Investigating age at onset in bipolar disorder

Bipolar disorder (BD) is a complex mental health disorder with a heterogenous clinical course, diagnostic delays, high relapse rates, and sub-optimal treatment outcomes. Age at onset (AAO) has been proposed as a useful specifier for defining more homogeneous BD subgroups that can inform clinical course and symptom profiles. This thesis aimed to investigate the utility of AAO as a clinical specifier by defining and validating AAO subgroups; identifying predictive factors for BD AAO; investigating the relationship between premorbid factors, AAO, and functional outcomes; and examining the association between AAO and mood instability. Using mixed methods across four experimental chapters, this thesis provides novel insights into the role of AAO in BD. Chapter 2 presents a systematic review of AAO distributions in BD and provides a recommended AAO definition. Chapter 3 uses machine learning approaches to explore predictive factors for BD AAO. Chapter 4 investigates the potential pathways between premorbid factors, BD AAO, and functional outcomes using prospective data. Chapter 5 examines the association between AAO and mood instability using longitudinal mood monitoring data. Findings reveal a trimodal distribution of AAO in BD, with distinct early-life risk factors, which may represent potential causal pathways to clinical outcomes. Additionally, mood instability is identified as a promising target for intervention in the clinical trajectory of BD. These results have important theoretical and practical implications, informing early intervention strategies and providing further evidence for the distinctiveness of AAO subgroups. The thesis concludes with a general discussion of the findings and implications for future research. Overall, this thesis provides valuable insights into the role of AAO in BD, highlights the importance of identifying more homogeneous subgroups to improve diagnosis and treatment outcomes, and underscores the need for continued research in this area

Impaired decisional impulsivity in pathological videogamers

Abstract Background Pathological gaming is an emerging and poorly understood problem. Impulsivity is commonly impaired in disorders of behavioural and substance addiction, hence we sought to systematically investigate the different subtypes of decisional and motor impulsivity in a well-defined pathological gaming cohort. Methods Fifty-two pathological gaming subjects and age-, gender- and IQ-matched healthy volunteers were tested on decisional impulsivity (Information Sampling Task testing reflection impulsivity and delay discounting questionnaire testing impulsive choice), and motor impulsivity (Stop Signal Task testing motor response inhibition, and the premature responding task). We used stringent diagnostic criteria highlighting functional impairment. Results In the Information Sampling Task, pathological gaming participants sampled less evidence prior to making a decision and scored fewer points compared with healthy volunteers. Gaming severity was also negatively correlated with evidence gathered and positively correlated with sampling error and points acquired. In the delay discounting task, pathological gamers made more impulsive choices, preferring smaller immediate over larger delayed rewards. Pathological gamers made more premature responses related to comorbid nicotine use. Greater number of hours played also correlated with a Motivational Index. Greater frequency of role playing games was associated with impaired motor response inhibition and strategy games with faster Go reaction time. Conclusions We show that pathological gaming is associated with impaired decisional impulsivity with negative consequences in task performance. Decisional impulsivity may be a potential target in therapeutic management

Data Analysis

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A systematic review of co-responder models of police mental health ‘street’ triage

Abstract Background Police mental health street triage is an increasingly common intervention when dealing with police incidents in which there is a suspected mental health component. We conducted a systematic review of street triage interventions with three aims. First, to identify papers reporting on models of co-response police mental health street triage. Second, to identify the characteristics of service users who come in to contact with these triage services. Third, to evaluate the effectiveness of co-response triage services. Methods We conducted a systematic review. We searched the following databases: Ovid MEDLINE, Embase, PsycINFO, EBSCO CINAHL, Scopus, Thompson Reuters Web of Science Core Collection, The Cochrane Library, ProQuest National Criminal Justice Reference Service Abstracts, ProQuest Dissertations & Theses, EThoS, and OpenGrey. We searched reference and citation lists. We also searched for other grey literature through Google, screening the first 100 PDFs of each of our search terms. We performed a narrative synthesis of our results. Results Our search identified 11,553 studies. After screening, 26 were eligible. Over two-thirds (69%) had been published within the last 3 years. We did not identify any randomised control trials. Results indicated that street triage might reduce the number of people taken to a place of safety under S136 of the Mental Health Act where that power exists, or reduce the use of police custody in other jurisdictions. Conclusions There remains a lack of evidence to evaluate the effectiveness of street triage and the characteristics, experience, and outcomes of service users. There is also wide variation in the implementation of the co-response model, with differences in hours of operation, staffing, and incident response

Correlation of severity measures with task outcomes.

<p>A. Correlation analyses of video gaming severity based on modified Yale Brown Obsessive Compulsive Scale scores adapted for gambling with Information Sampling Task outcome measures. B. Correlation analysis of video game hours played per week with Motivation Index from the premature responding task.</p

Information sampling task outcome measures.

<p>Mixed measures ANOVA of Information Sampling Task outcomes as a function of cost. Left: Boxes opened; Right: Points. Abbreviations: HV  =  healthy volunteers; VG  =  pathological gamers; YBOCS-G  =  modified Yale-Brown Obsessive Compulsive Score for gaming.</p

Delay discounting and information sampling task.

<p>K-value of the delay discounting task.</p

Videogame-playing measures.

<p>Abbreviations: SE  =  standard error; YBOCS-G  =  modified Yale Brown Obsessive Compulsive Score adapted for video gaming.</p

Outcome measures (data are mean +/− S.D).

<p>Abbreviations: HV  =  healthy volunteers; VG  =  pathological gamers; UPPS  =  UPPS Impulsive Behaviour Scale; BDI  =  Beck Depression Inventory-II; DDT  =  Delay Discounting Task; IST  =  Information Sampling Task.</p