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  • 1
    In: JMIR Research Protocols, JMIR Publications Inc., Vol. 11, No. 6 ( 2022-6-30), p. e38582-
    Abstract: US suicide rates have risen steadily in the past decade, and suicide risk is especially high in the months after discharge from inpatient psychiatric treatment. However, suicide research has lagged in examining dynamic within-person processes that contribute to risk over time among individuals known to be at high risk of suicide. Almost no research has examined how affective, cognitive, and physiological processes change over minutes, hours, or days to confer risk of suicidal behavior in daily life. Objective This protocol describes a longitudinal study designed to examine real-world changes in risk of suicide across multiple assessment domains. Specifically, the study involves following adults known to be at high risk of suicide after discharge from inpatient psychiatric care using self-report, interview, actigraphy, and behavioral methods to identify proximal contributors to suicidal thoughts and behaviors. First, we hypothesize that negative affective experiences, which are featured in most major suicide theories, will comprise a latent factor indicative of psychache (emotional pain), which will predict increases in suicidal thinking over time. Second, we hypothesize that poor inhibitory control in the context of negative affective stimuli, as well as emotion-related impulsivity, will predict the transition from suicidal thinking to suicidal behavior over time. Third, we hypothesize that short sleep duration will precede within-person increases in suicidal ideation as well as increased odds of suicidal behavior among those reporting suicidal thoughts. Methods The desired sample size is 130 adults with past-week suicidal thoughts or behaviors who are receiving inpatient psychiatric treatment. Participants will complete a battery of measures while on the inpatient unit to assess negative affective experiences, emotion-related impulsivity, inhibitory control, typical sleep patterns, and relevant covariates. After discharge from inpatient care, participants will complete 4 weeks of signal-contingent ecological momentary assessment surveys, as well as mobile behavioral measures of inhibitory control, while wearing an actigraphy device that will gather objective data on sleep. Participants will complete interviews regarding suicidal thoughts and behaviors at 4 and 8 weeks after discharge. Results The study was funded by the National Institutes of Health in November 2020. Recruitment began in April 2021. Data analysis will begin after completion of data collection. Conclusions This study will elucidate how affective, cognitive, and physiological risk factors contribute (or do not contribute) to within-person fluctuations in suicide risk in daily life, with important implications for extant theories of suicide. Of import, the examined risk factors are all modifiable; thus, the results will inform identification of key targets for just-in-time, flexible, personalized, digital interventions that can be used to decrease emotional distress and prevent suicide among those at highest risk. International Registered Report Identifier (IRRID) DERR1-10.2196/38582
    Type of Medium: Online Resource
    ISSN: 1929-0748
    Language: English
    Publisher: JMIR Publications Inc.
    Publication Date: 2022
    detail.hit.zdb_id: 2719222-2
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  • 2
    In: Sleep, Oxford University Press (OUP), Vol. 43, No. 4 ( 2020-04-15)
    Abstract: Sleep problems are common, serving as both a predictor and symptom of posttraumatic stress disorder (PTSD), with these bidirectional relationships well established in the literature. While both sleep phenotypes and PTSD are moderately heritable, there has been a paucity of investigation into potential genetic overlap between sleep and PTSD. Here, we estimate genetic correlations between multiple sleep phenotypes (including insomnia symptoms, sleep duration, daytime sleepiness, and chronotype) and PTSD, using results from the largest genome-wide association study (GWAS) to date of PTSD, as well as publicly available GWAS results for sleep phenotypes within UK Biobank data (23 variations, encompassing four main phenotypes). Methods Genetic correlations were estimated utilizing linkage disequilibrium score regression (LDSC), an approach that uses GWAS summary statistics to compute genetic correlations across traits, and Mendelian randomization (MR) analyses were conducted to follow up on significant correlations. Results Significant, moderate genetic correlations were found between insomnia symptoms (rg range 0.36–0.49), oversleeping (rg range 0.32–0.44), undersleeping (rg range 0.48–0.49), and PTSD. In contrast, there were mixed results for continuous sleep duration and daytime sleepiness phenotypes, and chronotype was not correlated with PTSD. MR analyses did not provide evidence for casual effects of sleep phenotypes on PTSD. Conclusion Sleep phenotypes, particularly insomnia symptoms and extremes of sleep duration, have shared genetic etiology with PTSD, but causal relationships were not identified. This highlights the importance of further investigation into the overlapping influences on these phenotypes as sample sizes increase and new methods to investigate directionality and causality become available.
