Trajectories of Response to Treatment for Posttraumatic Stress Disorder

Research on the predictors of response to cognitive-behavioral treatments for PTSD has often produced inconsistent or ambiguous results. We argue this is in part due to the use of statistical techniques that explore relationships among the entire sample of participants rather than homogeneous subgroups. Using 2 large randomized controlled trials of Cognitive Processing Therapy (CPT), CPT components, and Prolonged Exposure, we employed growth mixture modeling to identify distinct trajectories of treatment response and to determine the predictors of those trajectories. We determined that the participants’ trajectories could be best represented by 2 latent classes, which we subsequently labeled responders (87% of the sample) and nonresponders (13% of the sample). Notably, there was not a separate class for partial responders. Assignment to the nonresponder class was associated with receiving the written accounts (WA) component of CPT, a pretreatment diagnosis of major depression (MDD), and more pretreatment hyperarousal symptoms. Thus, it appears that some individuals do not benefit from merely writing about their trauma and processing it with the therapist; they may also need to engage in cognitive restructuring to successfully ameliorate their symptoms. Additionally, those who meet criteria for MDD or have high levels of hyperarousal at the onset of treatment might require additional treatment or support.     

Predicting premature termination within a randomized controlled trial for binge-eating patients

Understanding the dropout rates of efficacious forms of psychotherapy for patients with binge eating disorder (BED) is an unsolved problem within this increasing population. Up until now the role of psychotherapy process characteristics as predictors of premature termination has not been investigated in the BED literature. Within a randomized controlled trial (N=78) we investigated the degree to which early psychological process characteristics, such as components of the therapeutic relationship and the experiences of mastery and motivational clarification, predicted premature termination of treatment. We statistically controlled for the influences of covariates such as rapid response of treatment, treatment group, body mass index, Axis II disorder, and patients' preexisting generalized self-efficacy at baseline. Patients' postsession reports from Sessions 1 to 5 indicated that low self-esteem in-session experiences was a stable predictor of premature termination. Its predictive value persisted after controlling for the above-mentioned covariates. Exploratory analyses further revealed low self-esteem experiences, low global alliance, and low mastery and clarification experiences as predictors in those patients who explicitly specified discontentment with therapy as reason for premature termination. These results indicate that patients' self-esteem experiences may not be an epiphenomenon of their specific psychopathology but may represent general mechanisms on which remaining or withdrawing from psychotherapeutic treatment depends. Early psychotherapy process characteristics should therefore be considered in training and evaluation of psychotherapists carrying through BED treatments.     

Predictors of depressive symptoms among breast cancer patients during the first year post diagnosis

It is important to identify predictors of psychological health among breast cancer patients that can be relatively easily identified by medical care providers. This article investigates the role of one class of such potential predictors: easily identified demographics that have potential social and/or practical implications. Specifically, we examined whether income, marital status, presence of children in the home, education, travel distance, age and rurality interact with time to predict psychological health over the first year post diagnosis. Two hundred and twenty five breast cancer patients receiving radiation treatment completed four surveys over the course of 13 months that included measures of both their physical health and depressive symptoms. The results revealed that women who were not married had children living in the home or had to travel long distances to receive radiation treatment reported higher levels of depressive symptoms across the entire study. Women with lower incomes reported increased depressive symptoms, but only after the completion of treatment. Younger women reported elevated depressive symptoms during initial treatment, but this effect dissipated after the completion of treatment. The current results suggest that demographic patient characteristics may indeed be useful in identifying both when and for whom depressive symptoms are particularly likely to be problematic.     

Predicting Response to Therapist-Assisted Internet-Delivered Cognitive Behavior Therapy for Depression or Anxiety Within an Open Dissemination Trial

