Using smart‐messaging to enhance mindfulness‐based cognitive therapy for cancer patients: A mixed methods proof of concept evaluation

Objective Depression and anxiety lead to reduced treatment adherence, poorer quality of life, and increased care costs amongst cancer patients. Mindfulness‐based cognitive therapy (MBCT) is an effective treatment, but dropout reduces potential benefits. Smart‐message reminders can prevent dropout and improve effectiveness. However, smart‐messaging is untested for MBCT in cancer. This study evaluates smart‐messaging to reduce dropout and improve effectiveness in MBCT for cancer patients with depression or anxiety.MethodsFifty‐one cancer patients attending MBCT in a psycho‐oncology service were offered a smart‐messaging intervention, which reminded them of prescribed between‐session activities. Thirty patients accepted smart‐messaging and 21 did not. Assessments of depression and anxiety were taken at baseline, session‐by‐session, and one‐month follow‐up. Logistic regression and multilevel modelling compared the groups on treatment completion and clinical effectiveness. Fifteen post‐treatment patient interviews explored smart‐messaging use.ResultsThe odds of programme completion were eight times greater for patients using smart‐messaging compared with non‐users, controlling for age, gender, baseline depression, and baseline anxiety (OR = 7.79, 95% CI 1.75 to 34.58, p = .007). Smart‐messaging users also reported greater improvement in depression over the programme (B = ‐2.33, SEB = .78, p = .004) when controlling for baseline severity, change over time, age, and number of sessions attended. There was no difference between groups in anxiety improvement (B = ‐1.46, SEB = .86, p = .097). In interviews, smart‐messaging was described as a motivating reminder and source of personal connection. ConclusionsSmart‐messaging may be an easily integrated telehealth intervention to improve MBCT for cancer patients

Fast Label Embeddings via Randomized Linear Algebra

Many modern multiclass and multilabel problems are characterized by increasingly large output spaces. For these problems, label embeddings have been shown to be a useful primitive that can improve computational and statistical efficiency. In this work we utilize a correspondence between rank constrained estimation and low dimensional label embeddings that uncovers a fast label embedding algorithm which works in both the multiclass and multilabel settings. The result is a randomized algorithm whose running time is exponentially faster than naive algorithms. We demonstrate our techniques on two large-scale public datasets, from the Large Scale Hierarchical Text Challenge and the Open Directory Project, where we obtain state of the art results.Comment: To appear in the proceedings of the ECML/PKDD 2015 conference. Reference implementation available at https://github.com/pmineiro/randembe

Prenatal Bisphenol A Exposure and Early Childhood Behavior

BackgroundPrenatal exposure to bisphenol A (BPA) increases offspring aggression and diminishes differences in sexually dimorphic behaviors in rodents.ObjectiveWe examined the association between prenatal BPA exposure and behavior in 2-year-old children.MethodsWe used data from 249 mothers and their children in Cincinnati, Ohio (USA). Maternal urine was collected around 16 and 26 weeks of gestation and at birth. BPA concentrations were quantified using high-performance liquid chromatography–isotope-dilution tandem mass spectrometry. Child behavior was assessed at 2 years of age using the second edition of the Behavioral Assessment System for Children (BASC-2). The association between prenatal BPA concentrations and BASC-2 scores was analyzed using linear regression.ResultsMedian BPA concentrations were 1.8 (16 weeks), 1.7 (26 weeks), and 1.3 (birth) ng/mL. Mean (± SD) BASC-2 externalizing and internalizing scores were 47.6 ± 7.8 and 44.8 ± 7.0, respectively. After adjustment for confounders, log10-transformed mean prenatal BPA concentrations were associated with externalizing scores, but only among females [β = 6.0; 95% confidence interval (CI), 0.1–12.0]. Compared with 26-week and birth concentrations, BPA concentrations collected around 16 weeks were more strongly associated with externalizing scores among all children (β = 2.9; 95% CI, 0.2–5.7), and this association was stronger in females than in males. Among all children, measurements collected at ≤ 16 weeks showed a stronger association (β = 5.1; 95% CI, 1.5–8.6) with externalizing scores than did measurements taken at 17–21 weeks (β = 0.6; 95% CI, −2.9 to 4.1).ConclusionsThese results suggest that prenatal BPA exposure may be associated with externalizing behaviors in 2-year-old children, especially among female children

Lingual haemangiosarcoma in a crossbred dog

An eight-year-old, male neutered, crossbred dog was presented for investigation of a lingual mass of four months duration. Oral examination revealed a 7 cm × 5 cm soft, fluctuant mass at the caudal aspect of the tongue. Ultrasound examination of the mass demonstrated mixed echogenicity, with cavitations containing hypoechoic and anechoic regions. Lingual haemangiosarcoma was diagnosed on histopathological examination of multiple biopsy samples, with confirmation of the vascular endothelial origin of tumour cells by positive immunolabelling for factor VIII-related antigen

