Toward Gamified Pain Management Apps: Mobile Application Rating Scale-Based Quality Assessment of Pain-Mentor's First Prototype Through an Expert Study

Digital health tools for pain monitoring in pediatric oncology: a scoping review and qualitative assessment of barriers and facilitators of implementation

PURPOSE

We aimed to systematically identify and characterize existing digital health tools for pain monitoring in children with cancer, and to assess common barriers and facilitators of implementation.

METHODS

A comprehensive literature search (PubMed, Cochrane, Embase, and PsycINFO) was carried out to identify published research on mobile apps and wearable devices focusing on acute and/or chronic pain in children (0-18 years) with cancer (all diagnoses) during active treatment. Tools had to at least include a monitoring feature for one or more pain characteristic(s) (e.g., presence, severity, perceived cause interference with daily life). Project leaders of identified tools were invited for an interview on barriers and facilitators.

RESULTS

Of 121 potential publications, 33 met inclusion criteria, describing 14 tools. Two methods of delivery were used: apps (n=13), and a wearable wristband (n=1). Most publications focused on feasibility and acceptability. Results of interviews with project leaders (100% response rate), reveal that most barriers to implementation were identified in the organizational context (47% of barriers), with financial resources and insufficient time available mentioned most often. Most factors that facilitated implementation related to end users (56% of facilitators), with end-user cooperation and end-user satisfaction mentioned most often.

CONCLUSIONS

Existing digital tools for pain in children with cancer were mostly apps directed at pain severity monitoring and little is still known about their effectiveness. Paying attention to common barriers and facilitators, especially taking into account realistic funding expectations and involving end users during early stages of new projects, might prevent evidence based interventions from ending up unused.

Identification and Evaluation of Methodologies to Assess the Quality of Mobile Health Apps in High-, Low-, and Middle-Income Countries: Rapid Review

BACKGROUND

In recent years, there has been rapid growth in the availability and use of mobile health (mHealth) apps around the world. A consensus regarding an accepted standard to assess the quality of such apps has yet to be reached. A factor that exacerbates the challenge of mHealth app quality assessment is variations in the interpretation of quality and its subdimensions. Consequently, it has become increasingly difficult for health care professionals worldwide to distinguish apps of high quality from those of lower quality. This exposes both patients and health care professionals to unnecessary risks. Despite progress, limited understanding of the contributions of researchers in low- and middle-income countries (LMICs) exists on this topic. Furthermore, the applicability of quality assessment methodologies in LMIC settings remains relatively unexplored.

OBJECTIVE

This rapid review aims to identify current methodologies in the literature to assess the quality of mHealth apps, understand what aspects of quality these methodologies address, determine what input has been made by authors from LMICs, and examine the applicability of such methodologies in LMICs.

METHODS

This review was registered with PROSPERO (International Prospective Register of Systematic Reviews). A search of PubMed, EMBASE, Web of Science, and Scopus was performed for papers related to mHealth app quality assessment methodologies, which were published in English between 2005 and 2020. By taking a rapid review approach, a thematic and descriptive analysis of the papers was performed.

RESULTS

Electronic database searches identified 841 papers. After the screening process, 52 papers remained for inclusion. Of the 52 papers, 5 (10%) proposed novel methodologies that could be used to evaluate mHealth apps of diverse medical areas of interest, 8 (15%) proposed methodologies that could be used to assess apps concerned with a specific medical focus, and 39 (75%) used methodologies developed by other published authors to evaluate the quality of various groups of mHealth apps. The authors in 6% (3/52) of papers were solely affiliated to institutes in LMICs. A further 15% (8/52) of papers had at least one coauthor affiliated to an institute in an LMIC.

CONCLUSIONS

Quality assessment of mHealth apps is complex in nature and at times subjective. Despite growing research on this topic, to date, an all-encompassing appropriate means for evaluating the quality of mHealth apps does not exist. There has been engagement with authors affiliated to institutes across LMICs; however, limited consideration of current generic methodologies for application in LMIC settings has been identified.

TRIAL REGISTRATION

PROSPERO CRD42020205149; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=205149.

Conceptual Ambiguity Surrounding Gamification and Serious Games in Health Care: Literature Review and Development of Game-Based Intervention Reporting Guidelines (GAMING)

BACKGROUND

In health care, the use of game-based interventions to increase motivation, engagement, and overall sustainability of health behaviors is steadily becoming more common. The most prevalent types of game-based interventions in health care research are gamification and serious games. Various researchers have discussed substantial conceptual differences between these 2 concepts, supported by empirical studies showing differences in the effects on specific health behaviors. However, researchers also frequently report cases in which terms related to these 2 concepts are used ambiguously or even interchangeably. It remains unclear to what extent existing health care research explicitly distinguishes between gamification and serious games and whether it draws on existing conceptual considerations to do so.

OBJECTIVE

This study aims to address this lack of knowledge by capturing the current state of conceptualizations of gamification and serious games in health care research. Furthermore, we aim to provide tools for researchers to disambiguate the reporting of game-based interventions.

METHODS

We used a 2-step research approach. First, we conducted a systematic literature review of 206 studies, published in the Journal of Medical Internet Research and its sister journals, containing terms related to gamification, serious games, or both. We analyzed their conceptualizations of gamification and serious games, as well as the distinctions between the two concepts. Second, based on the literature review findings, we developed a set of guidelines for researchers reporting on game-based interventions and evaluated them with a group of 9 experts from the field.

RESULTS

Our results show that less than half of the concept mentions are accompanied by an explicit definition. To distinguish between the 2 concepts, we identified four common approaches: implicit distinction, synonymous use of terms, serious games as a type of gamified system, and distinction based on the full game dimension. Our Game-Based Intervention Reporting Guidelines (GAMING) consist of 25 items grouped into four topics: conceptual focus, contribution, mindfulness about related concepts, and individual concept definitions.

CONCLUSIONS

Conceptualizations of gamification and serious games in health care literature are strongly heterogeneous, leading to conceptual ambiguity. Following the GAMING can support authors in rigorous reporting on study results of game-based interventions.

A Biofeedback App to Instruct Abdominal Breathing (Breathing-Mentor): Pilot Experiment

BACKGROUND

Deep and slow abdominal breathing is an important skill for the management of stress and pain. However, despite multiple proofs on the effectiveness of biofeedback, most breathing apps remain limited to pacing specific breathing patterns, without sensor feedback on the actual breathing behavior.

OBJECTIVE

To fill this gap, an app named Breathing-Mentor was developed. This app combines effective visualization of the instruction with biofeedback on deep abdominal breathing, based on the mobile phone's accelerometers. The aim of this pilot study was to investigate users' feedback and breathing behavior during initial contact with the app.

METHODS

To reveal the possible effects of biofeedback, two versions of the mobile app were developed. Both contained the same visual instruction, but only the full version included additional biofeedback. In total, 40 untrained participants were randomly assigned to one of the two versions of the app. They had to follow the app's instructions as closely as possible for 5 min.

RESULTS

The group with additional biofeedback showed an increased signal-to-noise ratio for instructed breathing frequency (0.1 Hz) compared with those using visual instruction without biofeedback (F1,37=4.18; P<.048). During this initial contact with the full version, self-reported relaxation effectivity was, however, lower than the group using visual instruction without biofeedback (t37=-2.36; P=.02), probably owing to increased cognitive workload to follow the instruction.

CONCLUSIONS

This study supports the feasibility and usefulness of incorporating biofeedback in the Breathing-Mentor app to train abdominal breathing. Immediate effects on relaxation levels should, however, not be expected for untrained users.