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Recent advances in natural language processing (NLP), particularly in language processing methods, have opened new avenues in semantic data analysis. A promising application of NLP is data harmonization in questionnaire-based cohort studies, where it can be used as an additional method, specifically when only different instruments are available for one construct as well as for the evaluation of potentially new construct-constellations. The present article therefore explores embedding models' potential to detect opportunities for semantic harmonization. Using models like SBERT and OpenAI's ADA, we developed a prototype application (\"Semantic Search Helper\") to facilitate the harmonization process of detecting semantically similar items within extensive health-related datasets. The approach's feasibility and applicability were evaluated through a use case analysis involving data from four large cohort studies with heterogeneous data obtained with a different set of instruments for common constructs. With the prototype, we effectively identified potential harmonization pairs, which significantly reduced manual evaluation efforts. Expert ratings of semantic similarity candidates showed high agreement with model-generated pairs, confirming the validity of our approach. This study demonstrates the potential of embeddings in matching semantic similarity as a promising add-on tool to assist harmonization processes of multiplex data sets and instruments but with similar content, within and across studies.

ObjectivesPerceptual timing tasks are frequently applied in research on developmental disorders, but information on their reliability is lacking in pediatric studies. We therefore aimed to assess the reliability of the four paradigms most frequently used, i.e., time discrimination, time estimation, time production, and time reproduction.MethodsBased on the data from our recent longitudinal study by Marx et al. (Front Hum Neurosci 11:122, 2017), we estimated the internal consistency and test–retest reliability of these tasks in children with ADHD and typically developing children. Individual thresholds were used as dependent measures for the time discrimination task, whereas absolute error and accuracy coefficient scores were used for the other three tasks.ResultsAlthough less commonly used, the time estimation paradigm was the most robust measure of perceptual timing in terms of internal consistency and test–retest reliability in both ADHD and typically developing children, whereas the most frequently used paradigms showed poor internal consistency (time reproduction) and poor test–retest reliability (time discrimination). Compared to the absolute errors, accuracy coefficients showed almost exclusively higher internal consistency and test–retest reliability.ConclusionsOur findings call for more frequent use of the time estimation paradigm in studies of perceptual timing in ADHD. The time reproduction paradigm should be re-considered, avoiding pooling of a wide range of time intervals (2–48 s). The accuracy coefficient score is the more reliable and the more intuitive dependent variable and should be preferred in future timing research. To increase the reliability of the timing measurement, each experimental session should be performed twice, if possible.

BackgroundNowadays, both researchers and clinicians alike have to deal with increasingly larger datasets, specifically also in the context of mental health data. Sophisticated tools for dataset visualization of information from various item-based instruments, such as questionnaire data or data from digital applications or clinical documentations, are still lacking, specifically for an integration at multiple levels and for use in both data organization and appropriate construction for its valid use in subsequent analyses.MethodsHere, we introduce ItemComplex, a Python-based framework for ex-post visualization of large datasets. The method exploits the comprehensive recognition of instrument alignments and the identification of new content networks and graphs based on item similarities and shared versus differential conceptual bases within and across data and studies.ResultsThe ItemComplex framework was evaluated using four existing large datasets from four different cohort studies and demonstrated successful data visualization across multi-item instruments within and across studies. ItemComplex enables researchers and clinicians to navigate through big datasets reliably, informatively, and quickly. Moreover, it facilitates the extraction of new insights into construct representations and concept identifications within the data.ConclusionsThe ItemComplex app is an efficient tool in the field of big data management and analysis addressing the growing complexity of modern datasets to harness the potential hidden within these extensive collections of information. It is also easily adjustable for individual datasets and user preferences, both in the research and clinical field.

The diagnosis of major depressive disorder (MDD) should be based on multimodal evidence, because MDD not only affects mood, but also psychomotor and cognitive functions. Clinical markers such as executive dysfunctions and a reduction in daily motor activity have been observed in MDD. Neurophysiological biomarkers have also been described. In this study, we investigate the utility of combining biomarkers related to executive dysfunctions, motor activity, neurophysiological patterns (i.e. alpha power asymmetry and EEG-vigilance as indicators of brain arousal), and the interaction of these parameters in the diagnosis of MDD. Twenty (female: 11) patients with MDD (age: 51.05 ± 10.50) and 20 (female: 13) healthy controls (HC; age: 47.15 ± 12.57) underwent a 10-min resting EEG. Executive dysfunctions were assessed using the Trail Making Test B (TMT B). Motor activity was analysed by actigraphy measurements. MDD patients displayed significant impairments in executive functions and reduced daily motor activity. In the EEG, MDD patients showed more right than left frontal activity and lower brain arousal relative to HC. TMT B and asymmetrical frontal alpha power alone discriminated between MDD patients and HC with an accuracy of 78%. The interaction of motor activity and the EEG-vigilance stage alongside TMT B increased the accuracy of the discrimination test to 81%. This improved accuracy suggests that the combination of these biomarkers in a discriminant analysis resulted in a more reliable identification of MDD patients.

