"It Felt Like I Was Being Tailored to the Treatment Rather Than the Treatment Being Tailored to Me": Patient Experiences of Helpful and Unhelpful Psychotherapy.

OBJECTIVE: This qualitative study explores patients' experiences of psychotherapy, focusing on elements perceived as helpful or unhelpful and suggestions for improvement in the context of public mental health care. METHODS: A total of 148 adults (Mean age = 32.24, SD = 9.92) who had been or are currently receiving psychological treatment from the National Health Service (NHS) responded to an online survey. The survey included open-ended questions regarding their experiences of psychotherapy, asking them to identify helpful or unhelpful aspects, and suggestions for improvement. Using thematic analysis, key themes were identified. RESULTS: The analysis highlighted the patient's preference for personalized treatment, the importance of therapeutic alliance, the demand for depth in therapy, and life skills and agency as therapeutic outcomes. Participants suggested improvements such as more tailored approaches and stronger therapist-patient relationships, supporting an adaptable, patient-centered model. CONCLUSION: The study highlights challenges in public mental health services where patients might feel their specific needs are not being recognized and met and underscores the importance of personalized treatment plans that satisfy and evolve with patient needs, suggesting that therapists must be attentive and responsive to individual desires to enhance the patient experience.

The Revised Pathogenic Beliefs Scale: A Transtheoretical Measure of Maladaptive Beliefs That Are Associated with Psychological Distress.

Pathogenic beliefs are maladaptive cognitive schema that may obstruct a person's ability to achieve meaningful goals in their life. This study sought to revise a previously existing measure of pathogenic beliefs (the Pathogenic Beliefs Scale) by improving the quality of items and separating the ratings of the presence of a pathogenic belief from the distress associated with it. In Study 1 (n = 272), we used item-response theory to identify 21 items from an initial pool of 44 items. In Study 2 (n = 422), we tested the items from Study 1 using confirmatory factor analysis. Study 3 used the combined samples from Study 1 and Study 2 (total n = 528) to compare the revised measure to the Experiences in Close Relationships and the Measure of Parental Style. Results indicate that the revised 21-item PBS has good reliability and convergent validity with related measures, consistent with previous studies of the longer version of the PBS. The 21-item revised PBS is included as supplemental material, and freely available to clinicians and researchers.

Multiple DNA repair pathways prevent acetaldehyde-induced mutagenesis in yeast.

Acetaldehyde is the primary metabolite of alcohol and is present in many environmental sources including tobacco smoke. Acetaldehyde is genotoxic, whereby it can form DNA adducts and lead to mutagenesis. Individuals with defects in acetaldehyde clearance pathways have increased susceptibility to alcohol-associated cancers. Moreover, a mutation signature specific to acetaldehyde exposure is widespread in alcohol and smoking-associated cancers. However, the pathways that repair acetaldehyde-induced DNA damage and thus prevent mutagenesis are vaguely understood. Here, we used Saccharomyces cerevisiae to systematically delete genes in each of the major DNA repair pathways to identify those that alter acetaldehyde-induced mutagenesis. We found that deletion of the nucleotide excision repair (NER) genes, RAD1 or RAD14, led to an increase in mutagenesis upon acetaldehyde exposure. Acetaldehyde-induced mutations were dependent on translesion synthesis as well as DNA inter-strand crosslink (ICL) repair in Δrad1 strains. Moreover, whole genome sequencing of the mutated isolates demonstrated an increase in C→A changes coupled with an enrichment of gCn→A changes in the acetaldehyde-treated Δrad1 isolates. The gCn→A mutation signature has been shown to be diagnostic of acetaldehyde exposure in yeast and in human cancers. We also demonstrated that the deletion of the two DNA-protein crosslink (DPC) repair proteases, WSS1 and DDI1, also led to increased acetaldehyde-induced mutagenesis. Defects in base excision repair (BER) led to a mild increase in mutagenesis, while defects in mismatch repair (MMR), homologous recombination repair (HR) and post replicative repair pathways did not impact mutagenesis upon acetaldehyde exposure. Our results in yeast were further corroborated upon analysis of whole exome sequenced liver cancers, wherein, tumors with defects in ERCC1 and ERCC4 (NER), FANCD2 (ICL repair) or SPRTN (DPC repair) carried a higher gCn→A mutation load than tumors with no deleterious mutations in these genes. Our findings demonstrate that multiple DNA repair pathways protect against acetaldehyde-induced mutagenesis.

Interpersonal guilt and the working alliance in psychotherapy: The moderating role of childhood experience.

