Role of psychological questionnaires in clinical practice and research within functional gastrointestinal disorders

Intestinal Epithelial Serotonin as a Novel Target for Treating Disorders of Gut-Brain Interaction and Mood

BACKGROUND & AIMS

Mood disorders and disorders of gut-brain interaction (DGBI) are highly prevalent, commonly comorbid, and lack fully effective therapies. Although selective serotonin reuptake inhibitors (SSRIs) are first-line pharmacological treatments for these disorders, they may impart adverse effects, including anxiety, anhedonia, dysmotility, and, in children exposed in utero, an increased risk of cognitive, mood, and gastrointestinal disorders. SSRIs act systemically to block the serotonin reuptake transporter and enhance serotonergic signaling in the brain, intestinal epithelium, and enteric neurons. Yet, the compartments that mediate the therapeutic and adverse effects of SSRIs are unknown, as is whether gestational SSRI exposure directly contributes to human DGBI development.

METHODS

We used transgenic, surgical, and pharmacological approaches to study the effects of intestinal epithelial serotonin reuptake transporter or serotonin on mood and gastrointestinal function, as well as relevant communication pathways. We also conducted a prospective birth cohort study to assess effects of gestational SSRI exposure on DGBI development.

RESULTS

Serotonin reuptake transporter ablation targeted to the intestinal epithelium promoted anxiolytic and antidepressive-like effects without causing adverse effects on the gastrointestinal tract or brain; conversely, epithelial serotonin synthesis inhibition increased anxiety and depression-like behaviors. Afferent vagal pathways were found to be conduits by which intestinal epithelial serotonin affects behavior. In utero SSRI exposure is a significant and specific risk factor for development of the DGBI, functional constipation, in the first year of life, irrespective of maternal depressive symptoms.

CONCLUSION

These findings provide fundamental insights into how the gastrointestinal tract modulates emotional behaviors, reveal a novel gut-targeted therapeutic approach for mood modulation, and suggest a new link in humans between in utero SSRI exposure and DGBI development.

Evaluation of comorbid psychological disorders in functional gastrointestinal disorders patients by vibraimage technology: protocol of a prospective, single-center trial

Introduction

Functional gastrointestinal disorders (FGIDs) affect over 40% of individuals globally, and impact the quality of life. A significant portion of FGIDs patients comorbids with anxiety and depression. Traditional screening tools for psychological disorders may lack comprehensiveness. Vibraimage technology currently enables non-contact, objective analysis of psychological indicators through high-frame-rate cameras and computer analysis of micro-movements. Therefore, this study aims to (1) explore the use of vibraimage technology as a non-contact objective method to assess the psychological status of FGIDs patients, comparing this technology with the Hospital Anxiety and Depression Scale (HADS) to evaluate its screening efficacy, and (2) observe the therapeutic outcomes of FGIDs patients with or without comorbid psychological disorders after the same conventional treatment.

Methods

This is a prospective, single-center observational trial. 276 FGIDs outpatients who visit Peking Union Medical College Hospital will be evaluated simultaneously by HADS and vibraimage technology, then to evaluate the screen efficacy of this technology. The patients will be allocated into two groups (those with or without psychological disorders). The primary endpoint is the overall rate of improvement, specifically referring to the proportion of patients who achieved Likert scores greater than or equal to 4. The secondary endpoints encompass evaluating whether there is a reduction of more than 50% in symptom evaluation scores such as IBS-SSS. Additionally, the study will assess changes in health status and quality of life using SF-36 questionnaires and the patients' satisfaction with treatment. Furthermore, psychological status will be reassessed by vibraimage technology and HADS after treatment to evaluate the effect of combined psychological factors on FGIDs treatment.

