An increasing number of observational studies have reported associations between frailty and mental disorders, but the causality remains ambiguous.

To assess the bidirectional causal relationship between frailty and nine mental disorders.

We conducted a bidirectional two-sample Mendelian randomisation on genome-wide association study summary data, to investigate causality between frailty and nine mental disorders. Causal effects were primarily estimated using inverse variance weighted method. Several secondary analyses were applied to verify the results. Cochran's Q-test and Mendelian randomisation Egger intercept were applied to evaluate heterogeneity and pleiotropy.

Genetically determined frailty was significantly associated with increased risk of major depressive disorder (MDD) (odds ratio 1.86, 95% CI 1.36–2.53, P = 8.1 × 10−5), anxiety (odds ratio 2.76, 95% CI 1.56–4.90, P = 5.0 × 10−4), post-traumatic stress disorder (PTSD) (odds ratio 2.56, 95% CI 1.69–3.87, P = 9.9 × 10−6), neuroticism (β = 0.25, 95% CI 0.11–0.38, P = 3.3 × 10−4) and insomnia (β = 0.50, 95% CI 0.25–0.75, P = 1.1 × 10−4). Conversely, genetic liability to MDD, neuroticism, insomnia and suicide attempt significantly increased risk of frailty (MDD: β = 0.071, 95% CI 0.033–0.110, P = 2.8 × 10−4; neuroticism: β = 0.269, 95% CI 0.173–0.365, P = 3.4 × 10−8; insomnia: β = 0.160, 95% CI 0.141–0.179, P = 3.2 × 10−61; suicide attempt: β = 0.056, 95% CI 0.029–0.084, P = 3.4 × 10−5). There was a suggestive detrimental association of frailty on suicide attempt and an inverse relationship of subjective well-being on frailty.

Our findings show bidirectional causal associations between frailty and MDD, insomnia and neuroticism. Additionally, higher frailty levels are associated with anxiety and PTSD, and suicide attempts are correlated with increased frailty. Understanding these associations is crucial for the effective management of frailty and improvement of mental disorders.

Residential treatment facilities for eating disorders are becoming increasingly common and purport to provide recovery-orientated care in a less restrictive environment than traditional hospital settings. However, minimal attention has focused on individuals’ lived experiences of these residential services.

This study explores participants’ lived experiences of care at Australia’s first residential facility for the treatment of eating disorders.

Qualitative data were collected as part of a clinical evaluation (June 2021 to August 2023). Fifteen women participated in semi-structured interviews about their experience of treatment following discharge. Data were analysed with inductive reflexive thematic analysis.

Three main themes were generated from the data that included participants’ journeys to treatment, experiences of treatment and the transitions associated with and following discharge. Cutting across these main themes were participants’ encounters of barriers, setbacks and hope. Participant experiences of residential treatment were complex and multifaceted, marked by inherent ideological dilemmas that arose in balancing standardised treatment protocols with person-centred and recovery-oriented care. Participants also spoke of reclaiming a sense of self and identity beyond their eating disorder, emphasising the importance of relationships and consistent and collaborative care.

Participant accounts of residential treatment emphasised the importance of holistic, person-centred and recovery-oriented care. Despite the complexities of treatment experiences, participant narratives underscored how recovery may be more about the reclamation of a sense of identity outside of the eating disorder than merely symptom improvement. As such, adopting person-centred and recovery-oriented treatment approaches within residential treatment settings may maximise individual autonomy and promote holistic recovery pathways.

Research indicates that treatment outcomes are poorer for people with long-term physical health conditions (LTCs) in Talking Therapies services (formerly known as Improving Access to Psychological Therapies). However, the impact of having an LTC on attendance at assessment and treatment appointments within Talking Therapies remains unclear. Internet-enabled therapies may be one way to overcome barriers to treatment engagement in Talking Therapies. However, their effect on engagement and the influence of LTC status on receipt of internet-enabled therapies is unknown.

To explore the association between LTC status and assessment attendance, treatment engagement and internet-enabled therapy receipt within Talking Therapies services, and whether receipt of internet-enabled treatment bolsters engagement.

We used anonymous patient-level data from two inner London Talking Therapies services during January to December 2022 (n = 17 095 referrals). Binary logistic regression models were constructed to compare differences between LTC and non-LTC groups on (a) assessment attendance, (b) engagement and (c) internet-enabled therapy receipt. In our regression models, we controlled for key clinical and demographic covariates.

There were no differences between patients with or without an LTC in assessment attendance or treatment engagement, after controlling for covariates. Across the whole sample, receiving internet-enabled treatment increased engagement. People with an LTC were less likely to receive an internet-enabled treatment.

Having an LTC does not negatively affect assessment attendance and engagement with talking therapies. However, receiving an internet-enabled treatment bolstered engagement in our regression models. People with an LTC were less likely to receive internet-enabled treatment.

Preliminary evidence suggests that a ketogenic diet may be effective for bipolar disorder.

To assess the impact of a ketogenic diet in bipolar disorder on clinical, metabolic and magnetic resonance spectroscopy outcomes.

Euthymic individuals with bipolar disorder (N = 27) were recruited to a 6- to 8-week single-arm open pilot study of a modified ketogenic diet. Clinical, metabolic and MRS measures were assessed before and after the intervention.

