Steptacular: An incentive mechanism for promoting wellness

Gomes, Naini; Merugu, Deepak; O'Brien, Gearoid; Mandayam, Chinmoy; Yue, Jia Shuo; Atikoglu, Berk; Albert, Adrian; Fukumoto, N.; Liu, Huan; Prabhakar, Balaji; Wischik, Damon

doi:10.1109/comsnets.2012.6151377

Cited by 14 publications

(16 citation statements)

References 4 publications

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“…The majority of studies (93.0%, 103/111 ) involved adult participants; 8/111 studies (7.0%) involved children and adolescents. Participant numbers ranged from 2 [ 39 ] to 2980 [ 40 ]: 18.9% (21/111) of studies contained fewer than 13 participants. Study duration ranged from less than a day to 52 weeks.…”

Section: Resultsmentioning

confidence: 99%

Evaluating the Impact of Physical Activity Apps and Wearables: Interdisciplinary Review

McCallum¹,

Rooksby²,

Gray³

2018

JMIR Mhealth Uhealth

111

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BackgroundAlthough many smartphone apps and wearables have been designed to improve physical activity, their rapidly evolving nature and complexity present challenges for evaluating their impact. Traditional methodologies, such as randomized controlled trials (RCTs), can be slow. To keep pace with rapid technological development, evaluations of mobile health technologies must be efficient. Rapid alternative research designs have been proposed, and efficient in-app data collection methods, including in-device sensors and device-generated logs, are available. Along with effectiveness, it is important to measure engagement (ie, users’ interaction and usage behavior) and acceptability (ie, users’ subjective perceptions and experiences) to help explain how and why apps and wearables work.ObjectivesThis study aimed to (1) explore the extent to which evaluations of physical activity apps and wearables: employ rapid research designs; assess engagement, acceptability, as well as effectiveness; use efficient data collection methods; and (2) describe which dimensions of engagement and acceptability are assessed.MethodAn interdisciplinary scoping review using 8 databases from health and computing sciences. Included studies measured physical activity, and evaluated physical activity apps or wearables that provided sensor-based feedback. Results were analyzed using descriptive numerical summaries, chi-square testing, and qualitative thematic analysis.ResultsA total of 1829 abstracts were screened, and 858 articles read in full. Of 111 included studies, 61 (55.0%) were published between 2015 and 2017. Most (55.0%, 61/111) were RCTs, and only 2 studies (1.8%) used rapid research designs: 1 single-case design and 1 multiphase optimization strategy. Other research designs included 23 (22.5%) repeated measures designs, 11 (9.9%) nonrandomized group designs, 10 (9.0%) case studies, and 4 (3.6%) observational studies. Less than one-third of the studies (32.0%, 35/111) investigated effectiveness, engagement, and acceptability together. To measure physical activity, most studies (90.1%, 101/111) employed sensors (either in-device [67.6%, 75/111] or external [23.4%, 26/111]). RCTs were more likely to employ external sensors (accelerometers: P=.005). Studies that assessed engagement (52.3%, 58/111) mostly used device-generated logs (91%, 53/58) to measure the frequency, depth, and length of engagement. Studies that assessed acceptability (57.7%, 64/111) most often used questionnaires (64%, 42/64) and/or qualitative methods (53%, 34/64) to explore appreciation, perceived effectiveness and usefulness, satisfaction, intention to continue use, and social acceptability. Some studies (14.4%, 16/111) assessed dimensions more closely related to usability (ie, burden of sensor wear and use, interface complexity, and perceived technical performance).ConclusionsThe rapid increase of research into the impact of physical activity apps and wearables means that evaluation guidelines are urgently needed to promote efficiency through the use of rapid res...

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Section: Resultsmentioning

confidence: 99%

Evaluating the Impact of Physical Activity Apps and Wearables: Interdisciplinary Review

McCallum¹,

Rooksby²,

Gray³

2018

JMIR Mhealth Uhealth

111

View full text Add to dashboard Cite

show abstract

“…Physical activity [35,43,46,53,58,65,66,74,77] Sedentary behavior [36,45,48,60] Not defined [12,34,[37][38][39][40][41][42]44,47,[49][50][51][52][54][55][56][57]59,[61][62][63][64][67][68][69][70][71][72][73]75,76] Although the majority of the papers did not provide a definition of SB or PA, a general distribution of the main targeted behavior could be made based on the description of the interventions. Just over half of the interventions targeted PA (24) while 9 interventions targeted SB and 12 targeted both PA and SB.…”

