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Objective: The instrument THERapy-related InterACTion (THER-I-ACT) was developed to document therapeutic interactions comprehensively in the human therapist–patient setting. Here, we investigate whether the instrument can also reliably be used to characterise therapeutic interactions when a digital system with a humanoid robot as a therapeutic assistant is used.
Methods: Participants and therapy: Seventeen stroke survivors receiving arm rehabilitation (i.e., arm basis training (ABT) for moderate-to-severe arm paresis [n = 9] or arm ability training (AAT) for mild arm paresis [n = 8]) using the digital therapy system E-BRAiN over a course of nine sessions. Analysis of the therapeutic interaction: A total of 34 therapy sessions were videotaped. All therapeutic interactions provided by the humanoid robot during the first and the last (9th) session of daily training were documented both in terms of their frequency and time used for that type of interaction using THER-I-ACT. Any additional therapeutic interaction spontaneously given by the supervising staff or a human helper providing physical assistance (ABT only) was also documented. All ratings were performed by two trained independent raters.
Statistical analyses: Intraclass correlation coefficients (ICCs) were calculated for the frequency of occurrence and time used for each category of interaction observed.
Results: Therapeutic interactions could comprehensively be documented and were observed across the dimensions provision of information, feedback, and bond-related interactions. ICCs for therapeutic interaction category assessments from 34 therapy sessions by two independent raters were high (ICC ≥0.90) for almost all categories of the therapeutic interaction observed, both for the occurrence frequency and time used for categories of therapeutic interactions, and both for the therapeutic interaction performed by the robot and, even though much less frequently observed, additional spontaneous therapeutic interactions by the supervisory staff and a helper being present. The ICC was similarly high for an overall subjective rating of the concentration and engagement of patients (0.87).
Conclusion: Therapeutic interactions can comprehensively and reliably be documented by trained raters using the instrument THER-I-ACT not only in the traditional patient–therapist setting, as previously shown, but also in a digital therapy setting with a humanoid robot as the therapeutic agent and for more complex therapeutic settings with more than one therapeutic agent being present.
Background: Gastrointestinal hormones (GIHs) are crucial for the regulation of a variety of physiological functions and have been linked to hunger, satiety, and appetite control. Thus, they might constitute meaningful biomarkers in longitudinal and interventional studies on eating behavior and body weight control. However, little is known about the physiological levels of GIHs, their intra-individual stability over time, and their interaction with other metabolic and lifestyle-related parameters. Therefore, the aim of this pilot study is to investigate the intra-individual stability of GIHs in normal-weight adults over time. Methods: Plasma concentrations of ghrelin, leptin, GLP-1 (glucagon-like-peptide), and PP (pancreatic polypeptide) were assessed by enzyme-linked immunosorbent assay (ELISA) in 17 normal-weight, healthy adults in a longitudinal design at baseline and at follow-up six months later. The reliability of the measurements was estimated using intra-class correlation (ICC). In a second step, we considered the stability of GIH levels after controlling for changes in blood glucose and hemoglobin A1 (HbA1c) as well as self-reported physical activity and dietary habits. Results: We found excellent reliability for ghrelin, good reliability for GLP1 and PP, and moderate reliability for leptin. After considering glucose, HbA1c, physical activity, and dietary habits as co-variates, the reliability of ghrelin, GLP1, and PP did not change significantly; the reliability of leptin changed to poor reliability. Conclusions: The GIHs ghrelin, GLP1, and PP demonstrated good to excellent test–retest reliability in healthy individuals, a finding that was not modified after adjusting for glucose control, physical activity, or dietary habits. Leptin showed only moderate to poor reliability, which might be linked to weight fluctuations, albeit small, between baseline and follow-up assessment in our study sample. Together, these findings support that ghrelin, GLP1, and PP might be further examined as biomarkers in studies on weight control, with GLP1 and PP serving as anorexic markers and ghrelin as an orexigenic marker. Additional reliability studies in obese individuals are necessary to verify or refute our findings for this cohort.
Objective: The study aimed to test the reliability of a semi-structured telephone interview for the classification of headache disorders according to the ICHD-3.
Background: Questionnaire-based screening tools are often optimized for single primary headache diagnoses [e.g., migraine (MIG) and tension headache (TTH)] and therefore insufficiently represent the diagnostic precision of the ICHD-3, which limits epidemiological research of rare headache disorders. Brief semi-structured telephone interviews could be an effective alternative to improve classification.
Methods: A patient population representative of different primary and secondary headache disorders (n = 60) was recruited from the outpatient clinic (HSA) of a tertiary care headache center. These patients completed an established population-based questionnaire for the classification of MIG, TTH, or trigeminal autonomic cephalalgia (TAC). In addition, they received a semi-structured telephone interview call from three blinded headache specialists individually. The agreement of diagnoses made either using the questionnaires or interviews with the HSA diagnoses was evaluated.
Results: Of the 59 patients (n = 1 dropout), 24% had a second-order and 5% had a third-order headache disorder. The main diagnoses were as follows: frequent primary headaches with 61% MIG, 10% TAC, 9% TTH, and 5% rare primary and 16% secondary headaches. Second-order diagnosis was chronic migraine throughout, and third-order diagnoses were medication overuse headache and TTH. Agreement between main headaches from the HSA was significantly better for the telephone interview than for the questionnaire (questionnaire: κ = 0.330; interview: κ = 0.822; p < 0.001). Second-order diagnoses were not adequately captured by questionnaires, while there was a trend for good agreement with the telephone interview (κ = 0.433; p = 0.074). Headache frequency and psychiatric comorbidities were independent predictors of HSA and telephone interview agreement. Male sex, headache frequency, severity, and depressive disorders were independently predictive for agreement between the questionnaire and HSA. The telephone interview showed high sensitivity (≥71%) and specificity (≥92%) for all primary headache disorders, whereas the questionnaire was below 50% in either sensitivity or specificity.
Conclusion: The semi-structured telephone interview appears to be a more reliable tool for accurate diagnosis of headache disorders than self-report questionnaires. This offers the potential to improve epidemiological headache research and care even in underserved areas.