Interpersonal guilt often encompasses pathogenic beliefs that imply omnipotent responsibility for others and concerns about abandoning, humiliating or threatening others. This study sought to examine how interpersonal guilt may influence patients' and therapists' ratings of early working alliance and the potential moderating effect of perceived adverse parenting in childhood. Ninety-five patients and their 19 therapists in an outpatient psychotherapy clinic rated their early working alliance after the first and the fifth session in treatment. We conducted separate moderation analyses for patient and therapist-reported working alliance and controlled for psychological distress at baseline. Results suggest that perceived adverse parenting in childhood significantly moderated the effect of interpersonal guilt on the working alliance in such a way that for patients reporting very low levels of perceived adverse experiences, the interpersonal guilt beliefs had a positive effect on working alliance, whereas for those with very high levels of perceived adverse experiences, interpersonal guilt had a negative effect on working alliance. This same pattern of moderation was found for patient- and therapist-reported working alliance at session 1 and therapist-reported working alliance at session 5. Thus, although the effect of interpersonal guilt on the working alliance depends somewhat on the perspective of the working alliance rating (patient or therapist), it mainly depends on developmental experiences of the patient.

Within-patient perceptions of alliance and attunement: Associations with progress in psychotherapy.

The most frequently examined aspect of the therapeutic relationship is the working alliance, which reflects the conscious collaborative bond, and agreement on task and goal. In addition to the established importance of the working alliance, the therapists' attunement and responsiveness might reflect another important aspect of the therapeutic relationship that can be considered in relation to session-by-session progress over treatments. Emerging research suggests that the quality of the working alliance not only differs between patients but also within patients over time. However, little is known about the quality of the therapeutic relationship between and within patients in relation to progress in psychotherapy. We examined fluctuations of the working alliance measure (WAI) and the newly developed measure of the Patients' Experiences of Attunement and Responsiveness (PEAR) during treatment in a naturalistic sample of patients in an outpatient psychotherapy clinic. Multilevel modelling was used to examine the respective contribution of these measures to subsequent improvement in psychological functioning longitudinally. Results suggest that the within-patient effect, instead of between-patient effect, was significant for WAI (and did not reach significance for PEAR), indicating that the fluctuation of WAI was predictive of psychological functioning in the subsequent month. Based on these findings, therapists and their patients might benefit from regular tracking of the patient-reported working alliance. The findings underscore the importance of the alliance, specifically at the within-patient level. It also highlights the challenge for research to tap into other aspects of the therapeutic relationship that can help explain progress in therapy. Given the breadth and accessibility of the working alliance construct, more work is needed for researchers to examine the construct of attunement and responsiveness.

The development of a self-report scale to assess therapists' acceptance of telepsychotherapy.

OBJECTIVE: We aimed to develop a self-report measure of therapist acceptance of telepsychotherapy based on the Unified Theory of Acceptance and Use of Technology (UTAUT) framework. METHODS: Using a cross-sectional survey design, 1265 therapists completed the UTAUT-T, as well as additional questions. RESULTS: Confirmatory analysis indicated that the original UTAUT model did not fit the therapist context well. Exploratory factor analysis specified a better-fitting five-factor model, which showed good internal validity fit (χ2 = 17,753.36, RMSEA = 0.063, TLI = 0.886, SRMSR = 0.04). The five UTAUT-T subscales showed high internal consistency (Cronbach's α = 0.86) and together predicted the intention to use online therapy in the future (R2 = 0.42, F(5, 1259) = 181.9, p < 0.001). CONCLUSION: The 21-item UTAUT-T offers a promising self-report measure of therapist acceptance of telepsychotherapy and intention towards using it in the future. Future studies on the convergent and predictive validity of the UTAUT-T are warranted.

Interpersonal and Social Functioning Among Psychotherapy Patients: The Indirect Effect of Childhood Adversity.

ABSTRACT: This study examined the mediating role of pathogenic beliefs on the relationship between patients' recollections of experienced adverse parenting in childhood and adult interpersonal and social problems. A total of 210 psychotherapy outpatients rated their experiences of perceived adverse parenting in childhood and completed measures of psychological distress, interpersonal problems and social impairment, and internalized beliefs about self and others. Significant mediation effects were observed for two of the three belief domains: "cannot rely on others" and "undeserving." Although both were significant mediators between adverse parenting and symptom distress, only "cannot rely on others" was a significant mediator predicting interpersonal problems, and only "undeserving" was a significant mediator predicting impaired social functioning. Thus, patients' underlying convictions regarding their self-worth seem to play a role in the ability to develop social roles, whereas the beliefs about the steadfastness of others play an important role in the capacity for interpersonal relating.

