The COVID-19 pandemic has caused unprecedented stress and fear throughout the world.

To evaluate the psychological effects of the COVID-19 pandemic on the Saudi public, and to examine the performance of the Arabic version of the Four-Dimensional Symptom Questionnaire (4DSQ) scale.

We conducted an online questionnaire-based cross-sectional survey of a sample of the Saudi public.

The study included 347 participants, who reported significantly higher levels of distress, depressive symptoms, anxiety symptoms and somatisation compared with a normative sample. Females scored higher in terms of somatisation, depression and anxiety symptoms, and distress. Obtaining COVID-19 information from friends and relatives was associated with higher levels of somatisation, depression and anxiety symptoms, and distress. Cronbach's alpha was 0.93 for the distress scale, 0.88 for the depression scale, 0.88 for the anxiety scale and 0.86 for the somatisation scale.

Levels of psychological distress were high among the Saudi public during the COVID-19 pandemic. We found high reliability for the Arabic version of the 4DSQ scale. However, three items did not conform to the four-factor structure, namely, item 1: ‘During the past week, did you suffer from dizziness or feeling light-headed?’, item 20: ‘During the past week, did you suffer from disturbed sleep?’ and item 46: ‘During the past week did you ever think I wish I was dead?’.

Few studies have validated FFQ estimates of dietary glycaemic index (GI) and load (GL). We investigated how well our estimates of overall GI and GL from FFQs correlate with estimates from repeated 24 h recall data to validate overall GI and GL in the Adventist Health Study-2 (AHS-2).

The AHS-2 is a prospective population-based cohort of 95 873 Seventh-day Adventist adult church members enrolled from 2002 to 2007 to investigate diet, cancer and mortality.

A 204-item FFQ was used to assess race- and gender-specific validity of GI and GL and 24 h recall data, from the calibration sub-study, were used as the reference.

The 734 calibration study participants were randomly selected by church and included approximately equal numbers of blacks and whites but were otherwise similar to the whole cohort with respect to gender, age, education and vegetarian status.

The deattenuated correlation coefficients for overall GI ranged from 0·19 (95 % CI −0·06, 0·53) in black men to 0·46 (95 % CI 0·40, 0·60) in black women, with both non-black men and women falling between those values (0·45 (95 % CI 0·35, 0·65) and 0·38 (95 % CI 0·27, 0·57), respectively). GL correlations were somewhat higher for all study participants. When looking at the entire cohort, the deattenuated validity correlation value for overall GI was (r 0·38, 95 % CI 0·36, 0·47) and GL was (r 0·39, 95 % CI 0·34, 0·49).

Our findings support the cautious use of our FFQ in epidemiological studies when assessing associations of overall GI and GL with disease risk. However, observed differences by race should be considered when interpreting results.

This study was conducted to develop and validate a questionnaire to assess the impact of COVID-19 pandemic on lifestyle-related behaviour related to eating, activity and sleep pattern.

Indexed study used a mixed method design. Phase I employed qualitative methods for development of questionnaire including literature review, focus group discussion, expert evaluation and pre-testing. Phase II used quantitative methods for establishing construct validity of the questionnaire via parallel factor analysis.

Phase 1 involved participation of experts from different fields (Departments of Medicine, Nutrition and Clinical Psychology) and general adult population. For phase II, data were collected from 124 adult respondents (female = 57·26 %); mean age (36 ± 14·8 years) residing in an urban setting.

The questionnaire consisted of three sections: (A) socio-demographic and anthropometric parameters, (B) twenty-four items each for investigating the changes in eating, activity and sleep behaviour before v. during COVID-19, (C) six items assessing COVID-19 specific reasons for lifestyle change. The Cronbach’s α value of the questionnaire is 0·83 suggesting its good internal consistency.

This appears to be a valid tool to assess the impact of COVID-19 on lifestyle-related behaviours with potential utility for public health researchers to identify these changes at community level and develop strategies to reinforce corrective behaviours.

The aim of the present study was to develop and validate a vitamin D food frequency questionnaire (FFQ) for assessment of dietary vitamin D intake in healthy adults in England, UK.

The current study assessed the agreement between a four-day food diary (4d-FD) and a new vitamin D FFQ to measure dietary intake of vitamin D. Dietary intake was estimated using Nutritics dietary analysis software and Spearman’s and Bland-Altman tests were utilised to assess correlation and agreement, respectively. Participants also provided a blood sample for plasma analysis of vitamin D concentrations.

Home setting.

Fifty participants were recruited to the study from the University of Chester and vicinity.

Results showed a strong correlation between vitamin D intake recorded by the FFQ and the 4d-FD (r = 0.609; P < 0.0001) within 95% limits of agreement. Furthermore, a significant correlation between plasma 25(OH)D concentrations and vitamin D intake measured by the FFQ (r = 0.290, P = 0.041) and the 4d-FD (r = 0.360, P = 0.01) was observed.