Therapist-assisted Internet-delivered cognitive behavior therapy (ICBT) is efficacious for treating anxiety and depression, but predictors of response to treatment when delivered in clinical practice are not well understood. In this study, we explored demographic, clinical, and program variables that predicted modules started and symptom improvement (i.e., Generalized Anxiety Disorder-7 or Patient Health Questionnaire-9 total scores over pre-, mid-, and posttreatment) within a previously published open dissemination trial (Hadjistavropoulos et al., 2014). The sample consisted of 195 patients offered 12 modules of therapist-assisted ICBT for depression or generalized anxiety; ICBT was delivered by therapists working in six geographically dispersed clinics. Consistent across ICBT for depression or generalized anxiety, starting fewer modules was associated with more phone calls from therapists reflecting that therapists tended to call patients who did not start modules as scheduled. Also consistent for both ICBT programs, greater pretreatment condition severity and completion of more modules was associated with superior ICBT-derived benefit. Other predictors of response to treatment varied across the two programs. Younger age, lower education, taking psychotropic medication, being in receipt of psychiatric care and lower comfort with written communication were associated with either fewer program starts or lower symptom improvement in one of the two programs. It is concluded that monitoring response to ICBT may be particularly important in patients with these characteristics. Research directions for identifying patients who are less likely to benefit from ICBT are discussed.     

Caregiver Factors Predicting Service Utilization Among Youth Participating in a School-based Mental Health Intervention

Large numbers of children and adolescents experience diagnosable psychiatric disturbances; however, the majority of those with need do not utilize mental health services. Characteristics of caregivers are important predictors of which youth will access and continue to use services over time. In recent years school-based mental health intervention programs have played a key role in identifying youth with mental health needs and linking them to treatment. In this study we sought to identify the caregiver demographic and contextual factors that predict days of service use among youth participating in a school-based mental health intervention program. Our sample included 85 youth ages 5–18 and their caregivers. We analyzed the data using bivariate and multivariate Poisson regressions with caregiver factors as the independent variables and days of service as the dependant variable. We found significant bivariate and multivariate associations for every caregiver demographic (sex, age, race) and contextual (education, employment, income, insurance, health, strain, and was it the caregivers idea to seek treatment) factor that was examined. In this study we identified the caregiver factors that are likely important in predicting youth service utilization even when steps have been taken to improve identification and access.     

Predictors of improvement in an open-trial multisite evaluation of emotion regulation group therapy

Emotion regulation group therapy (ERGT) is a novel treatment specifically targeting deliberate non-suicidal self-harm (DSH) in individuals with borderline personality disorder (BPD). Identifying robust predictors of positive response to ERGT could aid clinicians in treatment selection; however, to date, only one such study has been conducted. Thus, we aimed to replicate previously identified predictors of treatment response to ERGT by investigating demographic, clinical, and diagnostic predictors in 95 women with BPD or subclinical BPD who had participated in an open-trial evaluation of ERGT. Outcomes evaluated were frequency of DSH and emotion dysregulation. Assessments were conducted at pretreatment, post-treatment, and 6-month follow-up. Multilevel mixed linear models and multilevel negative binomial generalized estimated equations were used to identify significant interactions between the predictors and outcomes.

We found that greater pretreatment DSH frequency was associated with greater improvements in DSH during treatment (b = 0.998, SE = 0.00, p = 0.03) and follow-up (b = 0.997, SE = 0.00, p < 0.01) and that greater BPD severity was associated with greater improvements in DSH during treatment (b = 0.84, SE = 0.06, p = 0.02) and in emotion dysregulation at follow-up (b = ?3.05, SE = 1.47, p = 0.04). Co-occurring disorders were associated with poorer treatment response during follow-up. Results were generally consistent with a previous study of the predictors of response to ERGT. The findings provide further support for the utility of this treatment across a range of BPD patients, including patients with severe DSH and BPD.     

Socio-demographic and psychopathological risk factors in obsessive-compulsive disorder: Epidemiologic study of school population

We assessed the presence of emotional disorders (obsessive-compulsive, anxiety and depressive) in 1,514 Spanish non-referred children (8–12 years old) to investigate the predictive ability of psychopathological and socio-demographic characteristics, and identify which of these were possible correlates for clinical obsessive-compulsive disorder (OCD) and subclinical OCD. At one year later, 562 subjects (risk group and without risk group) were re-assessed and we established the OCD diagnoses or the subclinical OCD diagnoses. We found that 20 participants presented clinical OCD and 46 participants presented subclinical OCD. Somatic and separation anxiety symptomatology were good predictors for clinical OCD, and obsessive concern was a predictor for subclinical OCD. Clinical OCD was associated with order/checking/pollution symptoms and with a lower socioeconomic status (SES). Subclinical OCD was associated with hyperactive and impulsive manifestations, obsessive concern, and superstition/mental compulsion. An early detection and the follow-up of anxiety or obsessive symptoms in children may be important for preventing the course of OCD.     