Section: Targeted Behavior Studiesmentioning

confidence: 99%

“…Phone applications in combination with wearables were often used to give information or prompts, and as a data collection tool. Seven interventions did not have a physical component, of which one used break-prompting software [60], one used a projected avatar [76], one was an email-based intervention [35], and four were platform-based interventions [37,44,46,47]. Figure 3 shows the different types of technologies used by the interventions in relation to the targeted behavior.…”

Section: Technology Typementioning

confidence: 99%

“…Figure 3 shows the different types of technologies used by the interventions in relation to the targeted behavior. [35,37,44,46,47,60,76] Several types of objective data were collected as input measures by the interventions. Twenty-one interventions used step count as input, six measured heartrate, eight used motions or gestures as input, and three calculated caloric intake or energy expenditure (Table 6).…”

Section: Technology Typementioning

confidence: 99%

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A Scoping Review of Digital Tools to Reduce Sedentary Behavior or Increase Physical Activity in Knowledge Workers

Damen

Brombacher

Lallemand

et al. 2020

IJERPH

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Background: There is increasing interest in the role that technology can play in improving the vitality of knowledge workers. A promising and widely adopted strategy to attain this goal is to reduce sedentary behavior (SB) and increase physical activity (PA). In this paper, we review the state-of-the-art SB and PA interventions using technology in the office environment. By scoping the existing landscape, we identified current gaps and underexplored possibilities. We discuss opportunities for future development and research on SB and PA interventions using technology. Methods: A systematic search was conducted in the Association for Computing Machinery digital library, the interdisciplinary library Scopus, and the Institute of Electrical and Electronics Engineers Xplore Digital Library to locate peer-reviewed scientific articles detailing SB and PA technology interventions in office environments between 2009 and 2019. Results: The initial search identified 1130 articles, of which 45 studies were included in the analysis. Our scoping review focused on the technologies supporting the interventions, which were coded using a grounded approach. Conclusion: Our findings showed that current SB and PA interventions using technology provide limited possibilities for physically active ways of working as opposed to the common strategy of prompting breaks. Interventions are also often offered as additional systems or services, rather than integrated into existing office infrastructures. With this work, we have mapped different types of interventions and provide an increased understanding of the opportunities for future multidisciplinary development and research of technologies to address sedentary behavior and physical activity in the office context.

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“…On va ainsi transformer l'objectif lointain et peu défini d'« être en forme » en des propositions d'actions concrètes et quotidiennes, des mesures et des gains donnant parfois lieu à des récompenses ou des badges. Pendant 6 mois, 5 000 employés volontaires de la société Accenture équipés de podomètres ont ainsi participé à un jeu transformant les pas effectués en points et récompenses dans un objectif de santé (Gomes et al [53]).…”

Section: Phase D'implémentation : Leunclassified

Le covoiturage domicile-travail : De l’approche technico-économique classique à une approche comportementale

Josset¹

2016

RTS

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Le covoiturage est souvent cité comme solution à la saturation des transports urbains mais reste une pratique marginale dans la population. Nous montrons dans ce papier qu'une approche comportementale permet la prise en compte de facteurs sociologiques et psychologiques qui constituent des freins majeurs à l'adoption de cette pratique. Nous en déduisons plusieurs hypothèses sur le passage à l'échelle, les incitations et la confiance que nous proposons d'explorer par des expérimentations de terrains. Mots clés covoiturage • économie comportementale • expérimentation Abstract Ridesharing is often viewed as a way to solve urban transport crisis but fails to become an effective widespread practice in the population. We show in this paper that a behavioral approach allows the consideration of sociological and psychological factors which constitute major challenges to the adoption of this practice. We deduct several hypotheses for promoting massification, finding incentives and enabling trust that we propose to explore with field experiments.

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Steptacular: An incentive mechanism for promoting wellness

Cited by 14 publications

References 4 publications

Evaluating the Impact of Physical Activity Apps and Wearables: Interdisciplinary Review

Evaluating the Impact of Physical Activity Apps and Wearables: Interdisciplinary Review

A Scoping Review of Digital Tools to Reduce Sedentary Behavior or Increase Physical Activity in Knowledge Workers

Le covoiturage domicile-travail : De l’approche technico-économique classique à une approche comportementale

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