Assessing internalized beliefs: Development of the Pathogenic Belief Scale.

The way that people internalize adverse experiences plays an important role in the development of psychopathology. The Pathogenic Belief Scale (PBS) is intended to operationalize a transtheoretical understanding of repetitive patterns of emotion-laden beliefs that develop in childhood and continue to influence people's current experience. Using a cross-sectional survey design, we recruited a large heterogeneous sample of 246 clinic outpatients and 732 adults in the community. Besides the PBS, measures of adverse parenting experiences and common psychopathology were administered. An exploratory factor analysis of the total sample of 978 participants was conducted followed by a convergent validity analysis for the 246 clinic outpatients. The three-factor solution included "cannot rely on others," "undeserving," and "interpersonal guilt," and it showed good psychometric properties, including convergent validity with the measures of adverse parenting experiences and psychopathology. The 34-item PBS offers a promising self-report measure that could help delineate and understand the pathogenic beliefs that heterogeneous samples of patients may hold. Pathogenic beliefs may be relevant to the psychotherapy process, regardless of model or theoretical context.

Perceived Adverse Parenting in Childhood and Psychological Distress Among Psychotherapy Patients: The Mediating Role of Pathogenic Beliefs.

ABSTRACT: The way people derive inferences from actual adverse experiences plays an important role in the development of psychopathology. This study aims to examine the mediating role of pathogenic beliefs (i.e., emotion-laden, powerful, painful convictions about self and others) on the relation between perceived adverse parenting behaviors in childhood and subsequent adult psychopathology. Participants (mostly Caucasian and heterosexual) were 204 consecutively admitted patients with a range of psychological difficulties, including depression, anxiety, and interpersonal problems, at a low-fee outpatient clinic. Participants completed standard self-report assessments of perceived parental style, depressive and anxiety symptoms, and a clinically derived measure of pathogenic beliefs. We examined the indirect effects of adverse parenting on anxiety and depressive symptom severity through pathogenic beliefs. Pathogenic beliefs reflecting the unreliability of others significantly mediated the relationship between adverse parenting and anxiety symptoms. The other mediation model is consistent with the theory that perceived adverse parenting contributes to the severity of depressive symptoms through beliefs about not being deserving and other people being unreliable. Within the limitations of the cross-sectional, retrospective, and self-report nature of the data, our results seem to suggest that attending to intermediary subjective beliefs might be important in understanding psychopathology development in the context of childhood adversity. Aiming to modify the beliefs in therapy might modify the symptoms. However, this would remain to be demonstrated through formal intervention research.

Transcriptional burst frequency and burst size are equally modulated across the human genome.

Gene expression occurs either as an episodic process, characterized by pulsatile bursts, or as a constitutive process, characterized by a Poisson-like accumulation of gene products. It is not clear which mode of gene expression (constitutive versus bursty) predominates across a genome or how transcriptional dynamics are influenced by genomic position and promoter sequence. Here, we use time-lapse fluorescence microscopy to analyze 8,000 individual human genomic loci and find that at virtually all loci, episodic bursting--as opposed to constitutive expression--is the predominant mode of expression. Quantitative analysis of the expression dynamics at these 8,000 loci indicates that both the frequency and size of the transcriptional bursts varies equally across the human genome, independent of promoter sequence. Strikingly, weaker expression loci modulate burst frequency to increase activity, whereas stronger expression loci modulate burst size to increase activity. Transcriptional activators such as trichostatin A (TSA) and tumor necrosis factor α (TNF) only modulate burst size and frequency along a constrained trend line governed by the promoter. In summary, transcriptional bursting dominates across the human genome, both burst frequency and burst size vary by chromosomal location, and transcriptional activators alter burst frequency and burst size, depending on the expression level of the locus.

Noise in biological circuits.

Noise biology focuses on the sources, processing, and biological consequences of the inherent stochastic fluctuations in molecular transitions or interactions that control cellular behavior. These fluctuations are especially pronounced in small systems where the magnitudes of the fluctuations approach or exceed the mean value of the molecular population. Noise biology is an essential component of nanomedicine where the communication of information is across a boundary that separates small synthetic and biological systems that are bound by their size to reside in environments of large fluctuations. Here we review the fundamentals of the computational, analytical, and experimental approaches to noise biology. We review results that show that the competition between the benefits of low noise and those of low population has resulted in the evolution of genetic system architectures that produce an uneven distribution of stochasticity across the molecular components of cells and, in some cases, use noise to drive biological function. We review the exact and approximate approaches to gene circuit noise analysis and simulation, and review many of the key experimental results obtained using flow cytometry and time-lapse fluorescent microscopy. In addition, we consider the probative value of noise with a discussion of using measured noise properties to elucidate the structure and function of the underlying gene circuit. We conclude with a discussion of the frontiers of and significant future challenges for noise biology.