Our analysis suggests this FFQ is a useful and rapid tool for researchers and health professionals to assess vitamin D dietary intakes in healthy adults in the UK.

Reassurance seeking (RS) is motivated by perceived general and social/relational threats across disorders, yet is often under-recognized because it occurs in covert (i.e. subtle) and overt forms. Covert safety-seeking behaviour may maintain disorders by preventing corrective learning and is therefore important to identify effectively.

This study presents the validation and psychometric analyses of a novel measure of covert and overt, general and social/relational threat-related interpersonal RS.

An initial 30-item measure was administered to an undergraduate sample (N = 1626), as well as to samples of individuals diagnosed with obsessive compulsive disorder (OCD; n = 50), anxiety disorders (n = 60) and depression (n = 30). The data were subjected to exploratory and confirmatory factor analyses, and validation analyses.

An exploratory factor analysis using principal axis factoring with oblique rotation yielded five interpretable factors, after removing four complex items. The resulting 26-item measure, the Covert and Overt Reassurance Seeking Inventory (CORSI), evidenced good convergent and divergent validity and accounted for 54.99% of the total variance after extraction. Factor correlations ranged from r = .268 to .736, suggesting that they may be tapping into unique facets of RS behaviour. In comparison with undergraduate participants, all clinical groups had significantly higher total scores [t (51.80–840) = 3.92–5.84, p < .001]. The CFA confirmed the five-factor model with good fit following the addition of four covariance terms (goodness of fit index = .897, comparative fit index = .918, Tucker–Lewis index = .907, root mean square error approximation = .061).

The CORSI is a brief, yet comprehensive and psychometrically strong measure of problematic RS. With further validation, the CORSI has potential for use within clinical and research contexts.

To conduct a systematic review of studies for the validation of semiquantitative FFQ (SFFQ) that assess food intake in adults.

The authors conducted a systematic search in PubMed for articles published as late as January 2020 in Spanish, English, French and Portuguese. Individual searches (twelve in total) paired three hyphenated and non-hyphenated variations of ‘semiquantitative food frequency questionnaire’ with both ‘validity’ and ‘validation’ using the ‘all fields’ and the ‘title/abstract’ retrieval categories. Independent extraction of articles was performed by four authors using predefined data fields.

We searched for original SFFQ validation studies that analysed general diet composition (nutrients with or without food groups or energy analysis) in healthy adults, in any setting, and that also reported correlation coefficients.

Healthy adults.

Sixty articles were included. The preferred comparison standard for validation was food records (n 37). The main correlation coefficients used were Pearson’s (n 41), and validity coefficients varied from −0·45 to 1. Most correlation coefficients were adjusted by energy (twelve studies presented only crude values). The elements mentioned most frequently were energy, macronutrients, cholesterol, SFA, PUFA, fibre, vitamin C, Ca and Fe.

Although all these SFFQ are reported as validated, coefficients may vary across groups of foods and nutrients. Based on our findings, we suggest researchers to consult our revision before choosing a SFFQ and to review important issues about them, such as their validation, number of items, number of participants, etc. Systematic Review Registration: PROSPERO number CRD42017064716. Available at: http://www.crd.york.ac.uk/PROSPERO/display_record.asp?ID=CRD42017064716.

Economic models play a central role in the decision-making process of the National Institute for Health and Care Excellence (NICE). Inadequate validation methods allow for errors to be included in economic models. These errors may alter the final recommendations and have a significant impact on outcomes for stakeholders.

To describe the patterns of technical errors found in NICE submissions and to provide an insight into the validation exercises carried out by the companies prior to submission.

All forty-one single technology appraisals (STAs) completed in 2017 by NICE were reviewed and all were on medicines. The frequency of errors and information on their type, magnitude, and impact was extracted from publicly available NICE documentation along with the details of model validation methods used.

Two STAs (5 percent) had no reported errors, nineteen (46 percent) had between one and four errors, sixteen (39 percent) had between five and nine errors, and four (10 percent) had more than ten errors. The most common errors were transcription errors (29 percent), logic errors (29 percent), and computational errors (25 percent). All STAs went through at least one type of validation. Moreover, errors that were notable enough were reported in the final appraisal document (FAD) in eight (20 percent) of the STAs assessed but each of these eight STAs received positive recommendations.

Technical errors are common in the economic models submitted to NICE. Some errors were considered important enough to be reported in the FAD. Improvements are needed in the model development process to ensure technical errors are kept to a minimum.

The aim of the current study was to evaluate the accuracy of the new software eAT24 used to assess dietary intake in the National Food, Nutrition and Physical Activity Survey (IAN-AF) against urinary biomarkers: N (nitrogen), K (potassium) and Na (sodium).

