Investigating episodes of mobile phone activity as indicators of opportune moments to deliver notifications

Fischer, Joel E.; Greenhalgh, Chris; Benford, Steve

doi:10.1145/2037373.2037402

Cited by 160 publications

(89 citation statements)

References 23 publications

(41 reference statements)

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“…with a mean age around 50) but four studies [7], [38], [39], [40] with participants younger than 30. Also, there is a gender imbalance, as only one study [41] established gender balance, while all other studies had more men than women with the gender ratio women to men going as low as 1 to 3 [7].…”

Section: A Search Strategy Resultsmentioning

confidence: 99%

Efficacy of mobile context-aware notification management systems: A systematic literature review and meta-analysis

Künzler

Kramer

Kowatsch

2017

2017 IEEE 13th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob)

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Abstract-Notifications can be relevant but they can also decrease productivity when delivered at the wrong point in time. Smartphones are increasingly capable of detecting relevant context information with the goal to decrease the number of these badly timed interruptions. Accordingly, research on contextaware notification management systems (CNMSs) on mobile devices has received increasing attention recently, prototypes have been built and empirically evaluated. However, there exists no systematic overview of mobile CNMSs evaluating their efficacy. The objectives of the current work are therefore to identify relevant empirical studies that have assessed the efficacy of mobile CNMSs and to discuss the findings with respect to future work. A systematic literature review and meta-analysis was conducted to address these objectives. Consistent with prior work, two efficacy metrics were applied: response rate and response delay. A keyword-based search strategy was used and resulted in 1'634 studies, out of which 8 were relevant for the topic. Findings indicate that mobile CNMSs increase the response rate, while there was only little evidence that they reduce response time, too. Implications for researchers and practitioners are discussed and future research is outlined that aims at further increasing the efficacy of mobile CNMSs.

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Section: A Search Strategy Resultsmentioning

confidence: 99%

Efficacy of mobile context-aware notification management systems: A systematic literature review and meta-analysis

Künzler

Kramer

Kowatsch

2017

2017 IEEE 13th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob)

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“…Decision making algorithms which are informed by sensors could also help determine the best times to interrupt. For example, Fischer and colleagues showed that people reacted faster to notifications if they were delivered after finishing a call or reading a text message [9]. Ho and Intille suggest that notifications may be received more positively if they occur between two physical activities (e.g.…”

Section: When To Promptmentioning

confidence: 99%

ForgetMeNot

Jamieson

O’Neill²,

Cullen

et al. 2017

Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems

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Smartphone reminding apps can compensate for memory impairment after acquired brain injury (ABI). In the absence of a caregiver, users must enter reminders themselves if the apps are going to help them. Poor memory and apathy associated with ABI can result in failure to initiate such configuration behaviour and the benefits of reminder apps are lost. ForgetMeNot takes a novel approach to address this problem by periodically encouraging the user to enter reminders with unsolicited prompts (UPs). An in situ case study investigated the experience of using a reminding app for people with ABI and tested UPs as a potential solution to initiating reminder entry. Three people with severe ABI living in a post-acute rehabilitation hospital used the app in their everyday lives for four weeks to collect real usage data. Field observations illustrated how difficulties with motivation, insight into memory difficulties and anxiety impact reminder app use in a rehabilitation setting. Results showed that when 6 UPs were presented throughout the day, reminder-setting increased, showing UPs are an important addition to reminder applications for people with ABI. This study demonstrates that barriers to technology use can be resolved in practice when software is developed with an understanding of the issues experienced by the user group.

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“…To compete with these other interesting distractions, multiple studies note the importance of triggers and prompts in order to encourage the use of applications (health behavior related or otherwise) [38,41]. Fischer et al suggest chaining triggers and prompts to the conclusion of other phone activities, such as sending a text message or making a phone call; this type of timing has been shown to increase user compliance in responding to a prompt, as the phone is already in hand [42].…”

Section: Human-computer Interaction Information Technology Mhealthmentioning

confidence: 99%

HCI and mobile health interventions

Poole

2013

Behav. Med. Pract. Policy Res.

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Advances in mobile computing offer the potential to change when, where, and how health interventions are delivered. Rather than relying on occasional in-clinic interactions, mobile health (mHealth) interventions may overcome constraints due to limited clinician time, poor patient adherence, and inability to provide meaningful interventions at the most appropriate time. Technological capability, however, does not equate with user acceptance and adoption. How then can we ensure that mobile technologies for behavior change meet the needs of their target audience? In this paper, we argue that overcoming acceptance and adoption barriers requires interdisciplinary collaborations, bringing together not only technologists and health researchers but also human-computer interaction (HCI) experts. We discuss the value of human-computer interaction research to the nascent field of mHealth and demonstrate how research from HCI can offer complementary insights on the creation of mobile health interventions. We conclude with a discussion of barriers to interdisciplinary collaborations in mobile health and suggest ways to overcome them. KeywordsHuman-computer interaction, Information technology, mHealth, Mobile technology Human-computer interaction is an interdisciplinary area of research and practice, drawing upon intellectual traditions of several disciplines including human factors, computer science, information systems, psychology, sociology, and visual design. For several decades, Human-computer interaction (HCI) research and practice has focused on designing human-centered technologies that fit into the everyday needs and routines of the people who use them [1], often referred to as user-centered design [2]. With this design philosophy, user needs are considered throughout the design of a technology-from initial requirements gathering to end stages of technology development. Rather than focusing on health outcomes or technical capabilities, a usercentered design approach provides insight into usability, usefulness, and fit of a technology into daily life. This approach can answer important questions on why technologies work in a given environment for a given set of users or why they fail to engage a target audience. In short, humancomputer interaction research can offer complementary insights into how people integrate smartphones, sensor networks, and social networks into their health behavior change efforts, as well as insight into how to design behavior change technologies such that they are more effective.Within HCI, there has been a recent movement to study the roles in which sensors, social networks, smartphones, and other technologies can take in behavior change related to water intake [3,4], diet [5][6][7][8][9][10][11], physical activity [12][13][14][15][16][17][18][19][20][21][22], healthy sleep behaviors [23,24], and chronic disease management [25][26][27][28][29][30]. Yet, there is a little overlap between HCI and the health sciences in these endeavors. This article not only describes the reasons for la...

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Investigating episodes of mobile phone activity as indicators of opportune moments to deliver notifications

Cited by 160 publications

References 23 publications

Efficacy of mobile context-aware notification management systems: A systematic literature review and meta-analysis

Efficacy of mobile context-aware notification management systems: A systematic literature review and meta-analysis

ForgetMeNot

HCI and mobile health interventions

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