Frege on the generality of logical laws

Frege claims that the laws of logic are characterized by their “generality,” but it is hard to see how this could identify a special feature of those laws. I argue that we must understand this talk of generality in normative terms, but that what Frege says provides a normative demarcation of the logical laws only once we connect it with his thinking about truth and science. He means to be identifying the laws of logic as those that appear in every one of the scientific systems whose construction is the ultimate aim of science, and in which all truths have a place. Though an account of logic in terms of scientific systems might seem hopelessly antiquated, I argue that it is not: A basically Fregean account of the nature of logic still looks quite promising.     

Factors Associated With Treatment Response in an Internet-Based Intervention for Prolonged Grief Disorder After Cancer Bereavement

Internet-based psychological interventions have proven effective in the treatment of prolonged grief disorder (PGD). Yet, some patients do not benefit from treatment in a clinically significant way. We aimed to examine predictors of symptom reduction in an Internet-based intervention for PGD after cancer bereavement, in order to identify possible treatment mechanisms and discern directions for future intervention design. A secondary analysis of data from a randomized wait-list controlled trial on an Internet-based intervention for PGD after cancer bereavement was conducted. Multiple regression models were used (1) to test for the influence of pretreatment PGD, working alliance, avoidance and gender on PGD symptom reduction; and (2) to explore further predictors of treatment success with a best subset selection protocol. The regression models explained 18% (Model 1) and 34% (Model 2) of variance in symptom reduction. Participants with more favorable symptom change had more severe pretreatment PGD scores and better working alliance. Those with lower social support and less posttraumatic growth experienced more PGD symptom change. In conclusion, therapeutic alliance is an important factor that should be monitored and fostered. Findings regarding social support and posttraumatic growth need further replication and clarification.     

Fibred Security Language

We study access control policies based on the says operator by introducing a logical framework called Fibred Security Language (FSL) which is able to deal with features like joint responsibility between sets of principals and to identify them by means of first-order formulas. FSL is based on a multimodal logic methodology. We first discuss the main contributions from the expressiveness point of view, we give semantics for the language both for classical and intuitionistic fragment), we then prove that in order to express well-known properties like ‘speaks-for’ or ‘hand-off’, defined in terms of says, we do not need second-order logic (unlike previous approaches) but a decidable fragment of first-order logic suffices. We propose a model-driven study of the says axiomatization by constraining the Kripke models in order to respect desirable security properties, we study how existing access control logics can be translated into FSL and we give completeness for the logic.     

SBNR Identity: The Role of Impersonal God Representations,Individualistic Spirituality,and Dissimilarity With Religious Groups

We conducted two studies investigating the extent to which self-identification as Spiritual but not Religious (SBNR) was associated with (H1) the development of idiosyncratic religious beliefs and exposure to religious diversity and/or (H2) negative attitudes toward organized religion and being hurt by members of a religious group. In Study 1, SBNRs scored higher than religious and nonreligious participants on belief in God as an impersonal cosmic force (but not as a personal being) and individualistic spirituality. Although SBNRs had positive attitudes toward religion, they were less positive than those identifying as religious. Exposure to religious diversity and hurt by religious groups were not significant predictors of SBNR. We replicated these results in Study 2 using a multi-item measure of God representations and also found that SBNRs’ attitudes toward religion were predicted by a perceived dissimilarity with religious groups over and above individualism, secular group participation, perceptions of Christianity as too structured, and liberalism.     

Predicting the Outcome of Treatment

The clinical question—“Which treatment(s) for which patients with what set of subgrouping characteristics working by what mechanism(s)?”—rests at the heart of differential therapeutics. Experimentally, this question reduces to a test of how well we can predict the outcome of treatment using the treatment conditions plus other moderating and mediating variables. Reflecting the discussions held at a recent National Institute of Mental Health (NIMH) conference on psychosocial treatments, and using pediatric anxiety disorders as a case in point, we discuss the problem of prediction in treatment outcome studies from the standpoint of definition of terms, using the general linear model of prediction. We also outline types of studies that may be useful in testing potential predictors, and put forward a possible matrix of predictor variables as currently implemented in an NIMH-funded treatment outcome study of pediatric obsessive-compulsive disorder (OCD). We conclude by making specific suggestions for implementing a broader approach to the study of predictors.     

