve different studies met our inclusion criteria [21], [22], [23], [24], [25], [26], [27], [28], [29], [30], [31], [32] (Table 1 for details and Fig. 1 for a flowchart of the search). Sample sizes of studies varied from 40 [28] to 263 [21], with eight out of twelve studies including <100 participants. The ICT modalities that were used by studies to deliver the interventions differed considerably, and four studies compared multiple interventions with one control condition [23], [24], [29],

Conclusions

This overview shows that eHealth interventions for promoting an active lifestyle, delivered in a wide variety of modalities, appear to be acceptable for older populations and have positive effects on increasing PA in the short-term. However, caution is warranted since many studies were underpowered and long-term effects have not yet been established. Larger studies with theory-based interventions and a longer follow-up are needed to fully understand the potential and effective components of

Contributors

All authors were involved in the study design.

Nini H Jonkman performed the data collection and analysis, and drafted the manuscript.

Kimberley S van Schooten, Andrea B Maier and Mirjam Pijnappels provided input with the interpretation of the data, and contributed to critical revision of the manuscript.

All authors approved the final version of the manuscript.

Nini H Jonkman had full access to all data and had final responsibility for the decision to submit for publication.

Nini H Jonkman, Andrea B

Conflict of interest

The authors declare that they have no conflict of interest.

Funding

This work was supported by funding from the European Unionā€™s Horizon 2020 research and innovation programme [grant agreement number 689238]. Kimberley S van Schooten was supported by the Human Frontier Science program [HFSP long-term fellowship number LT001080/2017]. The funding source had no involvement in study design; in the collection, analysis and interpretation of data; in the writing of the report; and in the decision to submit the article for publication.

Provenance and peer review

This article has undergone peer review.

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