Personality types revisited–a literature-informed and data-driven approach to an integration of prototypical and dimensional constructs of personality description

A new algorithmic approach to personality prototyping based on Big Five traits was applied to a large representative and longitudinal German dataset (N = 22,820) including behavior, personality and health correlates. We applied three different clustering techniques, latent profile analysis, the k-means method and spectral clustering algorithms. The resulting cluster centers, i.e. the personality prototypes, were evaluated using a large number of internal and external validity criteria including health, locus of control, self-esteem, impulsivity, risk-taking and wellbeing. The best-fitting prototypical personality profiles were labeled according to their Euclidean distances to averaged personality type profiles identified in a review of previous studies on personality types. This procedure yielded a five-cluster solution: resilient, overcontroller, undercontroller, reserved and vulnerable-resilient. Reliability and construct validity could be confirmed. We discuss wether personality types could comprise a bridge between personality and clinical psychology as well as between developmental psychology and resilience research

Effects of a Self-Guided Transdiagnostic Smartphone App on Patient Empowerment and Mental Health: Randomized Controlled Trial

Background: Mental disorders impact both individuals and health systems. Symptoms and syndromes often remain undetected and untreated, resulting in chronification. Besides limited health care resources, within-person barriers such as the lack of trust in professionals, the fear of stigmatization, or the desire to cope with problems without professional help contribute to the treatment gap. Self-guided mental health apps may support treatment seeking by reducing within-person barriers and facilitating mental health literacy. Digital mental health interventions may also improve mental health related self-management skills and contribute to symptom reduction and the improvement of quality of life. Objective: This study aims to investigate the effects of a self-guided transdiagnostic app for mental health on help seeking, reduced stigma, mental health literacy, self-management skills, mental health symptoms, and quality of life using a randomized controlled design. Methods: Overall, 1045 participants (recruited via open, blinded, and web-based recruitment) with mild to moderate depression or anxiety-, sleep-, eating-, or somatization-related psychopathology were randomized to receive either access to a self-guided transdiagnostic mental health app (MindDoc) in addition to care as usual or care as usual only. The core features of the app were regular self-monitoring, automated feedback, and psychological courses and exercises. The coprimary outcomes were mental health literacy, mental health–related patient empowerment and self-management skills (MHPSS), attitudes toward help seeking, and actual mental health service use. The secondary outcomes were psychopathological symptom burden and quality of life. Data were collected at baseline and 8 weeks and 6 months after randomization. Treatment effects were investigated using analyses of covariance, including baseline variables as predictors and applying multiple imputation. Results: We found small but robust between-group effects for MHPSS (Cohen d=0.29), symptoms burden (Cohen d=0.28), and quality of life (Cohen d=0.19) 8 weeks after randomization. The effects on MHPSS were maintained at follow-up. Follow-up assessments also showed robust effects on mental health literacy and preliminary evidence for the improvement of help seeking. Predictors of attrition were lower age and higher personality dysfunction. Among the non-attritors, predictors for deterioration were less outpatient treatment and higher initial symptom severity. Conclusions: A self-guided transdiagnostic mental health app can contribute to lasting improvements in patient empowerment. Symptoms of common mental disorders and quality of life improved faster in the intervention group than in the control group. Therefore, such interventions may support individuals with symptoms of 1 or more internalizing disorders, develop health-centered coping skills, prevent chronification, and accelerate symptom improvement. Although the effects for individual users are small and predictors of attrition and deterioration need to be investigated further, the potential public health impact of a self-guided intervention can be large, given its high scalability. Trial Registration: German Clinical Trials Register DRKS00022531; https://drks.de/search/de/trial/DRKS00022531 JMIR Ment Health 2023;10:e4506

Improving Mild to Moderate Depression With an App-Based Self-Guided Intervention: Protocol for a Randomized Controlled Trial

