BACKGROUND:Due to the side effects of antipsychotics, overtreatment is an important concern. Previous research focused on antipsychotic polypharmacy and excessively high doses. In this study, the aim is to map changes over the years in potential overtreatment, antipsychotic polypharmacy, total antipsychotic dose, and subjective side effect burden. Moreover, the association of the total dose and antipsychotic polypharmacy with the subjective side effect burden will be investigated. STUDY DESIGN:Data from a naturalistic longitudinal cohort were used (PHAMOUS, 2013-2021). Potential overtreatment was defined as a antipsychotic dose equivalent to > 5 mg risperidone or antipsychotic polypharmacy, in combination with a high subjective side effect burden. Mixed effect models were used to investigate trends in potential overtreatment, antipsychotic polypharmacy, total antipsychotic dose, and subjective side effect burden and to assess the association of total dose and antipsychotic polypharmacy with subjective side effect burden. STUDY RESULTS:Overall, 15,717 observations nested in 5,107 participants were used. One-third of the participants were potentially overtreated, which did not change over time. The prevalence of a dose above the equivalent of 5 mg risperidone decreased, antipsychotic polypharmacy prevalence increased, and the subjective side effect burden decreased. A higher dose and antipsychotic polypharmacy were associated with higher subjective side effect burden. CONCLUSION:Potentially overtreated patients should be revaluated to assess whether changes are needed. To assess whether a patient is truly overtreated, their clinical history, number of relapses, patients' preferences, overall functioning, previous attempts to reduce antipsychotic treatment, and previous severity of disease should be taken into account.

AIM:Individuals with mental health concerns face additional risks in reproductive health. The responsibility of mental healthcare professionals (MHPs) in discussing reproductive health themes - including sexuality, contraception, family planning, pregnancy and parenthood (SCUFPP) - remains underexplored. This study aimed to assess MHPs' opinions, practices, perceived competence and collaboration in discussing SCUFPP with patients. METHODS:Data from 236 Dutch MHPs who completed a 22-item questionnaire on SCUFPP between January 2023 and August 2024 (survey A) were combined with data from 139 Dutch MHPs who completed a nationwide previous survey in May 2022 (survey B) on family planning, to deepen the exploration. Subgroup analyses included gender, age and experience. RESULTS:In total, 55.5% of MHPs agree that family planning should be discussed with every patient of reproductive age, while 44.5% did not explicitly agree. Sexuality and parenthood were discussed more often than family planning, pregnancy and contraception. Older and more experienced MHPs initiated conversations more often. Most MHPs felt competent to discuss SCUFPP, while a minority (27.3%) was familiar with methods or conversation techniques. Female MHPs more often felt competent and expressed a greater need for education on pregnancy. Most MHPs valued collaboration with integrated and preconception care in mental healthcare. CONCLUSION:These findings point to a gap between MHPs' perceived responsibility and their ability to implement these conversations in practice. Enhanced training and collaboration with expert consultations in SCUFPP may improve MHPs' responsibility in informed reproductive choices, enhancing mental health outcomes for patients.

Background Antipsychotics are used to manage symptoms and reduce the risk of relapse. However, the antipsychotic side effects are associated with a lower quality of life and are seen as major barriers to achieving societal recovery by antipsychotic users. In this study, we investigate the association of side effects, antipsychotic dose, and antipsychotic polypharmacy with societal recovery and happiness. Study Design Data were used from a large, naturalistic, longitudinal cohort of people using an antipsychotic in long-term care (Pharmacotherapy Monitoring and Outcome Survey [PHAMOUS], 2013-2021). The association between subjective antipsychotic side-effect burden (measured with the Subjective Response to Antipsychotics questionnaire), antipsychotic dose, and antipsychotic polypharmacy with societal recovery and happiness was investigated using mixed-effect linear regression models. In an exploratory analysis, the associations between individual side effects with societal recovery and happiness were assessed. Study Results Data from 5971 observations nested in 2490 participants were used. The subjective antipsychotic side-effect burden, total antipsychotic dose, and antipsychotic polypharmacy were significantly negatively associated with societal recovery. Subjective antipsychotic side-effect burden and total antipsychotic dose were significantly negatively associated with happiness, but antipsychotic polypharmacy was not. Cognitive, mood, and physical anticholinergic side effects were most strongly negatively associated with societal recovery. Mood-, sedation-, cognitive-, and sexual-related side effects were most strongly negatively associated with happiness. Conclusions These results show that side effects and a higher dose of antipsychotic medication are negatively associated with societal functioning and happiness. Future research should focus on whether dose reduction is beneficial for societal recovery and happiness in the long-term.

