Literature DB >> 31610996

Using ambulatory assessment to measure dynamic risk processes in affective disorders.

Jonathan P Stange1, Evan M Kleiman2, Robin J Mermelstein3, Timothy J Trull4.   

Abstract

BACKGROUND: Rapid advances in the capability and affordability of digital technology have begun to allow for the intensive monitoring of psychological and physiological processes associated with affective disorders in daily life. This technology may enable researchers to overcome some limitations of traditional methods for studying risk in affective disorders, which often (implicitly) assume that risk factors are distal and static - that they do not change over time. In contrast, ambulatory assessment (AA) is particularly suited to measure dynamic "real-world" processes and to detect fluctuations in proximal risk for outcomes of interest.
METHOD: We highlight key questions about proximal and distal risk for affective disorders that AA methods (with multilevel modeling, or fully-idiographic methods) allow researchers to evaluate.
RESULTS: Key questions include between-subject questions to understand who is at risk (e.g., are people with more affective instability at greater risk than others?) and within-subject questions to understand when risk is most acute among those who are at risk (e.g., does suicidal ideation increase when people show more sympathetic activation than usual?). We discuss practical study design and analytic strategy considerations for evaluating questions of risk in context, and the benefits and limitations of self-reported vs. passively-collected AA. LIMITATIONS: Measurements may only be as accurate as the observation period is representative of individuals' usual life contexts. Active measurement techniques are limited by the ability and willingness to self-report.
CONCLUSIONS: We conclude by discussing how monitoring proximal risk with AA may be leveraged for translation into personalized, real-time interventions to reduce risk.
Copyright © 2019 Elsevier B.V. All rights reserved.

Entities:  

Year:  2019        PMID: 31610996      PMCID: PMC7250154          DOI: 10.1016/j.jad.2019.08.060

Source DB:  PubMed          Journal:  J Affect Disord        ISSN: 0165-0327            Impact factor:   4.839


  101 in total

Review 1.  Risk factors for suicidal thoughts and behaviors: A meta-analysis of 50 years of research.

Authors:  Joseph C Franklin; Jessica D Ribeiro; Kathryn R Fox; Kate H Bentley; Evan M Kleiman; Xieyining Huang; Katherine M Musacchio; Adam C Jaroszewski; Bernard P Chang; Matthew K Nock
Journal:  Psychol Bull       Date:  2016-11-14       Impact factor: 17.737

2.  Let your fingers do the talking: Passive typing instability predicts future mood outcomes.

Authors:  Jonathan P Stange; John Zulueta; Scott A Langenecker; Kelly A Ryan; Andrea Piscitello; Jenna Duffecy; Melvin G McInnis; Pete Nelson; Olusola Ajilore; Alex Leow
Journal:  Bipolar Disord       Date:  2018-03-08       Impact factor: 6.744

3.  Reductions in the diurnal rigidity of anxiety predict treatment outcome in cognitive behavioral therapy for generalized anxiety disorder.

Authors:  Aaron J Fisher; Michelle G Newman
Journal:  Behav Res Ther       Date:  2016-02-27

Review 4.  Atypical reactivity of heart rate variability to stress and depression across development: Systematic review of the literature and directions for future research.

Authors:  Jessica L Hamilton; Lauren B Alloy
Journal:  Clin Psychol Rev       Date:  2016-09-20

Review 5.  Future directions in vulnerability to depression among youth: integrating risk factors and processes across multiple levels of analysis.

Authors:  Benjamin L Hankin
Journal:  J Clin Child Adolesc Psychol       Date:  2012-08-17

6.  INFLEXIBLE COGNITION PREDICTS FIRST ONSET OF MAJOR DEPRESSIVE EPISODES IN ADOLESCENCE.

Authors:  Jonathan P Stange; Samantha L Connolly; Taylor A Burke; Jessica L Hamilton; Elissa J Hamlat; Lyn Y Abramson; Lauren B Alloy
Journal:  Depress Anxiety       Date:  2016-04-19       Impact factor: 6.505

7.  Affective instability: measuring a core feature of borderline personality disorder with ecological momentary assessment.

