A brief conversation analytic communication intervention can change history-taking in the seizure clinic

Developing and validating the Unhurried Conversations Assessment Tool (UCAT)

OBJECTIVE

Given the importance of unhurried conversations for providing careful and kind care, we sought to create, test, and validate the Unhurried Conversations Assessment Tool (UCAT) for assessing the unhurriedness of patient-clinician consultations.

METHODS

In the first two phases, the unhurried conversation dimensions were identified and transformed into an assessment tool. In the third phase, two independent raters used UCAT to evaluate the unhurriedness of 100 randomly selected consultations from 184 videos recorded for a large research trial. UCAT's psychometric properties were evaluated using this data.

RESULTS

UCAT demonstrates content validity based on the literature and expert review. EFA and reliability analyses confirm its construct validity and internal consistency. The seven formative dimensions account for 89.93% of the variance in unhurriedness, each displaying excellent internal consistency (α > 0.90). Inter-rater agreement for the overall assessment item was fair (ICC = 0.59), with individual dimension ICCs ranging from 0.26 (poor) to 0.95 (excellent).

CONCLUSION

UCAT components comprehensively assess the unhurriedness of consultations. The tool exhibits content and construct validity and can be used reliably.

PRACTICE IMPLICATIONS

UCAT's design and psychometric properties make it a practical and efficient tool. Clinicians can use it for self-evaluations and training to foster unhurried conversations.

"Are you otherwise fit and well?": Past medical history questions in UK paediatric consultations

Accurate diagnosis and treatment depend upon detailed knowledge of both the child's presenting symptoms and their past medical history. However, the process of soliciting past medical history has never been subject to systematic scrutiny in actual clinical practice.

OBJECTIVE

To examine the function of the question "are you otherwise fit and well?" to elicit a child's general medical history in UK paediatric allergy outpatient consultations.

METHODS

Examination of 30 video-recorded UK paediatric outpatient consultations involving children (2-10 years), caregivers, and one doctor. We identified, transcribed, and interrogated 13 examples, deploying the systematic and rigorous method of conversation analysis to elucidate the question's micro-design elements and their consequences for the consultation's trajectory.

RESULTS

Asking "Are you otherwise fit and well?" is built to efficiently solicit a problem-free report of good health. Nonetheless patients can and do raise other relevant matters. In practice, the question initiates several interactional matters simultaneously: establishing/resolving (mis)understandings of "fitness" and "wellness"; negotiating opportunities for children's participation; and importantly, a shift towards discussing more general wellbeing.

CONCLUSION

Past medical history questions unavoidably generate broader interactional matters which are skilfully resolved in real-time between clinicians, caregivers, and children.

PRACTICE IMPLICATIONS

Clinical training could be greatly enhanced by integrating insights into the interactional consequences of asking questions, particularly in the complex multiparty environment of paediatrics. While the question 'Are you otherwise fit and well' clearly serves an important function, clinicians should be alert to the possible problems it might raise, especially when directed towards younger children.

Differentiating between epileptic and functional/dissociative seizures using semantic content analysis of transcripts of routine clinic consultations

The common causes of Transient Loss of Consciousness (TLOC) are syncope, epilepsy, and functional/dissociative seizures (FDS). Simple, questionnaire-based decision-making tools for non-specialists who may have to deal with TLOC (such as clinicians working in primary or emergency care) reliably differentiate between patients who have experienced syncope and those who have had one or more seizures but are more limited in their ability to differentiate between epileptic seizures and FDS. Previous conversation analysis research has demonstrated that qualitative expert analysis of how people talk to clinicians about their seizures can help distinguish between these two TLOC causes. This paper investigates whether automated language analysis - using semantic categories measured by the Linguistic Inquiry and Word Count (LIWC) toolkit - can contribute to the distinction between epilepsy and FDS. Using patient-only talk manually transcribed from recordings of 58 routine doctor-patient clinic interactions, we compared the word frequencies for 21 semantic categories and explored the predictive performance of these categories using 5 different machine learning algorithms. Machine learning algorithms trained using the chosen semantic categories and leave-one-out cross-validation were able to predict the diagnosis with an accuracy of up to 81%. The results of this proof of principle study suggest that the analysis of semantic variables in seizure descriptions could improve clinical decision tools for patients presenting with TLOC.

Knowledge and emotional attitudes of health care practitioners regarding patients with psychogenic nonepileptic seizures

BACKGROUND

Psychogenic nonepileptic seizures (PNESs) are paroxysmal events that resemble epileptic seizures without concomitant changes in electroencephalograms (EEGs) or any other physiological cause. These seizures are one of the most common and dramatic conversion disorders. First responders treat many PNES patients with unnecessary emergency abortive medication and sometimes even intubate them. Several of our PNES patients have complained they have experienced harsh attitudes from health care practitioners (HCPs), especially during their stay in the emergency room (ER).

