Meta-analysis of the intervention effects of tai chi on fasting blood glucose, blood pressure and triglyceride in middle-aged and elderly people.

BACKGROUND: Hypertension, hyperlipidemia, and hyperglycemia have emerged as global health concerns of paramount significance. With the burgeoning popularity of mind-body therapy, cardiovascular patients have increasingly exhibited a vested interest in the practice of Tai Chi. The objective of this study seeks to quantitatively assess the impact of Tai Chi interventions on blood pressure, lipid levels, and glucose concentrations among the elderly population, thereby explaining the optimal intervention protocol. METHODS: An extensive search was conducted across multiple databases, including Web of Science, PubMed, CNKI, WANFANG DATA, RISS, KISS, and DBPIA, comprising English, Korean, and Chinese literature. The search strategy employed a retrieval method of subject term 1 + subject term 2, which included both full names and abbreviations of the terms. Specifically, "taijiquan" or "Tai Chi" were set as the Term 1, while Term 2 was set as "blood pressure," "BP," "Fasting blood glucose," "FBG," "Triglyceride," and "TG." Thereafter, the retrieved articles were filtered in accordance with the PICOS method. Risk of bias assessment was performed using RoB 2.0, while data analysis was conducted using Comprehensive Meta-Analysis 3.7. RESULTS: A total of 57 studies, including 3,856 research subjects, were eligible for inclusion. The findings of the primary effect quantitative synthesis demonstrated that Tai Chi exerted an improvement on systolic blood pressure (SBP) (ES = -0.764, p < .001), diastolic blood pressure (DBP) (ES = -0.426, p = .001), triglyceride (TG) (ES = -0.452, p < .001), and fasting blood glucose concentrations (FBG) (ES = -0.552, p = .002) among middle-aged and elderly individuals. Subgroup analysis further revealed that the intervention effects were significantly influenced by the characteristics of the research subjects and the specific intervention protocol employed. CONCLUSION: Tai Chi, as a gentle form of aerobic exercise, exerts a profound impact on reducing blood pressure, fasting blood glucose levels, and triglyceride concentrations among middle-aged and elderly individuals. Notably, the intervention effect is particularly pronounced among male patients afflicted with hypertension, hyperglycemia, and hyperlipidemia. Based on the collective advantages underscored by this research, we strongly recommend engaging in Tai Chi exercises for a minimum duration of 16 weeks, with each session lasting 30-50 min and conducted 6-7 times per week, without any restrictions on the style employed.

Causal Artificial Intelligence Models of Food Quality Data.