Background This review summarises the present state of research on health inequalities using a social network perspective, and it explores the available studies examining the interrelations of social inequality, social networks, and health. Methods Using the strategy of a scoping review, as outlined by Arksey and O’Malley (Int J Sci Res Methodol 8:19–32, 2005), our team performed two searches across eight scientific, bibliographic databases including papers published until October 2021. Studies meeting pre-defined eligibility criteria were selected. The data were charted in a table, and then collated, summarised, and reported in this paper. Results Our search provided a total of 15,237 initial hits. After deduplication ( n  = 6,168 studies) and the removal of hits that did not meet our baseline criteria ( n  = 8,767 studies), the remaining 302 full text articles were examined. This resulted in 25 articles being included in the present review, many of which focused on moderating or mediating network effects. Such effects were found in the majority of these studies, but not in all. Social networks were found to buffer the harsher effects of poverty on health, while specific network characteristics were shown to intensify or attenuate the health effects of social inequalities. Conclusions Our review showed that the variables used for measuring health and social networks differed considerably across the selected studies. Thus, our attempt to establish a consensus of opinion across the included studies was not successful. Nevertheless, the usefulness of social network analysis in researching health inequalities and the employment of health-promoting interventions focusing on social relations was generally acknowledged in the studies. We close by suggesting ways to advance the research methodology, and argue for a greater orientation on theoretical models. We also call for the increased use of structural measures; the inclusion of measures on negative ties and interactions; and the use of more complex study designs, such as mixed-methods and longitudinal studies.

BackgroundHeadache sufferers in need of professional health care often do not utilize the care available, and factors influencing headache-specific physician consultation are not yet understood. Objectives of this study are (1) to assess self-reported headache-specific physician consultations and (2) to identify headache-related and sociodemographic predictors.MethodsData of a random sample of the general population in Germany aged ≥14 years were analyzed (N = 2461). A multivariate binary logistic regression was conducted to identify a parsimonious model to predict physician consultation.Results50.7% of the participants with headache reported at least one headache-specific physician consultation during lifetime. Of these, 53.6% had seen one, 26.1% two, and 20.3% more than two physicians because of their headaches. The odds of physician consultation increased with the number of headache days per month (HDM) [(reference HDM < 1) HDM 1–3 (OR = 2.29), HDM 4–14 (OR = 2.41), and HDM ≥15 (OR = 4.83)] and increasing Headache Impact Test score (HIT-6) [(reference “no or little impact”) moderate impact (OR = 1.74), substantial impact (OR = 3.01), and severe impact (OR = 5.08)]. Middle-aged participants were more likely to have consulted than younger and older ones [(reference 14–34 years) 35–54 years (OR = 1.90), 55–74 years (OR = 1.96), ≥75 years (OR = 1.02)]. The odds of physician consultation among self-employed subjects were lower than among employed manual workers (OR = 0.48). The living environment (rural versus urban) did not have an influence on the consultation frequency.ConclusionThe results indicate that apart from burden-related factors (headache frequency; headache impact), health care utilization patterns are also influenced by patients’ occupational status and age. Further research is needed to analyze whether the lower consultation rate means that the self-employed have a higher risk of chronification or that they have more effective self-management strategies regarding headache.

Background Headache disorders are among the most prevalent neurological disorders worldwide. However, whether groups differing in socioeconomic position (SEP) are disproportionately affected by headache disorders has not yet been adequately clarified. Our aim was to analyse (1) the headache prevalence by socioeconomic position (SEP) and (2) the attack frequency by SEP in a German population-based adult sample. Methods Cross-sectional data from a random general population were used. The sample included N  = 2,189 participants aged ≥ 18 years. SEP was measured using net equivalised income (NEI) and education. A binary logistic regression model tested the effect of SEP in predicting the prevalence of headache in general. Ordinal logistic regressions were modeled to predict the effect of SEP on the likelihood of attack frequency. Attack frequency was categorized in low frequency episodic headache (LFEH: 0–3 days per month), moderate frequency episodic headache (MFEH: 4–14 days per month) and chronic headache (CH: ≥ 15 days per month). Results Of the 2,189 participants, 891 reported headache in the last six months. Neither income nor education was associated with headache prevalence. However, significant differences between income groups were found for attack frequency. Compared to participants with NEI > 150%, those with NEI < 60% were 5.21 times more likely (95%CI 2.03, 13.36) to experience higher headache frequency, and those with NEI between 60 and 150% were 2.29 times more likely (95%CI 1.02, 5.11), with adjustments made for a set of potential confounders, including depressive symptoms. Conclusions To reduce headache attacks, it is essential to address both low- and middle-income groups affected by headaches. Universal public health prevention campaigns are particularly appropriate.

