METHODS: The development of the MUAPHQ C-19 was conducted in two stages. Stage I resulted in the generation of the instrument's items (development), and stage II resulted in the performance of the instrument's items (judgement and quantification). Six-panel experts related to the study field and ten general public participated to evaluate the validity of the MUAPHQ C-19. The content validity index (CVI), content validity ratio (CVR) and face validity index (FVI) were analysed using Microsoft Excel.

RESULTS: There were 54 items and four domains, namely the understanding, attitude, practice and health literacy towards COVID-19, identified in the MUAPHQ C-19 (Version 1.0). The scale-level CVI (S-CVI/Ave) for every domain was above 0.9, which is considered acceptable. The CVR for all items was above 0.7, except for one item in the health literacy domain. Ten items were revised to improve the item's clarity, and two items were deleted due to the low CVR value and redundancy, respectively. The I-FVI exceeded the cut-off value of 0.83 except for five items from the attitude domain and four from the practice domains. Thus, seven of these items were revised to increase the clarity of items, while another two were deleted due to low I-FVI scores. Otherwise, the S-FVI/Ave for every domain exceeded the cut-off point of 0.9, which is considered acceptable. Thus, 50-item MUAPHQ C-19 (Version 3.0) was generated following the content and face validity analysis.

DESIGN/METHODOLOGY/APPROACH: The authors adopted a quantitative and qualitative approach, i.e., a self-administered questionnaire, unstructured and a semi-structured interview, which were used to collect the data. A questionnaire was distributed to Bahraini residents selected randomly. The framework was based on the technology acceptance model (TAM) and theory of reasoned action (TRA). Important variables from both the TAM model and TRA theory were extracted and jointly used to build the research model.

FINDINGS: The findings indicated that the most factors affecting e-health adoption are trust, health literacy and attitude. Additionally, people in the private and government sectors understand e-health benefits.

PRACTICAL IMPLICATIONS: If healthcare professionals understand the factors affecting e-health system adoption from an individual and organisational perspective, then nurses, pharmacists and others will be more conscious about e-health and its adoption status.

METHODS: A total of 322 participants from the MyBFF@home study completed the Newest Vital Sign (NVS) test at baseline. However, only data from 209 participants who completed the NVS test from baseline to WL intervention were used to determine the HL groups. Change of the NVS scores from baseline to WL intervention phase was categorized into two groups: those with HL improvement (increased 0.1 score and above) and those without HL improvement (no change or decreased 0.1 score and more). Independent variables in this study were change of energy intake, nutrient intake, physical activity, anthropometry measurements, and body composition measurements between baseline and WL intervention as well as between WL intervention and WL maintenance. An Independent sample t-test was used in the statistical analysis.

RESULTS: In general, both intervention and control participants have low HL. The study revealed that the intervention group increased the NVS mean score from baseline (1.19 scores) to the end of the WL maintenance phase (1.51 scores) compared to the control group. There was no significant difference in sociodemographic characteristics between the group with HL improvement and the group without HL improvement at baseline. Most of the dietary intake measurements at WL intervention were significantly different between the two HL groups among intervention participants. Physical activity and body composition did not differ significantly between the two HL groups among both intervention and control groups.

OBJECTIVE: The aim of this study was to translate and adapt cross-culturally the OHLI into French, to evaluate its psychometric properties and to compare its results to oral health knowledge.

METHOD: This study followed and applied well-established processes of translation, cross-cultural adaptation and validation, based on the recommendations of the World Health Organization guidelines and on the Consensus-Based Standards for the Selection of Health Measurement Instruments (COSMIN) study design checklist for patient-reported outcomes. Two psychometric assessments were planned, the comparison of OHLI-F scores according to education level and frequency of dental visits, and the test-retest reliability of the OHLI-F.

METHODS: A cross-sectional survey based on multistage random sampling in the target countries. A total of 10,024 participants aged ≥15 years were recruited during 2013-2014 in Indonesia, Kazakhstan, Malaysia, Myanmar, Taiwan, and Vietnam. The questionnaire was translated into local languages to measure general health literacy and its three domains. To evaluate the validity of the tool in these countries, data were analyzed by confirmatory factor analysis, internal consistency analysis, and regression analysis.

RESULTS: The questionnaire was shown to have good construct validity, satisfactory goodness-of-fit of the data to the hypothetical model in three health literacy domains, high internal consistency (Cronbach's alpha >0.90), satisfactory item-scale convergent validity (item-scale correlation ≥0.40), and no floor/ceiling effects in these countries. General health literacy index score was significantly associated with level of education (P from <0.001 to 0.011) and perceived social status (P from <0.001 to 0.016), with evidence of known-group validity.

METHODS: A systematic review was conducted according to the PRISMA guidelines. The study protocol was registered with PROSPERO (CRD42017056150). We searched MEDLINE, EMBASE, PsycINFO, CINAHL and ERIC for articles published up to January 2017. Articles that measured HL levels in adult patients with T2DM; that used validated HL tools; and that were reported in English were included. Two reviewers assessed studies for eligibility and quality, and extracted the data. Prevalence of limited HL is calculated from the number of patients with less than adequate HL over the total number of patients with T2DM in the study. Meta-analysis and meta-regression analysis were conducted using the Open Meta-analyst software.

RESULTS: Twenty-nine studies involving 13,457 patients with T2DM from seven countries were included. In total, seven different HL measurement tools were used. The prevalence of limited HL ranged from 7.3% to 82%, lowest in Switzerland and the highest in Taiwan. Meta-regression analysis of all included studies showed the country of study (p<0.001), HL tool used (p = 0.002), and the country's region (p<0.001) contributed to the variation findings. Thirteen studies in the USA measured functional HL. The pooled prevalence of inadequate functional HL among patients with T2DM in the USA was 28.9% (95% CI: 20.4-37.3), with high heterogeneity (I2 = 97.9%, p <0.001). Studies were done in the community as opposed to a hospital or primary care (p = 0.005) and populations with education level lower than high school education (p = 0.009) reported a higher prevalence of limited HL.

DESIGN: A cross-sectional study was conducted from January to March 2018; data on patients' sociodemographic characteristics, diabetes knowledge, perceived social support and health literacy level were collected. Health literacy level was measured using the European Health Literacy Survey Questionnaire (HLS-EU-Q47).

SETTING: Patients were recruited from four primary care clinics in Perak, Malaysia.

PARTICIPANTS: Adult patients diagnosed with T2DM who attended the study clinics during the study period.

PRIMARY OUTCOME VARIABLE: Patients with HLS-EU-Q47 General Index of ≤33 points were classified as having limited health literacy.

RESULTS: The prevalence of limited health literacy was 65.3% (n=279). In bivariate analysis, patients' ethnicity (p=0.04), highest education level (p<0.001), monthly income (p=0.003), having health insurance (p=0.007), English language fluency (p<0.001), Malay language fluency (p=0.021), attending diabetes education sessions (p<0.001), perceived social support (p<0.001) and diabetes knowledge (p=0.019) were factors associated with limited health literacy. In logistic regression, not being fluent in English was associated with limited health literacy (OR=2.36, 95% CI 1.30 to 4.30) whereas having high perceived social support (OR=0.52, 95% CI 0.40 to 0.69) and having attended diabetes education sessions (OR=0.42, 95% CI 0.27 to 0.68) were associated with adequate health literacy.