2018
DOI: 10.2196/mental.9539
|View full text |Cite
|
Sign up to set email alerts
|

Patient Willingness to Consent to Mobile Phone Data Collection for Mental Health Apps: Structured Questionnaire

Abstract: BackgroundIt has become possible to use data from a patient’s mobile phone as an adjunct or alternative to the traditional self-report and interview methods of symptom assessment in psychiatry. Mobile data–based assessment is possible because of the large amounts of diverse information available from a modern mobile phone, including geolocation, screen activity, physical motion, and communication activity. This data may offer much more fine-grained insight into mental state than traditional methods, and so we … Show more

Help me understand this report
View preprint versions

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

2
52
1

Year Published

2019
2019
2022
2022

Publication Types

Select...
6
1
1

Relationship

0
8

Authors

Journals

citations
Cited by 62 publications
(55 citation statements)
references
References 28 publications
2
52
1
Order By: Relevance
“…In addition to the hardware and software concerns, there are special concerns with passive monitoring related to stigma and privacy (Bauer et al 2017). Of patients interested in apps, a significant minority does not want to be monitored and tracked or provide private sensor-based data (Thornton and Kay-Lambkin 2018;Klasnja et al 2009;Torous et al 2018;Ben-Zeev et al 2016;Di Matteo et al 2018;Hendrikoff et al 2019). In a study of mobile sensing of 126 adults with depression recruited from the general public in Switzerland, half uninstalled the app within 2 weeks (Wahle et al 2016).…”
Section: Passive Monitoringmentioning
confidence: 99%
“…In addition to the hardware and software concerns, there are special concerns with passive monitoring related to stigma and privacy (Bauer et al 2017). Of patients interested in apps, a significant minority does not want to be monitored and tracked or provide private sensor-based data (Thornton and Kay-Lambkin 2018;Klasnja et al 2009;Torous et al 2018;Ben-Zeev et al 2016;Di Matteo et al 2018;Hendrikoff et al 2019). In a study of mobile sensing of 126 adults with depression recruited from the general public in Switzerland, half uninstalled the app within 2 weeks (Wahle et al 2016).…”
Section: Passive Monitoringmentioning
confidence: 99%
“…In addition, there was some uncertainty regarding how this level of data access by clinicians could impact the patient and their behaviours. Although patients in general are open to sharing their self-assessment data with clinicians via an app [47,48], some authors consider clinicians' ability to scrutinize their patients' actions and communications on a very fine-grained level to be unnecessarily intrusive [51]. Pain app studies involving older people who use the data sharing feature of the app areis needed to better understand this area.…”
Section: Discussionmentioning
confidence: 99%
“…Each card contained a different 'information item' (see Table 2). The choice of items was based on the analysis of previous works about data sensitivity and willingness to share [12,14,37,47,61,83,86,121,123,141,146], data collected in the different platforms, and mobile sensing frameworks for behavioural monitoring [23]. Three medical doctors were consulted to confirm that the card set contained only data relevant to health research.…”
Section: Methodsmentioning
confidence: 99%
“…Some factors can affect the intensity of privacy concerns. Previous research has found that more sensitive data types are disclosed less often [86,123], such as audio recordings [37], browser history [14], message/phone logs and social media activity [47], camera pictures [121], financial information [146], home address [83], feelings of loneliness [61], sexually transmitted diseases [146], toilet use [12], and any health-related data in general [141]. Privacy is also perceived differently across individuals [22].…”
Section: Privacymentioning
confidence: 99%