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To evaluate the effectiveness of aromatherapy on agitation and aggression in patients with cognitive impairment.
The impact of aromatherapy on agitation and aggression has been evaluated in various studies, but there is uncertainty about their impact.
A meta-analysis of randomised controlled trials was undertaken.
This meta-analysis was conducted under PRISMA guidelines. Following eight electronic literature databases were searched: Web of Science, PubMed, PsycINFO, Embase, Cochrane Library, Chinese Wanfang database, CNKI and VIP digital database from the inception of the databases up to 27 February 2021. Two reviewers assessed the risk of bias of the included studies independently using the Cochrane Collaboration tool. Overall, meta-analysis and three subgroup analyses regarding the type of aroma preparations, delivery mode and session length were performed using RevMan5.3 and stata14.0. Publication bias was assessed by visual inspection of the funnel plot asymmetry and Egger's regression test.
Fifteen studies comprising 693 participants were included. The meta-analysis indicated that aromatherapy could ameliorate agitation and aggression for cognitive impairment. The subgroup analysis based on the type of aroma preparations showed that lavender oil could significantly improve agitation and aggression. Most delivery modes of aromatherapy, including smearing and inhalation, were effective. Moreover, less length (≤4 weeks) aromatherapy showed a better effect on agitation behaviour than aromatherapy more than 4 weeks.
Despite the meta-analysis indicating that aromatherapy could alleviate agitation and aggression especially short-term (≤4 weeks) aromatherapy inhalation in different conditions, further researches are needed to investigate the appropriate dosage of essential oils and the side effects. More well-designed randomised controlled trials containing participants from more countries are needed to verify our findings before we can make strong recommendations.
This meta-analysis suggested that aromatherapy should be considered as a complementary programme for patients with cognitive impairment patients. Medical workers could apply aromatherapy into daily routine cares for cognitive impairment patients.
by Wanbo Lu, Qibo Liu, Haofang Li
This paper employs the mixed-frequency Granger causality test, reverse unconstrained mixed-frequency data sampling models, and Chinese data from January 2006 to June 2024 to test the nexus between consumer confidence and the macroeconomy. The results show that changes in the real estate market, GDP, and urban unemployment rate are Granger causes of consumer confidence. In reverse, consumer confidence is a Granger cause of the CPI. Second, GDP and the real estate market (CPI and urban unemployment rate) have a significant positive (negative) impact on consumer confidence, while the conditions of industrial production, interest rate, and stock market do not. Third, the “animal spirits” extracted from consumer confidence cannot lead to noticeable fluctuations in China’s macroeconomy. This suggests that the “animal spirits” will not dominate economic growth, even though they affect the macroeconomy slightly and inevitably. The results are robust after replacing the dependent variable and considering the influence of the global financial crisis and the COVID-19 pandemic.To explore the network characteristics of symptom clusters in people with type 2 diabetes mellitus through network analysis, identify the core and bridging symptoms within the symptom network, and provide a foundation for targeted interventions and symptom management in people with T2DM.
A cross-sectional survey.
A total of 360 people with T2DM who were hospitalised in the endocrinology departments of two hospitals with Grade A in Daqing City between August 2024 and February 2025 were selected using a convenience sampling method. The symptoms of people with T2DM were measured using the Chinese version of the Diabetes Symptom Checklist-Revised (DSC-R). Symptom clusters were identified through factor analysis, and network analysis was used to identify core and bridging symptoms. This research adhered to the STROBE guidelines.
Six symptom clusters were obtained from factor analysis, which were psychological-behavioural symptom cluster, ophthalmological-neuropathy symptom cluster, cardiovascular symptom cluster, metabolic symptom cluster, body symptom cluster and nephrotic symptom cluster. Symptom network analysis revealed that ‘Deteriorating vision’ exhibited the highest strength centrality and expected influence. The top three symptoms with the highest bridge strength and bridge expected influence were ‘Aching calves when walking’, ‘Queer feeling in the legs or feet’ and ‘Sleepiness or drowsiness’.
People with T2DM commonly exhibit a range of symptoms. ‘Deteriorating vision’ is the most core symptom in people with T2DM. ‘Aching calves when walking’, ‘Queer feeling in the legs or feet’ and ‘Sleepiness or drowsiness’ are identified as the bridging symptoms in the network analysis. Healthcare professionals can design targeted interventions based on symptom clusters, core symptoms and bridging symptoms, thereby improving the efficiency of symptom management and optimising outcomes for people with T2DM.
No patient or public contribution.
To classify the unmet integrated care needs of older adults with multimorbidity and to explore the factors associated with different categories of unmet integrated care needs among the target population.
A cross-sectional survey using the statistical method of latent profile analysis.
From July 2022 to March 2023, 397 older adults with multimorbidity, aged 60 years or older, were recruited from one primary healthcare setting and from four secondary and tertiary hospitals to participate in face-to-face questionnaire surveys. The questionnaire used in this study to assess unmet integrated care needs among older adults with multimorbidity was self-designed through a series of steps, including a scoping review, expert consultation and cognitive interviews. Latent profile analysis was applied to uncover distinct profiles of unmet integrated care needs, and multinomial logistic regression was employed to explore whether the profiles were further distinguished by participants' sociodemographic and health-related covariates. The data were analysed using IBM SPSS v.29.0 and Mplus v.8.0.
The optimal solution was a four-profile model, characterised by high unmet integration needs, high unmet system integration needs, low unmet system integration needs and low unmet integration needs, respectively. Multinomial logistic regression results indicated that profile differences were associated with place of residence, number of coresidents and the presence or absence of complex multimorbidity.
The integrated care needs of older adults with multimorbidity have not yet been fully met. Classifying and characterising unmet integrated care needs profiles is a crucial step in the rational allocation of integrated care resources.
This study was reported based on the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) for cross-sectional studies.
All participants were older adults with multimorbidity, and they were informed that they could withdraw from the study at any time.
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