Background: Covid-19 remains a pandemic that most countries in the world are still dealing with. This is study aims to report the psychological impact of Covid-19 over time on the Spanish population. Methods: A longitudinal study (N = 1041) was carried out with two measurements: after 2 and 5 weeks starting from the declaration of the state of emergency in Spain. The presence of depressive symptoms, anxiety, and posttraumatic stress disease (PTSD) was evaluated by means of screening tests. Sociodemographic data, variables about Covid-19, loneliness, spiritual well-being, social support, discrimination, and a sense of belonging were collected. Results: The data showed how depressive symptomatology increased significantly over time, while anxiety and PTSD did not show statistically significant changes. Spiritual well-being and loneliness were the main predictors of psychological impact. A younger age was a significant predictor of depression and anxiety, while female gender was associated with anxiety and PTSD. Conclusions: The impact of the pandemic is sustained over time, even increasing in depression, and vulnerable groups that need greater psychological health support could be identified.

Background: Since 2009 Time to Change has included among its strategies a social marketing campaign to tackle the stigma surrounding mental health problems. At the start of its third phase (2016–2021) the target group of the campaign was kept as people aged between mid-twenties and mid-forties but changed to middle-low income groups and the content was focused on men. Methods: Participants (n = 3700) were recruited through an online market research panel, before and after each burst of the campaign. They completed an online questionnaire evaluating knowledge (Mental Health Knowledge Schedule, MAKS); attitudes (Community Attitudes toward Mental Illness, CAMI); and desire for social distance (Intended Behaviour subscale of the Reported and Intended Behaviour Scale, RIBS). Socio-demographic data and awareness of the campaign were also collected. Results: For each of the 3 bursts, significant pre-post awareness differences were found (OR = 2.83, CI = 1.90–4.20, p < 0.001; OR = 1.72, CI = 1.22–2.42, p = 0.002; OR = 1.41, CI = 1.01–1.97, p = 0.043), and awareness at the end of the third burst was 33%. Demographic factors associated with awareness for one or more bursts included having children, familiarity with mental illness, male sex, being Black, Asian or other ethnic minorities and living in London or the East Midlands regions. An improvement across bursts in the “living with” subscale item of the RIBS, and in the “recover” and “advice to a friend” MAKS items were found. Familiarity with mental illness had the strongest association with all outcome measures, while the awareness of the campaign was also related with higher scores in MAKS and RIBS. Conclusions: These interim results suggest that the campaign is reaching and having an impact on its new target audience to a similar extent as did the TTC phase 1 campaign. While over the course of TTC we have found no evidence that demographic differences in stigma have widened, and indeed those by age group and region of England have narrowed, those for socioeconomic status, ethnicity and sex have so far remained unchanged. By targeting a lower socioeconomic group and creating relatively greater awareness among men and in Black and ethnic minority groups, the campaign is showing the potential to address these persistent differences in stigma.

Major depressive disorder (MDD) is one of the most prevalent conditions among mental disorders in individuals over 65 years. People over 65 who suffer from MDD are often functionally impaired, chronically physically ill, and express cognitive problems. The concordance between a clinician-assessed MDD diagnosis in a primary care setting and MDD assessed with a structured clinical interview in older adults is only approximately 18%. Network analysis may provide an alternative statistical technique to better understand MDD in this population by a dimensional approach to symptomatology. The aim of this study was to carry out a network analysis of major depressive disorder (MDD) in people over 65 years old. A symptom network analysis was conducted according to age and gender in 555 people over 65, using a sample from the MentDis_ICF65+ Study. The results revealed different networks for men and women, and for the age groups 65–74 and 75–84. While depressive mood stood out in women, in men the network was more dispersed with fatigue or loss of energy and sleep disturbances as the main symptoms. In the 65–74 age group, the network was complex; however, in the 75–84 age group, the network was simpler with sleep disturbances as the central symptom. The gaps between the networks indicate the different characteristics of MDD in the elderly, with variations by gender and age, supporting the idea that MDD is a complex dynamic system that has unique characteristics in each person, rather than a prototypical classification with an underlying mental disorder. These unique characteristics can be taken into account in the clinical practice for detection and intervention of MDD.