Background: Drug prescription networks (DPNs) model the temporal dynamics of medication co-prescription within a population. Understanding these networks can provide insights into polypharmacy and prescribing behaviors. Objective: This study assesses the structural characteristics of temporal DPNs derived from daily co-prescriptions of antidepressants, anxiolytics, and other therapeutic drug classes. By analyzing these networks using eigenvector centrality, we identify influential medications and prescribing patterns. Methods: We utilized the IADB.nl database, including prescriptions from 128 Dutch pharmacies (2018–2022). A cohort of patients prescribed antidepressants/anxiolytics was extracted. Medications were classified using the Anatomical Therapeutic Chemical (ATC) system into 24 therapeutic classes. Time-varying DPNs were constructed as undirected graphs using symmetric daily dose-adjusted co-prescriptions. Eigenvector centrality (ce) quantified relative nodal importance. Weekly-aggregated data included number of dispensing (nc) and eigenvector centrality, which were decomposed using a singular-spectrum approach. Results: Antidepressants (ce: 0.09, nc: 28,993) and anxiolytics (ce: 0.05, nc: 14,061) had high eigenvector centrality, demonstrating frequent co-prescription. Other ATC groups with high centrality included those for the alimentary tract and metabolism (A01-A16), blood and blood-forming organs (B01-B06), cardiovascular system (C01-C10), respiratory system (R01-R07), and analgesics (N02). Discussion: DPNs revealed key co-prescription patterns. High-centrality medications highlight potential targets for drug monitoring, such as identifying co-prescription trends that may warrant evaluation for safety, appropriateness, or policy oversight. This approach aids in identifying influential medications and refining prescribing oversight.

IntroductionChildhood traumatization can result in physical and mental health problems in adulthood, such as post-traumatic stress disorder (PTSD), which negatively influences quality of life and social functioning. Although evidence based trauma treatments benefit clients with PTSD after childhood abuse and comorbid personality disorders, they are less effective than in clients who were traumatized in adulthood, and drop-out is substantial. The current study aims to assess the effects of inpatient dialectical behavior therapy combined with prolonged exposure (DBT-PTSD) on severity of PTSD, dissociation, parasuicidal behavior and borderline personality disorder (BPD) in clients with severe PTSD and comorbid psychiatric disorders. Secondary outcomes are social functioning, quality of life, borderline and cluster C personality disorder symptoms as treatment predictors, treatment trajectories, clients’ experiences and health economic consequences.MethodsThe naturalistic, longitudinal Trauma Therapy Study is conducted from January 2019 until May 2025 in a mental healthcare center in the Netherlands. Clients with severe PTSD and comorbid conditions who are referred to inpatient DBT-PTSD are included into the study. Based on power analyses a total sample size of N=56 is needed. Measurements take place before the waiting list period, at pre- and posttreatment and at six- and twelve-months follow-up. Clients fill in a daily DBT-PTSD diary, which gives insight into individual symptom trajectories.ResultsStatistical analyses include two-sided paired samples t-tests, linear mixed model analyses and cost-effectiveness analyses. Qualitative interviews are conducted within two years posttreatment and analyzed using a phenomenological approach. We correct for chance capitalization by using a conservative α-level of.01. Multiple imputation is used to handle missing data.DiscussionResearch on the effects of integrated treatment programs for clients with severe PTSD and co-morbid conditions is scarce. This study extends current knowledge on the effects of inpatient DBT-PTSD on PTSD and BPD symptoms, clients’ social functioning and quality of life. In addition, it provides insight into individual symptom trajectories and experiences, inspiring future treatment improvements for clients with severe psychopathology.Trial registrationMedical Ethical Committee approval (NL669060018, RTPO1044/01.10.2018). Preregistration: Dutch registration database Centrale Commissie Mensgebonden Onderzoek and International Clinical Trials Registry Platform (NL-OMON46167/01.10.2018/https://trialsearch.who.int/Trial2.aspx?TrialID=NL-OMON46167).

