Authors Bastien Paris, Debora Brickau, Tetiana Stoianova, Maike Luhmann, Christopher Mikton, Julianne Holt-Lunstad, Marlies Maes, Hans IJzermanPlease use the format "First name initials family name" as in "Marie S. Curie, Niels H. D. Bohr, Albert Einstein, John R. R. Tolkien, Donna T. Strickland"
Abstract <p>Social connection is vital to health and longevity. To date, a plethora of instruments exists to measure social connection, assessing a variety of aspects of social connection like loneliness, social isolation, or social support. For comparability and consistency of the published literature and for policy recommendations, consolidation and evaluation of the quality of measures is crucial. To answer the call for comparability, in Study 1a, we conducted a systematic review to create a database of social connection measures (N=xx) for its structure (N=xx), function (N=xx), and quality components (N=xx), spanning [YEAR] to [YEAR]; after which, in Study 1b, we assessed the heterogeneity of these existing measures through an item-content analysis relying both on human coders, as well as ChatGPT. We identified a total of XX item categories (XX for structure, XX for function, and XX for quality components) with a Jaccard index of XX for structure, XX for function, and XX for quality components. To answer the call for quality assessment, in Study 2a, we conducted a second systematic review on the measures found in Study 1a, creating a database documenting overall validity evidence. In Study 2b, we then evaluated the measurement properties using the COnsensus-based Standards for the Selection of health Measurement Instruments. We found the measurement properties to be [sufficient / insufficient / inconsistent / indeterminate], [sufficient / insufficient / inconsistent / indeterminate], and [sufficient / insufficient / inconsistent / indeterminate]; with [high/moderate/low/very low], [high/moderate/low/very low], and [high/moderate/low/very low] quality of evidence for the structure, function, and quality components, respectively. Finally, we identified the country of origin of the measures and the population groups with which they were developed, using data from Study 1a. Most of the measures were developed in [country name] (XX%) and for [add population characteristics] (XX%). [Overall conclusion].</p>
Keywords measurement, social connection, social isolation, loneliness, social support, systematic review, quality assessment