Background: Depression is one of the most prevalent mental disorders and frequently co-occurs with other mental disorders. Despite the high direct and indirect costs to both individuals and society, more than 80% of those diagnosed with depression remain with their primary care physician and do not receive specialized treatment. Self-guided digital interventions have been shown to improve depression and, due to their scalability, have a large potential public health impact. Current digital interventions often focus on specific disorders, while recent research suggests that transdiagnostic approaches are more suitable. Objective: This paper presents the protocol for a study that aims to assess the efficacy of a self-guided transdiagnostic app-based self-management intervention in patients with mild or moderate depression with and without comorbid mental disorders. Specifically, we are investigating the impact of the intervention on symptoms of depression, quality of life, anxiety symptoms, and mental health–related patient empowerment and self-management skills. Methods: The intervention under investigation, MindDoc with Prescription, is a self-guided digital intervention aimed at supporting individuals with mild to moderate mental disorders from the internalizing spectrum, including depression. The app can be used as a low-threshold psychosocial intervention. Up to 570 adult patients will be randomized to either receive the intervention in addition to care as usual or only care as usual. We are including adults with a permanent residency in Germany and mild or moderate depression according to International Classification of Diseases, 10th Revision, criteria (F32.0, F32.1, F33.0, and F33.1). Clinical interviews will be conducted to confirm the diagnosis. Data will be collected at baseline as well as 8 weeks and 6 months after randomization. The primary outcome will be depression symptom severity after 8 weeks. Secondary outcomes will be quality of life, anxiety symptom severity, and patient empowerment and self-management behaviors. Data will be analyzed using multiple imputations, using the intention-to-treat principle, while sensitivity analyses will be based on additional imputation strategies and a per-protocol analysis. Results: Recruitment for the trial started on February 7, 2023, and the first participant was randomized on February 14, 2023. As of September 5, 2023, 275 participants have been included in the trial and 176 have provided the primary outcome. The rate of missing values in the primary outcome is approximately 20%. Conclusions: Data from this efficacy trial will be used to establish whether access to the intervention is associated with an improvement in depression symptoms in individuals diagnosed with mild or moderate depression. The study will contribute to expanding the evidence base on transdiagnostic digital interventions. Trial Registration: German Registry of Clinical Trials DRKS00030852; https://drks.de/search/de/trial/DRKS0003085

Screening accuracy of a 14-day smartphone ambulatory assessment of depression symptoms and mood dynamics in a general population sample: Comparison with the PHQ-9 depression screening

Introduction Major depression affects over 300 million people worldwide, but cases are often detected late or remain undetected. This increases the risk of symptom deterioration and chronification. Consequently, there is a high demand for low threshold but clinically sound approaches to depression detection. Recent studies show a great willingness among users of mobile health apps to assess daily depression symptoms. In this pilot study, we present a provisional validation of the depression screening app Moodpath. The app offers a 14-day ambulatory assessment (AA) of depression symptoms based on the ICD-10 criteria as well as ecologically momentary mood ratings that allow the study of short-term mood dynamics. Materials and methods N = 113 Moodpath users were selected through consecutive sampling and filled out the Patient Health Questionnaire (PHQ-9) after completing 14 days of AA with 3 question blocks (morning, midday, and evening) per day. The psychometric properties (sensitivity, specificity, accuracy) of the ambulatory Moodpath screening were assessed based on the retrospective PHQ-9 screening result. In addition, several indicators of mood dynamics (e.g. average, inertia, instability), were calculated and investigated for their individual and incremental predictive value using regression models. Results We found a strong linear relationship between the PHQ-9 score and the AA Moodpath depression score (r = .76, p < .001). The app-based screening demonstrated a high sensitivity (.879) and acceptable specificity (.745). Different indicators of mood dynamics covered substantial amounts of PHQ-9 variance, depending on the number of days with mood data that were included in the analyses. Discussion AA and PHQ-9 shared a large proportion of variance but may not measure exactly the same construct. This may be due to the differences in the underlying diagnostic systems or due to differences in momentary and retrospective assessments. Further validation through structured clinical interviews is indicated. The results suggest that ambulatory assessed mood indicators are a promising addition to multimodal depression screening tools. Improving app-based AA screenings requires adapted screening algorithms and corresponding methods for the analysis of dynamic processes over time