Research background: The aim of this study is to emphasize the importance of artificial intelligence (AI) and causality modelling of food quality and analysis with 'big data'. AI with structural causal modelling (SCM), based on Bayesian networks and deep learning, enables the integration of theoretical field knowledge in food technology with process production, physicochemical analytics and consumer organoleptic assessments. Food products have complex nature and data are highly dimensional, with intricate interrelations (correlations) that are difficult to relate to consumer sensory perception of food quality. Standard regression modelling techniques such as multiple ordinary least squares (OLS) and partial least squares (PLS) are effectively applied for the prediction by linear interpolations of observed data under cross-sectional stationary conditions. Upgrading linear regression models by machine learning (ML) accounts for nonlinear relations and reveals functional patterns, but is prone to confounding and failed predictions under unobserved nonstationary conditions. Confounding of data variables is the main obstacle to applications of the regression models in food innovations under previously untrained conditions. Hence, this manuscript focuses on applying causal graphical models with Bayesian networks to infer causal relationships and intervention effects between process variables and consumer sensory assessment of food quality. Experimental approach: This study is based on the data available in the literature on the process of wheat bread baking quality, consumer sensory quality assessments of fermented milk products, and professional wine tasting data. The data for wheat baking quality were regularized by the least absolute shrinkage and selection operator (LASSO elastic net). Bayesian statistics was applied for the evaluation of the model joint probability function for inferring the network structure and parameters. The obtained SCMs are presented as directed acyclic graphs (DAG). D-separation criteria were applied to block confounding effects in estimating direct and total causal effects of process variables and consumer perception on food quality. Probability distributions of causal effects of the intervention of individual process variables on quality are presented as partial dependency plots determined by Bayesian neural networks. In the case of wine quality causality, the total causal effects determined by SCMs are positively validated by the double machine learning (DML) algorithm. Results and conclusions: The data set of 45 continuous variables corresponding to different chemical, physical and biochemical variables of wheat properties from seven Croatian cultivars during two years of controlled cultivation were analysed. LASSO regularization of the data set yielded the ten key predictors, accounting for 98 % variance of the baking quality data. Based on the key variables, the quality predictive random forest model with 75 % cross-validation accuracy was derived. Causal analysis between the quality and key predictors was based on the Bayesian model shown as a DAG graph. Protein content shows the most important direct causal effect with the corresponding path coefficient of 0.71, and THMM (total high-molecular-mass glutenin subunits) content was an indirect cause with a path coefficient of 0.42, and protein total average causal effect (ACE) was 0.65. The large data set of the quality of fermented milk products included binary consumer sensory data (taste, odour, turbidity), continuous physical variables (temperature, fat, pH, colour) and three grade classes of products by consumer quality assessment. A random forest model was derived for the prediction of the quality classification with an out-of-bag (OOB) error of 0.28 %. The Bayesian network model predicts that the direct causes of the taste classification are temperature, colour and fat content, while the direct causes of the quality classification are temperature, turbidity, odour and fat content. The key quality grade ACE of temperature -0.04 grade/°C and 0.3 quality grade/fat content were estimated. The temperature ACE dependency shows a nonlinear type as negative saturation with the 'breaking' point at 60 °C, while for fat ACE had a positive linear trend. Causal quality analysis of red and white wine was based on the large data set of eleven continuous variables of physical and chemical properties and quality assessments classified in ten classes, from 1 to 10. Each classification was obtained in triplicate by a panel of professional wine tasters. A non-structural double machine learning (DML) algorithm was applied for total ACE quality assessment. The alcohol content of red and white wine had the key positive ACE relative factor of 0.35 quality/alcohol, while volatile acidity had the key negative ACE of -0.2 quality/acidity. The obtained ACE predictions by the unstructured DML algorithm are in close agreement with the ACE obtained by the structural SCM. Novelty and scientific contribution: Novel methodologies and results for the application of causal artificial intelligence models in the analysis of consumer assessment of the quality of food products are presented. The application of Bayesian network structural causal models (SCM) enables the d-separation of pronounced effects of confounding between parameters in noncausal regression models. Based on the SCM, inference of ACE provides substantiated and validated research hypotheses for new products and support for decisions of potential interventions for improvement in product design, new process introduction, process control, management and marketing.

Commentary for Special Issue on Using Baseline Target Moderation to Assess Variation in Prevention Impact: When (and How) to Revise Our Programs.

Developing a better understanding of sources and mechanisms of heterogeneity is a key route to improving outcomes and targeting of preventive interventions. This commentary attempts to draw together findings from eight intervention trials in this special issue, each exploring baseline target moderation (BTM) or baseline target moderated mediation (BTMM). It considers their implications for prevention research and program design, particularly the question of whether they can help us to revise or adapt interventions. The studies cover a range of interventions, targets, and contexts, including parenting, couple, and CBT interventions, for depression, anxiety, conduct problems, or obesity. Some important findings stand out. Where studies found moderator effects, they tended to operate in a "compensatory" fashion, such that greater benefit was found in higher risk groups, suggesting that closer targeting might be warranted. It was rare for harmful effects to be detected for any subgroups. In other respects, patterns of BTM/BTMM findings were quite mixed across studies, suggesting it would be premature to change our interventions based on these trials. Implications of the findings for equity, for "slimming down" and scaling up interventions, and for research are discussed, including the need to combine BTMM with intervention component research, and to accumulate a more robust body of evidence by pooling data across trials.

Collateral benefits from a school-readiness intervention on breastfeeding: A cross-domain impact evaluation.

