Category: Nevin Manimala

JMIR Public Health Surveill. 2023 Jun 28;9:e43776. doi: 10.2196/43776.

ABSTRACT

BACKGROUND: Opioid drug prescription (ODP) and opioid-related mortality (ORM) have increased in Spain. However, their relationship is complex, as ORM is registered without considering the type of opioid (legal or illegal).

OBJECTIVE: This ecological study aimed to examine the correlation between ODP and ORM in Spain and discuss their usefulness as a surveillance tool.

METHODS: This was an ecological descriptive study using retrospective annual data (2000-2019) from the Spanish general population. Data were collected from people of all ages. Information on ODP was obtained from the Spanish Medicines Agency in daily doses per 1000 inhabitants per day (DHD) for total ODP, total ODP excluding those with better safety protocols (codeine and tramadol), and each opioid drug separately. Rates of ORM (per 1,000,000 inhabitants) were calculated based on deaths registered (International Classification of Diseases, 10th Revision codes) as opioid poisoning by the National Statistics Institute, derived from the drug data recorded by medical examiners in death certificates. Opioid-related deaths were considered to be those that indicated opioid consumption (accidental, infringed, or self-inflicted) as the main cause of death: death due to accidental poisoning (X40-X44), intentional self-inflicted poisoning (X60-X64), drug-induced aggression (X85), and poisoning of undetermined intention (Y10-Y14). A descriptive analysis was carried out, and correlations between the annual rates of ORM and DHD of the prescribed opioid drugs globally, excluding medications of the least potential risk of overdose and lowest treatment tier, were analyzed using Pearson linear correlation coefficient. Their temporal evolution was analyzed using cross-correlations with 24 lags and the cross-correlation function. The analyses were carried out using Stata and StatGraphics Centurion 19.

RESULTS: The rate of ORM (2000-2019) ranged between 14 and 23 deaths per 1,000,000 inhabitants, with a minimum in 2006 and an increasing trend starting in 2010. The ODP ranged between 1.51 to 19.94 DHD. The rates of ORM were directly correlated with the DHD of total ODP (r=0.597; P=.006), total ODP without codeine and tramadol (r=0.934; P<.001), and every prescribed opioid except buprenorphine (P=.47). In the time analysis, correlations between DHD and ORM were observed in the same year, although not statistically significant (all P≥.05).

CONCLUSIONS: There is a correlation between greater availability of prescribed opioid drugs and an increase in opioid-related deaths. The correlation between ODP and ORM may be a useful tool in monitoring legal opiates and possible disturbances in the illegal market. The role of tramadol (an easily prescribed opioid) is important in this correlation, as is that of fentanyl (the strongest opioid). Measures stronger than recommendations need to be taken to reduce off-label prescribing. This study shows that not only is opioid use directly related to the prescribing of opioid drugs above what is desirable but also an increase in deaths.

PMID:37379061 | DOI:10.2196/43776

J Med Internet Res. 2023 Jun 28;25:e44024. doi: 10.2196/44024.

ABSTRACT

BACKGROUND: Digital health engagement may serve many support functions, such as providing access to information; checking or evaluating one’s state of health; and tracking, monitoring, or sharing health data. Many digital health engagement behaviors are associated with the potential to reduce inequalities in information and communication. However, initial studies suggest that health inequalities may persist in the digital realm.

OBJECTIVE: This study aimed to explore the functions of digital health engagement by describing how frequently respective services are used for a range of purposes and how these purposes can be categorized from the users’ perspective. This study also aimed to identify the prerequisites for successfully implementing and using digital health services; therefore, we shed light on the predisposing, enabling, and need factors that may predict digital health engagement for different functions.

METHODS: Data were gathered via computer-assisted telephone interviews during the second wave of the German adaption of the Health Information National Trends Survey in 2020 (N=2602). The weighted data set allowed for nationally representative estimates. Our analysis focused on internet users (n=2001). Engagement with digital health services was measured by their reported use for 19 different purposes. Descriptive statistics showed the frequency with which digital health services were used for these purposes. Using a principal component analysis, we identified the underlying functions of these purposes. Using binary logistic regression models, we analyzed which predisposing factors (age and sex), enabling factors (socioeconomic status, health- and information-related self-efficacy, and perceived target efficacy), and need factors (general health status and chronic health condition) can predict the use of the distinguished functions.