OBJECTIVE

To assess the emotional attitude of HCPs toward PNES patients.

METHODS

We handed a questionnaire containing 23 questions regarding PNES patients to HCPs from emergency medicine, internal medicine, and neurology disciplines. The questions dealt with three categories: diagnosis, management, and emotional attitudes.

RESULTS

Overall, 47 HCPs participated in this study: 11 ER, 18 internal medicine, and 18 neurology practitioners. The HCP from those disciplines showed high knowledge and good management practice of PNES patients. On the other hand, the HCPs agreed with most emotional attitude statements regarding PNES patients, reflecting a high percentage of negative emotional attitudes toward this group of patients. We did not find any correlation between negative emotional attitude and HCP department, profession, or seniority.

CONCLUSIONS

Although HCPs in our center perform good management practice regarding PNES patients, most reported a negative emotional attitude. This finding implies that what PNES patients feel regarding the harsh attitudes is also reflected by HCP views. Emotional attitudes towards PNES patients may not depend solely on the level of knowledge of the HCPs.

Feasibility of using an automated analysis of formulation effort in patients' spoken seizure descriptions in the differential diagnosis of epileptic and nonepileptic seizures

OBJECTIVE

There are three common causes of Transient Loss of Consciousness (TLOC), syncope, epileptic and psychogenic nonepileptic seizures (PNES). Many individuals who have experienced TLOC initially receive an incorrect diagnosis and inappropriate treatment. Whereas syncope can be distinguished relatively easily with a small number of "yes"/"no" questions, the differentiation of the other two causes of TLOC is more challenging. Previous qualitative research based on the methodology of Conversation Analysis has demonstrated that the descriptions of epileptic seizures contain more formulation effort than accounts of PNES. This research investigates whether features likely to reflect the level of formulation effort can be automatically elicited from audio recordings and transcripts of speech and used to differentiate between epileptic and nonepileptic seizures.

METHOD

Verbatim transcripts of conversations between patients and neurologists were manually produced from video and audio recordings of 45 interactions (21 epilepsy and 24 PNES). The subsection of each transcript containing the person's account of their first seizure was manually extracted for the analysis. Seven automatically detectable features were designed as markers of formulation effort. These features were used to train a Random Forest machine learning classifier.

RESULT

There were significantly more hesitations and repetitions in descriptions of epileptic than nonepileptic seizures. Using a nested leave-one-out cross validation approach, 71% of seizures were correctly classified by the Random Forest classifier.

DISCUSSION

This pilot study provides proof of principle that linguistic features that have been automatically extracted from audio recordings and transcripts could be used to distinguish between epileptic seizures and PNES and thereby contribute to the differential diagnosis of TLOC. Future research should explore whether additional observations can be incorporated into a diagnostic stratification tool and compare the performance of these features when they are combined with additional information provided by patients and witnesses about seizure manifestations and medical history.

How and why children instigate talk in pediatric allergy consultations: A conversation analytic account

Involving children in their healthcare encounter is a national and international priority. While existing research has examined the ways in which children are recruited to participate in the consultation, no work has examined whether and how children instigate talk, and the extent to which their contributions are successful. This paper presents a conversation analysis of a selection of 10 out of 30 video recordings in which children aged 4-10 years instigate talk during consultations they attend with their parents/carers at a UK pediatric clinic. The analysis reveals for the first time that children do successfully instigate talk without being asked or selected in 22 episodes during their consultation with the doctor. Children most frequently address their parent/carer (16/22). They capitalize on specific contexts within the consultation to instigate talk, for example: history-taking questions about what they ate or how they reacted (10/22); or discussions surrounding the child's feelings or sensations following the skin-prick testing (7/22) - aspects of experience to which they have access. Children's non-solicited talk necessarily occurs when they are not currently active participators and children engage in extra interactional work including various verbal strategies (summons and prosodic variations) and non-verbal resources (tapping and gaze) to break into the interaction. The benefits of their contributions include the opportunity to affirm the child's role as a legitimate contributor, and the potential for additional medically-relevant information to arise which could enrich the clinical process. Our analysis shows that the previously overlooked phenomenon of children instigating talk, although not common, can play a crucial role in the consultation. We suggest that strategies to increase such involvement have the potential to augment the healthcare process. Our findings offer a critical baseline for the introduction of new consultations models, such as digital appointments, which may exclude some children completely.