One More Tool in the Tool Belt: A Qualitative Interview Study Investigating Patient and Clinician Opinions on the Integration of Psychometrics Into Routine Testing for Disorders of Gut-Brain Interaction

Introduction Disorders of gut-brain interaction (DGBIs) encompass a common group of disorders characterised by chronic gastrointestinal symptoms. Psychological comorbidities are common in patients with DGBIs and are linked with poorer patient outcomes. Consequently, assessing and managing mental wellbeing may lead to improvements in symptoms and quality of life. Methods This study aimed to explore patients' and clinicians' opinions on integrating psychometrics into routine DGBI testing. Semi-structured interviews were conducted with 16 patients with gastroduodenal DGBI and 19 clinicians who see and treat these patients. Interviews were analysed using inductive, reflexive thematic analysis. Results Three key clinician themes were developed: (1) psychology as part of holistic care, emphasising the importance of a multidisciplinary approach; (2) the value of psychometrics in clinical practice, highlighting their potential for screening and expanding management; and (3) navigating barriers to utilising psychometrics, addressing the need for standardisation to maintain the therapeutic relationship. Four key patient themes were developed: (1) the utility of psychometrics in clinical care, reflecting the perceived benefits; (2) openness to psychological management, indicating patients' willingness to explore psychological treatments; (3) concerns with psychological integration, addressing potential stigma and fear of labelling; and (4) the significance of clinician factors, emphasising the importance of clinician bedside manner, knowledge and collaboration. Conclusions These themes demonstrate that patients and clinicians see value in integrating psychometrics into routine DGBI testing. Despite potential barriers, psychometrics advance patient and clinician understanding and facilitate multidisciplinary management. Recommendations for navigating challenges were provided, and considering these, patients and clinicians supported the use of psychometrics as screening tools for patients with DGBIs.

Development and validation of the Alimetry Gut-Brain Wellbeing Survey: a novel patient-reported mental health scale for patients with chronic gastroduodenal symptoms

Objective

There is currently a lack of validated questionnaires designed specifically to assess mental health within patients with chronic gastroduodenal symptoms. This research describes the multi-phase process used to develop and validate a novel mental health scale for patients with chronic gastroduodenal symptoms, the Alimetry® Gut-Brain Wellbeing (AGBW) Survey.

Methods

A patient-centered multi-phase process was implemented. In Phase 1, the most relevant concepts for this patient population were selected from existing mental health scales, using data from 79 patients. In Phase 2, an interdisciplinary panel of experts generated scale items. In Phase 3, the scale underwent pre-testing with gastroenterologists (n = 9), health psychologists (n = 3), and patients (n = 12), with feedback incorporated over multiple rounds. Lastly, the psychometric properties of the scale were assessed in a sample of 311 patients via an online survey.

Results

The AGBW Survey comprises a patient preface, 10 close-ended questions, and an optional open-ended question. This multidimensional scale assesses general mental health, alongside specific subscales relating to depression, stress, and anxiety. The subscale and total scores demonstrated high internal consistency (α = 0.91 for the total scale; α = 0.72-0.86 for subscales) and good convergent, divergent, concurrent validity, and known groups validity, with large effect sizes.

Conclusion

The AGBW Survey is a brief, valid, and reliable scale for assessing mental health in patients with chronic gastroduodenal symptoms. It can be used as a tool to complement physiological tests and has the potential to guide psychological referrals, inform multidisciplinary management, and evaluate treatment outcomes.

Cognitive behavioural therapy-based interventions for gastroduodenal disorders of gut-brain interaction: A systematic review

OBJECTIVE

Cognitive behavioural therapy (CBT) is increasingly used to manage Disorders of Gut-Brain Interaction (DGBIs). This systematic review aimed to review the evidence for the effectiveness of CBT-based interventions for patients with gastroduodenal DGBIs.

METHODS

Medline, Embase, PubMed, Cochrane Central, and Scopus were searched in July 2022. Studies were included if they investigated the effects of a CBT-based intervention on gastrointestinal symptoms and/or psychological outcomes pre- and post-intervention in patients with gastroduodenal DGBIs. Case studies, studies not in English, and studies with patients under 18 years were excluded. Results were synthesised narratively, and standardised effect sizes were calculated where possible.