CAPACIDADE DE LIBERAÇÃO, DISPONIBILIDADE E RENDIMENTO DE GRÃOS, COM DIFERENTES FONTES DE FÓSFORO EM SUCESSÃO DE CULTURAS

Existem vários problemas relacionados ao manejo da adubação fosfatada no solo, desde os mais básicos até aqueles de ajuste fino. Sabendo que o fósforo é um dos elementos mais importantes para a nutrição das plantas e também o que possui uma série de problemas sobre sua disponibilidade no solo, torna-se importante descobrir, com estudos, a eficiência de diferentes tipos de fertilizantes fosfatos, em especial dos novos produtos introduzidos no mercado e que supostamente poderiam ser melhor aproveitados pelas culturas, em relação aos produtos já existentes no mercado. Esse trabalho foi realizado em duas etapas, sendo a primeira realizada em uma propriedade de cultivo de grãos, localizada na comunidade de Linha São Vicente, interior do Município de Guaraciaba, SC; o solo da propriedade é classificado como um Latossolo Vermelho com declividade média de 3% e apresenta um teor de P baixo. Nessa etapa, utilizou-se o método experimental de blocos ao acaso, tendo três parcelas e quatro tratamentos. Como o objetivo foi de avaliar a resposta de diferentes tipos de fertilizantes fosfatados no quesito produção e rendimento, elevou-se cada um destes ao nível crítico de P exigido pelo solo, considerando a concentração de cada fertilizante utilizado. A segunda etapa do projeto foi realizada na Linha Derrubada Alta, interior do Município de São Jose do Cedro, SC, sendo realizada em casa de vegetação (estufa), e as características do solo utilizado para a realização do trabalho são semelhantes às da primeira área, com teores de P baixo a muito baixo e K baixo, tendo alto teor de acidez no solo, e observa-se que nas duas etapas a correção do nível do P no solo foi elevada a nível critico. O objetivo na segunda etapa do trabalho foi a avaliação da resposta dos tratamentos em solo ácido e solo corrigido, avaliando o desenvolvimento, massa verde e seca da parte vegetativa e radicular. Para a avaliação, utilizou-se a cultura da Aveia Branca cultivar Comum, o método experimental utilizado foi delineamento inteiramente casualizado em vasos com cinco repetições e seis tratamentos. Em ambas as etapas não se observaram grandes diferenças significativas aos tratamentos, sendo apenas observado na primeira etapa a campo um aumento na quantidade de MV da aveia, o que não foi observado em sua MS; e na segunda, observou-se um aumento na MS com o tratamento THOP-PHOS, sendo utilizado o dobro da dose. Como não existem muitos trabalhos a respeito da eficiência desse fertilizante, ainda não se pode confirmar o resultado do complexo natural exclusivo CSP-PI que protege o elemento fósforo do THOP-PHÓS da fixação com o alumínio, o ferro e o cálcio no solo.Palavras-chave: Milho. THOP-PHOS. Fósforo

Impaired Personality Functioning in Children and Adolescents Assessed with the LoPF-Q 6-18 PR in Parent-Report and Convergence with Maladaptive Personality Traits and Personality Structure in School and Clinic Samples

