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Marquez, J., Francis-Hew, L., & Humphrey, N. (2023). Protective factors for wellbeing resilience in adolescence: a longitudinal analysis using the residuals approach. Soc ArXiv.
This paper is currently under review which means it is being considered for publication. We used an innovative approach (the residuals approach) to advance our understanding of wellbeing resilience processes in adolescence. We analysed longitudinal #BeeWell data on 12, 130 young people to examine how adversity exposure impacts later wellbeing (life satisfaction, and internalising mental health difficulties) in the transition from year 8 (age 12/13) to year 9 (age 13/14); whether gender and ethnic differences in wellbeing resilience exist; which internal and external factors confer protective effects for wellbeing resilience; and whether the protective effect of these factors differs by gender and level of adversity exposure. Multiple adversity factors (e.g., home material deprivation, sexuality discrimination, bullying) were found to impact later wellbeing. Girls and white adolescents presented lower wellbeing resilience than their peers. Internal psychological factors (self-esteem, emotional regulation, optimism) consistently presented the strongest protective effects, but behavioural/activity factors (physical activity, sleep) also contributed to wellbeing resilience. Among external factors, friendships and peer support were the most salient. Physical activity yielded stronger protective effects among boys (compared to girls), while the reverse was true of self-esteem. Effects of protective factors were stronger among those at lower (compared to higher) levels of adversity exposure, which suggests that prevention and intervention efforts to reduce said exposure in the first place should be prioritised. These findings provide clear implications for policy and practice in terms of prevention (of adversity exposure) and intervention (to facilitate resilience).
Black, L., Humphrey, N., Panayiotou, M., & Marquez, J. (2023). Mental health and wellbeing measures for mean comparison and screening in adolescents: An assessment of unidimensionality and sex and age measurement invariance. Assessment, Online First.
The #BeeWell survey examines several domains of young people's wellbeing, drawing on consultation from young people and experts in its development (see here for more information). For instance, it covers questions about autonomy, optimism, as well as about stress and negative affect. Developing good measures is a difficult, lengthy and resource-intensive process. While the #BeeWell survey is made up of those supported by good evidence, there is still work to be done in this field in general. We therefore examined how our different wellbeing measures performed from several perspectives through psychometric analyses. First, we considered how well questions hung together when considering total scores for a given measure (e.g., autonomy or stress). Second, we analysed whether the measures were interpreted in the same way by boys versus girls (sex), and by those in Year 8 versus Year 10 (age). We found five of the eight measures had good evidence for use as total scores. For these five, we did however find differences in how the measures worked across sex and age. This means complex models should ideally be used rather than basic mean differences when comparing across these groups to ensure valid conclusions are drawn. Score cut-offs (e.g., considering a score of 10 or more to be indicative of increased risk) tended to be applicable across groups except for negative affect, for which the same score across girls and boys likely substantially underestimates the amount of problems experienced by boys.
Marquez, J., Humphrey, N., Black, L., Cutts, M., & Khanna, D. (2022). Gender and sexual identity-based inequalities in adolescent wellbeing: Findings from the #BeeWell study. BMC Public Health
In #BeeWell Evidence Briefing 1 we reported substantial inequalities in wellbeing affecting LGTBQI+ young people in Greater Manchester. These were routinely substantially greater than those concerning other characteristics (e.g. disparities across ethnic groups), meaning that LGTBQI+ young people reported much lower levels of wellbeing than their non-LGTBQI+ peers. In this paper, we extended our analysis to focus on a wider range of wellbeing domains, including life satisfaction, positive and negative affect. autonomy, self-esteem, optimism, positive relationships, symptoms of distress and mental wellbeing. For each of these, we found further evidence that wellbeing inequalities affecting LGTBQI+ young people were greater than those relating to other characteristics (e.g., socio-economic disadvantage). Young people whose identities transcend traditional binaries (e.g., non-binary) were subject to the most substantial inequalities when considering gender. Regarding sexual orientation, the greatest disparities were apparent for those who identified as gay/lesbian or bi/pansexual. Although these inequalities were substantial across all the wellbeing domains studied, they were particularly strong for negative affect (e.g. sadness, worry). We discuss the implications of these findings, including the importance of a whole-system response to tackle gender- and sexuality-based discrimination and prejudice, and provide safer and more inclusive cultures and spaces in which all young people can thrive.
Marquez, J., Humphrey, N., Black, L., & Wozmirska, S. (2023). This is the place: a multi-level analysis of neighbourhood correlates of young people’s wellbeing. Social Psychiatry and Psychiatric Epidemiology, OnlineFirst.