Background:Major depressive disorders significantly impact the lives of individuals, with varied treatment responses necessitating personalized approaches. Shared decision-making (SDM) enhances patient-centered care by involving patients in treatment choices. To date, instruments facilitating SDM in depression treatment are limited, particularly those that incorporate personalized information alongside general patient data and in cocreation with patients. Objective:This study outlines the development of an instrument designed to provide patients with depression and their clinicians with (1) systematic information in a digital report regarding symptoms, medical history, situational factors, and potentially successful treatment strategies and (2) objective treatment information to guide decision-making. Methods:The study was co-led by researchers and patient representatives, ensuring that all decisions regarding the development of the instrument were made collaboratively. Data collection, analyses, and tool development occurred between 2017 and 2021 using a mixed methods approach. Qualitative research provided insight into the needs and preferences of end users. A scoping review summarized the available literature on identified predictors of treatment response. K-means cluster analysis was applied to suggest potentially successful treatment options based on the outcomes of similar patients in the past. These data were integrated into a digital report. Patient advocacy groups developed treatment option grids to provide objective information on evidence-based treatment options. Results:The Instrument for shared decision-making in depression (I-SHARED) was developed, incorporating individual characteristics and preferences. Qualitative analysis and the scoping review identified 4 categories of predictors of treatment response. The cluster analysis revealed 5 distinct clusters based on symptoms, functioning, and age. The cocreated I-SHARED report combined all findings and was integrated into an existing electronic health record system, ready for piloting, along with the treatment option grids. Conclusions:The collaboratively developed I-SHARED tool, which facilitates informed and patient-centered treatment decisions, marks a significant advancement in personalized treatment and SDM for patients with major depressive disorders.

Inpatient Dialectical Behavioural Therapy combined with trauma treatment (DBT-PTSD) focuses on clients with severe posttraumatic stress disorder (PTSD) and comorbid complaints. Previous research demonstrated the effectiveness of the treatment program in a randomized controlled trial with a 'treatment as usual' condition in a group of women with a PTSD after childhood sexual abuse. The treatment, which on the one hand is protocolised, and on the other hand adaptable to the individual complaints and treatment goals of the patient, is illustrated with two cases. 'Maaike' and 'Klaas', two clients with an extensive trauma history and a long psychiatric background, benefitted from this integrated treatment program. Beside a severe PTSD, they suffered from very different forms of comorbid complaints. Inpatient DBT-PTSD is part of recent developments in the trauma field and exists in the treatments on offer for patients with severe trauma related complaints within the Netherlands.

BACKGROUND:Optimizing depression treatment intensity and duration is crucial, given an overburdened mental healthcare system. However, decision-making is challenged by heterogeneous treatment effects. We aimed to investigate these effects, accounting for confounders and population heterogeneity, in a real-world dataset from specialized mental healthcare. METHODS:The study included 36,946 participants from mental healthcare providers in the Northern Netherlands. We measured the effects of treatment duration and intensity on time to depression recurrence, using monthly costs as a proxy for treatment intensity. An accelerated failure time model was used, adjusting for confounding via entropy weighting. Non-linear effects were examined using restricted cubic splines to identify turning points, after which linear analyses were stratified. Population heterogeneity was explored through K-means clustering analyses, followed by cluster-specific analyses. RESULTS:In the high-intensity group (above €360/month), a €1000/month increase in treatment intensity may reduce time to recurrence by 16% (acceleration factor [AF] 0.84, 95% CI 0.77-0.92). Conversely, the same increase in the low-intensity group might prolong recurrence-free time by 9.6-fold (AF 9.6, 95% CI 2.18-42.31). Extending treatment duration by 6 months may reduce time to recurrence by 7% (AF 0.93, 95% CI 0.89-0.97) in the long-duration group, with no significant effect in the short-duration group. Five clusters emerged, three of which comprised only women, with AFs of 0.67, 0.80, and 0.81, respectively, under high treatment intensity. CONCLUSIONS:Increasing treatment intensity appears worthwhile only in the low-intensity group, though residual confounding remains possible.

To enable patient-centred treatment choices, shared decision-making (SDM) is essential. To date, instruments facilitating SDM in depression treatment are scarce, especially those that add personalized information, next to more general patient information. Co-creation is essential and seldom used in the development of such tools. We describe the development of an instrument that provides patients with depression and their clinicians with: (1) systematic information regarding symptoms, medical history, situational factors and potentially successful treatment strategies in a digital report and (2) objective treatment information guiding treatment decisions. The study was co-led by researchers and patient representatives, indicating all decisions regarding the development of the instrument were taken together. Data collection, analyses and tool development took place between 2017 – 2021. A mixed-methods approach was applied. Qualitative research provided insight into the end-users’ needs and preferences. A scoping review provided a summary of the available literature on identified predictors of treatment response. K-means cluster analysis was applied to suggest potentially successful treatment options based on similar patients and their outcomes in the past. These data were combined in a digital report. Treatment option grids were developed by patient advocacy groups to provide objective information on evidence-based treatment options. The ‘Instrument for SDM in Depression’ (I-SHARED) was developed, incorporating individual characteristics and preferences. Qualitative analysis and the scoping review resulted in the identification of four categories of predictors of treatment response. The cluster analysis identified five distinct clusters based on symptoms, functioning and age. The co-created I-SHARED report combined all findings and was integrated into an existing electronic health record system ready for piloting, together with the treatment option grids. The collaboratively developed decision aid for depression, including a clustering algorithm to predict potentially successful treatment options, has the potential to support SDM between patients and clinicians.

