With the increasing accessibility of tools such as ChatGPT, Copilot, DeepSeek, Dall-E, and Gemini, generative artificial intelligence (GenAI) has been poised as a potential, research timesaving tool, especially for synthesising evidence. Our objective was to determine whether GenAI can assist with evidence synthesis by assessing its performance using its accuracy, error rates, and time savings compared to the traditional expert-driven approach.

To systematically review the evidence, we searched five databases on 17 January 2025, synthesised outcomes reporting on the accuracy, error rates, or time taken, and appraised the risk-of-bias using a modified version of QUADAS-2.

We identified 3,071 unique records, 19 of which were included in our review. Most studies had a high or unclear risk-of-bias in Domain 1A: review selection, Domain 2A: GenAI conduct, and Domain 1B: applicability of results. When used for (1) searching GenAI missed 68% to 96% (median = 91%) of studies, (2) screening made incorrect inclusion decisions ranging from 0% to 29% (median = 10%); and incorrect exclusion decisions ranging from 1% to 83% (median = 28%), (3) incorrect data extractions ranging from 4% to 31% (median = 14%), (4) incorrect risk-of-bias assessments ranging from 10% to 56% (median = 27%).

Our review shows that the current evidence does not support GenAI use in evidence synthesis without human involvement or oversight. However, for most tasks other than searching, GenAI may have a role in assisting humans with evidence synthesis.

This study aimed to refine the content of a new patient-reported outcome (PRO) measure via cognitive interviewing techniques to assess the unique presentation of depressive symptoms in older adults with cancer (OACs).

OACs (≥ 70years) with a history of a depressive disorder were administered a draft measure of the Older Adults with Cancer – Depression (OAC-D) Scale, then participated in a semi-structured cognitive interview to provide feedback on the appropriateness, comprehensibility, and overall acceptability of measure. Interviews were audio-recorded and transcribed, and qualitative methods guided revision of scale content and structure.

OACs (N = 10) with a range of cancer diagnoses completed cognitive interviews. Participants felt that the draft measure took a reasonable amount of time to answer and was easily understandable. They favored having item prompts and response anchors repeated with each item for ease of completion, and they helped identify phrasing and wording of key terms consistent with the authors’ intended constructs. From this feedback, a revised version of the OAC-D was created.

The OAC-D Scale is the first PRO developed specifically for use with OACs. The use of expert and patient input and rigorous cognitive interviewing methods provides a conceptually accurate means of assessing the unique symptom experience of OACs with depression.

To investigate the association between energy drink (ED) use and sleep-related disturbances in a population-based sample of young adults from the Raine Study.

Analysis of cross-sectional data obtained from self-administered questionnaires to assess ED use and sleep disturbance (Epworth Sleepiness Scale, Functional Outcomes of Sleep Questionnaire (FOSQ-10) and the Pittsburgh Sleep Symptoms Questionnaire–Insomnia (PSSQ-I)). Regression modelling was used to estimate the effect of ED use on sleep disturbances. All models adjusted for various potential confounders.

Western Australia.

Males and females, aged 22 years, from Raine Study Gen2–22 year follow-up.

Of the 1115 participants, 66 % were never/rare users (i.e. <once/month) of ED, 17·0 % were occasional users (i.e. >once/month to <once/week) and 17 % were frequent users (≥once/week). Compared with females, a greater proportion of males used ED occasionally (19 % v. 15 %) or frequently (24 % v. 11 %). Among females, frequent ED users experienced significantly higher symptoms of daytime sleepiness (FOSQ-10: β = 0·93, 95 % CI 0·32, 1·54, P = 0·003) and were five times more likely to experience insomnia (PSSQ-I: OR = 5·10, 95 % CI 1·81, 14·35, P = 0·002) compared with never/rare users. No significant associations were observed in males for any sleep outcomes.

We found a positive association between ED use and sleep disturbances in young adult females. Given the importance of sleep for overall health, and ever-increasing ED use, intervention strategies are needed to curb ED use in young adults, particularly females. Further research is needed to determine causation and elucidate reasons for gender-specific findings.

Childhood obesity is a global issue. Excessive weight gain in early pregnancy is independently associated with obesity in the next generation. Given the uptake of e-health, our primary aim was to pilot the feasibility of an e-health intervention, starting in the first trimester, to promote healthy lifestyle and prevent excess weight gain in early pregnancy. Methods: Women were recruited between 8 and 11 weeks gestation and randomised to the intervention or routine antenatal care. The intervention involved an e-health program providing diet, physical activity and well-being advice over 12 weeks.

Women (n = 57, 43.9% overweight/obese) were recruited at 9.38 ± 1.12 (control) and 9.06 ± 1.29 (intervention) weeks’ gestation, mainly from obstetric private practices (81.2%). Retention was 73.7% for the 12-week intervention, 64.9% at birth and 55.8% at 3 months after birth.

No difference in gestational weight gain or birth size was detected. Overall treatment effect showed a mean increase in score ranking the perceived confidence of dietary change (1.2 ± 0.46, p = 0.009) and score ranking readiness to exercise (1.21 ± 0.51, p = 0.016) over the intervention. At 3 months, infants weighed less in the intervention group (5405 versus 6193 g, p = 0.008) and had a lower ponderal index (25.5 ± 3.0 versus 28.8 ± 4.0 kg/m3) compared with the control group.

A lifestyle intervention starting in the first-trimester pregnancy utilising e-health mode of delivery is feasible. Future studies need strategies to target recruitment of participants of lower socio-economic status and ensure maximal blinding. Larger trials (using technology and focused on early pregnancy) are needed to confirm if decreased infant adiposity is maintained.