We conducted a cross-sectional study. Two non-consecutive 24-h dietary recalls (24-HDR) were applied, and a 24-h urine sample was collected. We examined differences between estimates from dietary and urine measures, Pearson correlation coefficients were calculated and the Bland–Altman plots were drawn. Multiple linear regression was used to evaluate the factors associated with the difference between estimates.

Sub-sample from the Portuguese IAN-AF sampling frame.

Ninety-five adults (men and women) aged 18–84 years.

The estimated intake calculated using the dietary recall data was lower than that estimated from urinary excretion for the three biomarkers studied (protein 94·3 v. 100·4 g/d, K 3212 v. 3416 mg/d and Na 3489 v. 4003 mg/d). Considering 2 d of recall, the deattenuated correlation coefficients were 0·33, 0·64 and 0·26 for protein, K and Na, respectively. For protein, differences between dietary and urinary estimates varied according to BMI (β = −1·96, P = 0·017). The energy intake and 24-h urine volume were significantly associated with the difference between estimates for protein (β = 0·03, P < 0·001 and β = −0·02, P = 0·002, respectively), K (β = 0·71, P < 0·001 and β = −0·42, P = 0·040, respectively) and Na (β = 1·55, P < 0·001 and β = −0·81, P = 0·011, respectively).

The new software eAT24 performed well in estimating protein and K intakes, but lesser so in estimating Na intake, using two non-consecutive 24-HDR.

This study aimed to validate a nutrition knowledge questionnaire appropriate for use in Australia.

Nutrition knowledge is essential in establishing and maintaining strategies that reduce the burden of disease and promote wellbeing. The General Nutrition Knowledge Questionnaire (GNKQ) was developed in the United Kingdom in 1999 and validated for Australia in 2008. Changes in national nutrition recommendations and food availability prompted the redevelopment and revalidation of the UK questionnaire in 2016. However, the Australian questionnaire had not been subsequently updated.

Australia.

Content validity was determined using a sample of academic dietitians in Australia (n 8). Face validity was undertaken with retail employees (n 11) whose highest level of education was secondary school. Ninety-three undergraduate nutrition and engineering students at Queensland University of Technology completed the questionnaire for construct validity, and nineteen students were contacted a week later for test–retest reliability.

In the 117-scored questionnaire, nutrition students scored consistently higher in each of the four sections and overall (87 %, M 102, IQR 95, 107) compared with engineering students (77 %, M 82, IQR 76, 87·25, P < 0·01). Internal reliability of the questionnaire was high (α = 0·92) as was test–retest reliability (rs = 0·96, ICC2,1 = 0·99). AUS-R NKQ determined significant differences between individuals with known higher levels of nutrition knowledge and obtained high validity, reliability and consistency within an Australian sample.

AUS-R NKQ refined through this research is valid and would be an appropriate questionnaire for assessing the effectiveness of nutrition knowledge-based interventions for public health programmes, clinicians and researchers.

Le Metacognitions Questionnaire-30 (MCQ-30), développé par Wells et Cartwright-Hatton (2004) [1], est une échelle de mesure multidimensionnelle de facteurs métacognitifs impliqués dans le développement et la persistance de troubles psychiques. La théorie définitoire inhérente à cette échelle est résumée par Wells et Matthews [2] dans le modèle Self-Regulatory Executive Function (S-REF). Dans la dépression, une rumination pathogène serait induite par des pensées (croyances métacognitives évaluées par le MCQ-30) et des stratégies de contrôle qui perpétuent une cognition et des stratégies de coping inadaptées. Le but de notre étude est d’adapter et de valider une version française du MCQ-30 en évaluant ses propriétés psychométriques dans un échantillon de patients qui ont un diagnostic de dépression.

L’adaptation française de l’instrument a été réalisée après une traduction back-forward permettant une bonne validité de face. Elle est en cours de passation dans un échantillon de patients hospitalisés ayant un diagnostic de dépression établi selon les critères du DSM 4 TR. Le nombre de sujets nécessaires est estimé à 150 [3]. Une analyse factorielle confirmatoire permettra de vérifier la structure dimensionnelle à 5 facteurs retrouvée dans l’étude de validation de la version originale. Pour l’évaluation de la validité convergente, nous étudierons la corrélation des différents facteurs du MCQ-30 avec une mesure de l’anxiété d’état (Penn State Worry Questionnaire), de la rumination (Rumination on Sadness Scale), et de la dépression (Beck Depression Inventory). Hypothèses sur le comportement de l’échelle : en accord avec les validations étrangères, nous supposerons une corrélation positive et significative de la MCQ-30 avec les échelles sus-citées.

Des résultats partiels seront présentés et discutés à la lumière de la taille de l’échantillon.