The #BeeWell data provide an excellent opportunity to study how neighbourhoods influence young people’s wellbeing in Greater Manchester. To investigate neighbourhood characteristics, data collected by the Co-op’s Community Wellbeing Index (CWI) were linked to #BeeWell dataset. The CWI uses neighbourhood boundaries called ‘seamless locales’, which are based on user feedback, data on observed travel, work and shop patterns, and administrative data. We studied neighbourhood effects for 35,902 young people across 243 neighbourhoods in Greater Manchester using a statistical analysis technique known as multi-level regression. In line with previous research, neighbourhoods accounted for a small but significant proportion of the variation in young people’s life satisfaction (0.61%) and internalising symptoms (1.17%). Furthermore, we found evidence that wellbeing inequalities for some groups (e.g. gender diverse young people) varied across neighbourhoods. Finally, several neighbourhood characteristics were found to predict individual wellbeing outcomes. For example, higher levels of perceived wellbeing support from local people predicted lower internalising symptoms. On the basis of such findings, we make a number of recommendations for placed-based, hyper-local policy responses. We also provide guidance for future research in this area, including the need for longitudinal work that uses indices of neighbourhoods and their characteristics designed by young people.
Black, L., Farzinnia, R., Humphrey, N. & Marquez, J. (2023). Variation in global network properties across risk factors for adolescent internalizing symptoms: evidence of cumulative effects on structure and connectivity. Psychological Medicine, OnlineFirst.
Teenagers can be particularly vulnerable to developing ‘internalizing symptoms’ (e.g. worry, sadness) and certain factors, such as perceived lack of family support, can heighten this risk further. The number of these risk factors to which a given young person is exposed may be important in predicting experiences of symptoms. However, previous studies have analysed symptoms in a simple way, treating mental health problems like a disease. More recently, researchers have begun to consider them as an interacting network of symptoms. For instance, worry might cause sleep problems, which might cause concentration issues, which might cause feelings of sadness, and so on. The idea is that symptoms reinforce each other to cause a distressed mental state. In this study, we assessed the effect of nine risk factors, and cumulative risk, on the structure and connectivity of internalizing symptom networks. By structure we mean which symptoms are interacting with one another, and by connectivity we mean how strongly they are related. Cumulative risk refers to the number of risk factors to which an individual is exposed. Network theory suggests that those at risk should show stronger connectivity and altered structure compared to those who are less vulnerable, and indeed, this is what we found in relation to individual risk factors and cumulative risk, though effects were mostly small. However, gender and sexual minority risk groups, as well those experiencing low parent/carer support, showed bigger differences for connectivity than the risk-absent groups. Furthermore, cumulative risk was a strong predictor of network connectivity. We conclude that network approaches to internalizing symptoms in adolescents can be useful to understand risks further. Gender and sexual minority groups, as well as those with low parent/carer support, may be particularly vulnerable and should be prioritized in prevention and intervention efforts. Our analysis also supports the idea that the number of risk factors experienced, regardless of their nature, predicts mental health outcomes. Young people experiencing multiple known risk factors should therefore receive additional support.
Marquez, J., Qualter, P., Petersen, K., Humphrey, N., & Black, L. (2023). Neighbourhood effects on loneliness among adolescents. Journal of Public Health, 45(3), 663-675.
Loneliness is a growing public health concern, but little is known about how place affects loneliness, especially in adolescence. This is the first study to examine the influence of neighbourhoods and their characteristics on loneliness in early/middle adolescence. We used #BeeWell data and administrative data collected at the neighbourhood (Lower Super Output Area) level to study neighbourhood effects on loneliness for 36,141 young people across 1,590 neighbourhoods in Greater Manchester using a statistical analysis technique known as multi-level regression. Neighbourhoods accounted for a small but significant proportion of the variation in adolescents’ loneliness (1.18%). We also found higher levels of loneliness among older adolescents (vs younger), whites (vs ethnic minorities), girls and gender diverse individuals (vs boys), sexual minorities (vs heterosexual), and those eligible for free school meals (vs non-eligible). Moreover, we found evidence that ethnic, gender and sexual orientation inequalities in loneliness varied across neighbourhoods. Furthermore, loneliness was higher in neighbourhoods with higher skills deprivation among children and young people, lower skills deprivation among adults, higher geographical barriers, lower outdoor environment deprivation, and higher population density, as well as among those who have to travel further from home to school. Finally, more positive perceptions of the local area (feeling safe, trust in local people, feeling supported by local people, seeing neighbours as helpful, and the availability of good places to spend your free time) were associated with lower levels of loneliness. Our findings suggest that local-level interventions may be particularly helpful to tackle adolescent loneliness and reduce loneliness inequalities affecting vulnerable groups (e.g. those who identify as LGBTQ+).