This study evaluated the collateral, or unanticipated, impacts of Smart Beginnings (SB), a two-site, tiered intervention designed to promote responsive parenting and school readiness, on breastfeeding intensity in a low-income sample. Impact analyses for the SB intervention were conducted using an intent-to-treat design leveraging a two-arm random assignment structure. Mothers assigned to the SB intervention group were more than three times more likely to give breastmilk as the only milk source at infant age 6 months than mothers assigned to the control group at one site, an effect not evident at the other study site. As development and growth are the two most salient domains of child health, understanding how interventions impact subsequent parenting practices across both domains is critical to address long-term economic and racial/ethnic disparities. Implications of the findings are discussed for improving the efficacy of interventions based on paediatric primary care.

Comparison of Conditional and Marginal Models in Assessing a Child Nutrition Intervention in Armenia.

INTRODUCTION: Child malnutrition is a major issue in conflict zones. Evidence-based interventions and their thorough evaluation could help to eliminate malnutrition. We aimed to assess the causal effect of a community-based multidisciplinary nutrition program for children in a chronic conflict zone near the northeastern border of Armenia on two main outcomes: stunting and anemia. We further compared the interpretations and public health relevance of the obtained effect estimates. METHODS: In 2016, the study measured hemoglobin and anthropometric measures and collected data from the children's caregivers. We used propensity score matching analyses, inverse probability weighting, and overlap weighting methods to examine the average treatment effects among treated population (ATT), and among population with overlapping weights (ATO). RESULTS: The ATT for stunting among children who participated in the intervention program estimated by propensity score matching analyses (PSM-ATT) was (1.95; 95%CI 1.15-3.28). Nevertheless, children who took part in the program had a lower risk of anemia (0.28; 95%CI 0.19-0.42). The ATT, estimated by inverse probability weighting (IPTW-ATT), was slightly lower for stunting (1.82; 95%CI 1.16-2.86) while similar for anemia (0.33; 95%CI 0.23-0.46) compared to PSM-ATT. Compared to the IPTW-ATT and PSM-ATT the ATO was lower for stunting (1.75; 95%CI 1.14-2.68) and similar for anemia (0.31; 95%CI 0.22-0.43). DISCUSSION: Marginal models could be used in similar quasi-experimental settings to identify the causal effect of interventions in specific populations of interest. Nonetheless, these methods do not eliminate threats to internal validity. Thorough study design and accurate data collection are necessary to improve the efficiency of marginal models.

Responsiveness to mHealth Intervention for Cannabis Use in Young Adults Predicts Improved Outcomes.

Mobile health (mHealth) interventions have proliferated rapidly in part because of their advantages in reducing consumer and provider burden, but less attention has been paid to participant responsiveness to mHealth programs and how this may affect outcomes. This study adds to that literature by examining whether participant responsiveness to a text messaging-delivered intervention was predictive of treatment outcomes over baseline levels of the outcome. We analyzed data from a pilot-randomized controlled trial of a text messaging-intervention to treat young adults with cannabis use disorder (treatment arm, N = 47), examining three indicators of responsiveness (two behavioral: treatment completion and booster message participation; and one subjective: perceived helpfulness of treatment) on abstinence from cannabis use and use-related problems measured at 3-month follow-up. With the exception of completion, the indicators were positively correlated with each other. Each of the indicators was predictive of better treatment outcomes above and beyond baseline risk. Treatment completion and booster participation-measured via technical data captured during intervention administration-appeared to be stronger predictors of improved outcomes than self-reported perceived helpfulness. Results suggest that behavioral and subjective responsiveness measures appear to be valid indicators of treatment response to mHealth interventions for substance use. Responsiveness measured via technical data captured during intervention administration may be a stronger and more efficient strategy for monitoring continued engagement. We discuss implications of these findings for deploying mHealth interventions at scale and monitoring responsiveness.

Mechanisms Through Which a Family Caregiver Coaching Intervention Might Reduce Anxiety Among Children in Military Households.