Background Combining non-specialists and digital technologies in mental health interventions could decrease the mental healthcare gap in resource scarce countries. This systematic review examined different combinations of non-specialists and digital technologies in mental health interventions and their effectiveness in reducing the mental healthcare gap in low-and middle-income countries. Methods Literature searches were conducted in four databases (September 2023), three trial registries (January–February 2022), and using forward and backward citation searches (May–June 2022). The review included primary studies on mental health interventions combining non-specialists and digital technologies in low-and middle-income countries. The outcomes were: (1) the mental health of intervention receivers and (2) the competencies of non-specialists to deliver mental health interventions. Data were expressed as standardised effect sizes (Cohen’s d) and narratively synthesised. Risk of bias assessment was conducted using the Cochrane risk-of-bias tools for individual and cluster randomised and non-randomised controlled trials. Results Of the 28 included studies ( n = 32 interventions), digital technology was mainly used in non-specialist primary-delivery treatment models for common mental disorders or subthreshold symptoms. The competencies of non-specialists were improved with digital training (d ≤ 0.8 in 4/7 outcomes, n = 4 studies, 398 participants). The mental health of receivers improved through non-specialist-delivered interventions, in which digital technologies were used to support the delivery of the intervention (d > 0.8 in 24/40 outcomes, n = 11, 2469) or to supervise the non-specialists’ work (d = 0.2–0.8 in 10/17 outcomes, n = 3, 3096). Additionally, the mental health of service receivers improved through digitally delivered mental health services with non-specialist involvement (d = 0.2–0.8 in 12/27 outcomes, n = 8, 2335). However, the overall certainty of the evidence was poor. Conclusion Incorporating digital technologies into non-specialist mental health interventions tended to enhance non-specialists’ competencies and knowledge in intervention delivery, and had a positive influence on the severity of mental health problems, mental healthcare utilization, and psychosocial functioning outcomes of service recipients, primarily within primary-deliverer care models. More robust evidence is needed to compare the magnitude of effectiveness and identify the clinical relevance of specific digital functions. Future studies should also explore long-term and potential adverse effects and interventions targeting men and marginalised communities.

Background:The prevalence of Major Depressive Disorder (MDD) is twice as high in women as in men. Because the mechanisms underlying this sex-difference remain poorly understood, we took a bottom-up approach to identify factors explaining the sex-MDD relationship. Methods:Data came from the TRacking Adolescents' Individual Lives Survey (TRAILS), a population study investigating youths’ development from age 11 into adulthood. We assessed multiple baseline covariates at ages 11-13 years and MDD onset at ages 19 and 25 years. In regression analyses, each covariate’s role in the sex-MDD association as an effect modifier or confounder/explanatory variable was investigated. Replicability was evaluated in an independent sample. Results:The analyses identified no effect-modifiers. Baseline internalizing problems, behavioral inhibition, dizziness, comfort in classroom, somatic complaints, attention problems, cooperation and computer use all partially explained the association between sex and MDD at age 19. Largely the same variables explained the association between sex and MDD at age 25. Here, additionally identified explanatory variables were shyness, fear, acne, antisocial behavior, aggression, affection from classmates and time spent shopping. The explanatory roles of internalizing problems, behavioral inhibition and leisure-time spending (computer-use/shopping) were replicated. Limitations:Some potentially important baseline variables were not included (e.g., environmental factors) or had very low endorsement rates. The study focused only on dichotomous biological sex and did not consider gender roles or identification. The presence of MDD at baseline was not adjusted for. Conclusion: The sex-MDD association is partially explained by sex differences in symptoms and vulnerability factors already present in early adolescence.

