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Pain is prevalent and poorly managed in older adults. Although pain self-management strategies are helpful, adoption and access are limited; thus, technology provides an opportunity for intervention delivery. Mobile health (mHealth) is feasible to use in older adults; however, we have yet to understand the effect of mHealth pain self-management interventions on pain outcomes in older adults.
The purpose of this scoping review is to examine the characteristics of mHealth interventions and their efficacy on pain outcomes in older adults with musculoskeletal pain.
With the assistance of a medical librarian, keywords and subject headings were generated, including but not limited to mobile health application, mHealth, digital, pain, pain management, and older. A search was conducted for papers in journal databases, including PubMed, Embase, CINAHL, Scopus, and IEEE Xplore, between 2000 and 2022. Papers were screened according to predetermined inclusion and exclusion criteria, and reference lists were reviewed for additional paper inclusion. Three authors appraised the methodology of papers independently, then collaboratively to synthesize the evidence.
Six publications were included in the scoping review. The design and methodology ranged widely from pilot studies to a comparative effectiveness trial. Older participants in the studies reported a variety of musculoskeletal conditions. Delivery of the mHealth pain self-management interventions incorporated mobile devices, such as a smartphone or tablet. Most mHealth-delivered interventions were multicomponent and incorporated elements of in-person and telephone access to an interventionist. The findings suggested mHealth interventions may reduce pain intensity; however, pain interference and other pain-related conditions did not have a statistically significant reduction.
Research that has explored mHealth for pain self-management is beginning to move beyond feasibility. The few experimental studies conducted in older adults are heterogeneous, and the interventions are mostly multicomponent. It is premature to conclude the interventions’ significant effect on pain or pain-related symptoms. As technology continues to integrate into health care, more experimental research is warranted to examine the efficacy of mHealth interventions on a variety of pain outcomes in older adults.
The population of older adults in the United States is expected to reach 80.8 million by 2040. Along with the population increase, it is likely that the number of individuals with chronic conditions and symptoms, such as chronic pain, will grow [
The concept of “pain self-management” has not been well-defined in the literature. Some researchers have defined self-management as a behavior that helps patients maintain wellness through several tasks: condition management, creation of new meaningful behaviors, and emotion management [
Pain self-management has been historically encouraged among older adults with chronic pain [
While definitions of mHealth vary, it is often defined as the use of mobile phones, tablets, sensors, and other wireless devices to help accomplish health objectives [
The possibilities are numerous for mHealth and older adults who have pain. In total, 28% of older adults currently use at least one mHealth app, and 49% of those between the ages of 50 and 64 years were more likely to have used an app than 38% of older adults between 65 and 80 years of age [
The aim of a scoping review is to conduct a broad analysis of available evidence to answer a research question [
To obtain a comprehensive review of the literature, the research team performed a search across multiple bioscience and biomedical databases, including MEDLINE via PubMed, Embase, CINAHL, Scopus, and IEEE Xplore for pertinent papers. The results were limited to peer-reviewed papers published in English between 2000 and 2022. The search was performed in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. The search strategy, designed by an experienced academic medical librarian (KH), combined controlled vocabulary terms and free-text words on the concepts of mobile apps, pain management, and adults aged 60 years or older. The full search strategy is included in
Studies were included in this review if they aimed to explore the outcomes of using mHealth pain interventions in older adults. Older adults were defined as those individuals 60 years of age or older as characterized by the World Health Organization [
Scoping review flowchart mHealth interventions for pain outcomes in older adults.
