Toward tailored care for families with multiple problems: A quasi-experimental study on effective elements of care.
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ABSTRACT:
SUBMITTER: Visscher L
PROVIDER: S-EPMC9305733 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Evidence from correlational studies supporting the benefits of breastfeeding on children's externalising problems is mixed. Quasi-experimental approaches can help in better understanding possible 'effects'. We aimed to investigate the longitudinal impact of breastfeeding on externalising problems from childhood into adolescence. Participants included ~ 5000 full-term children, from the Growing Up in Ireland Child Cohort. Externalising problems (conduct problems and hyperactivity) were assessed using both the parent and teacher versions of the Strengths and Difficulties Questionnaire when children were age 9 and 13. Maternal reports were used to collect retrospective information on breastfeeding. Propensity score matching, and adjusting for multiple testing were used to compare the average treatment effects for children who were breastfed. Post matching results revealed statistically significant reductions in hyperactivity at age nine, using both maternal and teacher reports (difference score - 0.48, 95% CI - 0.85, - 0.11; and - 0.51, 95% CI - 0.90, - 0.12, respectively), for children who were breastfed between 6 and 12 months, but not thereafter. These effects were not maintained at age 13. Moreover, no effects of breastfeeding on conduct problems were found at any age, regardless of duration, using either maternal or teacher report. While some benefits of breastfeeding were found, compatible with a temporary modest reduction in hyperactivity, related to being breastfed for 26-50 weeks, these results must be viewed in the context of reliance of propensity score matching on observable characteristics. Additionally, our results are suggestive of a potential non-linear dose-response of breastfeeding on hyperactivity.
| S-EPMC6013516 | biostudies-literature
Project description:BackgroundResults-based financing (RBF) describes health system approaches addressing both service quality and use. Effective coverage is a metric measuring progress towards universal health coverage (UHC). Although considered a means towards achieving UHC in settings with weak health financing modalities, the impact of RBF on effective coverage has not been explicitly studied.MethodsMalawi introduced the Results-Based Financing For Maternal and Neonatal Health (RBF4MNH) Initiative in 2013 to improve quality of maternal and newborn health services at emergency obstetric care facilities. Using a quasi-experimental design, we examined the impact of the RBF4MNH on both crude and effective coverage of pregnant women across four districts during the two years following implementation.ResultsThere was no effect on crude coverage. With a larger proportion of women in intervention areas receiving more effective care over time, the overall net increase in effective coverage was 7.1%-points (p = 0.07). The strongest impact on effective coverage (31.0%-point increase, p = 0.02) occurred only at lower cut-off level (60% of maximum score) of obstetric care effectiveness. Design-specific and wider health system factors likely limited the program's potential to produce stronger effects.ConclusionThe RBF4MNH improved effective coverage of pregnant women and seems to be a promising reform approach towards reaching UHC. Given the short study period, the full potential of the current RBF scheme has likely not yet been reached.
| S-EPMC6194711 | biostudies-literature
Project description:Specific stressors associated with caregiving in Mexican American (MA) families are not well documented, yet caregiving issues are paramount because informal care for parents is central to their culture. Although MA families who band together to provide care for one member are not unique, the literature does not describe the phenomenon of collective caregiving, which may be widespread but unrecognized. This article describes these understudied families who are poorly served by contemporary health systems because their characteristics are unknown.Descriptive, multisite, longitudinal mixed-methods study of MA caregiving families.We identified three types of collective caregivers: those providing care for multiple family members simultaneously, those providing care successively to several family members, and/or those needing care themselves during their caregiving of others.Collective caregiving of MA elders warrants further investigation.Exploration of collective caregiving may provide a foundation for tailored family interventions.