To investigate if the Personality Disorder (PD) severity concept (Criterion A) of the ICD-11 and DSM-5 AMPD is applicable to children and adolescents, following the ICD-11 lifespan perspective of mental disorders, age-specific and informant-adapted assessment tools are needed. The LoPF-Q 6-18 PR (Levels of Personality Functioning Questionnaire Parent Rating) was developed to assess Impaired Personality Functioning (IPF) in children aged 6–18 in parent-reported form. It is based on the established self-report questionnaire LoPF-Q 12-18. Psychometric properties were investigated in a German-speaking clinical and school sample containing 599 subjects. The final 36-item version of LoPF-Q 6-18 PR showed good scale reliabilities with 0.96 for the total scale IPF and 0.90-0.87 for the domain scales Identity, Self-direction, Empathy, and Intimacy/Attachment and an acceptable model fit in a hierarchical CFA with CFI = 0.936, RMSEA = 0.078, and SRMR = 0.068. The total score discriminated significantly and with large effect sizes between the school population and (a) adolescent PD patients (d = 2.7 standard deviations) and (b) the younger patients (6–11-year-olds) with internalizing and externalizing disorders (d = 2.2 standard deviations). Informant agreement between parent and self-report was good at 0.47. Good construct validity can be assumed given sound covariation with related measures of psychopathology (CBCL 4-18, STiP-5.1, OPD-CA2-SQ PR) and maladaptive traits (PID5BF+ M CA IRF) in line with theory and matching the result patterns obtained in older samples in self-report. The results suggest that parent-reported assessments of IPF and maladaptive traits are equivalent to self-reported measures for Criterion A and B. Assessing IPF as early as age six might be a valuable step to foster early detection of PD, or maladaptive personality development, respectively individuals at risk

Impaired Personality Functioning in Children and Adolescents Assessed with the LoPF-Q 6-18 PR in Parent-Report and Convergence with Maladaptive Personality Traits and Personality Structure in School and Clinic Samples

To investigate if the Personality Disorder (PD) severity concept (Criterion A) of the ICD-11 and DSM-5 AMPD is applicable to children and adolescents, following the ICD-11 lifespan perspective of mental disorders, age-specific and informant-adapted assessment tools are needed. The LoPF-Q 6-18 PR (Levels of Personality Functioning Questionnaire Parent Rating) was developed to assess Impaired Personality Functioning (IPF) in children aged 6–18 in parent-reported form. It is based on the established self-report questionnaire LoPF-Q 12-18. Psychometric properties were investigated in a German-speaking clinical and school sample containing 599 subjects. The final 36-item version of LoPF-Q 6-18 PR showed good scale reliabilities with 0.96 for the total scale IPF and 0.90-0.87 for the domain scales Identity, Self-direction, Empathy, and Intimacy/Attachment and an acceptable model fit in a hierarchical CFA with CFI = 0.936, RMSEA = 0.078, and SRMR = 0.068. The total score discriminated significantly and with large effect sizes between the school population and (a) adolescent PD patients (d = 2.7 standard deviations) and (b) the younger patients (6–11-year-olds) with internalizing and externalizing disorders (d = 2.2 standard deviations). Informant agreement between parent and self-report was good at 0.47. Good construct validity can be assumed given sound covariation with related measures of psychopathology (CBCL 4-18, STiP-5.1, OPD-CA2-SQ PR) and maladaptive traits (PID5BF+ M CA IRF) in line with theory and matching the result patterns obtained in older samples in self-report. The results suggest that parent-reported assessments of IPF and maladaptive traits are equivalent to self-reported measures for Criterion A and B. Assessing IPF as early as age six might be a valuable step to foster early detection of PD, or maladaptive personality development, respectively individuals at risk

Adverse childhood experiences and personality functioning interact substantially in predicting depression, anxiety, and somatization

Etiological theories on the development of psychopathology often incorporate adverse childhood experiences (ACE) as an important contributing factor. Recent studies suggest personality functioning (PF; i.e., stability of the self and interpersonal relationships) as an important transdiagnostic construct that could be useful in better understanding when persons with ACE do (not) develop psychopathological symptoms. A representative sample of N = 2363 was assessed by questionnaires on ACE, PF (Level of Personality Functioning Scale—Brief Form 2.0), and current symptoms of depression, anxiety, and somatization (Brief Symptom Inventory 18). The interaction between ACE and PF on symptoms was investigated using multiple group models and Bayesian structural equation modeling. ACE were positively associated with psychopathology and PF impairments. The interaction effect between ACE and PF explained incremental variance in current symptoms, ranging from 26% for somatization to 49% for depression with the complete model explaining up to 91% of the latent variance in psychopathology. Our findings indicate a diathesis–stress model with PF as a resource or resilience that may buffer against the development of symptoms in the face of adversity. Treatments of depression and anxiety targeting self and interpersonal functioning therefore may lead to improvements in resilience and relapse prevention. [Correction added on 15 March 2023, after first online publication: Level of Personality Functioning Scale—Brief Form has been replaced to Level of Personality Functioning Scale—Brief Form 2.0