OBJECTIVES: Children of injured or disabled veterans and service members may be at risk for mental health and adjustment problems due to household stress. Yet, there are few widely available interventions to address the needs of this population. Reducing distress and improving coping skills of the parent who cares for the injured or disabled adult may improve child outcomes. This paper examines whether changes in caregiver psychosocial outcomes after a caregiver coaching intervention are associated with decreases in child anxiety. METHODS: Using programmatic data collected between 2015 and 2019 from participants in a family caregiver coaching intervention (170 caregivers, 294 children), we apply linear mixed models to assess associations between changes in family caregiver well-being, including problem solving, depressive symptoms, burden, health complaints and quality of life, and changes in parent-reported child anxiety. RESULTS: The baseline median Spence Children's Anxiety Scale-Parent score was 17; children aged 6-11 had slightly higher scores. Child anxiety scores decreased on average 2.8 points (SD 8.4) between baseline and follow-up. In adjusted models, decreases in caregiver depressive symptoms and health complaints were associated with decreases in child anxiety. Caregiver problem-solving skills, quality of life, and subjective burden were not associated with changes in child anxiety. CONCLUSION: Family caregiver-focused interventions that decrease caregiver stress may positively affect children in the household. Few resources are directed at military children; therefore, practitioners should consider ways to leverage caregiver interventions to address child well-being, such as incorporating information on parenting strategies and addressing issues faced by military children.

The Effects of Hepatitis C Treatment Eligibility Criteria on All-cause Mortality Among People With Human Immunodeficiency Virus.

BACKGROUND: The cost of direct-acting antivirals (DAAs) for hepatitis C virus (HCV) prompted many payers to restrict treatment to patients who met non-evidence-based criteria. These restrictions have implications for survival of people with HCV, especially for people with human immunodeficiency virus (HIV)/HCV coinfection who are at high risk for liver disease progression. The goal of this work was to estimate the effects of DAA access policies on 10-year all-cause mortality among people with HIV. METHODS: The study population included 3056 adults with HIV in the Women's Interagency HIV Study and Multicenter AIDS Cohort Study from 1 October 1994 through 30 September 2015. We used the parametric g-formula to estimate 10-year all-cause mortality under DAA access policies that included treating (i) all people with HCV; (ii) only people with suppressed HIV; (iii) only people with severe fibrosis; and (iv) only people with HIV suppression and severe fibrosis. RESULTS: The 10-year risk difference of treating all coinfected persons with DAAs compared with no treatment was -3.7% (95% confidence interval [CI], -9.1% to .6%). Treating only those with suppressed HIV and severe fibrosis yielded a risk difference of -1.1% (95% CI, -2.8% to .6%), with 51% (95% CI, 38%-59%) of coinfected persons receiving DAAs. Treating a random selection of 51% of coinfected persons at baseline decreased the risk by 1.9% (95% CI, -4.7% to .3%). CONCLUSIONS: Restrictive DAA access policies may decrease survival compared to treating similar proportions of people with HIV/HCV coinfection with DAAs at random. These findings suggest that lives could be saved by thoughtfully revising access policies.

Regression to the mean for the bivariate binomial distribution.

Regression to the mean (RTM) occurs when subjects having relatively high or low measurements are remeasured and found closer to the population mean. This phenomenon can potentially lead to an inaccurate conclusion in a pre-post study design. Expressions are available for quantifying RTM when the distribution of pre and post observations are bivariate normal and bivariate Poisson. However, situations exist where the response variables are the number of successes in a fixed number of trials and follow the bivariate binomial distribution. In this article, expressions for quantifying RTM effects are derived when the underlying distribution is the bivariate binomial. Unlike the normal and Poisson distributions, the correlation between pre and post observations can be either negative or positive under the bivariate binomial distribution and the severity of RTM is greater in the former case. The percentage relative difference is used to highlight the differences in quantifying RTM under the bivariate binomial distribution and normal and Poisson approximations to the bivariate binomial distribution. Expressions for estimating RTM using the method of maximum likelihood along with its asymptotic distribution are derived. A simulation study is conducted to empirically assess the statistical properties of the RTM estimator and its asymptotic distribution. Data examples using the number of obese individuals and the number of nonconforming cardboard cans are discussed.

[Intervention effects of selenium yeast on fine particulate matters-induced lung injury in rats].

