Smartphone-based ecological momentary assessment (EMA) in psychiatric patients and student controls: A real-world feasibility study

Porras-Segovia, Alejandro; Molina-Madueño, Rosa María; Berrouiguet, Sofian; López-Castromán, Jorge; Barrigón, María Luisa; Pérez-Rodríguez, María Sandra; Marco, José H.; Díaz-Oliván, Isaac; León, Santiago; Courtet, Philippe; Artés‐Rodríguez, Antonio; Baca‐García, Enrique

doi:10.1016/j.jad.2020.05.067

Cited by 57 publications

(51 citation statements)

References 47 publications

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“…Indeed, in this regard, projects are rapidly arising that exactly tailor to these needs, such as MAPS (Mobile Assessment for the Prediction of Suicide; https://grantome.com/grant/NIH/U01-MH116923-01), the Emma app [Ecological Momentary Mental Assessment; (31)], or the Smartcrisis Study [Smartphone Survey of Suicidal Risk; (32,33)]. Preliminary results from this research indeed suggests the feasibility (33,34) and potential utility of combining EMA with passive mobile sensing in predicting and intervening in suicidal crises (34).…”

Section: Introductionmentioning

confidence: 80%

SIMON: A Digital Protocol to Monitor and Predict Suicidal Ideation

et al. 2021

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Each year, more than 800,000 persons die by suicide, making it a leading cause of death worldwide. Recent innovations in information and communication technology may offer new opportunities in suicide prevention in individuals, hereby potentially reducing this number. In our project, we design digital indices based on both self-reports and passive mobile sensing and test their ability to predict suicidal ideation, a major predictor for suicide, and psychiatric hospital readmission in high-risk individuals: psychiatric patients after discharge who were admitted in the context of suicidal ideation or a suicidal attempt, or expressed suicidal ideations during their intake. Specifically, two smartphone applications -one for self-reports (SIMON-SELF) and one for passive mobile sensing (SIMON-SENSE)- are installed on participants' smartphones. SIMON-SELF uses a text-based chatbot, called Simon, to guide participants along the study protocol and to ask participants questions about suicidal ideation and relevant other psychological variables five times a day. These self-report data are collected for four consecutive weeks after study participants are discharged from the hospital. SIMON-SENSE collects behavioral variables -such as physical activity, location, and social connectedness- parallel to the first application. We aim to include 100 patients over 12 months to test whether (1) implementation of the digital protocol in such a high-risk population is feasible, and (2) if suicidal ideation and psychiatric hospital readmission can be predicted using a combination of psychological indices and passive sensor information. To this end, a predictive algorithm for suicidal ideation and psychiatric hospital readmission using various learning algorithms (e.g., random forest and support vector machines) and multilevel models will be constructed. Data collected on the basis of psychological theory and digital phenotyping may, in the future and based on our results, help reach vulnerable individuals early and provide links to just-in-time and cost-effective interventions or establish prompt mental health service contact. The current effort may thus lead to saving lives and significantly reduce economic impact by decreasing inpatient treatment and days lost to inability.

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Section: Introductionmentioning

confidence: 80%

SIMON: A Digital Protocol to Monitor and Predict Suicidal Ideation

et al. 2021

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“…However, in a prior EMA study by our research group we also found a predominance of women in the sample. 7 Another potential limitation is that we did not ask directly about suicide intent but employed the indirect measure ‘wish to die’. However, a recent systematic review and meta-analysis exploring passive suicide ideation found that it was highly similar to active suicide ideation and that it was strongly associated with suicide attempts.…”

Section: Discussionmentioning

confidence: 99%

“…The MEmind EMA questionnaire has shown good acceptability in preliminary studies. 7 As constant repetition of questions can place a significant burden on the user, we have incorporated a turn-over system for questions. Out of the pool of 32 questions participants were asked two to four random questions every day, at random times from 10.00 to 22.00 h. Figure 1 shows the variables explored in the EMA questionnaire and the frequency with which the questions were asked.…”

Section: Methodsmentioning

confidence: 99%

Patients at high risk of suicide before and during a COVID-19 lockdown: ecological momentary assessment study

et al. 2021

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The coronavirus disease 2019 (COVID-19) outbreak may have affected the mental health of patients at high risk of suicide. In this study we explored the wish to die and other suicide risk factors using smartphone-based ecological momentary assessment (EMA) in patients with a history of suicidal thoughts and behaviour. Contrary to our expectations we found a decrease in the wish to die during lockdown. This is consistent with previous studies showing that suicide rates decrease during periods of social emergency. Smartphone-based EMA can allow us to remotely assess patients and overcome the physical barriers imposed by lockdown.

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“…collider bias, ( 39, 40 )), whilst also decreasing measurement error (particularly compared to self-report, which may not be a very accurate measure of online activity, ( 41 )). Further, the sample for the main analysis was representative of the target population (85-87% recruitment rate from the outpatient clinic in parent studies, ( 42 )), and users were behaving naturalistically in the community, free from the influence of perceived experimenter demands. Although we found no evidence for differences in clinical or sociodemographic features between users included in the main analysis and mood sub-sample, the latter is likely to be affected by self-selection bias (see Results), therefore we focus our discussion on findings from the larger group.…”

Section: Discussionmentioning

confidence: 99%

Social media and smartphone app use predicts maintenance of physical activity during Covid-19 enforced isolation in psychiatric outpatients

Norbury

Liu

Campaña-Montes

et al. 2020

Preprint

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Public health professionals have raised concerns that the social and physical distancing measures implemented in response to the Covid-19 pandemic may negatively impact health in other areas, via both decreased physical activity and increased social isolation. Here, we investigated whether increased engagement with digital social tools may help mitigate effects of enforced isolation on physical activity and mood, in a naturalistic study of at-risk individuals. Passively sensed smartphone app use and actigraphy data, collected from a sample of psychiatric outpatients both before and during imposition of strict lockdown conditions (N=163), were analysed using Gaussian graphical models: a form of network analysis which gives insight into the predictive relationships between measures across timepoints. Within-individuals, we found evidence of a positive predictive path between digital social engagement, general smartphone use, and physical activity - selectively under lockdown conditions. Further, we observed a positive relationship between social media use and total daily steps across individuals during (but not prior to) lockdown. We interpret these findings in terms of individuals using these digital tools to harness online social support structures, which may help guard against negative effects of in-person social deprivation and other pandemic-related stress. Monitoring of these measures is low burden and unintrusive and therefore, given appropriate consent, could potentially help identify individuals who are failing to engage this mechanism, providing a route to early intervention in this and other vulnerable populations.

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Smartphone-based ecological momentary assessment (EMA) in psychiatric patients and student controls: A real-world feasibility study

Cited by 57 publications

References 47 publications

SIMON: A Digital Protocol to Monitor and Predict Suicidal Ideation

SIMON: A Digital Protocol to Monitor and Predict Suicidal Ideation

Patients at high risk of suicide before and during a COVID-19 lockdown: ecological momentary assessment study

Social media and smartphone app use predicts maintenance of physical activity during Covid-19 enforced isolation in psychiatric outpatients

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