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The INE (2017; 2018) indicates, for the metropolitan area of Lisbon, the total of 12 913 nurses in the hospital context and that of 1,836 FGM physicians in office. Therefore, a total of 14 749 health professionals. In an attempt to optimize the quality of the sample as much as possible, the calculation was applied to finite populations and, through quotas, proportions of reality were inserted. The total sample to be computed, applying the calculation for finite populations – <100,000 elements – (Pocinho, 2009, pp. 18-19) and considering a confidence level of 95% and a sampling error of 5%, is: 389.
The socio-demographic characterization of these respondents also seeks an approximation to the Portuguese reality. In order for the sample to be proportional to the total number of physicians and nurses, the simple three rule was applied. Intending a sampling by proportional quotas of profession and gender, the sample for the survey consisted of 341 nurses (87.7% of the total) and 48 FGM physicians (12.3%). Given the feminization rate (SNS, 2016) of medical staff – 59.1% – and that of nursing staff of 83.4% (SNS, 2016, p. 149), 21 males and 27 females and, in nursing, 283 women and 58 men ( table 2 ) are considered among physicians.
The request for the application of the survey was made to the Ethical Committees of the Regional Health Administration of Lisbon and Tagus Valley (ARSLVT), and to the EC of the University Hospital Center of Central Lisbon (CHULC). Within the CHULC, authorization was obtained by the Ethical Comission, through its Board of Directors, for the application of the online questionnaire.
Considering the reliability indexes, which are between 0.75 and 1 and, given the result for Cronbach's alpha of the Q-COM-LIT of 0.788 (for the 50 items), the values confirm the reliability of the instrument.

CFA is used to test the three factor structure of the English eHEALS using multinational versions from the UK, New zealand, and the USA on MRI and CT outpatients

The structure of the mental health literacy scale was to some extent different from the one in O'Connor et al. study, but it was consistent with the definition of MHL presented by Jorm et al.

The content validity was examined by five experts specialized in dentistry, oral health
science, public health, and community health nursing regarding the accuracy, content
suitability and clarity of the translated scale and amendments were made based on their
expert opinions. A content validity index (CVI) value ≥80% was used as the assessment
standard (the proportion in which ≥80% of the experts agreed with scores ≥3 points on the
scale). All suggestions of experts were considered in modifying the questionnaire. The mean
score of total 17 items was 3.79, and the overall CVI calculated for MOHL-AQ was 95%.

Definitions of health literacy were reviewed to identify key domains for weight-specific health literacy. Consultation with a diverse expert panel led to the creation of a preliminary item pool, which was then subjected to a Delphi process to select the final items. These 17 items were subsequently pilot tested. After statistical analyses, 4 items were eliminated leading to a 13 item final version.

The development of the tool included an expert panel in Nutrition education and 1 Psychometrician who revised the NLit looking improve the clarity of the format and content for the target patient population.

The traditional Chinese version of the HLS-EU-Q was used in this study. IT was developed using the translation-back translation method from the original English version. It was verified by a panel of public health experts in Taiwan, and then pretested and readability and understandability.

This measure was developed using response theory. Items for this measure were generated based on qualitative studies in English and Spanish speaking adults and translated into Spanish using a group translation and consensus process.

To ensure the content validity of the question items for the ten domains, the items were examined and adapted through discussions with researchers from public health, nursing, and social sciences working in related fields. No questions were revised in this task.

The development of the tool included rigorous translation and back‐translation technique from the original Japanese version of the HLS. Two bilingual laypersons were independently involved in each translation, and there was an expert panel that discussed any discrepancies between the versions

The original NVS was translated into Chinese by two independent translators with health backgrounds and the two version were then synthesized. Some cultural adaptations were made to the nutrition label (i.e. changing the units of measure) and the syntehsized version was then back translated to English. A group volunteer of volunteers were then cognitively debriefed to ensure there were no difficulties in comprehension of the NVS-TC.

The development of the tool included adaptation and validation of the SAHLPA-18 tool and addition of 5 new items to the tool. The method of administration and scoring was also modified for this tool.

40 real medical words and 30 non-medical words

Based on a priori hypothesis that scores were related to health-related occupation and educational attainment.

An original list of previously used 27 behavior questions drawn from EFNEP along with other research was used as the starting point and narrowed down to 18 behavior items for the pilot testing for face validity. Consideration was given to colloquial terms, and these were changed as necessary such as 'grocery' used in the US to 'shopping' in Australia. Items selected were to be consistently answered on the same Likert scale of frequency from 'never'(1) to 'always'(5).

An expert panel assessed content and face validity. Exploratory and confirmatory analyses were used to evaluate the metrics of the tool.

Initial list of ChMLM was adapted from a previously validated medication-related instrument by a pharmacist researcher. The first version contained 25 items and was reviewed by a panel of 11 multidisciplinary and bilingual experts and researchers with backgrounds in psychometrics. Most experts were bilingual and were encouraged to modify items. The final version contained 17 items and utilized a Likert scale. Content validity was confirmed by the expert panel.