OBJECTIVE: To evaluate if selenium yeast could inhibit the rat lung injury induced by ambient fine particulate matter( PM_(2. 5) ). METHODS: Fifty-six male SpragueDawley rats were randomly allocated in seven groups( n = 8 each). Saline control group, the rats were exposed to 0. 9% saline by instillation. PM_(2. 5) exposure group, rats were exposed to PM_(2. 5) by intra-tracheal instillation every other day for three times with the accumulated dose of 40 mg/kg. Selenium yeast treatment groups, three groups of rat were exposed to PM_(2. 5) . Then the rats were given low, middle and high dose of selenium yeast, and the doses were 8. 75, 17. 5 and 35 mg/kg, respectively. High dose selenium yeast control group, rats were given high dose of selenium yeast only. Solvent control group, therats were given 1% carboxymethyl cellulose. Saline and PM_(2. 5) were given in the first week. In the second week, selenium yeast and solvent were given by gavage. The rats were sacrificed 24 hours after the last gavage. The bronchoalveolar lavage fluid( BALF)was collected to count the neutrophils numbers and analyze the markers related to inflammation, oxidative stress and cell damage. The lung lobe that was not been lavaged was processed for light microscopic examination. RESULTS: The proportions of neutrophils in BALF and the pathologic scores of lung in PM_(2. 5) - exposed groups were significantly higher than control( P < 0. 05). Selenium yeast treatment caused decrease in tumor necrosis factor-α( TNF-α), interleukin-1ß( IL-1ß), lactate dehydrogenase( LDH), total protein( TP), alkaline phosphatase( AKP) and malondialdehyde( MDA) compared with the only PM_(2. 5) exposure group. Meanwhile, the dose-dependent increase in totalsuperoxide dismutase( T-SOD) and glutathione peroxidase( GSH-Px) activities were observed. There were no significant differences among the groups of saline control group, high dose selenium yeast control group and solvent control group. CONCLUSION: Selenium yeast treatment may protect against acute injury induced by PM_(2. 5) in rat lung.

Assessing the effects of malaria interventions on the geographical distribution of parasitaemia risk in Burkina Faso.

BACKGROUND: Burkina Faso conducted its first nationally representative household malaria survey in 2010/2011. The survey collected among others, information on malaria interventions, treatment choices and malaria parasite prevalence in children aged 6-59 months. METHODS: In this study, Bayesian geostatistical models were employed to assess the effects of health interventions related to insecticide-treated bed nets (ITN), indoor residual spray (IRS), artemisinin-based combination therapy (ACT) coverage associated with childhood malaria parasite risk at national and sub-national level, after taking into account geographical disparities of climatic/environmental and socio-economic factors. Several ITN coverage measures were calculated and Bayesian variable selection was used to identify the most important ones. Parasitaemia risk depicting spatial patterns of infections were estimated. RESULTS: The results show that the predicted population-adjusted parasitaemia risk ranges from 4.04 % in Kadiogo province to 82 % in Kompienga province. The effect of ITN coverage was not important at national level; however ITNs have an important protective effect in Ouagadougou as well as in three districts in the western part of the country with high parasitaemia prevalence and low to moderate coverage. There is a large variation in ACT coverage between the districts. Although at national level the ACT effects on parasitaemia risk was not important, at sub-national level 18 districts around Ouagadougou deliver effective treatment. CONCLUSION: The produced maps show great variations in parasitaemia risk across the country and identify the districts where interventions are being effective. These outputs are valuable tools that can help improve malaria control in Burkina Faso.

Effect of cognitive behavioral group therapy for recovery of self-esteem on community-living individuals with mental illness: Non-randomized controlled trial.