RESULTS: Digital health engagement was most commonly linked to acquiring information and less frequently to more active or interactive purposes such as sharing health information with other patients or health professionals. Across all purposes, the principal component analysis identified 2 functions. Information-related empowerment comprised items on acquiring health information in various forms, critically assessing one’s state of health, and preventing health problems. In total, 66.62% (1333/2001) of internet users engaged in this behavior. Health care-related organization and communication included items on patient-provider communication and organizing health care. It was applied by 52.67% (1054/2001) of internet users. Binary logistic regression models showed that the use of both functions was determined by predisposing factors (female and younger age) and certain enabling factors (higher socioeconomic status) and need factors (having a chronic condition).

CONCLUSIONS: Although a large share of German internet users engage with digital health services, predictors show that existing health-related disparities prevail in the digital realm. To make use of the potential of digital health services, fostering digital health literacy at different levels, especially in vulnerable groups, is key.

PMID:37379058 | DOI:10.2196/44024

JMIR Mhealth Uhealth. 2023 Jun 28;11:e42750. doi: 10.2196/42750.

ABSTRACT

BACKGROUND: Over the past few decades, there has been a rapid increase in the number of wearable sleep trackers and mobile apps in the consumer market. Consumer sleep tracking technologies allow users to track sleep quality in naturalistic environments. In addition to tracking sleep per se, some sleep tracking technologies also support users in collecting information on their daily habits and sleep environments and reflecting on how those factors may contribute to sleep quality. However, the relationship between sleep and contextual factors may be too complex to be identified through visual inspection and reflection. Advanced analytical methods are needed to discover new insights into the rapidly growing volume of personal sleep tracking data.

OBJECTIVE: This review aimed to summarize and analyze the existing literature that applies formal analytical methods to discover insights in the context of personal informatics. Guided by the problem-constraints-system framework for literature review in computer science, we framed 4 main questions regarding general research trends, sleep quality metrics, contextual factors considered, knowledge discovery methods, significant findings, challenges, and opportunities of the interested topic.

METHODS: Web of Science, Scopus, ACM Digital Library, IEEE Xplore, ScienceDirect, Springer, Fitbit Research Library, and Fitabase were searched to identify publications that met the inclusion criteria. After full-text screening, 14 publications were included.

RESULTS: The research on knowledge discovery in sleep tracking is limited. More than half of the studies (8/14, 57%) were conducted in the United States, followed by Japan (3/14, 21%). Only a few of the publications (5/14, 36%) were journal articles, whereas the remaining were conference proceeding papers. The most used sleep metrics were subjective sleep quality (4/14, 29%), sleep efficiency (4/14, 29%), sleep onset latency (4/14, 29%), and time at lights off (3/14, 21%). Ratio parameters such as deep sleep ratio and rapid eye movement ratio were not used in any of the reviewed studies. A dominant number of the studies applied simple correlation analysis (3/14, 21%), regression analysis (3/14, 21%), and statistical tests or inferences (3/14, 21%) to discover the links between sleep and other aspects of life. Only a few studies used machine learning and data mining for sleep quality prediction (1/14, 7%) or anomaly detection (2/14, 14%). Exercise, digital device use, caffeine and alcohol consumption, places visited before sleep, and sleep environments were important contextual factors substantially correlated to various dimensions of sleep quality.

CONCLUSIONS: This scoping review shows that knowledge discovery methods have great potential for extracting hidden insights from a flux of self-tracking data and are considered more effective than simple visual inspection. Future research should address the challenges related to collecting high-quality data, extracting hidden knowledge from data while accommodating within-individual and between-individual variations, and translating the discovered knowledge into actionable insights.