Of 27 recruited participants, 26 began and 20 completed the ketogenic diet. For participants completing the intervention, mean body weight fell by 4.2 kg (P < 0.001), mean body mass index fell by 1.5 kg/m2 (P < 0.001) and mean systolic blood pressure fell by 7.4 mmHg (P < 0.041). The euthymic participants had average baseline and follow-up assessments consistent with them being in the euthymic range with no statistically significant changes in Affective Lability Scale-18, Beck Depression Inventory and Young Mania Rating Scale. In participants providing reliable daily ecological momentary assessment data (n = 14), there was a positive correlation between daily ketone levels and self-rated mood (r = 0.21, P < 0.001) and energy (r = 0.19 P < 0.001), and an inverse correlation between ketone levels and both impulsivity (r = −0.30, P < 0.001) and anxiety (r = −0.19, P < 0.001). From the MRS measurements, brain glutamate plus glutamine concentration decreased by 11.6% in the anterior cingulate cortex (P = 0.025) and fell by 13.6% in the posterior cingulate cortex (P = <0.001).

These findings suggest that a ketogenic diet may be clinically useful in bipolar disorder, for both mental health and metabolic outcomes. Replication and randomised controlled trials are now warranted.

Parents of children with autisma demonstrate elevated traumatic stress symptoms, but seldom receive diagnoses of post-traumatic stress disorder (PTSD) or complex PTSD. An accurate assessment of Criterion A is essential for a valid diagnosis of these disorders, yet it is uncertain whether Criterion A, as defined by the two primary international diagnostic systems (DSM-5-TR and ICD-11), yields consistent interrater reliability, when psychologists rely solely on self-report from these parents for assessing PTSD or complex PTSD.

This study aims to investigate interrater reliability across psychologists when assessing Criterion A events against the ICD-11 and DSM-5-TR.

Ten Australian psychologists rated parents’ self-reported traumatic events related to parenting, using the Life Events Checklist for DSM-5-TR and ICD-11 Criterion A. Data from 200 randomly selected parents of children, all meeting symptom thresholds for PTSD or complex PTSD, were analysed. Bootstrapping calculated kappa coefficients, differences between ICD-11 and DSM-5-TR criteria, and self-reports of threat/no threat, with 95% confidence intervals for these differences.

Interrater reliability varied from poor to moderate. The ICD-11 had significantly higher reliability than the DSM-5-TR for Criterion A (κdifference = 0.105, 95% CI 0.052–0.153, P < 0.001). The interrater reliability was lower when parents reported life threat, serious injury or death (κdifference = 0.096, 95% CI 0.019–0.176, P = 0.007).

This study highlights challenges in assessing PTSD and complex PTSD Criterion A in parents of children with autism, using DSM-5-TR and ICD-11 criteria with the Life Events Checklist, revealing less than adequate interrater reliability.

Decision-making capacity (DMC) is key to capacity-based mental health laws. In 2017, Norway introduced a lack of DMC as an additional criterion for involuntary care and treatment to strengthen patient autonomy and reduce involuntary care. Health registry data reveal an initial reduction followed by rising involuntary care and treatment rates post-2017. Despite jurisdictions moving towards capacity-based mental health laws, little is known about their impact.

To explore the impact of introducing a capacity-based mental health law governing involuntary care and treatment.

Semi-structured interviews and focus groups were conducted in 2018 with 60 purposively sampled stakeholders, including patients, families, health professionals and lawyers. Of these, 26 participated in individual follow-up interviews in 2022–23. The transcribed interviews were thematically analysed following Braun and Clarke.

Four themes emerged: (a) increased awareness of patient autonomy and improved patient involvement; (b) altered thresholds for involuntary admission and discharge and more challenging to help certain patient groups; (c) more responsibility for primary health services; and (d) increased family responsibility but unchanged involvement by health services.

Introducing a capacity-based mental health law appears to raise awareness of patient autonomy, but its impact depends on an interplay of complex health, social and legal systems. Post-2017 changes, including rising involuntary care and treatment rates, higher thresholds for admissions and increased pressure on primary health services and families, may be influenced by several factors. These include implementation of decision-making capacity, legal interpretations, formal measures for care of non-resistant incompetent individuals, reduced in-patient bed availability, inadequate voluntary treatment options and societal developments. Further research is needed to better understand these changes and their causes.

There is currently no definitive method for identifying individuals with psychosis in secondary care on a population-level using administrative healthcare data from England.

To develop various algorithms to identify individuals with psychosis in the Mental Health Services Data Set (MHSDS), guided by national estimates of the prevalence of psychosis.

Using a combination of data elements in the MHSDS for financial years 2017–2018 and 2018–2019 (mental health cluster (a way to describe and classify a group of individuals with similar characteristics), Health of the Nation Outcome Scale (HoNOS) scores, reason for referral, primary diagnosis, first-episode psychosis flag, early intervention in psychosis team flag), we developed 12 unique algorithms to detect individuals with psychosis seen in secondary care. The resulting numbers were then compared with national estimates of the prevalence of psychosis to ascertain whether they were reasonable or not.

The 12 algorithms produced 99 204–138 516 and 107 545–134 954 cases of psychosis for financial years 2017–2018 and 2018–2019, respectively, in line with national prevalence estimates. The numbers of cases of psychosis identified by the different algorithms differed according to the type and number (3–6) of data elements used. Most algorithms identified the same core of patients.

The MHSDS can be used to identify individuals with psychosis in secondary care in England. Users can employ several algorithms to do so, depending on the objective of their analysis and their preference regarding the data elements employed. These algorithms could be used for surveillance, research and/or policy purposes.