AIM: The aim of this study was to examine over a 12-month post-intervention period whether the participation of community-living individuals with mental illness in cognitive behavioral group therapy for recovery of self-esteem (CBGTRS) resulted in improved outcomes. METHODS: This was a non-randomized controlled trial. The participants were persons with mental illness who resided in communities in the Chugoku region of Japan. In total, 41 were assigned to an experimental group (CBGTRS intervention, 12 group sessions), and 21 to a control group. Outcome indices (self-esteem, moods, cognition, subjective well-being, psychiatric symptoms) were measured for the experimental group prior to intervention (T0), immediately post-intervention (T1), and at 3 (T2) and 12 (T3) months post-intervention. The control group was measured at the same intervals. RESULTS: For the experimental group, self-esteem scores at T1, T2, and T3 were significantly higher than at T0. Moods and cognition scores remained significantly low until T2. Scores for Inadequate Mental Mastery in the subjective well-being index had not decreased by T3. Confidence in Coping remained significantly high until T2. Psychiatric symptoms scores at T0, T1, T2, and T3 were significantly lower than at T0. The means and standard errors for self-esteem and Inadequate Mental Mastery increased until T3, and those for Tension-Anxiety, Depression-Dejection, and Confusion decreased until T2. CONCLUSION: From within-group trends and between-group differences in self-esteem, we conclude that CBGTRS may have a relatively long-term effect on self-esteem recovery. T2 is the turning point for moods and cognition; thus, follow-up is needed 3 months following the initial program.

Changing Friend Selection in Middle School: A Social Network Analysis of a Randomized Intervention Study Designed to Prevent Adolescent Problem Behavior.

Adolescent friendships that promote problem behavior are often chosen in middle school. The current study examines the unintended impact of a randomized school-based intervention on the selection of friends in middle school, as well as on observations of deviant talk with friends 5 years later. Participants included 998 middle school students (526 boys and 472 girls) recruited at the onset of middle school (age 11-12 years) from three public middle schools participating in the Family Check-up model intervention. The current study focuses only on the effects of the SHAPe curriculum-one level of the Family Check-up model-on friendship choices. Participants nominated friends and completed measures of deviant peer affiliation. Approximately half of the sample (n = 500) was randomly assigned to the intervention, and the other half (n = 498) comprised the control group within each school. The results indicate that the SHAPe curriculum affected friend selection within school 1 but not within schools 2 or 3. The effects of friend selection in school 1 translated into reductions in observed deviancy training 5 years later (age 16-17 years). By coupling longitudinal social network analysis with a randomized intervention study, the current findings provide initial evidence that a randomized public middle school intervention can disrupt the formation of deviant peer groups and diminish levels of adolescent deviance 5 years later.

Impacts of a Support Intervention for Zimbabwean and Sudanese Refugee Parents: "I Am Not Alone".

Knowledge about the beneficial effects of social support has not been used to systematically develop and evaluate interventions to help refugee new parents cope. The purpose of this study was to design and evaluate a social support intervention for refugee new parents. A multi-method research design was used and participatory research strategies were employed. Qualitative and quantitative measures were used to understand experiences of participants and to assess the perceived psychosocial and health-related outcomes of the intervention. Mentored support groups, matched by gender and ethnicity, met biweekly over 7 months. The participants were 48 Sudanese and 37 Zimbabwean refugee parents in 2 Canadian provinces. Increases were found in informational support, spousal support, community engagement, coping, and support-seeking. Decreases were found in parenting stress, loneliness, and isolation. The authors conclude that there is a need for culturally appropriate nursing practices and programs for refugee new parents from diverse cultures.

Les connaissances concernant les effets bénéfiques du soutien social n'ont pas été utilisées de manière systématique pour élaborer et évaluer les interventions visant à aider les réfugiés nouveaux parents à s'adapter à leur situation. L'objectif de cette étude est de concevoir et d'évaluer une intervention pour venir en aide aux réfugiés nouveaux parents. Diverses méthodes de recherche et différentes stratégies de recherche participative ont été utilisées pour la réalisation de l'étude. Des mesures quantitatives et qualitatives ont été effectuées pour comprendre l'expérience vécue par les participants et pour évaluer les résultats perçus de l'intervention sur les plans psychologique et de la santé. Des groupes de soutien encadrés et formés en fonction du sexe et de l'ethnie se sont réunis toutes les deux semaines pendant sept mois. L'ensemble des nouveaux parents participants comprenait 48 réfugiés soudanais et 37 réfugiés zimbabwéens établis dans deux provinces canadiennes. Ces groupes ont donné lieu à un accroissement du soutien informationnel, du soutien conjugal, de la participation communautaire, de l'adaptation et des demandes d'aide, ainsi qu'à une diminution du stress, de la solitude et de l'isolement des parents. En conclusion de leur étude, les auteurs signalent la nécessité d'adopter des programmes et des pratiques de soins infirmiers adaptés sur le plan culturel aux besoins des réfugiés nouveaux parents appartenant à diverses cultures.

