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  1. C. Mccallum1,
  2. M. Campbell2,
  3. M. Higgs1,
  4. J. Vines1,
  5. T. Rapley1,
  6. K. Hackett1
  1. 1Northumbria University, Newcastle upon Tyne, United Kingdom
  2. 2Teesside University, Middlesbrough, United Kingdom


Background: Sjögren’s syndrome (SS) is a rheumatic disease requiring self-management which may be delivered through smartphones. When developing digital interventions it is important to review what is already available (market segmentation)1 to identify unique selling points and aid uptake and adoption. While there are no dedicated SS apps, many are publicly available for other rheumatic conditions2. Understanding user preferences for existing apps may help to design an engaging app for SS self-management.

Objectives: To explore apps targeting SS symptoms of dryness, sleep disturbances, fatigue and pain. To explore views of people with SS on these app features.

Methods: Apple Store apps were retrieved on 04 March 2019 using the following search terms: dry, dry eye, sleep, insomnia, fatigue, tiredness and pain. Included apps were English and in Medical or Health & Fitness genres. Exclusion criteria were; duplicates, additional external devices required and apps targeting alcohol reduction or children.

Included apps were grouped by symptom. App descriptions were open-coded to generate a thematic coding framework (i.e. full list of features) for each symptom which was then applied to all app descriptions. To obtain views of people with SS, several of the reviewed apps for each symptom covering the full list of features were given to 13 focus group participants to use in ‘think aloud’ sessions (n=4). Audio data was recorded, transcribed and deductively analysed using the framework to gather opinions relating to each feature.

Results: Of 914 apps retrieved, 542 were included. Features within apps targeting dryness (n=15) provided dry eye information, self-assessment and reminders to blink or look away from screens. Apps targeting sleep (n=310) included features to support sleep restriction, sleep hygiene, sleep tracking (sleep onset and wake up times, time in bed, overall sleep quality), relaxing sounds, guided meditation, sleep stories, snore recording and alarms. Fatigue apps (n=79) included features to detect current physical and mental fatigue levels, support pacing (i.e. track fatigue, label tasks as ‘high energy’, prioritise tasks), and self-massage instructions. Apps targeting pain (n=138) featured pain tracking (of severity, affected body areas), guided exercises, and mindfulness.

Dryness apps prompted participants to reflect on its impact on daily activities, but further dryness features were desired relating to: using a humidifier; eye drop reminders; and dryness tips for other body areas e.g. vaginal dryness. Sleep restriction features were believed to be irrelevant but viewing and selecting sleep hygiene tips to “try” were considered useful. Beyond entering sleep onset and wake up times, participants wished to track “when and why I woke up”, to understand night awakenings in relation to other symptoms. Fatigue detection features were felt to be more useful for those recently diagnosed, as experienced participants could easy identify when they were fatigued (“I don’t need an app to tell me!”). Participants valued pacing features but found them difficult to use. Daily pain tracking was considered demotivating, but useful for remembering and explaining issues to healthcare professionals. Participants believed that a dedicated app for SS would support self-management and raise SS awareness.

Conclusion: Existing apps targeting SS symptoms do not meet the needs of those with SS. App features should be tailored to SS by supporting dryness management in body areas beyond eyes, and night-awakenings. Pacing features must be easy to use. The ability to track pain should be optional and tracking prompts should be limited. Design considerations should be implemented alongside evidence-based behaviour change techniques to support self-management.

References: [1] Araújo-Soares, V. et al (2019). European Psychologist, 24(1), 7

[2] Knitza, J., et al (2019). JMIR mHealth and uHealth, 7(8), e14991

Acknowledgments: Versus Arthritis (Grant 22026)

Disclosure of Interests: None declared

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