Mental Health and Well-being Measures for Mean Comparison and Screening in Adolescents: An Assessment of Unidimensionality and Sex and Age Measurement Invariance

Abstract

Adolescence is a period of increased vulnerability for low well-being and mental health problems, particularly for girls and older adolescents. Accurate measurement via brief self-report is therefore vital to understanding prevalence, group trends, screening efforts, and response to intervention. We drew on data from the #BeeWell study ( N = 37,149, aged 12–15) to consider whether sum-scoring, mean comparisons, and deployment for screening were likely to show bias for eight such measures. Evidence for unidimensionality, considering dynamic fit confirmatory factor models, exploratory graph analysis, and bifactor modeling, was found for five measures. Of these five, most showed a degree of non-invariance across sex and age likely incompatible with mean comparison. Effects on selection were minimal, except sensitivity was substantially lower in boys for the internalizing symptoms measure. Measure-specific insights are discussed, as are general issues highlighted by our analysis, such as item reversals and measurement invariance.

Neighbourhood effects on loneliness among adolescents

“…The characteristics of the sample are noted in Table 1 . They closely mirror those of the population of young people aged 11–16 years both in Greater Manchester and in England (although, compared to national levels, the proportion of Asian youth is somewhat higher, and the proportion of White youth is somewhat smaller 25 ).…”

The influence of minority stress-related experiences on mental wellbeing for trans/gender-diverse and cisgender youth: a comparative longitudinal analysis

“…Consideration of adolescent mental health and wellbeing must therefore be handled carefully in terms of selecting outcome measures and modelling structure. Based on these issues, and in-depth psychometric analysis of all mental health and wellbeing measures in the #BeeWell dataset [ 6 ], we opted to focus on mental wellbeing via the Short Warwick Edinburgh Mental Wellbeing Scale. While there is often interest in disease burden from a policy perspective [ 7 ], this measure includes experiences relevant to mental disorder such as relaxedness [ 8 ], has favourable scoring properties and demonstrates more acceptable sex/age measurement invariance, particularly compared with the available symptom measure [ 6 ].…”

“…Based on these issues, and in-depth psychometric analysis of all mental health and wellbeing measures in the #BeeWell dataset [ 6 ], we opted to focus on mental wellbeing via the Short Warwick Edinburgh Mental Wellbeing Scale. While there is often interest in disease burden from a policy perspective [ 7 ], this measure includes experiences relevant to mental disorder such as relaxedness [ 8 ], has favourable scoring properties and demonstrates more acceptable sex/age measurement invariance, particularly compared with the available symptom measure [ 6 ]. In addition, wellbeing has considerable utility in population mental health research [ 9 ], given that most young people would not meet diagnostic criteria for disorder [ 8 , 10 ], and dimensional symptom measures tend to show substantial floor effects in non-clinical populations, limiting their reliability and validity [ 11 ].…”

“…Specifically, for the present study, the following factors make a registered report appropriate: first, our registered hypotheses are confirmatory. Second, we proposed a relatively complex analysis pipeline to accommodate known measurement issues in this field [ 3 , 6 ]. This represents potentially increased researcher degrees of freedom, particularly since alternative modelling frameworks (e.g.…”

“…Prior knowledge of data can lead to bias because expectations are formed that lead researchers to pursue particular analyses after testing related questions with the same variables. We therefore declare our prior access and other analyses of the T1 #BeeWell dataset [ 6 , 22 , 58 , 59 ]. We note in particular our existing analysis that suggests disparities in mental wellbeing between gender and sexual minority adolescents and their peers (which serves as a key motivation for the current study; [ 22 ]), but also highlight that this pertains specifically to data gathered at T1 only, concerns a range of mental health and wellbeing outcomes and different approach to analysing gender, without any analysis of minority stressors that might underpin such inequalities.…”