Real-time fMRI neurofeedback and smartphone-based interventions to modulate mental functions

Our brains are constantly changing on a molecular level depending on the demands thrown at them by our environments, behavior, and thoughts. This neuronal plasticity allows us to voluntarily influence mental functions. Taking conscious control over mental functions goes potentially back millenia, but it was psychotherapy since the early 20th century which moulded this concept into a concrete form to target specific mental disorders. Mental disorders constitute a large burden on modern societies. Stress-related disorders like anxiety and depression particularly make up a large part of this burden and new ways to treat or prevent them are highly desirable, since traditional approaches are not equally helpful to every person affected. This might be because the infrastructure is not available where the person lives, their schedules and obligations or financial means do not enable them to seek help or they simply do not respond to traditional forms of treatment. Technological advances bring forth new potential approaches to modulate mental functions and allow using additional information to tailor an intervention better to an individual patient. The focus of this dissertation lies on two promising approaches to cognitively intervene and modulate mental functions: real-time functional magnetic resonance imaging neurofeedback (rtfMRInf) on one hand and smartphone-based interventions (SBIs) on the other. To investigate various aspects of both these methods in the context of stress and in relation to personalized interventions, we designed and conducted two experiments with a main rtfMRInf intervention, and also with ambulatory training of mental strategies, which participants accessed on their mobile phones. The four publication this thesis entails, are related to this topic as follows: The first publication focuses on rtfMRInf effects on the physiological stress response, exploring whether neurofeedback could reduce stress-related changes in brain activity and blood pressure. The second publication focuses on rtfMRInf effects on psychological measures related to the stress response, namely on arousal and mood, based on data from self-report by the participants. The third publication focuses on rtfMRInf methodology itself, looking at complex connectivity data between major neural networks. Finally, the fourth publication focuses on personalized prediction of intervention success of an SBI using data from previous training days

Polypharmacy and drug-drug interactions among older and younger male prisoners in Switzerland

The purpose of this paper is to determine the prevalence of polypharmacy and drug-drug interactions (DDIs) in older and younger prisoners, and compared if age group is associated with risks of polypharmacy and DDIs.; For 380 prisoners from Switzerland (190 were 49 years and younger; 190 were 50 years and older), data concerning their medication use were gathered. MediQ identified if interactions of two or more substances could lead to potentially adverse DDI. Data were analysed using descriptive statistics and generalised linear mixed models.; On average, older prisoners took 3.8 medications, while younger prisoners took 2.1 medications. Number of medications taken on one reference day was higher by a factor of 2.4 for older prisoners when compared to younger prisoners (; p; = 0.002). The odds of polypharmacy was significantly higher for older than for younger prisoners (>=5 medications: odds ratio = 5.52,; p; = 0.035). Age group analysis indicated that for potentially adverse DDI there was no significant difference (odds ratio = 0.94;; p; = 0.879). However, when controlling for the number of medication, the risk of adverse DDI was higher in younger than older prisoners, but the result was not significant.; Older prisoners are at a higher risk of polypharmacy but their risk for potentially adverse DDI is not significantly different from that of younger prisoners. Special clinical attention must be given to older prisoners who are at risk for polypharmacy. Careful medication management is also important for younger prisoners who are at risk of very complex drug therapies

Association between mental disorders and physical diseases in adolescents from a nationally representative cohort

Pediatric health care and research focus mostly on single morbidities, although the single-disease framework has been challenged. The main objective was to estimate associations between childhood mental disorders and physical diseases.; This study is based on weighted data (n = 6482) from the National Comorbidity Survey Replication Adolescent Supplement (age, 13-18 years). Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition lifetime mental disorders were assessed using the fully structured World Health Organization Composite International Diagnostic Interview, complemented by parent report. Lifetime medical conditions and doctor-diagnosed diseases were assessed by adolescent self-report.; Of 6469 participants, 2137 (35.33%) reported at least one mental disorder and one physical disease. The most substantial associations included those between affective disorders and diseases of the digestive system (odds ratio [OR] = 3.46, 95% confidence interval [CI] = 2.28-5.24), anxiety disorders and arthritis (OR = 2.27, CI = 1.34-3.85), anxiety disorders and heart diseases (OR = 2.41, CI = 1.56-3.73), anxiety disorders and diseases of the digestive system (OR = 2.18, CI = 1.35-3.53), and eating disorders and epilepsy/seizures (OR = 5.45, CI = 1.57-18.87). Sociodemographic factors did not account for the association between mental disorders and physical diseases.; Findings suggest that mental disorders and physical diseases often co-occur in childhood. This association is a major public health challenge, and the child health system needs additional strategies in patient-centered care, research, medical education, health policy, and economics to develop well-coordinated interdisciplinary approaches linking mental and physical care in children