| S-EPMC5219842 | biostudies-other
Project description:BackgroundAmerican Indian and Alaska Native peoples experience poor end-of-life care, including more hospitalizations and lower use of hospice and do-not-resuscitate orders. Although advance care planning (ACP) can improve end-of-life care, ACP rates are disproportionately low in American Indians and Alaska Natives.ObjectiveWe culturally tailored and delivered an existing evidence-based ACP program for an American Indian tribal community. Here, we present the protocol for assessing the intervention's feasibility and efficacy.MethodsWe measured feasibility via participant recruitment, participants' evaluation (acceptability, appropriateness, comprehension, and satisfaction), and intervention fidelity. Recruitment was measured with participant screening, eligibility, enrollment, and retention. Participant's evaluation of the intervention was measured with surveys. Fidelity was measured with direct observation and the Make Your Wishes About You (MY WAY) Fidelity Checklist Tool. To assess the intervention's efficacy, we used a quasi-experimental waitlist control design with 2 cohorts who were surveyed each on three separate occasions. The intervention's efficacy was assessed by the following: ACP barriers and facilitators as well as ACP self-efficacy, readiness, and completion.ResultsA total of 166 participants were screened for eligibility; 11 were deemed ineligible, and 155 participants were enrolled in the study. Of those enrolled, 113 completed the intervention and will be included in subsequent analyses. We finalized data collection in January 2023, and analyses are underway. Study enrollment was successful, and we expect that participants will report high levels of acceptability, appropriateness, comprehension, and satisfaction with the intervention. We expect that the intervention was implemented with fidelity and will demonstrate decreases in ACP barriers and increases in ACP facilitators, self-efficacy, readiness, and completion.ConclusionsEnrolling over twice as many participants as we had hoped suggests that members of this tribal community are willing to engage in end-of-life ACP. We were able to implement a waitlist study design to show that a culturally tailored ACP program for a tribal community is feasible.Trial registrationClinicalTrials.gov NCT05304117; https://clinicaltrials.gov/study/NCT05304117.International registered report identifier (irrid)DERR1-10.2196/50654.
| S-EPMC10787334 | biostudies-literature
Project description:Advancements in the implementation of quantum hardware have enabled the acquisition of data that are intractable for emulation with classical computers. The integration of classical machine learning (ML) algorithms with these data holds potential for unveiling obscure patterns. Although this hybrid approach extends the class of efficiently solvable problems compared to using only classical computers, this approach has been only realized for solving restricted problems because of the prevalence of noise in current quantum computers. Here, we extend the applicability of the hybrid approach to problems of interest in many-body physics, such as predicting the properties of the ground state of a given Hamiltonian and classifying quantum phases. By performing experiments with various error-reducing procedures on superconducting quantum hardware with 127 qubits, we managed to acquire refined data from the quantum computer. This enabled us to demonstrate the successful implementation of theoretically suggested classical ML algorithms for systems with up to 44 qubits. Our results verify the scalability and effectiveness of the classical ML algorithms for processing quantum experimental data.