Non-specialist mental health interventions serve as a potential solution to reduce the mental healthcare gap in low- and middle-income countries, such as Sri Lanka. However, contextual factors often influence their effective implementation, reflecting a research-to-practice gap. This study, using a qualitative, participatory approach with local mental health workers (n = 9) and potential service users (n = 11), identifies anticipated barriers and facilitators to implementing these interventions while also exploring alternative strategies for reducing the mental healthcare gap in this context. Perceived barriers include concerns about effectiveness, acceptance and feasibility in the implementation of non-specialist mental health interventions (theme 1). The participants’ overall perception that these interventions are a beneficial strategy for reducing the mental healthcare gap was identified as a facilitating factor for implementation (theme 2). Further facilitators relate to important non-specialist characteristics (theme 3), including desirable traits and occupational backgrounds that may aid in increasing the acceptance of this cadre. Other suggestions relate to facilitating the reach, intervention acceptance and feasibility (theme 4). This study offers valuable insights to enhance the implementation process of non-specialist mental health interventions in low-and middle-income countries such as Sri Lanka.

Background More knowledge on the cost-effectiveness of various depression treatment programmes can promote efficient treatment allocation and improve the quality of depression care.Objective This study aims to compare the real-world cost-effectiveness of an algorithm-guided programme focused on remission to a predefined duration, patient preference-centred treatment programme focused on response using routine care data.Methods A naturalistic study (n=6295 in the raw dataset) was used to compare the costs and outcomes of two programmes in terms of quality-adjusted life years (QALY) and depression-free days (DFD). Analyses were performed from a healthcare system perspective over a 2-year time horizon. Incremental cost-effectiveness ratios were calculated, and the uncertainty of results was assessed using bootstrapping and sensitivity analysis.Findings The algorithm-guided treatment programme per client yielded more DFDs (12) and more QALYs (0.013) at a higher cost (€3070) than the predefined duration treatment programme. The incremental cost-effectiveness ratios (ICERs) were around €256/DFD and €236 154/QALY for the algorithm guided compared with the predefined duration treatment programme. At a threshold value of €50 000/QALY gained, the programme had a probability of <10% of being considered cost-effective. Sensitivity analyses confirmed the robustness of these findings.Conclusions The algorithm-guided programme led to larger health gains than the predefined duration treatment programme, but it was considerably more expensive, and hence not cost-effective at current Dutch thresholds. Depending on the preferences and budgets available, each programme has its own benefits.Clinical implication This study provides valuable information to decision-makers for optimising treatment allocation and enhancing quality of care cost-effectively.

Background Despite growing concerns about mental health during the COVID-19 pandemic, particularly in people with pre-existing mental health disorders, research has shown that symptoms of depression and anxiety were generally quite stable, with modest changes in certain subgroups. However, individual differences in cumulative exposure to COVID-19 stressors have not been yet considered. Aims We aimed to quantify and investigate the impact of individual-level cumulative exposure to COVID-19-pandemic-related adversity on changes in depressive and anxiety symptoms and loneliness. In addition, we examined whether the impact differed among individuals with various levels of pre-pandemic chronicity of mental health disorders. Method Between April 2020 and July 2021, 15 successive online questionnaires were distributed among three psychiatric case–control cohorts that started in the 2000s (N = 1377). Outcomes included depressive and anxiety symptoms and loneliness. We developed a COVID-19 Adversity Index (CAI) summarising up to 15 repeated measures of COVID-19-pandemic-related exposures (e.g. exposure to COVID-19 infection, negative economic impact and quarantine). We used linear mixed linear models to estimate the effects of COVID-19-related adversity on mental health and its interaction with pre-pandemic chronicity of mental health disorders and CAI. Results Higher CAI scores were positively associated with higher increases in depressive symptoms, anxiety symptoms and loneliness. Associations were not statistically significantly different between groups with and without (chronic) pre-pandemic mental health disorders. Conclusions Individual differences in cumulative exposure to COVID-19-pandemic-related adversity are important predictors of mental health, but we found no evidence for higher vulnerability among people with (chronic) pre-pandemic mental health disorders.

