ScreenLife Capture: An open-source and user-friendly framework for collecting screenomes from Android smartphones

Smartphone-based text obtained via passive sensing as it relates to direct suicide risk assessment

BACKGROUND

Recent research highlights the dynamics of suicide risk, resulting in a shift toward real-time methodologies, such as ecological momentary assessment (EMA), to improve suicide risk identification. However, EMA's reliance on active self-reporting introduces challenges, including participant burden and reduced response rates during crises. This study explores the potential of Screenomics-a passive digital phenotyping method that captures intensive, real-time smartphone screenshots-to detect suicide risk through text-based analysis.

METHOD

Seventy-nine participants with past-month suicidal ideation or behavior completed daily EMA prompts and provided smartphone data over 28 days, resulting in approximately 7.5 million screenshots. Text from screenshots was analyzed using a validated dictionary encompassing suicide-related and general risk language.

RESULTS

Results indicated significant associations between passive and active suicidal ideation and suicide planning with specific language patterns. Detection of words related to suicidal thoughts and general risk-related words strongly correlated with self-reported suicide risk, with distinct between- and within-person effects highlighting the dynamic nature of suicide risk factors.

CONCLUSIONS

This study demonstrates the feasibility of leveraging smartphone text data for real-time suicide risk detection, offering a scalable, low-burden alternative to traditional methods. Findings suggest that dynamic, individualized monitoring via passive data collection could enhance suicide prevention efforts by enabling timely, tailored interventions. Future research should refine language models and explore diverse populations to extend the generalizability of this innovative approach.

Consumers acceptability of using screen capture methods to capture marketing strategies on online food delivery platforms: a qualitative study

OBJECTIVE

The use of online food delivery (OFD) platforms is on the rise, and currently, there are no public health policies that regulate what and how food is sold on these platforms. Research quantifying and describing the marketing strategies on OFD platforms is limited. Our study aimed to test the consumers' acceptability of using two screen capture methods to record their food purchasing behaviour on OFD platforms and describe consumers' exposure to, and engagement with, marketing strategies on OFD platforms in real time.

DESIGN

Semi-structured online interviews on the consumer acceptability of using the screen capture methods were analysed using thematic analysis. Screen recordings of OFD orders were analysed using content analysis, guided by the marketing mix framework (i.e. product, placement, price and promotion).

SETTINGS

Victoria, Australia.

PARTICIPANTS

Twenty adults using the OFD service at least once a month were recruited.

RESULTS

The mean age of the sample was 28 years. 75 % were females, over 80 % had completed higher education and 20 % lived with children < 18 years of age. Over half used OFD service two to five times per week. Participants expressed that both smartphone's in-built screen recording function and third-party screen recording application are easy-to-use and time-efficient with high levels of user satisfaction. A range of marketing strategies were observed on the OFD platform. These included the presence of, and strategic placement of selected food products, price discounts and promotion strategies. Participants appeared to engage with marketing strategies through multiple clicks to reduce the total cost of their OFD order.

CONCLUSIONS

Our study demonstrates that screen recording is an acceptable method for capturing and assessing consumers' real-time exposure to, and engagement with, a range of marketing strategies on the OFD platform. Studies with larger samples are needed to substantiate our findings.

From dusk to dawn: examining how adolescents engage with digital media using objective measures of screen time in a repeated measures study

BACKGROUND

Although evening screen time is thought to impair subsequent sleep, current measures are limited to questionnaires which seem unlikely to accurately assess screen time in youth. Given the ubiquitous nature of digital devices, improving measurement of screen time is required before related health effects can be appropriately determined. The aim of this study was to objectively quantify screen time before sleep using video camera footage.

METHODS

This repeated-measures observational study in healthy adolescents (11-14 years) from Dunedin, New Zealand measured screen time on four evenings over one week in the home environment from March-December 2021. Wearable and stationary PatrolEyes video cameras captured screen time from two hours before bedtime until sleep and manually coded for device type (phone, tablet, laptop computer, desktop computer, handheld gaming console, gaming console, television and other) and screen activity (watching, listening, reading, educational/creative, browsing, communication, social media, video gaming, multitasking) using a reliable coding schedule (κ ≥ 0.8). Descriptive findings are reported.

FINDINGS

Among the 83 participants (mean 12.3 [SD 1.0] years, 42% female, 52% New Zealand European, 37% Māori [indigenous]), 82 used screens in the two hours before bed on 308 of 344 (90%) nights for a mean of 54.4 min (SD 25.5). Televisions (median 37 min, 56% of nights), phones (19 min, 64% nights), and multitasking using multiple devices (19 min, 48% nights) were most commonly used (> 75% of adolescents). Once in bed but before trying to sleep, 58% of adolescents engaged in screen time for 17 (26.3) minutes on 36% of nights. The most common screen activities were watching (32.5%), social media (26.5%) and communication (20.5%). Even after attempting sleep, 32.5% of participants used screens for 8.0 min (median) on 16% of nights, mostly listening on phones.

CONCLUSIONS

Objective video cameras offer detailed insight into evening screen habits, capturing frequency, content, and duration. Youth frequently engage with screens before bed and throughout the night on a range of activities, despite recommendations to restrict screen time prior to sleep.

TRIAL REGISTRATION

Australian New Zealand Clinical Trials Registry (anzctr.org.au), AACTRN12621000193875, Registered 23 February 2021, https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=380926&isReview=true .

Examining Passively Collected Smartphone-Based Data in the Days Prior to Psychiatric Hospitalization for a Suicidal Crisis: Comparative Case Analysis

BACKGROUND

Digital phenotyping has seen a broad increase in application across clinical research; however, little research has implemented passive assessment approaches for suicide risk detection. There is a significant potential for a novel form of digital phenotyping, termed screenomics, which captures smartphone activity via screenshots.

OBJECTIVE

This paper focuses on a comprehensive case review of 2 participants who reported past 1-month active suicidal ideation, detailing their passive (ie, obtained via screenomics screenshot capture) and active (ie, obtained via ecological momentary assessment [EMA]) risk profiles that culminated in suicidal crises and subsequent psychiatric hospitalizations. Through this analysis, we shed light on the timescale of risk processes as they unfold before hospitalization, as well as introduce the novel application of screenomics within the field of suicide research.

METHODS

To underscore the potential benefits of screenomics in comprehending suicide risk, the analysis concentrates on a specific type of data gleaned from screenshots-text-captured prior to hospitalization, alongside self-reported EMA responses. Following a comprehensive baseline assessment, participants completed an intensive time sampling period. During this period, screenshots were collected every 5 seconds while one's phone was in use for 35 days, and EMA data were collected 6 times a day for 28 days. In our analysis, we focus on the following: suicide-related content (obtained via screenshots and EMA), risk factors theoretically and empirically relevant to suicide risk (obtained via screenshots and EMA), and social content (obtained via screenshots).

RESULTS

Our analysis revealed several key findings. First, there was a notable decrease in EMA compliance during suicidal crises, with both participants completing fewer EMAs in the days prior to hospitalization. This contrasted with an overall increase in phone usage leading up to hospitalization, which was particularly marked by heightened social use. Screenomics also captured prominent precipitating factors in each instance of suicidal crisis that were not well detected via self-report, specifically physical pain and loneliness.

CONCLUSIONS

Our preliminary findings underscore the potential of passively collected data in understanding and predicting suicidal crises. The vast number of screenshots from each participant offers a granular look into their daily digital interactions, shedding light on novel risks not captured via self-report alone. When combined with EMA assessments, screenomics provides a more comprehensive view of an individual's psychological processes in the time leading up to a suicidal crisis.