From exposures to population interventions: pregnancy and response to HIV therapy.

Many epidemiologic studies identify contrasts between an "always-exposed" population and a "never-exposed" population. Such "exposure effects" are perhaps most valuable in discussing individual lifestyle changes, or in clinical care; they may be less valuable in estimating the potential effects of realistic public health interventions. Various methods, among them population attributable fractions and generalized impact fractions, attempt to obtain more policy-relevant estimates of "population intervention" effects, but such methods remain rare in the epidemiologic literature. Here, we describe the use of the parametric g-formula as a tool for the estimation of population intervention effects in longitudinal data. Our discussion is motivated by a previous study of the effect of incident pregnancy on time to virological failure among human immunodeficiency virus-positive women initiating antiretroviral therapy in South Africa between 2004 and 2011. We show that 1) interventional estimates of effect can be estimated in longitudinal data using the parametric g-formula and 2) exposure effects and population interventional effects can have dramatically different interpretations and magnitudes in real-world data. Epidemiologists should consider estimating interventional effects in addition to exposure effects; doing so would allow the results of epidemiologic studies to be more immediately relevant to policy-makers and to implementation science efforts.

Estimation of intervention effects using recurrent event time data in the presence of event dependence and a cured fraction.

Recurrent event data with a fraction of subjects having zero event are often seen in randomized clinical trials. Those with zero event may belong to a cured (or non-susceptible) fraction. Event dependence refers to the situation that a person's past event history affects his future event occurrences. In the presence of event dependence, an intervention may have an impact on the event rate in the non-cured through two pathways-a primary effect directly on the outcome event and a secondary effect mediated through event dependence. The primary effect combined with the secondary effect is the total effect. We propose a frailty mixture model and a two-step estimation procedure for the estimation of the effect of an intervention on the probability of cure and the total effect on event rate in the non-cured. A summary measure of intervention effects is derived. The performance of the proposed model is evaluated by simulation. Data on respiratory exacerbations from a randomized, placebo-controlled trial are re-analyzed for illustration.

Intervention effects of telenursing based on M-O-A model in empty-nest older adult individuals with chronic diseases: a randomized controlled trial.

Aim: This study aims to verify the effectiveness of M-O-A telenursing intervention model in improving the health status and quality of life of the empty-nest older adult individuals with chronic diseases by a randomized comparative trial. Methods: M-O-A telenursing intervention model was constructed based on the needs of the participants. The control group (N = 39) received routine nursing, the experimental group (N = 39) received M-O-A telenursing intervention in addition to routine nursing. After 12 weeks of intervention, the intervention effects of being a participant in the two groups were evaluated. SPSS 26.0 was used for data analysis. Results: After 12 weeks of intervention, for the experimental group, each dimension of quality of life based on EQ-5D-3L became better, especially for "pain/discomfort," "anxiety/depression," "HRQoL" and "EQ-VAS" (all p < 0.05) and each dimension of quality of life based on SF-36 became better too, especially for "GH," "BP," "RE," "MH," "VT," "SF," "PCS," "MCS," "SF-36" (all p < 0.05). In addition, there was a statistical downward trend in blood pressure, blood glucose, weight, BMI, fat rate, nap duration, number of nocturnal awakenings, light sleep rate and a statistical upward trend in water rate, basal metabolic rate, nighttime sleep duration, deep sleep rate, rapid eye movement sleep rate, especially at the end of intervention (all p < 0.05). While for the control group, there was no statistical improvement in all these aspects. Conclusion: The M-O-A telenursing model could effectively regulate quality of life and health condition of the empty-nest older adult individuals with chronic diseases, making it worthy of further promotion and application.

Cognitive vs. Linguistic Training in Children with Developmental Language Disorder: Exploring Their Effectiveness on Verbal Short-Term Memory and Verbal Working Memory.