BACKGROUND:People with severe mental illness (SMI) often suffer from long-lasting symptoms that negatively influence their social functioning, their ability to live a meaningful life, and participation in society. Interventions aimed at increasing physical activity can improve social functioning, but people with SMI experience multiple barriers to becoming physically active. Besides, the implementation of physical activity interventions in day-to-day practice is difficult. In this study, we aim to evaluate the effectiveness and implementation of a physical activity intervention to improve social functioning, mental and physical health. METHODS:In this pragmatic stepped wedge cluster randomized controlled trial we aim to include 100 people with SMI and their mental health workers from a supported housing organization. The intervention focuses on increasing physical activity by implementing group sports activities, active guidance meetings, and a serious game to set physical activity goals. We aim to decrease barriers to physical activity through active involvement of the mental health workers, lifestyle courses, and a medication review. Participating locations will be divided into four clusters and randomization will decide the start of the intervention. The primary outcome is social functioning. Secondary outcomes are quality of life, symptom severity, physical activity, cardiometabolic risk factors, cardiorespiratory fitness, and movement disturbances with specific attention to postural adjustment and movement sequencing in gait. In addition, we will assess the implementation by conducting semi-structured interviews with location managers and mental health workers and analyze them by direct content analysis. DISCUSSION:This trial is innovative since it aims to improve social functioning in people with SMI through a physical activity intervention which aims to lower barriers to becoming physically active in a real-life setting. The strength of this trial is that we will also evaluate the implementation of the intervention. Limitations of this study are the risk of poor implementation of the intervention, and bias due to the inclusion of a medication review in the intervention that might impact outcomes. TRIAL REGISTRATION:This trial was registered prospectively in The Netherlands Trial Register (NTR) as NTR NL9163 on December 20, 2020. As the The Netherlands Trial Register is no longer available, the trial can now be found in the International Clinical Trial Registry Platform via: https://trialsearch.who.int/Trial2.aspx?TrialID=NL9163 .

Background: Little is known about the longer-term impact of the Covid-19 pandemic beyond the first months of 2020, particularly for people with pre-existing mental health disorders. Studies including pre-pandemic data from large psychiatric cohorts are scarce. Methods: Between April 2020 and February 2021, twelve successive online questionnaires were distributed among participants of the Netherlands Study of Depression and Anxiety, Netherlands Study of Depression in Older Persons, and Netherlands Obsessive Compulsive Disorder Association Study (N = 1714, response rate 62%). Outcomes were depressive symptoms, anxiety, worry, loneliness, perceived mental health impact of the pandemic, fear of Covid-19, positive coping, and happiness. Using linear mixed models we compared trajectories between subgroups with different pre-pandemic chronicity of disorders and healthy controls. Results: Depressive, anxiety and worry symptoms were stable since April-May 2020 whereas happiness slightly decreased. Furthermore, positive coping steadily decreased and loneliness increased - exceeding pre-Covid and April-May 2020 levels. Perceived mental health impact and fear of Covid-19 fluctuated in accordance with national Covid-19 mortality rate changes. Absolute levels of all outcomes were poorer with higher chronicity of disorders, yet trajectories did not differ among subgroups. Limitations: The most vulnerable psychiatric groups may have been underrepresented and results may not be generalizable to lower income countries. Conclusions: After a year, levels of depressive and worry symptoms remained higher than before the pandemic in healthy control groups, yet not in psychiatric groups. Nevertheless, persistent high symptoms in psychiatric groups and increasing loneliness in all groups are specific points of concern for mental health care professionals.

Background Mental health was only modestly affected in adults during the early months of the COVID-19 pandemic on the group level, but interpersonal variation was large. Aims We aim to investigate potential predictors of the differences in changes in mental health. Method Data were aggregated from three Dutch ongoing prospective cohorts with similar methodology for data collection. We included participants with pre-pandemic data gathered during 2006–2016, and who completed online questionnaires at least once during lockdown in The Netherlands between 1 April and 15 May 2020. Sociodemographic, clinical (number of mental health disorders and personality factors) and COVID-19-related variables were analysed as predictors of relative changes in four mental health outcomes (depressive symptoms, anxiety and worry symptoms, and loneliness), using multivariate linear regression analyses. Results We included 1517 participants with ( n = 1181) and without ( n = 336) mental health disorders. Mean age was 56.1 years (s.d. 13.2), and 64.3% were women. Higher neuroticism predicted increases in all four mental health outcomes, especially for worry ( β = 0.172, P = 0.003). Living alone and female gender predicted increases in depressive symptoms and loneliness ( β = 0.05–0.08), whereas quarantine and strict adherence with COVID-19 restrictions predicted increases in anxiety and worry symptoms ( β = 0.07–0.11).Teleworking predicted a decrease in anxiety symptoms ( β = −0.07) and higher age predicted a decrease in anxiety ( β = −0.08) and worry symptoms ( β = −0.10). Conclusions Our study showed neuroticism as a robust predictor of adverse changes in mental health, and identified additional sociodemographic and COVID-19-related predictors that explain longitudinal variability in mental health during the COVID-19 pandemic.