Maternal psychopathology and offspring mental health service utilization in adolescents without mental disorders: a national representative survey

We investigated whether maternal psychopathology predicts offspring mental health service utilization in adolescents without mental disorders. We used weighted data (N = 2317) from NCS-A participants (age: 13-18 years) who did not meet DSM-IV criteria for any lifetime mental disorder. Adolescent mental disorders were assessed with the WHO CIDI. Maternal psychopathology was obtained by self-report. Adolescent mental health service use was assessed with the Service Assessment for Children and Adolescents. Substantial associations between maternal psychopathology and mental health service use in offspring without mental disorders were found between affective disorders and the mental health/medical specialty (hazard ratio (HR) = 2.49, 95% confidence interval (CI) = 1.60-3.90) and any service sector (HR = 2.14, CI = 1.45-3.16), anxiety disorders and any service sector (HR = 1.63, CI = 1.13-2.35), behavior disorders and the school (HR = 3.69, CI = 1.39-9.77) and any service sector (HR = 2.81, CI = 1.12-7.07), substance use disorders and the mental health/medical specialty (HR = 3.75, CI = 1.75-8.03), the school (HR = 3.17, CI = 1.43-7.02), and any service sector (HR = 3.66, CI = 2.00-6.70), and any mental disorder and the mental health/medical specialty (HR = 2.10, CI = 1.34-3.30) and any service sector (HR = 2.03, CI = 1.40-2.92). Results were comparable when restricting analyses to offspring with no indication of suicidality and no more than three life events during the past 12 months. The likelihood of service use was higher among offspring of mothers with mental disorders, compared to mothers without mental disorders. Considering maternal mental disorder status may help to identify subjects at risk of overtreatment

Comorbidity of Mental Disorders and Chronic Pain: Chronology of Onset in Adolescents of a National Representative Cohort

This study sought to estimate (1) the prevalence of the co-occurrence of, (2) the association between, and (3) the sequence of onset of chronic pain and mental disorders in adolescents. We used weighted data (N = 6,483) from the National Comorbidity Survey Replication Adolescent Supplement (participants' age, 13-18 years). Lifetime chronic pain was assessed by adolescent self-report; lifetime DSM-IV mental disorders were assessed by the WHO Composite International Diagnostic Interview, complemented by parent report. Among the participants in the study, 1,600 of 6,476 (25.93%) had experienced any type of chronic pain and any mental disorder in their lifetime. All types of pain were related to mental disorders. The most substantial temporal associations were those with onset of mental disorders preceding onset of chronic pain, including those between affective disorders and headaches and any chronic pain; between anxiety disorders and chronic back/neck pain, headaches, and any chronic pain; between behavior disorders and headaches and any chronic pain; and between any mental disorder and chronic back/neck pain, headaches, and any chronic pain.; Findings indicate that affective, anxiety, and behavior disorders are early risk factors of chronic pain, thereby highlighting the relevance of child mental disorders for pain medicine. To improve prevention and interventions for chronic pain, integrative care should be considered

Chronology of Onset of Mental Disorders and Physical Diseases in Mental-Physical Comorbidity - A National Representative Survey of Adolescents