Towards Sub-Quadratic Diameter Computation in Geometric Intersection Graphs

We initiate the study of diameter computation in geometric intersection graphs from the fine-grained complexity perspective. A geometric intersection graph is a graph whose vertices correspond to some shapes in d-dimensional Euclidean space, such as balls, segments, or hypercubes, and whose edges correspond to pairs of intersecting shapes. The diameter of a graph is the largest distance realized by a pair of vertices in the graph. Computing the diameter in near-quadratic time is possible in several classes of intersection graphs [Chan and Skrepetos 2019], but it is not at all clear if these algorithms are optimal, especially since in the related class of planar graphs the diameter can be computed in ̃(n^{5/3}) time [Cabello 2019, Gawrychowski et al. 2021]. In this work we (conditionally) rule out sub-quadratic algorithms in several classes of intersection graphs, i.e., algorithms of running time $(n^{2-δ})$ for some $δ > 0$. In particular, there are no sub-quadratic algorithms already for fat objects in small dimensions: unit balls in $ℝ^3$ or congruent equilateral triangles in $ℝ^2$. For unit segments and congruent equilateral triangles, we can even rule out strong sub-quadratic approximations already in $ℝ^2$. It seems that the hardness of approximation may also depend on dimensionality: for axis-parallel unit hypercubes in $ℝ^{12}$, distinguishing between diameter 2 and 3 needs quadratic time (ruling out $(3/2-ε)$- approximations), whereas for axis-parallel unit squares, we give an algorithm that distinguishes between diameter 2 and 3 in near-linear time. Note that many of our lower bounds match the best known algorithms up to sub-polynomial factors. Ultimately, this fine-grained perspective may enable us to determine for which shapes we can have efficient algorithms and approximation schemes for diameter computation

Dynamic Time Warping Under Translation: Approximation Guided by Space-Filling Curves

The Dynamic Time Warping (DTW) distance is a popular measure of similarity for a variety of sequence data. For comparing polygonal curves π, σ in $ℝ^d$, it provides a robust, outlier-insensitive alternative to the Fréchet distance. However, like the Fréchet distance, the DTW distance is not invariant under translations. Can we efficiently optimize the DTW distance of π and σ under arbitrary translations, to compare the curves\u27 shape irrespective of their absolute location? There are surprisingly few works in this direction, which may be due to its computational intricacy: For the Euclidean norm, this problem contains as a special case the geometric median problem, which provably admits no exact algebraic algorithm (that is, no algorithm using only addition, multiplication, and k-th roots). We thus investigate exact algorithms for non-Euclidean norms as well as approximation algorithms for the Euclidean norm. For the $L_1$ norm in $ℝ^d$, we provide an $(n^{2(d+1)})$-time algorithm, i.e., an exact polynomial-time algorithm for constant d. Here and below, n bounds the curves\u27 complexities. For the Euclidean norm in $ℝ^2$, we show that a simple problem-specific insight leads to a $(1+ε)$-approximation in time $(n^3/ε^2)$. We then show how to obtain a subcubic ̃(n^{2.5}/ε^2) time algorithm with significant new ideas; this time comes close to the well-known quadratic time barrier for computing DTW for fixed translations. Technically, the algorithm is obtained by speeding up repeated DTW distance estimations using a dynamic data structure for maintaining shortest paths in weighted planar digraphs. Crucially, we show how to traverse a candidate set of translations using space-filling curves in a way that incurs only few updates to the data structure. We hope that our results will facilitate the use of DTW under translation both in theory and practice, and inspire similar algorithmic approaches for related geometric optimization problems