Validation and Refinement of the Sense of Coherence Scale for a French Population: Observational Study.

BACKGROUND: Salutogenesis focuses on understanding the factors that contribute to positive health outcomes. At the core of the model lies the sense of coherence (SOC), which plays a crucial role in promoting well-being and resilience. OBJECTIVE: Using the validscale Stata command, we aimed to assess the psychometric properties of the French version of the 3-dimension 13-item SOC questionnaire (SOC-13), encompassing the comprehensibility, manageability, and meaningfulness dimensions. We also aimed to determine if a refined scale, assessed through this method, exhibits superior psychometric properties compared to the SOC-13. METHODS: A sample of 880 consecutive primary care patients recruited from 35 French practices were asked to complete the SOC-13. We tested for internal consistency and scalability using the Cronbach α and Loevinger H coefficients, respectively, and we tested for construct validity using confirmatory factor analysis and goodness-of-fit indices (root mean square error of approximation [RMSEA] and comparative fit index [CFI]). RESULTS: Of the 880 eligible patients, 804 (91.4%) agreed to participate (n=527, 65.6% women; median age 51 years). Cronbach α and Loevinger H coefficients for the SOC-13 were all <0.70 and <0.30, respectively, indicating poor internal consistency and poor scalability (0.64 and 0.29 for comprehensibility, 0.56 and 0.26 for manageability, and 0.46 and 0.17 for meaningfulness, respectively). The RMSEA and CFI were >0.06 (0.09) and <0.90 (0.83), respectively, indicating a poor fit. By contrast, the psychometric properties of a unidimensional 8-item version of the SOC questionnaire (SOC-8) were excellent (Cronbach α=0.82, Loevinger H=0.38, RMSEA=0.05, and CFI=0.97). CONCLUSIONS: The psychometric properties of the 3-dimension SOC-13 were poor, unlike the unidimensional SOC-8. A questionnaire built only with these 8 items could be a good candidate to measure the SOC. However, further validation studies are needed before recommending its use in research.

Who are the patients who use non-pharmacological home remedies? Cross-sectional study in Switzerland and France.

BACKGROUND: Many patients may be tempted to use non-pharmacological home remedies (NPHRs) to relieve various complaints. To the best of our knowledge, there is little data on the characteristics of patients using NPHRs. In this cross-sectional study carried out between March 2020 and July 2021, we examined the socio-demographic factors underlying their use in patient populations in Switzerland and France. METHODS: Using official registries, we randomly selected 50 primary care physicians (PCPs) in Geneva (Switzerland) and Lyon/Grenoble (France). Seven research assistants consecutively recruited patients from PCP waiting rooms (20-25 patients per practice). Patients completed a paper-based questionnaire assessing the use [yes/no] of 304 NPHRs for 79 medical conditions. The NPHR list was developed by our team with input from 97 patients. We used univariable and multivariable logistic regressions, adjusting for intra-cluster correlations, to examine associations between NPHR use and patient characteristics (gender, age, practice location, nationality, education level, and self-rated health). RESULTS: Of the 1198 eligible patients, 1012 agreed to participate (85%). Overall, 635 patients (63%) reported using at least one of the remedies tested in the study. In multivariable analysis, women (OR = 1.7 [95%CI = 1.3-2.3], P-value < 0.001), younger patients (< 40 years: OR = 2.1 [95%CI = 1.6-2.9], P-value < 0.001), and French patients (OR = 1.6 [95%CI = 1.1-2.3], P-value < 0.001) tended to use NPHRs more often than other patients. CONCLUSIONS: Many patients, particularly women, young people, and French patients, reported using NPHRs. This survey's findings hold the potential to inform healthcare providers, policymakers, and researchers about the diverse preferences that shape patients' healthcare choices.

Performance of machine translators in translating French medical research abstracts to English: A comparative study of DeepL, Google Translate, and CUBBITT.

BACKGROUND: Non-English speaking researchers may find it difficult to write articles in English and may be tempted to use machine translators (MTs) to facilitate their task. We compared the performance of DeepL, Google Translate, and CUBBITT for the translation of abstracts from French to English. METHODS: We selected ten abstracts published in 2021 in two high-impact bilingual medical journals (CMAJ and Canadian Family Physician) and used nine metrics of Recall-Oriented Understudy for Gisting Evaluation (ROUGE-1 recall/precision/F1-score, ROUGE-2 recall/precision/F1-score, and ROUGE-L recall/precision/F1-score) to evaluate the accuracy of the translation (scores ranging from zero to one [= maximum]). We also used the fluency score assigned by ten raters to evaluate the stylistic quality of the translation (ranging from ten [= incomprehensible] to fifty [= flawless English]). We used Kruskal-Wallis tests to compare the medians between the three MTs. For the human evaluation, we also examined the original English text. RESULTS: Differences in medians were not statistically significant for the nine metrics of ROUGE (medians: min-max = 0.5246-0.7392 for DeepL, 0.4634-0.7200 for Google Translate, 0.4815-0.7316 for CUBBITT, all p-values > 0.10). For the human evaluation, CUBBITT tended to score higher than DeepL, Google Translate, and the original English text (median = 43 for CUBBITT, vs. 39, 38, and 40, respectively, p-value = 0.003). CONCLUSION: The three MTs performed similarly when tested with ROUGE, but CUBBITT was slightly better than the other two using human evaluation. Although we only included abstracts and did not evaluate the time required for post-editing, we believe that French-speaking researchers could use DeepL, Google Translate, or CUBBITT when writing articles in English.