The objective was to estimate temporal associations between mental disorders and physical diseases in adolescents with mental-physical comorbidities.; This article bases upon weighted data (N = 6483) from the National Comorbidity Survey Adolescent Supplement (participant age: 13-18 years), a nationally representative United States cohort. Onset of Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition lifetime mental disorders was assessed with the fully structured World Health Organization Composite International Diagnostic Interview, complemented by parent report. Onset of lifetime medical conditions and doctor-diagnosed diseases was assessed by self-report.; The most substantial temporal associations with onset of mental disorders preceding onset of physical diseases included those between affective disorders and arthritis (hazard ratio (HR) = 3.36, 95%-confidence interval (CI) = 1.95 to 5.77) and diseases of the digestive system (HR = 3.39, CI = 2.30 to 5.00), between anxiety disorders and skin diseases (HR = 1.53, CI = 1.21 to 1.94), and between substance use disorders and seasonal allergies (HR = 0.33, CI = 0.17 to 0.63). The most substantial temporal associations with physical diseases preceding mental disorders included those between heart diseases and anxiety disorders (HR = 1.89, CI = 1.41 to 2.52), epilepsy and eating disorders (HR = 6.27, CI = 1.58 to 24.96), and heart diseases and any mental disorder (HR = 1.39, CI = 1.11 to 1.74).; Findings suggest that mental disorders are antecedent risk factors of certain physical diseases in early life, but also vice versa. Our results expand the relevance of mental disorders beyond mental to physical health care, and vice versa, supporting the concept of a more integrated mental-physical health care approach, and open new starting points for early disease prevention and better treatments, with relevance for various medical disciplines

Discrete-time proportional hazard models for school mental health service utilization (time-varying) predicting out-of-school service use in different sectors.

<p>Abbreviations: CI, confidence interval; HR, hazard ratio.</p><p>Note: All analyses are based on samples for which information on mental disorders was available from both self and parent report (N = 6483). Due to missing information on service utilization, sizes of the completer samples are as follows: Mental health specialty sector: n = 6358, Medical specialty sector: n = 6326, Other out-of-school service sector: n = 6322, Any out-of-school service sector: n = 6307). To calculate the hazard ratios, periods without any event were dropped.</p

Adjusted discrete-time proportional hazard models estimating the temporal associations of physical diseases predicting subsequent mental disorders.

<p>Note: We based our analyses on completer sample sizes* of the total study sample (N = 6483), and adjusted for sociodemographic variables shown in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0165196#pone.0165196.t001" target="_blank">Table 1</a>. The strength of the associations (hazard ratios (HR) is illustrated by the circle diameter, given in the circles, with 95% confidence intervals, given below the circles). Blue color of the circle (and HRs provided in small standard type font) represent p≥0.05 in the total study sample; orange color of the circle and HRs provided in medium-sized bold type font represent p<0.05 in the total study sample and in less than two independent subsamples; red color of the circle and HRs provided in large bold and italic type font represent p<0.05 in the total study sample and in at least two independent subsamples. * Due to missing information on physical diseases from adolescent self-report, sizes of the completer samples are as follows: arthritis: n = 6473, seasonal allergy: n = 6475, skin disease: n = 6479, heart disease: n = 6481, asthma: n = 6477, diabetes/high blood sugar: n = 6481, disease of the digestive system: n = 6481, epilepsy or seizures: n = 6481, any physical disease: n = 6469.</p

Adjusted discrete-time proportional hazard models estimating the temporal associations of mental disorders predicting subsequent physical diseases.

<p>Note: We based our analyses on completer sample sizes* of the total study sample (N = 6483), and adjusted for sociodemographic variables shown in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0165196#pone.0165196.t001" target="_blank">Table 1</a>. The strength of the associations (hazard ratios (HR) is illustrated by the circle diameter, given in the circles, and 95% confidence intervals, given below the circles). Blue color of the circle (and HRs provided in small standard type font) represent p≥0.05 in the total study sample; orange color of the circle and HRs provided in medium-sized bold type font represent p<0.05 in the total study sample and in less than two independent subsamples; red color of the circle and HRs provided in large bold and italic type font represent p<0.05 in the total study sample and in at least two independent subsamples. * Due to missing information on physical diseases from adolescent self-report, sizes of the completer samples are as follows: arthritis: n = 6473, seasonal allergy: n = 6475, skin disease: n = 6479, heart disease: n = 6481, asthma: n = 6477, diabetes/high blood sugar: n = 6481, disease of the digestive system: n = 6481, epilepsy or seizures: n = 6481, any physical disease: n = 6469.</p

Sociodemographic characteristics of the study sample^* (<i>N</i> = 6483).

<p>Sociodemographic characteristics of the study sample^{<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0165196#t001fn002" target="_blank">*</a>} (<i>N</i> = 6483).</p