| S-EPMC11364692 | biostudies-literature
Project description:BACKGROUND:Alcohol use is prevalent in many societies and has major adverse impacts on health, but the availability of effective interventions limits treatment options for those who want assistance in changing their patterns of alcohol use. OBJECTIVE:This study evaluated the new Daybreak program, which is accessible via mobile app and desktop and was developed by Hello Sunday Morning to support high-risk drinking individuals looking to change their relationship with alcohol. In particular, we compared the effect of adding online coaching via real-time chat messages (intervention group) to an otherwise self-guided program (control group). METHODS:We designed the intervention as a randomized control trial, but as some people (n=48; 11.9%) in the control group were able to use the online coaching, the main analysis comprised all participants. We collected online surveys at one-month and three-months follow-up. The primary outcome was change in alcohol risk (measured with the alcohol use disorders identification test-consumption [AUDIT-C] score), but other outcomes included the number of standard drinks per week, alcohol-related days out of role, psychological distress (Kessler-10), and quality of life (EUROHIS-QOL). Markers of engagement with the program included posts to the site and comments on the posts of others. The primary analysis used Weighted Generalized Estimating Equations. RESULTS:We recruited 398 people to the intervention group (50.2%) and 395 people to the control group (49.8%). Most were female (71%) and the mean age was 40.1 years. Most participants were classified as probably dependent (550, 69%) on the AUDIT-10, with 243 (31%) classified with hazardous or harmful consumption. We followed up with 334 (42.1%) participants at one month and 293 (36.9%) at three months. By three months there were significant improvements in AUDIT-C scores (down from mean 9.1 [SD 1.9] to 5.8 [SD 3.1]), alcohol consumed per week (down from mean 37.1 [SD 28.3] to mean 17.5 [SD 18.9]), days out of role (down from mean 1.6 [SD 3.6] to 0.5 [SD 1.6]), quality of life (up from 3.2 [SD 0.7] to 3.6 [SD 0.7]) and reduced distress (down from 24.8 [SD 7.0] to 19.0 [SD 6.6]). Accessing online coaching was not associated with improved outcomes, but engagement with the program (eg, posts and comments on the posts of others) were significantly associated with improvements (eg, in AUDIT-C, alcohol use and EUROHIS-QOL). Reduced alcohol use was found for both probably dependent (estimated marginal mean of 40.8 to 20.1 drinks) and hazardous or harmful alcohol users (estimated marginal mean of 22.9 to 11.9 drinks). CONCLUSIONS:Clinically significant reductions in alcohol use were found, as well as reduced alcohol risk (AUDIT-C) and days out of role. Importantly, improved alcohol-related outcomes were found for both hazardous or harmful and probably dependent drinkers. Since October 2016, Daybreak has reached more than 50,000 participants. Therefore, there is the potential for the program to have an impact on alcohol-related problems at a population health level, importantly including an effect on probably dependent drinkers. TRIAL REGISTRATION:Australian New Zealand Clinical Trials Registry: ACTRN12618000010291; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=373110. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID):RR2-10.2196/9982.
| S-EPMC6753690 | biostudies-literature
Project description:BACKGROUND:Substance use by adolescents remains to be at unacceptably high levels, and there is evidence that teens' social norms are becoming more favorable toward recreational use and perceived safety of substances such as marijuana and prescription opioids. Social media offer a low-cost, potentially high-impact approach to disseminate prevention messages. OBJECTIVE:Living the Example (LTE) is a program that trains adolescent youth ambassadors to develop and disseminate prevention messages within their own social media networks and through in-school activities. This study aimed to evaluate the effects of exposure to LTE-based social media on students in the youth ambassadors' networks. METHODS:The George Washington (GW) University designed and implemented a quasi-experimental evaluation of the LTE program in 3 Maryland high schools. Before program launch, a sample of 826 students (wave 1) at the 3 schools, drawn from a census of freshmen enrolled in a class attended by all students at the grade level, completed a survey. A total of 584 students were surveyed at the wave 2 program midpoint and 542 at the wave 3 endpoint. The survey contained questions on drug use-related attitudes, beliefs, intentions, and behaviors, all based on validated measures. We evaluated the effects of LTE on the intended next 30-day drug use, and controlling for LTE self-reported exposure, age, and gender from waves 2 and 3 was appended into a single dataset. We first conducted ordinal logistic regressions for each drug use intention in wave 3 (ie, sell or distribute illegal drugs, smoke cigarettes, drink beer/wine/hard liquor when parents do not know about it, use marijuana, use lysergic acid diethylamide, cocaine, amphetamines or other illegal drugs, use heroin, use synthetic drugs, and use any prescription pills without a prescription) to examine the association between LTE exposure and drug use intentions. We included an interaction term for the study wave to examine intervention effects. RESULTS:We found a significant positive effect of LTE exposure on all 8 measured drug use intentions: sell/distribute illegal drugs; smoke cigarettes; drink beer, wine, or liquor when my parents do not know about it; use marijuana; use cocaine, amphetamines, or other illegal drug; use heroin; use synthetic drugs; use any prescription pills without a prescription (all P<.05; odds ratios ranging from 2.12 to 3.71). We also found that boys were more likely than girls to exhibit reduced drug use intentions. We also found reductions in 30-day intentions between the second and third survey waves for all 8 measured drug use variables. CONCLUSIONS:Overall, the results are consistent with and indicate a stronger LTE effect in this study compared with a previous pilot study. LTE appears to offer a protective effect, with exposure to program messages leading to reduced/improved drug use intentions.