Using noise to probe and characterize gene circuits.

Stochastic fluctuations (or "noise") in the single-cell populations of molecular species are shaped by the structure and biokinetic rates of the underlying gene circuit. The structure of the noise is summarized by its autocorrelation function. In this article, we introduce the noise regulatory vector as a generalized framework for making inferences concerning the structure and biokinetic rates of a gene circuit from its noise autocorrelation function. Although most previous studies have focused primarily on the magnitude component of the noise (given by the zero-lag autocorrelation function), our approach also considers the correlation component, which encodes additional information concerning the circuit. Theoretical analyses and simulations of various gene circuits show that the noise regulatory vector is characteristic of the composition of the circuit. Although a particular noise regulatory vector does not map uniquely to a single underlying circuit, it does suggest possible candidate circuits, while excluding others, thereby demonstrating the probative value of noise in gene circuit analysis.

Frequency domain analysis of noise in simple gene circuits.

Recent advances in single cell methods have spurred progress in quantifying and analyzing stochastic fluctuations, or noise, in genetic networks. Many of these studies have focused on identifying the sources of noise and quantifying its magnitude, and at the same time, paying less attention to the frequency content of the noise. We have developed a frequency domain approach to extract the information contained in the frequency content of the noise. In this article we review our work in this area and extend it to explicitly consider sources of extrinsic and intrinsic noise. First we review applications of the frequency domain approach to several simple circuits, including a constitutively expressed gene, a gene regulated by transitions in its operator state, and a negatively autoregulated gene. We then review our recent experimental study, in which time-lapse microscopy was used to measure noise in the expression of green fluorescent protein in individual cells. The results demonstrate how changes in rate constants within the gene circuit are reflected in the spectral content of the noise in a manner consistent with the predictions derived through frequency domain analysis. The experimental results confirm our earlier theoretical prediction that negative autoregulation not only reduces the magnitude of the noise but shifts its content out to higher frequency. Finally, we develop a frequency domain model of gene expression that explicitly accounts for extrinsic noise at the transcriptional and translational levels. We apply the model to interpret a shift in the autocorrelation function of green fluorescent protein induced by perturbations of the translational process as a shift in the frequency spectrum of extrinsic noise and a decrease in its weighting relative to intrinsic noise.

The sorting direct method for stochastic simulation of biochemical systems with varying reaction execution behavior.

A key to advancing the understanding of molecular biology in the post-genomic age is the development of accurate predictive models for genetic regulation, protein interaction, metabolism, and other biochemical processes. To facilitate model development, simulation algorithms must provide an accurate representation of the system, while performing the simulation in a reasonable amount of time. Gillespie's stochastic simulation algorithm (SSA) accurately depicts spatially homogeneous models with small populations of chemical species and properly represents noise, but it is often abandoned when modeling larger systems because of its computational complexity. In this work, we examine the performance of different versions of the SSA when applied to several biochemical models. Through our analysis, we discover that transient changes in reaction execution frequencies, which are typical of biochemical models with gene induction and repression, can dramatically affect simulator performance. To account for these shifts, we propose a new algorithm called the sorting direct method that maintains a loosely sorted order of the reactions as the simulation executes. Our measurements show that the sorting direct method performs favorably when compared to other well-known exact stochastic simulation algorithms.

Analysis of noise in quorum sensing.

Noise may play a pivotal role in gene circuit functionality, as demonstrated for the genetic switch in the bacterial phage lambda. Like the lambda switch, bacterial quorum sensing (QS) systems operate within a population and contain a bistable switching element, making it likely that noise plays a functional role in QS circuit operation. Therefore, a detailed analysis of the noise behavior of QS systems is needed. We have developed a set of tools generally applicable to the analysis of gene circuits, with an emphasis on investigations in the frequency domain (FD), that we apply here to the QS system in the marine bacterium Vibrio fischeri. We demonstrate that a tight coupling between exact stochastic simulation and FD analysis provides insights into the structure/function relationships in the QS circuit. Furthermore, we argue that a noise analysis is incomplete without consideration of the power spectral densities (PSDs) of the important molecular output signals. As an example we consider reversible reactions in the QS circuit, and show through analysis and exact stochastic simulation that these circuits make significant and dynamic modifications to the noise spectra. In particular, we demonstrate a "whitening" effect, which occurs as the noise is processed through these reversible reactions.