Selected Research Publications

NeuroFlow is committed to delivering evidence-based behavioral health support based on rigorous scientific research. Here are the latest studies inspiring and fueling our mission.

Summary: NeuroFlow analyzed the impact of Natural Language Processing (NLP) technology on identifying individuals experiencing suicidal ideation. NLP analyzes free text entries within the NeuroFlow platform and flags individuals with an urgent alert if the text indicates suicidal ideation. In this analysis, 425 people were flagged for suicidal ideation through NLP. A large portion of these individuals would not have been identified through a PHQ-9 assessment during the same period because they either did not complete the assessment or took the assessment and screened negative for suicidal ideation.

Stats at a glance:

  • Of all users identified by our NLP protocol, 81% had completed a PHQ-9 assessment. However, roughly half of those users did not endorse thoughts of self-harm on the PHQ-9, underscoring the potential for NLP to surface risk that may elude traditional screening approaches.
  • The remaining 19% did not complete a PHQ-9 at all – missing an opportunity for detection.
  • In conclusion, more than half of these users (58%) may not have been identified as having suicidal ideation without NLP.

Summary: Findings from this study support use of a technology-enabled behavioral health tool to decrease emergency department use and highlight the importance of measurement-based care. Future research will be key to enhancing behavioral health technology and integration to further improve patient outcomes and reduce emergency department utilization.

Stats at a glance:

  • 34% decrease in ED visits for patients using NeuroFlow
  • 17.3% of patients reported improvements in PHQ-9 scores

Summary: The use of measurement-based care in integrated care settings offers a means to address existing treatment gaps for individuals with mental health disorders seeking care. Findings from this study demonstrate the large-scale feasibility (n > 4,000) of remotely collecting mental health data via a mobile technology platform and that changes in depression and anxiety symptoms, including suicidal ideation, can be reliably assessed. Findings further revealed that digitally-enabled measurement-based care (MBC) supported patients experiencing moderate, moderately severe, or severe depression or anxiety in achieving clinically and statistically significant symptom improvements.

Stats at a glance:

  • Individuals with suicidal ideation (SI) and an initial clinical PHQ-9 score (≥10) saw a decrease in SI from 25% to 15% at eight weeks, as measured by PHQ-9 (p < 0.001)
  • Both GAD-7 and PHQ-9 mean scores decreased by over 4 points in eight weeks (p < 0.001)
  • Of those who continued to engage with mHealth supported MBC, PHQ-9 and GAD-7 scores reached subclinical values (9.03 and 7.48, respectively)

See related research: Counselor and student perceptions of an mHealth technology platform used in a school counseling setting

Summary: The ability to risk stratify a patient population to inform population level interventions is key to efficient, high quality, measurement-based care. Current methodologies focus predominantly on validated assessments alone, without consideration of other qualitative measures of symptom impact on functionality. This study details the development of the NeuroFlow Severity Score (NFSS) and evaluates its utility for population level risk stratification when compared to the Personal Health Questionnaire-9 (PHQ-9) and Generalized Anxiety Disorder-7 (GAD-7), and expert clinician review.  Based on over 35,000 NeuroFlow users, the NFSS demonstrates the simultaneous credibility and clinical validity of a comprehensive single risk index while reducing effort and burden for clinicians. 

Stats at a glance

  • A strong correlation between NFSS and PHQ-9 (r = 0.74, p < 0.001) and GAD-7 (r = 0.80, p < 0.001)
  • A strong positive correlation between the NFSS and expert panel clinical assessments (r = 0.80-0.84, p < 0.001)
  • The inclusion of self reported and engagement metrics provides evidence of the utility of the NFSS in identifying at-risk individuals otherwise unidentified by the PHQ-9 alone

Be sure to check this page regularly for our latest updates regarding our ongoing research efforts!

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