The relative importance of math‐ and music‐related cognitive and affective factors in predicting undergraduate music theory achievement

Based on research identifying relations between math and music, we aimed to identify the group of cognitive and affective factors related to math and music theory that best explained undergraduate music theory achievement. Using dominance analysis, we predicted the music theory course grades of 230 undergraduate music majors. Potential predictors were narrowed from measures of knowledge, aptitude, experience, confidence, and anxiety in both music theory and math as well as spatial skills and reading test scores. Results suggested that ACT math scores and music theory confidence were important predictors for Music Theories I and II grades. Music Theory I was also predicted by aptitude‐based music theory skills, and Music Theory II was also predicted by math course experience. These findings provide evidence for a relation between math and music theory and support the use of several readily available measures for college‐level music instructors to identify students who may struggle in music theory.     

Relationship between patient characteristics and treatment allocation for patients with personality disorders

Within a large multi-center study in patients with personality disorders, we investigated the relationship between patient characteristics and treatment allocation. Personality pathology, symptom distress, treatment history, motivational factors, and sociodemographics were measured at intake in 923 patients, who subsequently enrolled in short-term or long-term outpatient, day hospital, or inpatient psychotherapy for personality pathology. Logistic regressions were used to examine the predictors of allocation decisions. We found a moderate relationship (R(2) = 0.36) between patient characteristics and treatment setting, and a weak relationship (R(2) = 0.18) between patient characteristics and treatment duration. The most prominent predictors for setting were: symptom distress, cluster C personality pathology, level of identity integration, treatment history, motivation, and parental responsibility. For duration the most prominent predictor was age. We conclude from this study that, in addition to pathology and motivation factors, sociodemographics and treatment history are related to treatment allocation in clinical practice.     

Individual differences in cognitive plasticity: an investigation of training curves in younger and older adults

To date, cognitive intervention research has provided mixed but nevertheless promising evidence with respect to the effects of cognitive training on untrained tasks (transfer). However, the mechanisms behind learning, training effects and their predictors are not fully understood. Moreover, individual differences, which may constitute an important factor impacting training outcome, are usually neglected. We suggest investigating individual training performance across training sessions in order to gain finer-grained knowledge of training gains, on the one hand, and assessing the potential impact of predictors such as age and fluid intelligence on learning rate, on the other hand. To this aim, we propose to model individual learning curves to examine the intra-individual change in training as well as inter-individual differences in intra-individual change. We recommend introducing a latent growth curve model (LGCM) analysis, a method frequently applied to learning data but rarely used in cognitive training research. Such advanced analyses of the training phase allow identifying factors to be respected when designing effective tailor-made training interventions. To illustrate the proposed approach, a LGCM analysis using data of a 10-day working memory training study in younger and older adults is reported.     

Identifying careless responses in survey data

When data are collected via anonymous Internet surveys, particularly under conditions of obligatory participation (such as with student samples), data quality can be a concern. However, little guidance exists in the published literature regarding techniques for detecting careless responses. Previously several potential approaches have been suggested for identifying careless respondents via indices computed from the data, yet almost no prior work has examined the relationships among these indicators or the types of data patterns identified by each. In 2 studies, we examined several methods for identifying careless responses, including (a) special items designed to detect careless response, (b) response consistency indices formed from responses to typical survey items, (c) multivariate outlier analysis, (d) response time, and (e) self-reported diligence. Results indicated that there are two distinct patterns of careless response (random and nonrandom) and that different indices are needed to identify these different response patterns. We also found that approximately 10%-12% of undergraduates completing a lengthy survey for course credit were identified as careless responders. In Study 2, we simulated data with known random response patterns to determine the efficacy of several indicators of careless response. We found that the nature of the data strongly influenced the efficacy of the indices to identify careless responses. Recommendations include using identified rather than anonymous responses, incorporating instructed response items before data collection, as well as computing consistency indices and multivariate outlier analysis to ensure high-quality data. (PsycINFO Database Record (c) 2012 APA, all rights reserved).     