An Interactional Profile to Assist the Differential Diagnosis of Neurodegenerative and Functional Memory Disorders

OBJECTIVE

Specialist services for dementia are seeing an increasing number of patients. We investigated whether interactional and linguistic features in the communication behavior of patients with memory problems could help distinguish between those with problems secondary to neurological disorders (ND) and those with functional memory disorder (FMD).

METHODS

In part 1 of this study, a diagnostic scoring aid (DSA) was developed encouraging linguists to provide quantitative ratings for 14 interactional features. An optimal cut-off differentiating ND and FMD was established by applying the DSA to 30 initial patient-doctor memory clinic encounters. In part 2, the DSA was tested prospectively in 10 additional cases analyzed independently by 2 conversation analysts blinded to medical information.

RESULTS

In part 1, the median score of the DSA was +5 in ND and -5 in FMD (P<0.001). The optimal numeric DSA cut-off (+1) identified patients with ND with a sensitivity of 86.7% and a specificity of 100%. In part 2, DSA scores of rater 1 correctly predicted 10/10 and those of rater 2 predicted 9/10 diagnoses.

CONCLUSIONS

This study indicates that interactional and linguistic features can help distinguish between patients developing dementia and those with FMD and could aid the stratification of patients with memory problems.

Value of witness observations in the differential diagnosis of transient loss of consciousness

OBJECTIVE

This retrospective study explores to what extent additional information from event witnesses provided using the novel 31-item Paroxysmal Event Observer (PEO) Questionnaire improves the differentiation among epilepsy, syncope, and psychogenic nonepileptic seizures (PNES) achievable with information provided by patients alone.

METHODS

Patients with transient loss of consciousness caused by proven epilepsy (n = 86), syncope (n = 79), or PNES (n = 84) attending specialist neurology/syncope services in the United Kingdom and event observers provided Paroxysmal Event Profile (PEP), PEO, and personal information (PI) (e.g., sex, age, medical history) data. PEO data were subjected to exploratory factor analysis (EFA) followed by confirmatory factor analysis (CFA). PEO, PEP, and PI data were used separately and in combination to differentiate diagnoses by pairwise and multinomial logistic regressions. Predicted diagnoses were compared with gold standard medical diagnoses.

RESULTS

EFA/CFA identified a 4-factor structure of the PEO based on 26/31 questionnaire items with loadings ≥0.4. Observer-reported factors alone differentiated better between syncope and epilepsy than patient-reported factors (accuracy: 96% vs 85%, p = 0.0004). Observer-reported data improved accuracy over differentiation based on patient-reported data alone from 90% to 100% between syncope and epilepsy (p = 0.005), 76% to 83% between epilepsy and PNES (p = 0.006), and 93% to 95% between syncope and PNES (p = 0.098).

CONCLUSIONS

Information from observers can make an important contribution to the differentiation of epilepsy from syncope or PNES but adds less to that of syncope from PNES.

Identifying patterns of communication in patients attending memory clinics: a systematic review of observations and signs with potential diagnostic utility

BACKGROUND

Subjective cognitive complaints are commonly encountered in primary care and often result in memory clinic referral. However, meta-analyses have shown that such concerns do not consistently correspond to objective memory impairment or predict future dementia. Memory clinic referrals are increasing, with greater proportions of patients attending who do not have dementia. Studies of interaction during memory clinic assessments have identified conversational profiles that can differentiate between dementia and functional disorders of memory. To date, studies exploring communication patterns for the purpose of diagnosis have not been reviewed. Such profiles could reduce unnecessary investigations in patients without dementia.

AIM

To identify and collate signs and observable features of communication, which could clinically differentiate between dementia and functional disorders of memory.

DESIGN AND SETTING

This was a systematic review and synthesis of evidence from studies with heterogeneous methodologies.

METHOD

A qualitative, narrative description and typical memory clinic assessment were employed as a framework.

RESULTS

Sixteen studies met the criteria for selection. Two overarching themes emerged: 1) observable clues to incapacity and cognitive impairment during routine assessment and interaction, and 2) strategies and accounts for loss of abilities in people with dementia.

CONCLUSION

Whether the patient attends with a companion, how they participate, give autobiographical history, demonstrate working memory, and make qualitative observations during routine cognitive testing are all useful in building a diagnostic picture. Future studies should explore these phenomena in larger populations, over longer periods, include dementia subtypes, and develop robust definitions of functional memory disorders to facilitate comparison.

The first seizure as an indicator of epilepsy

PURPOSE OF REVIEW

Optimal treatment of a possible first seizure depends on the determination if the paroxysmal event was an epileptic seizure and was on an accurate assessment of the recurrence risk. This review summarizes evidence from the last 5 years addressing the following questions: Is it an epileptic seizure? Is it a first seizure? When does a first seizure indicate epilepsy?