Authors:  Timothy J Trull; Marika B Solhan; Sarah L Tragesser; Seungmin Jahng; Phillip K Wood; Thomas M Piasecki; David Watson
Journal:  J Abnorm Psychol       Date:  2008-08

8.  Digital phenotyping of suicidal thoughts.

Authors:  Evan M Kleiman; Brianna J Turner; Szymon Fedor; Eleanor E Beale; Rosalind W Picard; Jeff C Huffman; Matthew K Nock
Journal:  Depress Anxiety       Date:  2018-04-10       Impact factor: 6.505

9.  Biological risk factors for suicidal behaviors: a meta-analysis.

Authors:  B P Chang; J C Franklin; J D Ribeiro; K R Fox; K H Bentley; E M Kleiman; M K Nock
Journal:  Transl Psychiatry       Date:  2016-09-13       Impact factor: 6.222

10.  Predicting Mood Disturbance Severity with Mobile Phone Keystroke Metadata: A BiAffect Digital Phenotyping Study.

Authors:  John Zulueta; Andrea Piscitello; Mladen Rasic; Rebecca Easter; Pallavi Babu; Scott A Langenecker; Melvin McInnis; Olusola Ajilore; Peter C Nelson; Kelly Ryan; Alex Leow
Journal:  J Med Internet Res       Date:  2018-07-20       Impact factor: 5.428

View more
  7 in total

1.  Effects of mood and aging on keystroke dynamics metadata and their diurnal patterns in a large open-science sample: A BiAffect iOS study.

Authors:  Claudia Vesel; Homa Rashidisabet; John Zulueta; Jonathan P Stange; Jennifer Duffecy; Faraz Hussain; Andrea Piscitello; John Bark; Scott A Langenecker; Shannon Young; Erin Mounts; Larsson Omberg; Peter C Nelson; Raeanne C Moore; Dave Koziol; Keith Bourne; Casey C Bennett; Olusola Ajilore; Alexander P Demos; Alex Leow
Journal:  J Am Med Inform Assoc       Date:  2020-07-01       Impact factor: 4.497

2.  Inflexible autonomic responses to sadness predict habitual and real-world rumination: A multi-level, multi-wave study.

Authors:  Jonathan P Stange; Jessica L Hamilton; Robert Shepard; Jenny Wu; David M Fresco; Lauren B Alloy
Journal:  Biol Psychol       Date:  2020-05-08       Impact factor: 3.251

3.  Applying multiverse analysis to experience sampling data: Investigating whether preprocessing choices affect robustness of conclusions.

Authors:  Ginette Lafit; Glenn Kiekens; Jeroen Weermeijer; Martien Wampers; Gudrun Eisele; Zuzana Kasanova; Thomas Vaessen; Peter Kuppens; Inez Myin-Germeys
Journal:  Behav Res Methods       Date:  2022-02-09

4.  Decentering predicts attenuated perseverative thought and internalizing symptoms following stress exposure: A multi-level, multi-wave study.

Authors:  Jenny L Wu; Jessica L Hamilton; David M Fresco; Lauren B Alloy; Jonathan P Stange
Journal:  Behav Res Ther       Date:  2021-12-27

Review 5.  Reexamining Social Media and Socioemotional Well-Being Among Adolescents Through the Lens of the COVID-19 Pandemic: A Theoretical Review and Directions for Future Research.

Authors:  Jessica L Hamilton; Jacqueline Nesi; Sophia Choukas-Bradley
Journal:  Perspect Psychol Sci       Date:  2021-11-10

Review 6.  Emotion context insensitivity in depression: Toward an integrated and contextualized approach.

Authors:  Lauren M Bylsma
Journal:  Psychophysiology       Date:  2020-12-04       Impact factor: 4.016

7.  Opening the Black Box of Daily Life in Nonsuicidal Self-injury Research: With Great Opportunity Comes Great Responsibility.

Authors:  Glenn Kiekens; Kealagh Robinson; Ruth Tatnell; Olivia J Kirtley
Journal:  JMIR Ment Health       Date:  2021-11-19
  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.