| S-EPMC7240438 | biostudies-literature
Project description:BACKGROUND:We sought to determine whether patients with a coordinated care plan developed using the Health Links model of care in the Hamilton Niagara Haldimand Brant Local Health Integration Network differed in their use of health care (no. of emergency department visits, inpatient admissions, length of inpatient stay) when compared with a matched control group of patients with no care plans. METHODS:We performed a propensity score-matched study of 12 months pre- and 12 months post-health care use. Patients who had a coordinated care plan that started between 2013 and 2015 were propensity score matched to patients in a control group. Patient information was obtained from Client Health and Related Information System, National Ambulatory Care Reporting System and Discharge Abstract Database. Differences in health care use pre- and post-index date were compared using the Wilcoxon signed-rank test. A negative binomial regression model was fit for each health care use outcome at 6 and 12 months post-index date. RESULTS:Six hundred coordinated care plan enrollees and 25 449 potential control patients were included in the matching algorithm, which resulted in 548 matched pairs (91.3%). Both groups showed decreases in health care use post-index date. Matched care plan enrollees had significantly fewer emergency department visits at 6 (incidence rate ratio [IRR] 0.81, 95% confidence interval [CI] 0.72-0.91, p < 0.01) and 12 months post-index date (IRR 0.88, 95% CI 0.79-0.99, p < 0.05) compared with the matched controls. Other use parameters were not significantly different between care plan enrollees and the control group. INTERPRETATION:Care plan enrollees show a decrease in the number of times they visit emergency departments, which may be attributed to integrated and coordinated care planning. This association should be examined to see whether these reductions persist for more than 1 year.
| S-EPMC5984145 | biostudies-literature
Project description:In a randomized controlled trial, behavioral day treatment, including contingency management (CM+), was compared to contingency management components alone (CM). All 206 cocaine-dependent homeless participants received a furnished apartment with food and work training/employment contingent on drug-negative urine tests. CM+ also received cognitive-behavioral therapy, therapeutic goal management, and other intervention components. Results revealed that CM+ treatment attendance and abstinence were not significantly different from CM during 24 weeks of treatment. After treatment and contingencies ended, however, CM+ showed more abstinence than CM, indicating a delayed effect of treatment from 6 to 18 months. CM+ had more consecutive weeks abstinent across 52 weeks, but not during active treatment. We conclude that CM alone may be viable as initial care for cocaine-dependent homeless persons. That CM+ yields more durable abstinence indicates that it may be appropriate as stepped-up care for clients not responding to CM (Clinical Trials.gov, no. NCT00368524).
| S-EPMC2764243 | biostudies-literature
Project description:Binary classification is a widely employed problem to facilitate the decisions on various biomedical big data questions, such as clinical drug trials between treated participants and controls, and genome-wide association studies (GWASs) between participants with or without a phenotype. A machine learning model is trained for this purpose by optimizing the power of discriminating samples from two groups. However, most of the classification algorithms tend to generate one locally optimal solution according to the input dataset and the mathematical presumptions of the dataset. Here we demonstrated from the aspects of both disease classification and feature selection that multiple different solutions may have similar classification performances. So the existing machine learning algorithms may have ignored a horde of fishes by catching only a good one. Since most of the existing machine learning algorithms generate a solution by optimizing a mathematical goal, it may be essential for understanding the biological mechanisms for the investigated classification question, by considering both the generated solution and the ignored ones.
| S-EPMC5634418 | biostudies-literature