ABSTRACT
Good data also provide an understanding of the factors contributing to and protecting against these conditions, and information on the accompanying impact on peoples' lives.1 We (the authors) are proposing an innovative approach to defining what good epidemiological data is in the Aotearoa New Zealand context;how to collect it, and most importantly how it can be used to design and offer supports and services that respond to peoples' needs. National prevalence surveys In 2006, the landmark epidemiological study, Te Rau Hinengaro: The New Zealand Mental Health Survey, was published.2 For the first time this gave Aotearoa New Zealand population level information on the prevalence of a range of mental health conditions and substance use disorders. Te Pou have published a series of reports and resources exploring existing data and commonly used measures for the adult population.10-12 Similarly, Theodore and colleagues in this issue highlight the inequities for Māori youth compared to non-Māori from an examination of routinely available service use data.13 What these, and other recent surveys show is that something different is happening emotionally, particularly for rangatahi, and that there are growing inequities across different priority groups which we must pay attention to.7'14'15 To respond appropriately and effectively, a better understanding of the person, their whānau, community and their needs is required. Brief screening tools are intentionally designed to identify more people, and therefore overestimate prevalence.16'17 In addition, symptoms such as psychological distress often have peaks and troughs in a population, without similar rises in underlying prevalence of mental health conditions and substance use disorders.12,18 Global and national events, such as the COVID19 pandemic and subsequent lockdowns are known to have psychological impacts on the population, but it remains unknown whether there has been a greater shift in underlying prevalence of mental health conditions or substance use disorders, or whether the rises we are seeing in levels of psychological distress are a reactionary peak.
ABSTRACT
To design effective pro-vaccination messaging, it is important to know "where people are coming from"-the personal experiences and long-standing values, motives, lifestyles, preferences, emotional tendencies, and information-processing capacities of people who end up resistant or hesitant toward vaccination. We used prospective data from a 5-decade cohort study spanning childhood to midlife to construct comprehensive early-life psychological histories of groups who differed in their vaccine intentions in months just before COVID vaccines became available in their country. Vaccine-resistant and vaccine-hesitant participants had histories of adverse childhood experiences that foster mistrust, longstanding mental-health problems that foster misinterpretation of messaging, and early-emerging personality traits including tendencies toward extreme negative emotions, shutting down mentally under stress, nonconformism, and fatalism about health. Many vaccine-resistant and -hesitant participants had cognitive difficulties in comprehending health information. Findings held after control for socioeconomic origins. Vaccine intentions are not short-term isolated misunderstandings. They are part of a person's style of interpreting information and making decisions that is laid down before secondary school age. Findings suggest ways to tailor vaccine messaging for hesitant and resistant groups. To prepare for future pandemics, education about viruses and vaccines before or during secondary schooling could reduce citizens' level of uncertainty during a pandemic, and provide people with pre-existing knowledge frameworks that prevent extreme emotional distress reactions and enhance receptivity to health messages. Enhanced medical technology and economic resilience are important for pandemic preparedness, but a prepared public who understands the need to mask, social distance, and vaccinate will also be important.
ABSTRACT
BACKGROUND: Loneliness co-occurs alongside many mental health problems and is associated with poorer treatment outcomes. It could therefore be a phenomenon of interest to clinicians as an indicator of generalised risk for psychopathology. The present study tested whether a short measure of loneliness can accurately classify individuals who are at increased risk of common mental health problems. METHODS: Data were drawn from two nationally representative cohorts: the age-18 wave of the UK-based Environmental Risk (E-Risk) Longitudinal Twin Study and the age-38 wave of the New Zealand-based Dunedin Multidisciplinary Health and Development Study. In both cohorts, loneliness was assessed using the three-item UCLA Loneliness Scale, plus two stand-alone items about feeling alone and feeling lonely. Outcome measures consisted of diagnoses of depression and anxiety and self-reports of self-harm/suicide attempts, assessed via a structured interview. RESULTS: ROC curve analysis showed that the Loneliness Scale had fair accuracy in classifying individuals meeting criteria for all three outcomes, with a cut-off score of 5 (on a scale from 3 to 9) having the strongest empirical support. Both of the stand-alone items showed modest sensitivity and specificity but were more limited in their flexibility. The findings were replicated across the two cohorts, indicating that they are applicable both to younger and older adults. In addition, the accuracy of the loneliness scale in detecting mental health problems was comparable to a measure of poor sleep quality, a phenomenon which is often included in screening tools for depression and anxiety. CONCLUSIONS: These findings indicate that a loneliness measure could have utility in mental health screening contexts, as well as in research.