Identifying factors impacting missingness within smartphone-based research: Implications for intensive longitudinal studies of adolescent suicidal thoughts and behaviors.

Intensive longitudinal research-including experience sampling and smartphone sensor monitoring-has potential for identifying proximal risk factors for psychopathology, including suicidal thoughts and behaviors (STB). Yet, missing data can complicate analysis and interpretation. This study aimed to address whether clinical and study design factors are associated with missing data and whether missingness predicts changes in symptom severity or STB. Adolescents ages 13- to 18 years old (N = 179) reporting depressive, anxiety, and/or substance use disorders were enrolled; 65% reported current suicidal ideation and 29% indicated a past-year attempt. Passively acquired smartphone sensor data (e.g., global positioning system, accelerometer, and keyboard inputs), daily mood surveys, and weekly suicidal ideation surveys were collected during the 6-month study period using the effortless assessment research system smartphone app. First, acquisition of passive smartphone sensor data (with data on ∼80% of days across the whole sample) was strongly associated with survey data acquisition on the same day (∼44% of days). Second, STB and psychiatric symptoms were largely not associated with missing data. Rather, temporal features (e.g., length of time in study, weekends, and summer) explained more missingness of survey and passive smartphone sensor data. Last, within-participant changes in missing data over time neither followed nor predicted subsequent change in suicidal ideation and psychiatric symptoms. Findings indicate that considering technical and study design factors impacting missingness is critical and highlight several factors that should be addressed to maximize the validity of clinical interpretations in intensive longitudinal research. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

The effects of family support and smartphone-derived homestay on daily mood and depression among sexual and gender minority adolescents.

Sexual and gender minority (SGM) adolescents are at elevated risk for depression. This risk is especially pronounced among adolescents whose home environment is unsupportive or nonaffirming, as these adolescents may face familial rejection due to their identity. Therefore, it is critical to better understand the mechanisms underlying this risk by probing temporally sensitive associations between negative mood and time spent in potentially hostile home environments. The current study included adolescents (N = 141; 43% SGM; 13-18 years old), oversampled for depression history, who completed clinical interviews assessing lifetime psychiatric history and depression severity as well as self-report measures of social support. Participants also installed an app on their personal smartphones, which assessed their daily mood and geolocation-determined mobility patterns over a 6-month follow-up period. Over the 6-month follow-up period, SGM adolescents reported elevated depression severity and lower daily mood relative to non-SGM youth. Interestingly, SGM adolescents who reported low family support experienced lower daily mood than non-SGM adolescents, particularly on days when they spent more time at home. Current findings reinforce evidence for disparities in depression severity among SGM adolescents and highlight family support as a key factor. Specifically, more time spent in home environments with low family support was associated with worse mood among SGM adolescents. These results underscore the need for clinical interventions to support SGM youth, particularly interventions that focus on familial relationships and social support within the home environment. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Neurophysiological responses to emotional faces predict dynamic fluctuations in affect in adolescents.

The ability to accurately identify and interpret others' emotions is critical for social and emotional functioning during adolescence. Indeed, previous research has identified that laboratory-based indices of facial emotion recognition and engagement with emotional faces predict adolescent mood states. Whether socioemotional information processing relates to real-world affective dynamics using an ecologically sensitive approach, however, has rarely been assessed. In the present study, adolescents (N = 62; ages 13-18) completed a Facial Recognition Task, including happy, angry, and sad stimuli, while EEG data were acquired. Participants also provided ecological momentary assessment (EMA) data probing their current level of happiness, anger, and sadness for 1-week, resulting in indices of emotion (mean-level, inertia, instability). Analyses focused on relations between (1) accuracy for and (2) prolonged engagement with (LPP) emotional faces and EMA-reported emotions. Greater prolonged engagement with happy faces was related to less resistance to changes in happiness (i.e., less happiness inertia), whereas greater prolonged engagement with angry faces associated with more resistance to changes in anger (i.e., greater anger inertia). Results suggest that socioemotional processes captured by laboratory measures have real-world implications for adolescent affective states and highlight potentially actionable targets for novel treatment approaches (e.g., just-in-time interventions). Future studies should continue to assess relations among socioemotional informational processes and dynamic fluctuations in adolescent affective states.

Detecting adolescent depression through passive monitoring of linguistic markers in smartphone communication.