Three authors (MS, AMH, and MK) selected the final set of studies. Two authors (MS and MK) reviewed and organized the data that pertained to research questions. The data included country, median or mean age, sample size, race or ethnicity, clinical pain diagnoses or conditions that were the subject of treatment, devices used to deliver mHealth, mHealth intervention characteristics, and pain outcomes. Six papers were included, and the data are summarized in
In total, 4 of the selected studies were conducted in the United States, 1 study was conducted in Sweden, and 1 in the United Kingdom. The study designs varied; 2 studies were randomized controlled trials [
The papers included men and women (mean age range 63-70 years; 45%-91.7% White). Sample sizes of the studies ranged from 12 [
In 3 studies, a smartphone or tablet were used to deliver a downloaded software app or stream content as an mHealth intervention [
Despite the similarity in using mHealth, the interventions varied widely in the structure, content, and duration. Overall, the structure of the intervention components varied. Interventions incorporated a mixture of mHealth along with in-person and access to other interventionalists such as a coach or therapist. An in-person component was present in one study [
The studies also varied in content and duration. In 2 studies, exercise and osteoarthritis education were the main intervention components [
In each study, the intervention’s efficacy for decreasing pain intensity was measured. In 5 studies [
Pain interference was measured in 2 studies. In one study [
Additional pain-related outcomes were measured in the selected papers. Depressive symptoms were measured in 2 studies [
A scoping review was conducted to examine the characteristics of mHealth interventions and their efficacy on pain outcomes in older adults. Consistent with the purpose of a scoping review, we demonstrated the breadth of evidence on a topic [
The number of studies that focus on measuring pain or pain-related outcomes in older adults is sparse. Most studies where mHealth for pain was explored were excluded due to participants having a mean age of less than 60 years old. The sample sizes of the studies varied, which may be attributed to usability barriers in the oldest old of adults, leading to challenges in recruiting older participants for mHealth pain intervention studies. Many excluded studies also focused on usability, acceptance, and design of mHealth pain interventions, and yet while important for aiding adoption, many of these studies did not measure an effect on pain outcomes.
There were a variety of devices used to deliver mHealth interventions, including smartphones or tablets. The use of smartphones would be the most logical device to deliver mHealth interventions due to the availability and increased use by older adults. Despite the common assumption that older adults do not use technology, many have adopted mobile devices, which is consistent with Pew research describing older adult’s use of smartphones has grown [
Most pain self-management strategies incorporate content elements of pain education, training or coaching to strengthen relaxation skills, coping, problem-solving, and communication [
Pain is a biopsychosocial symptom, and several instruments were used to assess pain outcomes. Pain intensity was a universal outcome, but measurement occurred at different time points. For example, it is not clear if mHealth interventions affect the older adult’s current pain intensity or pain that occurred within the past week. Surprisingly, pain interference was only measured in 2 studies [
More experimental studies are needed with large and culturally diverse samples to examine the efficacy of mHealth pain interventions on pain outcomes. Recruitment strategies must be such that older adults will be assured that training and assistance with technology will be provided to help alleviate apprehensions associated with usability. One example of assistance would be “navigators” that help older adults become acclimated with and troubleshoot the technology [
There are some limitations in this scoping review. The search identified few papers that focused on mHealth interventions for pain in older adults. As this is a rapidly growing body of research, other relevant papers could have been missed. For example, we did not include conference proceedings or abstracts from human-computer interaction databases, which may include additional experiments of mHealth pain interventions in older adults. The mental and behavioral health database, PsycInfo, was eliminated during the medical librarian’s preliminary search due to zero returns on the search terms combining keywords and controlled vocabulary for the concepts of mobile apps and chronic pain. Publication bias may have also caused us to miss papers with a negative or poor pain outcomes associated with mHealth interventions. Additionally, we only selected papers published in English.
This scoping review was conducted to examine the characteristics of mHealth interventions and pain outcomes in older adults. Although the research is beginning to move beyond usability and acceptance, few experimental studies have been conducted in older adults that focus on improving pain outcomes. The studies that have been conducted vary in design, sample size and diversity, measured outcomes, and interventional approach. As technology continues to integrate into health care, more research is warranted to examine the efficacy of mHealth interventions on pain outcomes in older adults.
Search strategy.
Mobile health intervention characteristics and outcomes.
mobile health
Preferred Reporting Items for Systematic Reviews and Meta-Analyses
Patient-Reported Outcomes Measurement Information System
virtual reality
None declared.