Predictors of engagement with remote sensing technologies for symptom measurement in Major Depressive Disorder

BACKGROUND

Remote sensing for the measurement and management of long-term conditions such as Major Depressive Disorder (MDD) is becoming more prevalent. User-engagement is essential to yield any benefits. We tested three hypotheses examining associations between clinical characteristics, perceptions of remote sensing, and objective user engagement metrics.

METHODS

The Remote Assessment of Disease and Relapse - Major Depressive Disorder (RADAR-MDD) study is a multicentre longitudinal observational cohort study in people with recurrent MDD. Participants wore a FitBit and completed app-based assessments every two weeks for a median of 18 months. Multivariable random effects regression models pooling data across timepoints were used to examine associations between variables.

RESULTS

A total of 547 participants (87.8% of the total sample) were included in the current analysis. Higher levels of anxiety were associated with lower levels of perceived technology ease of use; increased functional disability was associated with small differences in perceptions of technology usefulness and usability. Participants who reported higher system ease of use, usefulness, and acceptability subsequently completed more app-based questionnaires and tended to wear their FitBit activity tracker for longer. All effect sizes were small and unlikely to be of practical significance.

LIMITATIONS

Symptoms of depression, anxiety, functional disability, and perceptions of system usability are measured at the same time. These therefore represent cross-sectional associations rather than predictions of future perceptions.

CONCLUSIONS

These findings suggest that perceived usability and actual use of remote measurement technologies in people with MDD are robust across differences in severity of depression, anxiety, and functional impairment.

Predictive capacity of prodromal symptoms in first-episode psychosis of recent onset

BACKGROUND

Both the nature and number of a wide range of prodromal symptoms have been related to the severity and type of psychopathology in the psychotic phase. However, at present there is an incomplete picture focused mainly on the positive pre-psychotic dimension.

AIM

To characterize the prodromal phase retrospectively, examining the number and nature of prodromal symptoms as well as their relationship with psychopathology at the onset of first-episode psychosis.

METHODS

Retrospective study of 79 patients experiencing a first-episode psychosis of less than 1 year from the onset of full-blown psychosis. All patients were evaluated with a comprehensive battery of instruments including socio-demographic and clinical questionnaire, IRAOS interview, PANSS, stressful life events scale (PERI) and WAIS/WISC (vocabulary subtest). Bivariate associations and multiple regression analysis were performed.

RESULTS

Regression models revealed that several prodromal dimensions of IRAOS (delusions, affect, language, behaviour and non-hallucinatory disturbances of perception) predicted the onset of psychosis, with positive (22.4% of the variance) and disorganized (25.6% of the variance) dimensions being the most widely explained.

CONCLUSION

In addition to attenuated positive symptoms, other symptoms such as affective, behavioural and language disturbances should also be considered in the definitions criteria of at-high-risk people.