Using Client Narratives to Identify Predictors of Outcome in Written Exposure Therapy and Cognitive Processing Therapy

Written exposure therapy (WET) is a brief, five-session treatment for posttraumatic stress disorder (PTSD) that aims to improve access to care. WET has been demonstrated to be an efficacious PTSD treatment with lower rates of dropout and noninferior PTSD symptom outcome compared to cognitive processing therapy (CPT), a 12-session, gold-standard treatment. To identify predictors of treatment outcome in both WET and CPT, the current study examined the content of participants’ written narratives. Participants were 123 adults with PTSD who were randomly assigned to receive WET (n = 61) or CPT (n = 62). The Change and Growth Experiences Scale (CHANGE) coding system was used to code all available narratives in both treatment conditions for variables hypothesized to be relevant to therapeutic change. Linear regression analyses revealed that in WET, higher average levels of accommodated (healthy, balanced) beliefs and an increase in accommodated beliefs from the first to the final impact statement predicted better PTSD symptom outcome at 12 weeks postrandomization. In CPT, higher average levels of overgeneralized and accommodated beliefs and lower levels of avoidance expressed in the narratives predicted better PTSD outcome. There were no significant predictors of outcome in analyses of change from the first to final impact statement in CPT. These findings add to research identifying predictors of change in WET and CPT by highlighting the importance of low avoidance in CPT and of trauma-related cognitions in both CPT and WET, even though WET is a brief written intervention that does not explicitly target cognitive change.     

Automatic sequential response priming and intentional response preparation in choice reaction tasks: Evidence from response repetition and response cuing

This study examined the interaction of response repetition and response cuing in a finger cuing task with a short and a long cue-stimulus interval (CSI). We observed shorter reaction times (RTs) with increasing CSI and a substantial response repetition benefit. However, this benefit was abolished at the long CSI, suggesting that response cuing neutralized the repetition effect. According to additive-factors logic, the observed interaction suggests that both repetition and cuing exert their influence on a common processing stage, which we identify as the response selection stage. We argue that cuing and repetition effects are expressions of distinct mental operations: cuing is based on intentional response code activation, whereas repetition is based on sequential, automatic response code priming. Cue-based intentional code activation starts slowly and increases with CSI, but sequential response priming is independent of CSI, explaining why cuing abolishes the response repetition benefit at the long CSI.     

The Undecidability of Quantified Announcements

This paper demonstrates the undecidability of a number of logics with quantification over public announcements: arbitrary public announcement logic (APAL), group announcement logic (GAL), and coalition announcement logic (CAL). In APAL we consider the informative consequences of any announcement, in GAL we consider the informative consequences of a group of agents (this group may be a proper subset of the set of all agents) all of which are simultaneously (and publicly) making known announcements. So this is more restrictive than APAL. Finally, CAL is as GAL except that we now quantify over anything the agents not in that group may announce simultaneously as well. The logic CAL therefore has some features of game logic and of ATL. We show that when there are multiple agents in the language, the satisfiability problem is undecidable for APAL, GAL, and CAL. In the single agent case, the satisfiability problem is decidable for all three logics.     

A controlled evaluation of paraspinal EMG biofeedback in the treatment of chronic low back pain

Sixty-six chronic low back pain sufferers were randomly divided into three groups. Following individual assessments consisting of psychological questionnaires, pain monitoring, and measurement of paraspinal electromyogram (EMG), one group received paraspinal EMG biofeedback and another a placebo treatment. The third group received no intervention. Two further assessments were carried out on all groups immediately after treatment and at a 3-month follow-up. All groups showed significant reduction in pain, anxiety, depression, and paraspinal EMG following treatment and at follow-up, but there were no differences between groups. A regression analysis failed to identify subjects' characteristics that predicted positive outcome in the biofeedback group. However, high scores on the Evaluative scale of the McGill Pain Questionnaire and high hypnotizability were significant predictors of positive outcome for the placebo group. It is concluded that paraspinal EMG biofeedback is not a specific treatment for chronic low back pain in a nonhospitalized population.