Neural processing of criticism and positive comments from relatives in individuals with schizotypal personality traits

Objectives. High negative expressed emotion by family members towards schizophrenia patients increases the risk of subsequent relapse. The study aimed to determine whether individuals with high schizotypy (HS) and low schizotypy (LS) would differ in activation of brain areas involved in cognitive control when listening to relative criticism

Invasion speeds for structured populations in fluctuating environments

We live in a time where climate models predict future increases in environmental variability and biological invasions are becoming increasingly frequent. A key to developing effective responses to biological invasions in increasingly variable environments will be estimates of their rates of spatial spread and the associated uncertainty of these estimates. Using stochastic, stage-structured, integro-difference equation models, we show analytically that invasion speeds are asymptotically normally distributed with a variance that decreases in time. We apply our methods to a simple juvenile-adult model with stochastic variation in reproduction and an illustrative example with published data for the perennial herb, \emph{Calathea ovandensis}. These examples buttressed by additional analysis reveal that increased variability in vital rates simultaneously slow down invasions yet generate greater uncertainty about rates of spatial spread. Moreover, while temporal autocorrelations in vital rates inflate variability in invasion speeds, the effect of these autocorrelations on the average invasion speed can be positive or negative depending on life history traits and how well vital rates ``remember'' the past

Behavioral activation interventions for well-being: A meta-analysis

One of the most promising ways to increase well-being is to engage in valued and enjoyable activities. Behavioral activation (BA), an intervention approach most commonly associated with the treatment of depression, is consistent with this recommendation and can easily be adapted for non-clinical populations. This study reports on a meta-analysis of randomized controlled studies to examine the effect of BA on well-being. Twenty studies with a total of 1353 participants were included. The pooled effect size (Hedges's g) indicated that the difference in well-being between BA and control conditions at posttest was 0.52. This significant effect, which is comparable to the pooled effect achieved by positive psychology interventions, was found for non-clinical participants and participants with elevated symptoms of depression. Behavioral activation would seem to provide a ready and attractive intervention for promoting the well-being of a range of populations in both clinical and non-clinical settings

Relationship between craving and personality in treatment-seeking women with substance-related disorders

BACKGROUND: Individual differences may impact susceptibility to addiction. The impact of personality features on drug craving, however, has not been studied, particularly in women. METHODS: Ninety-five treatment-seeking women with substance dependence, abstinent for at least 5 and no more than 21 days, were investigated regarding the correlation between personality factors and craving. Personality was assessed using the Temperament and Character Inventory (TCI), the NEO Personality Inventory Revised (NEO-PI-R), and the Barratt Impulsiveness Scale version 11 (BIS-11). Cravings were assessed through the Pennsylvania Craving Scale (PCS), and the Craving Questionnaire (CQ). Anxiety and depressive symptomatology were also recorded. RESULTS: Craving scores were positively correlated with depression and negatively correlated with number of days abstinent from substance use. Also, craving scores were positively associated with the novelty-seeking factor from the TCI and the total score on the BIS-11, and negatively associated with the conscientiousness and agreeableness facets of the NEO-PI-R. CONCLUSION: Findings suggest that personality features, particularly impulsiveness, can be important predictors of craving in women, which has important implications for treatment planning

Individualization as driving force of clustering phenomena in humans

One of the most intriguing dynamics in biological systems is the emergence of clustering, the self-organization into separated agglomerations of individuals. Several theories have been developed to explain clustering in, for instance, multi-cellular organisms, ant colonies, bee hives, flocks of birds, schools of fish, and animal herds. A persistent puzzle, however, is clustering of opinions in human populations. The puzzle is particularly pressing if opinions vary continuously, such as the degree to which citizens are in favor of or against a vaccination program. Existing opinion formation models suggest that "monoculture" is unavoidable in the long run, unless subsets of the population are perfectly separated from each other. Yet, social diversity is a robust empirical phenomenon, although perfect separation is hardly possible in an increasingly connected world. Considering randomness did not overcome the theoretical shortcomings so far. Small perturbations of individual opinions trigger social influence cascades that inevitably lead to monoculture, while larger noise disrupts opinion clusters and results in rampant individualism without any social structure. Our solution of the puzzle builds on recent empirical research, combining the integrative tendencies of social influence with the disintegrative effects of individualization. A key element of the new computational model is an adaptive kind of noise. We conduct simulation experiments to demonstrate that with this kind of noise, a third phase besides individualism and monoculture becomes possible, characterized by the formation of metastable clusters with diversity between and consensus within clusters. When clusters are small, individualization tendencies are too weak to prohibit a fusion of clusters. When clusters grow too large, however, individualization increases in strength, which promotes their splitting.Comment: 12 pages, 4 figure