BACKGROUND: Cross sectional studies have identified linguistic correlates of major depressive disorder (MDD) in smartphone communication. However, it is unclear whether monitoring these linguistic characteristics can detect when an individual is experiencing MDD, which would facilitate timely intervention. METHODS: Approximately 1.2 million messages typed into smartphone social communication apps (e.g. texting, social media) were passively collected from 90 adolescents with a range of depression severity over a 12-month period. Sentiment (i.e. positive vs. negative valence of text), proportions of first-person singular pronouns (e.g. 'I'), and proportions of absolutist words (e.g. 'all') were computed for each message and converted to weekly aggregates temporally aligned with weekly MDD statuses obtained from retrospective interviews. Idiographic, multilevel logistic regression models tested whether within-person deviations in these linguistic features were associated with the probability of concurrently meeting threshold for MDD. RESULTS: Using more first-person singular pronouns in smartphone communication relative to one's own average was associated with higher odds of meeting threshold for MDD in the concurrent week (OR = 1.29; p = .007). Sentiment (OR = 1.07; p = .54) and use of absolutist words (OR = 0.99; p = .90) were not related to weekly MDD. CONCLUSIONS: Passively monitoring use of first-person singular pronouns in adolescents' smartphone communication may help detect MDD, providing novel opportunities for early intervention.

Capturing mood dynamics through adolescent smartphone social communication.

Most adolescents with depression remain undiagnosed and untreated-missed opportunities that are costly from both personal and public health perspectives. A promising approach to detecting adolescent depression in real-time and at a large scale is through their social communication on the smartphone (e.g., text messages, social media posts). Past research has shown that language from online social communication reliably indicates interindividual differences in depression. To move toward detecting the emergence of depression symptoms intraindividually, the present study tested whether sentiment (i.e., words connoting positive and negative affect) from smartphone social communication prospectively predicted daily mood fluctuations in 83 adolescents (Mage = 16.49, 73.5% female) with a wide range of depression severity. Participants completed daily mood ratings across a 90-day period, during which 354,278 messages were passively collected from social communication apps. Greater positive sentiment (i.e., more positive weighted composite valence score and a greater proportion of words expressing positive sentiment) predicted more positive next-day mood, controlling for previous-day mood. Moreover, greater proportions of positive and negative sentiment were, respectively, associated with lower anhedonia and greater dysphoria symptoms measured at baseline. Exploratory analyses of nonaffective linguistic features showed that greater use of social engagement words (e.g., friends and affiliation) and emojis (primarily consisting of hearts) predicted more positive changes in mood. Collectively, findings suggest that language from smartphone social communication can detect mood fluctuations in adolescents, laying the foundation for language-based tools to identify periods of heightened depression risk. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Feasibility and Safety of Taxane-PIPAC in Patients with Peritoneal Malignancies-a Retrospective Bi-institutional Study.

Taxanes have a favorable pharmacokinetic profile for intraperitoneal application. We report our initial experience with taxane-PIPAC (pressurized intraperitoneal chemotherapy) for unresectable peritoneal metastases from different primary sites in terms of safety, feasibility, response rate, and conversion to resectability. In this retrospective study, PIPAC was performed alone or in combination with systemic chemotherapy. Paclitaxel was used as a single agent, whereas docetaxel was used in combination with cisplatin-adriamycin or oxaliplatin-adriamycin. From December 2019 to December 2021, 47 patients underwent 82 PIPAC procedures (1 PIPAC in 55.3%, 2 in 29.7%, 3 in 14.8%). The most common primary sites were ovarian cancer (31.9%), gastric cancer (23.4%), and colorectal cancer (21.2%). Docetaxel-cisplatin-adriamycin was used in 33 (70.2%) patients, docetaxel-oxaliplatin-adriamycin in 12 (25.5%), and paclitaxel alone in 2 (4.2%) patients. Grade 1-2 complications were observed in 24 (51%) and grade 3-4 complications in 6 (12.7%) patients (8.5% of 82 PIPACs). 16/47 (34.0%) patients had a clinical response to PIPAC. The mean PCI was 25.9 ± 9.2 for the first PIPACs and 22.4 ± 9 for the subsequent PIPACs with an average reduction of 3.6 points [change in PCI ranged from - 14 to + 8]. The PRGS was 1/2 in 4/47 (8.5%) patients (19.0% patients with > 1 PIPAC). A reduction in ascites was observed in 35.4% presenting with ascites. Nine (19.1%) patients had conversion to operability leading to a subsequent cytoreductive surgery in 8 (17%) patients. PIPAC with docetaxel is feasible and safe. The role of PIPAC with both docetaxel and paclitaxel either alone or in combination with other drugs should be investigated in prospective studies.