BackgoundHeadache disorders are not only among the most prevalent, they are also among the most disabling disorders worldwide. This paper investigates the association between headache impact on daily life and the socioeconomic status (SES) of headache sufferers.MethodsData stem from a random general population sample in Germany. Respondents who reported having headache for at least a year and were aged ≥ 18 years were included in the study. A standardized questionnaire addressing headache and headache treatment was filled in during the face-to-face survey. The impact of headache on daily life was measured using the German version of the Headache Impact Test (HIT-6).ResultsHigher headache impact was found in low and medium SES compared to high SES. After adjustment for sociodemographics, headache-related factors (analgesic use, headache duration, headache frequency, migraine diagnosis), depressive symptoms, physical inactivity and obesity, an increased odds ratio of having higher headache impact in low SES compared to high SES was found: OR = 1.83, 95% CI [1.43, 2.23], p = .014. When the interactions \"SES*obesity\", \"SES*depressive symptoms\", and \"SES*physical inactivity\" were added, the results showed a significant interaction effect of “SES*obesity”. Obese persons with low SES were 3.64 times more likely to have higher headache impact than non-obese persons with low SES. No significant differences between obese and non-obese persons were found in the medium and high SES groups.ConclusionsSES is an important factor that should not be neglected in headache awareness campaigns and headache treatment. Longitudinal studies are needed in the future to investigate whether lifestyle interventions, such as weight reduction, can help to reduce headache impact in people in lower SES.

Satisfaction with sexual activity i.e. sexual satisfaction and the importance of sexuality and affection were analysed using data from the German \"Interdisciplinary Longitudinal Study of Adult Development\" (ILSE). At three measurement points, 1993-1995, 1997-1998, and 2004-2006 i.e. subjects' ages of 63, 67, and 74 years, participants' reports about their affection and sexual activity were collected. The sample of completed records used for this study consisted of 194 urban non-institutionalised participants, 68% male, all living with partners. Median levels of sexual satisfaction were reported, fluctuating between the measurement points of ages 63 to 74. Between baseline, first and second follow-up no differences were found in levels of sexual satisfaction, though at measurement points age 63 and 67 women were more satisfied than men. When measured at age 74, affection was given a higher priority than sexual activity. Although men and women reported similar priorities, sexual activity and affection were more important for men than for women. Satisfaction within the relationship can be predicted by the importance of affection, but not by that of sexual activity. Our results confirm the thesis of the 'second language of sexuality': for humans in their later years affection seems to be more important than for younger individuals.

This study aims (1) to describe the context of drinking among adolescents with acute alcohol intoxication (AAI) by gender, (2) to explore temporal changes in the context of drinking and (3) to analyse the association between the context of drinking and blood alcohol concentration (BAC). A retrospective chart review of 12- to 17-year-old inpatients with AAI ( n  = 1441) of the years 2000 to 2006 has been conducted in five participating hospitals in Germany. Gender differences in the context of drinking were tested with t test and chi 2 test. Differences over time were analysed using logistic regressions. Multivariate linear regression was used to predict BAC. Girls and boys differed in admission time, drinking situation, drinking occasion and admission context. No temporal changes in drinking situation and in admission to hospital from public locations or places were found. Higher BAC coincided with male gender and age. Moreover, BAC was higher among patients admitted to hospital from public places and lower among patients who drank for coping. Conclusion : The results suggest gender differences in the context of drinking. The context of drinking needs to be considered in the development and implementation of target group-specific prevention and intervention measures. What is known: • The context of drinking, e.g . when, where, why and with whom is associated with episodic heavy drinking among adolescents. What is new: • Male and female inpatients with acute alcohol intoxication differ with regards to the context of drinking, i.e. in admission time, drinking situation, drinking occasion and admission context. • Being admitted to hospital from public places is associated with higher blood alcohol concentration.