Thornton, E., & Humphrey, N. (2023). Prevalence, inequalities, and sequelae of bullying in adolescence: insights from the #BeeWell study. PsyArXiv
This paper is currently under review which means it is being considered for publication. Being bullied can lead to mental health difficulties, as well as other negative outcomes for young people. Although it is thought to be common in childhood and adolescence, estimates vary across studies due to differences in how bullying is measured. It is also important to identify any inequalities in exposure among different groups, as some groups (for example, those with special educational needs) may be more at risk of being bullied and the associated consequences than others. We therefore investigated whether changes in how we qualify someone as being bullied, or the specific type (physical, relational, or cyber) of bullying experienced, influences what our analyses tell us about how many young people are bullied, who is more likely to be a victim of bullying, and the extent to which exposure to bullying associated with mental health difficulties, using a range of statistical analyses of the #BeeWell dataset. The extent of bullying exposure ranged between 5% and 16%, depending on how this was defined, with young people who reported being bullied frequently on at least one of physical, relational, or cyber bullying being the most common (16%). Inequalities in exposure to bullying were consistently found among LGBTQ+ young people (compared to cisgender heterosexual males); those with special educational needs (compared to those without); younger students (compared with older students); and those from more disadvantaged neighbourhoods (compared to more advantaged neighbourhoods). However, inequalities among cisgender heterosexual females (compared to cisgender heterosexual males) and ethnic minority groups (compared to those of a White ethnicity) varied based on how bullying exposure was defined and the type of bullying being considered. Our findings also indicated that those who are bullied (regardless of how this was defined) are more likely to experience significant mental health difficulties. One of our analyses indicated that if bullying could be effectively prevented, we could reduce the rate of such difficulties by nearly 20%. Finally, the impact of being bullied on mental health difficulties was stable across sociodemographic groups, with the exceptions of being more strongly associated among LGBTQ+ young people and cisgender heterosexual females (compared to cisgender heterosexual males), and less strongly associated among Black students (compared to White students). We discuss the implications of our findings, for both research and practice, including the potential of targeting bullying to reduce rates of mental health difficulties among young people, and the importance of explicitly defining how bullying has been measured, so that any findings can be interpreted within that specific context.
Black, L., Humphrey, N. & Marquez, J. (2023). The influence of minority stress-related experiences on mental wellbeing for trans/gender-diverse and cisgender youth: a comparative longitudinal analysis. Royal Society Open Science, 10(7), 1-21.
Trans and gender-diverse (TGD) young people are likely to experience poorer mental health and wellbeing than their cisgender peers. Minority stress theory suggests that this may be because increased exposure to factors such as bullying and discrimination lead to excess stress and reduced wellbeing. However, the evidence base remains limited. In this study we set out to examine these ideas using #BeeWell data. First, we examined differences in wellbeing between TGD young people and their peers. Second, we examined differences between these groups in exposure to minority-related stressors (bullying, gender discrimination, lack of family support, and feeling unsafe). Third, we examined the extent to which exposure to minority-related stressors predicted later wellbeing. Our analysis showed that compared to cisgender boys, TGD young people, cisgender girls, and those who preferred not to say their gender identity reported lower wellbeing (with the largest effect evident for the TGD group). TGD young people also reported higher rates of exposure to all minority-related stressors. We found that exposure to these stressors predicted later wellbeing (e.g., being bullied more in 2021 predicted lower wellbeing in 2022), but that this effect was not moderated by gender (e.g., the magnitude of the impact of bullying on later wellbeing was equivalent for all our gender groups). We discuss the implications of these findings in relation to things like coverage of gender identity in relationships and sex education guidance for schools, in addition to tailored services to support TGD young people.
Thornton, E., Petersen, K., Marquez, J. & Humphrey, N. (2023). Do patterns of adolescent participation in arts, culture and entertainment activities predict later wellbeing? A latent class analysis. PsyArXiv
This paper is currently under review which means it is being considered for publication. The ways in which we spend our free time (i.e., leisure) can benefit us in terms of our mental wellbeing. This includes participation in arts, culture, and entertainment (PACE) activities (e.g. creative hobbies, playing videogames, reading for pleasure). We used a statistical method called Latent Class Analysis (LCA) to identify common profiles (groups) of PACE among young people in Greater Manchester, based on the amount of time they reported spending doing each activity. We could then assess whether certain socio-demographic characteristics (e.g., socio-economic disadvantage) predicted membership of a given PACE group, and whether PACE group membership predicted later wellbeing. Patterns of PACE fell into four distinct groups, which we called 1) the Dynamic Doers, who had high probabilities of taking part in a wide range of activities; 2) the Mind and Body Crew, who were likely to spend their time reading for enjoyment, participating in arts and crafts or other creative hobbies, doing exercise or other physical activities, and playing video games; 3) the Game and Gain Squad, who were highly likely to play sports, do exercise or other physical activities, and play video games; and 4) the Activity Free Association, who were unlikely to take part in any PACE activities. Associations between socio-demographic characteristics and PACE classification were established (e.g., socio-economic disadvantage increased the likelihood of Activity Free Association classification, compared to Game and Gain Squad classification). We also found that PACE classification predicted later wellbeing (e.g., Dynamic Doers reported significantly higher wellbeing than the Activity Free Association). These findings emphasise the role of PACE in supporting young people’s wellbeing and underscore the importance of making PACE activities appealing and accessible to all.
