To assess the accuracy of seven commonly used Global Positioning System (GPS)-based geolocation techniques, including a handheld GPS device and smartphones using Google Maps, Open Data Kit (ODK) and Research Electronic Data Capture (REDCap) with and without internet connectivity, for measuring distances between houses in a field epidemiology setting.

Cross-sectional study conducted in February–March 2024.

Field study in a village in the Comoros where leprosy is endemic.

55 randomly selected house pairs, of which 50 were included in the analysis.

Measurement error, defined as the difference in straight-line distance between house pairs measured by each index test (GPS-based geolocation technique) and the reference standard (surveyor map).

Three index tests showed substantial shortcomings, including indeterminate results (one technique), outliers (two techniques), systematic underestimation (mean measurement error –3.0 m for one technique) and high variability (SD of measurement error ranging from 9.4 m to 16.6 m). The remaining four index tests showed little bias (mean measurement error ranging from –1.7 m to 0.4 m across techniques) and low variability (SD of measurement error ranging from 5.7 m to 7.4 m). For the most precise technique, 95% of measurements were estimated to fall between an underestimation of 11.9 m (95% CI 8.9 to 17.5 m) and an overestimation of 10.5 m (95% CI 8.4 to 13.7 m). Even this narrowest range was two to three times wider than the claimed accuracy.

GPS-based geolocation techniques may show substantial variability under field conditions and may give rise to misplaced confidence in their accuracy when this is assumed rather than empirically assessed. Careful selection and testing of techniques in context, along with transparent data handling and consideration of uncertainty, are needed to improve the reliability of geospatial data in public health research and practice.

To validate the cross-national psychometric properties of the Mental Health Quality of Life questionnaire (MHQoL) and to develop an open-source toolbox for its scoring, transformation and presentation.

Secondary analysis of data from a multicentre international randomised controlled trial (EMPOWER).

Workplace settings in small-sized and medium-sized enterprises (SMEs) and public sector organisations in Finland, Spain and the UK.

The sample included 564 employees: 122 from Finland, 114 from Spain and 328 from the UK. Most were white-collar workers in SMEs or public organisations, mainly in public administration, manufacturing, health/life sciences or higher education. Women were the majority (56%–91% across countries), and mean age ranged from 43 to 48 years.

No intervention was delivered for this analysis; data were drawn from baseline assessments.

Primary outcomes were internal consistency and construct validity of the MHQoL, evaluated using Cronbach’s alpha, measurement invariance testing and multilevel analyses of associations between MHQoL dimensions and its visual analogue scale (VAS). Secondary outcomes were convergent validity, assessed through correlations between MHQoL scores and other mental health and quality of life measures (EuroQol 5-Dimension 5- level questionnaire (EQ-5D-5L), Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder-7 (GAD-7), Insomnia Severity Index, Perceived Stress Scale-4 (PSS-4), Psychosocial Risk Scale, and World Health Organization Five Well-Being Index (WHO-5)).

The MHQoL showed good internal consistency across countries, with Cronbach’s alpha ranging from 0.741 in Finland to 0.806 in Spain (overall α=0.787). Measurement invariance across Finland, Spain and the UK supported construct validity. Multilevel regression analyses showed associations between MHQoL dimensions and the MHQoL-VAS, with strongest contributions from Self-Image, Daily Activities, Mood and Future. Convergent validity was supported by moderate to strong correlations between MHQoL, EQ-5D-5L and related mental health measures. An open-source R package and Shiny web application (‘MHQoL Toolbox’) were developed for scoring, transformation and visualisation

The MHQoL is a reliable and valid measure of mental health-related quality of life across countries. The MHQoL toolbox supports consistent, transparent implementation, facilitating use in research, clinical practice and economic evaluations.

NCT04907604.