    Type of Medium: Online Resource
    ISSN: 0161-8105 , 1550-9109
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2020
    detail.hit.zdb_id: 2056761-3
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  • 3
    In: Sleep Advances, Oxford University Press (OUP), Vol. 4, No. 1 ( 2023-01-01)
    Abstract: Although sleep disruption has emerged as a theoretically consistent and empirically supported suicide risk factor, the mechanistic pathways underlying the sleep–suicide link are less understood. This paper describes the methodology of a study intended to examine longitudinal mechanisms driving the link between sleep and suicide in Veterans at elevated suicide risk. Participants will be 140 Veterans hospitalized for suicide attempt or ideation with plan and intent or those identified through the Suicide Prevention Coordinator (SPC) office as being at acute risk. After study enrollment, actigraphy and ecological momentary assessment (EMA) data will be collected for 8 weeks, with follow-up assessments occurring at 2, 4, 6, 8, and 26 weeks. Participants respond to EMA questionnaires, derived from psychometrically validated assessments targeting emotional reactivity, emotion regulation, impulsivity, suicide risk, and sleep timing constructs, five times a day. First and last daily EMA target sleep parameters including sleep quantity, quality, timing, nightmares, and nocturnal awakenings. During follow-up assessments, participants will complete self-report assessments and interviews consistent with EMA constructs and the Iowa Gambling Task. The primary outcome for aim 1 is suicide ideation severity and for the primary outcome for aim 2 is suicide behavior. Findings from this study will improve our understanding of the dynamic interactions among sleep disturbance, emotion reactivity/regulation, and impulsivity to inform conceptual Veteran sleep–suicide mechanistic models. Improved models will be critical to optimizing the precision of suicide prevention efforts that aim to intervene and mitigate risk in Veteran populations, especially during a period of acute risk.
    Type of Medium: Online Resource
    ISSN: 2632-5012
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2023
    detail.hit.zdb_id: 3102566-3
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  • 4
    Online Resource
    Online Resource
    Oxford University Press (OUP) ; 2021
    In:  Translational Behavioral Medicine Vol. 11, No. 4 ( 2021-04-26), p. 993-1005
    In: Translational Behavioral Medicine, Oxford University Press (OUP), Vol. 11, No. 4 ( 2021-04-26), p. 993-1005
    Abstract: We developed a smartphone-based just-in-time adaptive intervention (JITAI), called OnTrack, that provides personalized intervention to prevent dietary lapses (i.e., nonadherence from the behavioral weight loss intervention diet). OnTrack utilizes ecological momentary assessment (EMA; repeated electronic surveys) for self-reporting lapse triggers, predicts lapses using machine learning, and provides brief intervention to prevent lapse. We have established preliminary feasibility, acceptability, and efficacy of OnTrack, but no study has examined our hypothesized mechanism of action: reduced lapse frequency will be associated with greater weight loss while using OnTrack. This secondary analysis investigated the association between lapse frequency and the weekly percentage of weight loss. Post hoc analyses evaluated the moderating effect of OnTrack engagement on this association. Participants (N = 121) with overweight/obesity (MBMI = 34.51; 84.3% female; 69.4% White) used OnTrack with a digital weight loss program for 10 weeks. Engagement with OnTrack (i.e., EMA completed and interventions accessed) was recorded automatically, participants self-reported dietary lapses via EMA, and weighed weekly using Bluetooth scales. Linear mixed models with a random effect of subject and fixed effect of time revealed a nonsignificant association between weekly lapses and the percentage of weight loss. Post hoc analyses revealed a statistically significant moderation effect of OnTrack engagement such that fewer EMA and interventions completed conferred the expected associations between lapses and weight loss. Lapses were not associated with weight loss in this study and one explanation may be the influence of engagement levels on this relationship. Future research should investigate the role of engagement in evaluating JITAIs.
    Type of Medium: Online Resource
    ISSN: 1869-6716 , 1613-9860
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2021
    detail.hit.zdb_id: 2586893-7
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  • 5
    In: BMC Nephrology, Springer Science and Business Media LLC, Vol. 15, No. 1 ( 2014-12)
    Type of Medium: Online Resource
    ISSN: 1471-2369
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2014
    detail.hit.zdb_id: 2041348-8
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