The present study explores comparatively the effectiveness of a cognitive (verbal short-term memory (vSTM), verbal working memory (vWM)) and of a linguistic training (10-week duration each) in the diffusion of gains in cognitive abilities (vSTM and vWM) of in school-aged Greek-speaking children with developmental language disorder (DLD). To this purpose, two computerized training programs i.e., a linguistic and a cognitive one, were developed and applied to three groups (A, B, and C) of children with DLD (N = 49, in total). There were three assessments with two vSTM tasks (non-word repetition and forward digit span) and a vWM task (backward digit span): pre-therapeutically (time 1), where no significant between-group differences were found, post-therapeutically I (time 2), and post-therapeutically II (time 3) and two training phases. In phase Ι, group A received meta-syntactic training, whereas group B vSTM/vWM training and group C received no training. In phase ΙΙ, a reversal of treatment was performed for groups A and B: group A received vSTM/vWM while group B meta-syntactic training. Again, group C received no training. Overall, the results indicated a significant performance improvement for the treatment groups and revealed beneficial far-transfer effects as language therapy can affect vSTM and vWM in addition to direct and near transfer effects. In addition, the intervention type order affected performance as follows: first, better performance on the vSTM task (non-word repetition) was shown when the linguistic treatment was delivered first; second, better performance on the vWM in Time 2 and Time 3 was shown by group B, for which the cognitive treatment was delivered first. Concluding, not only intervention type but also intervention type order can affect performance in DLD.

Exploring the Relationship Between Anticipated Stigma and Community Shared Concerns about HIV on Defaulting from HIV Care in Rural South Africa.

Although stigma has been associated with people living with HIV defaulting from care, there is a gap in understanding the specific impact of individual stigma and community-level concern about HIV on defaulting. Methods: This is a secondary analysis of a unique dataset that links health facility-based medical records to a population-representative community survey conducted in 2018 in rural Mpumalanga province, South Africa. We used the parametric g-formula to estimate associations among individual anticipated stigma, low perceived community and local leader concern about HIV, and defaulting from care in the prior year. In addition, we estimated the population-level effects of intervening to reduce stigma and increase concern on defaulting. Results: Among 319 participants on treatment, 42 (13.2%) defaulted from care during the prior year. Anticipated stigma (risk ratio [RR] 1.22, 95% confidence interval [CI]: 0.72, 2.74), low perceived concern about HIV/AIDS from community leadership (RR 1.12, 95% CI 0.76, 3.38), and low shared concerns about HIV/AIDS in the community (RR 1.37; 95% CI 0.79, 3.07) were not significantly associated with default. Hypothetical population intervention effects to remove individual anticipated stigma and low community concerns yielded small reductions in default (~1% reduction). Conclusions: In this sample, we found limited impact of reducing anticipated stigma and increasing shared concern about HIV on retention in care. Future studies should consider the limitations of this study by examining the influence of other sources of stigma in more detail and assessing how perceptions of stigma and concern impact the full HIV testing and care cascade.

Effects of a Smartphone-Based, Multisession Interpretation-Bias Modification for Anxiety: Positive Intervention Effects and Low Attrition.

While interpretation-bias modification (IBM) is an effective intervention for treating anxiety, it is not broadly used in clinical or daily practice. To this end, this study developed and tested a smartphone-based IBM application. We adopted the ambiguous situation paradigm as an intervention task in conjunction with robust training materials that broadly covered situations encountered in daily life. We recruited participants with high-trait anxiety and divided them into three groups: (1) positive training; (2) 50% positive-50% negative training; and (3) no-training control. The first two groups completed 28 days of smartphone-based training (IBM in positive cases), and all groups completed six rounds of assessments. The smartphone-based IBM training changed positive and negative endorsements and more specific measures of interpretation bias, thus reducing anxiety. The results also showed that changes in the number of negative interpretations played a mediating role in anxiety reduction. It is notable that the attrition rate was extremely low across the experiment. Our follow-up showed that positive gains persisted throughout the intervening period. Smartphone-based IBM can help individuals with anxiety shift negative biases, broaden their thoughts, enhance their information processing, and effectively target the clinical features of anxiety.