Modern psychometric methods make it possible to eliminate nonperforming items and reduce measurement error. Application of these methods to existing outcome measures can reduce variability in scores, and may increase treatment effect sizes in depression treatment trials.

We aim to determine whether using confirmatory factor analysis techniques can provide better estimates of the true effects of treatments, by conducting secondary analyses of individual patient data from randomised trials of antidepressant therapies.

We will access individual patient data from antidepressant treatment trials through Clinicalstudydatarequest.com and Vivli.org, specifically targeting studies that used the Hamilton Rating Scale for Depression (HRSD) as the outcome measure. Exploratory and confirmatory factor analytic approaches will be used to determine pre-treatment (baseline) and post-treatment models of depression, in terms of the number of factors and weighted scores of each item. Differences in the derived factor scores between baseline and outcome measurements will yield an effect size for factor-informed depression change. The difference between the factor-informed effect size and each original trial effect size, calculated with total HRSD-17 scores, will be determined, and the differences modelled with meta-analytic approaches. Risk differences for proportions of patients who achieved remission will also be evaluated. Furthermore, measurement invariance methods will be used to assess potential gender differences.

Our approach will determine whether adopting advanced psychometric analyses can improve precision and better estimate effect sizes in antidepressant treatment trials. The proposed methods could have implications for future trials and other types of studies that use patient-reported outcome measures.

Low-frequency repetitive transcranial magnetic stimulation (rTMS) of the prefrontal cortex has been shown to have a statistically and clinically significant anti-depressant effect. The present pilot study was carried out to investigate if right prefrontal low-frequency rTMS as an add-on to electroconvulsive therapy (ECT) accelerates the anti-depressant effect and reduces cognitive side effects.

In this randomised, controlled, double-blind study, thirty-five patients with major depression were allocated to ECT+placebo or ECT+low-frequency right prefrontal rTMS. The severity of depression was evaluated during the course using the Hamilton scale for depression (the 17-item as well as the 6-item scale) and the major depression inventory (MDI). Furthermore, neuropsychological assessment of cognitive function was carried out.

The study revealed no significant difference between the two groups for any of the outcomes, but with a visible trend to lower scores for MDI after treatment in the placebo group. The negative impact of ECT on neurocognitive functions was short-lived, and scores on logical memory were significantly improved compared to baseline 4 weeks after last treatment. The ECT-rTMS group revealed generally less impairment of cognitive functions than the ECT-placebo group.

The addition of low-frequency rTMS as an add-on to ECT treatment did not result in an accelerated response. On the contrary, the results suggest that low-frequency rTMS could inhibit the anti-depressant effect of ECT.

National guidance cautions against low-intensity interventions for people with personality disorder, but evidence from trials is lacking.

To test the feasibility of conducting a randomised trial of a low-intensity intervention for people with personality disorder.

Single-blind, feasibility trial (trial registration: ISRCTN14994755). We recruited people aged 18 or over with a clinical diagnosis of personality disorder from mental health services, excluding those with a coexisting organic or psychotic mental disorder. We randomly allocated participants via a remote system on a 1:1 ratio to six to ten sessions of Structured Psychological Support (SPS) or to treatment as usual. We assessed social functioning, mental health, health-related quality of life, satisfaction with care and resource use and costs at baseline and 24 weeks after randomisation.

A total of 63 participants were randomly assigned to either SPS (n = 33) or treatment as usual (n = 30). Twenty-nine (88%) of those in the active arm of the trial received one or more session (median 7). Among 46 (73%) who were followed up at 24 weeks, social dysfunction was lower (−6.3, 95% CI −12.0 to −0.6, P = 0.03) and satisfaction with care was higher (6.5, 95% CI 2.5 to 10.4; P = 0.002) in those allocated to SPS. Statistically significant differences were not found in other outcomes. The cost of the intervention was low and total costs over 24 weeks were similar in both groups.

SPS may provide an effective low-intensity intervention for people with personality disorder and should be tested in fully powered clinical trials.

Poorer patient views of mental health inpatient treatment predict both further admissions and, for those admitted involuntarily, longer admissions. As advocated in the UK Francis report, we investigated the hypothesis that improving staff training improves patients’ views of ward care.

Cluster randomised trial with stepped wedge design in 16 acute mental health wards randomised (using the ralloc procedure in Stata) by an independent statistician in three waves to staff training. A psychologist trained ward staff on evidence-based group interventions and then supported their introduction to each ward. The main outcome was blind self-report of perceptions of care (VOICE) before or up to 2 years after staff training between November 2008 and January 2013.

In total, 1108 inpatients took part (616 admitted involuntarily under the English Mental Health Act). On average 51.6 staff training sessions were provided per ward. Involuntary patient's perceptions of, and satisfaction with, mental health wards improved after staff training (N582, standardised effect −0·35, 95% CI −0·57 to −0·12, p = 0·002; interaction p value 0·006) but no benefit to those admitted voluntarily (N469, −0.01, 95% CI −0.23 to 0.22, p = 0.955) and no strong evidence of an overall effect (N1058, standardised effect −0.18 s.d., 95% CI −0.38 to 0.01, p = 0.062). The training costs around £10 per patient per week. Resource allocation changed towards patient perceived meaningful contacts by an average of £12 (95% CI −£76 to £98, p = 0.774).

Staff training improved the perceptions of the therapeutic environment in those least likely to want an inpatient admission, those formally detained. This change might enhance future engagement with all mental health services and prevent the more costly admissions.

To evaluate the efficacy of transcranially applied pulsed electromagnetic fields (PEMF) on functional impairments and symptom severity in multiple chemical sensitivity (MCS) patients.

The study was conducted as a nationwide trial in Denmark using a randomised, parallel-group, double-blind and placebo-controlled design. Sample size was estimated at 40 participants. Eligibility criteria were age 18–75 years and fulfilment of the MCS case criteria. Participants received either PEMF or placebo PEMF (no stimulation) applied transcranially for 6 weeks. The primary outcome was the Life Impact Scale (LIS) of the Quick Environmental Exposure and Sensitivity Inventory (QEESI). Secondary outcomes were the Symptom Severity Scale (SSS) and the Chemical Intolerance Scale of QEESI.

A total of 39 participants were randomised to PEMF or placebo treatment. No significant difference was observed on QEESI LIS between groups with a mean change score of −5.9 in the PEMF group compared with −1.5 in the placebo group (p=0.35, effect size=−0.31). However, a significant decrease was detected on QEESI SSS within and between groups with a mean change score of −11.3 in the PEMF group compared with −3.2 in the placebo group (p=0.03, effect size=−0.60).

PEMF treatment of 6 weeks showed no effect on functional impairments in MCS. However, a significant decrease in symptom severity was observed.

Suppose you are the developer of a new therapy for a mental health problem or you have several years of experience working with such a therapy, and you would like to prove that it is effective. Randomised trials have become the gold standard to prove that interventions are effective, and they are used by treatment guidelines and policy makers to decide whether or not to adopt, implement or fund a therapy.

You would want to do such a randomised trial to get your therapy disseminated, but in reality your clinical experience already showed you that the therapy works. How could you do a trial in order to optimise the chance of finding a positive effect?

Methods that can help include a strong allegiance towards the therapy, anything that increases expectations and hope in participants, making use of the weak spots of randomised trials (risk of bias), small sample sizes and waiting list control groups (but not comparisons with existing interventions). And if all that fails one can always not publish the outcomes and wait for positive trials.

Several methods are available to help you show that your therapy is effective, even when it is not.