RECENT FINDINGS

The acts of taking and interpreting the history from patients and witnesses continue to be the most important tools in the diagnosis of first seizures. Assessment tools based on factual questions and the observation of patients' conversational behaviour can contribute to the differentiation of patients with epileptic seizures from those who have experienced other types of transient loss of consciousness (TLOC). At present, only about 40% of patients are seen after their very first seizure. Tests have a limited role in the initial diagnosis of a seizure but help to determine the recurrence risk based on the cause. A remote symptomatic cause and detection of epileptiform discharges are associated with a recurrence risk of at least 60% and allow a diagnosis of epilepsy after a first seizure. The risk of recurrence after an acute symptomatic first seizure is well below 60%.

SUMMARY

Expert history-taking continues to be the most important tool in the diagnosis of a first seizure. Cause is the most important determinant of the recurrence risk. Unfortunately, there is currently no formula enabling a precise calculation of an individualized recurrence risk.

Differentiating PNES from epileptic seizures using conversational analysis

We applied conversation analysis in an unselected continuous series of 70 patients to discriminate patients with psychogenic nonepileptic seizures (PNES) from patients with epilepsy. Two psychologists examined the patients' recorded reports. Patients were also submitted to an extensive neuropsychological battery in order to verify whether specific cognitive deficits or mental health problems are typical of patients with PNES and whether some cognitive deficits could prevent the correct diagnosis. The results showed a good percentage of correct diagnosis, with a sensitivity of 0.795 and a specificity of 0.83, while no difference in the cognitive profile was found between patients with PNES and patients with epilepsy. The results also suggest that psychologists can apply the conversation analysis as well as linguists, which is an important finding since psychologists are employed in specialized centers, while linguists in general are not part of the team.

Is it acceptable to video-record palliative care consultations for research and training purposes? A qualitative interview study exploring the views of hospice patients, carers and clinical staff

BACKGROUND

Research using video recordings can advance understanding of healthcare communication and improve care, but making and using video recordings carries risks.

AIM

To explore views of hospice patients, carers and clinical staff about whether videoing patient-doctor consultations is acceptable for research and training purposes.

DESIGN

We used semi-structured group and individual interviews to gather hospice patients, carers and clinical staff views. We used Braun and Clark's thematic analysis.

SETTING/PARTICIPANTS

Interviews were conducted at one English hospice to inform the development of a larger video-based study. We invited patients with capacity to consent and whom the care team judged were neither acutely unwell nor severely distressed (11), carers of current or past patients (5), palliative medicine doctors (7), senior nurses (4) and communication skills educators (5).

RESULTS

Participants viewed video-based research on communication as valuable because of its potential to improve communication, care and staff training. Video-based research raised concerns including its potential to affect the nature and content of the consultation and threats to confidentiality; however, these were not seen as sufficient grounds for rejecting video-based research. Video-based research was seen as acceptable and useful providing that measures are taken to reduce possible risks across the recruitment, recording and dissemination phases of the research process.

CONCLUSION

Video-based research is an acceptable and worthwhile way of investigating communication in palliative medicine. Situated judgements should be made about when it is appropriate to involve individual patients and carers in video-based research on the basis of their level of vulnerability and ability to freely consent.

Neurologists can identify diagnostic linguistic features during routine seizure clinic interactions: results of a one-day teaching intervention

The diagnostic distinction between epilepsy and psychogenic nonepileptic seizures (PNES) can be challenging. Previous studies have demonstrated that experts in conversation analysis can identify linguistic and interactional features in transcripts and recordings of interviews with patients that reliably distinguish between epilepsy and PNES. In this study, ten senior neurology trainees took part in a one-day intervention workshop about linguistic and interactional differences in the conversation behavior of patients with epilepsy and those with PNES. Participants were familiarized with a 12-item questionnaire designed to capture their conversational observations immediately after talking to a patient with seizures. After the intervention, 55 initial outpatient visits of patients referred to seizure clinics were video and audio recorded. All medical diagnoses were confirmed two years after initial presentation on the basis of a chart review (including MRI and EEG findings) by a fully trained epilepsy expert. Postvisit questionnaires relating to patients confirmed to have epilepsy (n=20) or PNES (n=13) were analyzed. Doctors' mean responses to 6 of the 12 questions about linguistic and interactional observations differed significantly between the groups with epilepsy and PNES. Receiver operating curve analysis showed that a summation scale based on items demonstrating significant between-group differences correctly classified 81.8% of patients as having epilepsy or PNES. This study shows that a brief Conversation Analytic teaching intervention can enable neurologists to identify linguistic and interactional features supporting the differentiation of epilepsy and PNES as they take their patients' history in routine seizure clinic consultations, potentially improving diagnostic accuracy.