RESULTS

Nine studies (seven RCTs and two pre/post studies) were identified, with data reported in 10 articles (total N = 602). The studies investigated patients with functional dyspepsia (n = 7), rumination syndrome (n = 1), and supragastric belching (n = 1). The studies had heterogeneous interventions, methodologies, and outcomes, precluding meta-analysis, as well as a moderate-high risk of bias and high drop-outs rates. Findings demonstrated decreased gastrointestinal symptoms and improved anxiety, depression, and quality of life, from pre- to post-intervention, with medium to large effect sizes for symptoms and small to large effect sizes for psychological outcomes. Efficacy was maintained at follow-up, up to one year later.

CONCLUSIONS

This review suggests promising evidence that CBT effectively improves gastrointestinal symptoms and psychological outcomes in patients with gastroduodenal DGBIs. However, heterogeneity, risk of bias, and lack of statistical reporting were noted, indicating the need for more robust research and standardisation.

Understanding and managing patients with overlapping disorders of gut-brain interaction

Disorders of gut-brain interaction (DGBI) are frequently encountered in clinical practice, and recommendations for diagnosis and management are well established. In a large subset of patients, more than one DGBI diagnosis is present. This group of patients with more than one DGBI diagnosis have higher symptom severity and impact than patients with only one DGBI diagnosis, and the management approach is not well established for those with overlapping diagnoses. This Review aims to guide clinicians to understand, recognise, and manage overlapping DGBI by identifying causes and pitfalls of overlap conditions, and presenting potential practical approaches to diagnosis, treatment, and follow-up. Several clinical factors can contribute to finding overlapping DGBI, including the anatomical basis of the Rome diagnostic criteria, the potential confusion of symptom descriptors, and patients' biases towards higher symptom intensity ratings. Overlapping DGBI could also be caused by mechanistic factors such as pathophysiological mechanisms involving multiple gastrointestinal segments, and the effect of disorders in one segment on sensorimotor function in remote gastrointestinal parts, through neural or hormonal signalling. Key initial steps in the management of overlapping DGBI are detailed history taking, which can be facilitated using pictograms; carefully assessing the relative timing and cohesion of different symptoms; and recognising associated psychosocial dysfunction. Unnecessary technical investigations and complex combination treatment schedules should be avoided. Based on the identification of the dominant symptom pattern and putative underlying pathophysiological mechanisms, a single treatment modality should preferably be initiated, considering the efficacy spectrum of different therapies. Follow-up of the patient's condition allows the therapeutic approach to be adjusted as needed, while avoiding unnecessary additional technical investigations.

A psychological symptom based machine learning model for clinical evaluation of irritable bowel syndrome

Background: Irritable bowel syndrome (IBS) is a chronic functional gastrointestinal disorder characterized by recurrent abdominal pain associated with alterations  in stool form and/or stool frequency. Co-morbidities such as anxiety, depression, fatigue, and insomnia are frequently reported by patients suffering from IBS. Identification of these symptoms should thus be an integral part of an IBS assessment.      However, an optimal tool to screen for core psychological symptoms in IBS is still  missing. Here, we aim to develop a psychological symptom based machine learning model to efficiently help clinicians to identify patients suffering from IBS. Methods: We developed a machine learning workflow to select the most significant psychological features associated with IBS in a dataset including 49 patients with IBS and 35 healthy controls. These features were used to train three different types of machine learning models: logistic regression, decision trees and support vector machine classifiers; which were validated on a holdout validation dataset and an unseen test set. The performance of these models was compared in terms of balanced accuracy scores. Results: A logistic regression model including a combination of symptom features associated with anxiety and fatigue resulted in a balanced accuracy score of 0.93 (0.81-1.0) on unseen test data and outperformed the other comparable models. The same model correctly identified all patients with IBS in a test set (recall score 1) and misclassified one non-IBS subject (precision score 0.91). A complementary post-hoc leave-one-out cross validation analysis including the same symptom features showed similar, but slightly inferior results (balanced accuracy 0.84, recall 0.88, precision 0.86). Conclusions: Inclusion of machine learning based psychological evaluation can complement and improve existing clinical procedure for diagnosis of IBS.