PMID:37379057 | DOI:10.2196/42750

JMIR Res Protoc. 2023 Jun 28;12:e48499. doi: 10.2196/48499.

ABSTRACT

BACKGROUND: Patients with colorectal cancer (CRC) receiving chemotherapy often experience psychoneurological symptoms (PNS; ie, fatigue, depression, anxiety, sleep disturbance, pain, and cognitive dysfunction) that negatively impact both patients’ and their caregivers’ health outcomes. Limited information is available on PNS management for CRC patient and caregiver dyads.

OBJECTIVE: The purposes of this study are to (1) develop a web-based dyadic intervention for patients with CRC receiving chemotherapy and their caregivers (CRCweb) and (2) evaluate the feasibility, acceptability, and preliminary effects of CRCweb among patient-caregiver dyads in a cancer clinic.

METHODS: A mixed methods approach will be used. Semistructured interviews among 8 dyads will be conducted to develop CRCweb. A single-group pre- and posttest clinical trial will be used to examine the feasibility, acceptability, and preliminary effects of the intervention (CRCweb) among 20 dyads. Study assessments will be conducted before (T1) and after intervention (T2). Content analysis will be performed for semistructured interviews. Descriptive statistics will be calculated separately for patients and caregivers, and pre-post paired t tests will be used to evaluate treatment effects.

RESULTS: This study was funded in November 2022. As of April 2023, we have obtained institutional review board approval and completed clinical trial registration and are currently recruiting patient-caregiver dyads in a cancer clinic. The study is expected to be completed in October 2024.

CONCLUSIONS: Developing a web-based dyadic intervention holds great promise to reduce the PNS burden in patients with CRC receiving chemotherapy and their caregivers. The findings from this study will advance intervention development and implementation of symptom management and palliative care for patients with cancer and their caregivers.

TRIAL REGISTRATION: ClinicalTrials.gov NCT05663203; https://clinicaltrials.gov/ct2/show/NCT05663203.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/48499.

PMID:37379055 | DOI:10.2196/48499

J Gerontol Nurs. 2023 Jul;49(7):17-23. doi: 10.3928/00989134-20230615-04. Epub 2023 Jul 1.

ABSTRACT

People living with dementia (PLWD) experience pain like other older adults, but with changes due to dementia, they rely more on family caregivers for pain assessment. Many different elements contribute to a pain assessment. Changes in characteristics of PLWD may be associated with changes in the use of these different pain assessment elements. The current study reports associations between PLWD’s agitation, cognitive function, and dementia severity and the frequency with which family caregivers use pain assessment elements. In a sample of family caregivers (N = 48), statistically significant associations were found between worsening cognitive function and greater use of rechecking for pain after intervention (rho = 0.36, p = 0.013), and between lower cognitive scores on a subscale of dementia severity and asking others if they have noticed a behavior change in the PLWD (rho = 0.30, p = 0.044). Limited statistically significant associations suggest that, overall, family caregivers of PLWD do not use pain assessment elements more frequently with changes in characteristics of PLWD. [Journal of Gerontological Nursing, 49(7), 17-23.].

PMID:37379047 | DOI:10.3928/00989134-20230615-04

J Gerontol Nurs. 2023 Jul;49(7):5-8. doi: 10.3928/00989134-20230615-02. Epub 2023 Jul 1.

ABSTRACT

Using the Kirkpatrick Model as a framework, the current program evaluation was performed to examine the effect of an online dementia training program on the rate of antipsychotic medication use in a nursing home. Antipsychotic medication use before program implementation was compared to use post-implementation. Run charts and a Wilcoxon analysis were used to look for trends or variances in antipsychotic medication use before and after implementation of the program. A nonrandom reduction was noted, and a statistically significant difference was noted in the percentage of residents receiving antipsychotic medications in the 6-month data prior to the training compared to the 6-month data after initial training (p = 0.026). Staff were satisfied with the training program and learning was noted, as evidenced by staff being able to list behaviors using the CARES^® approach. Fully embedding the training into facility culture will need to be examined by facility administration. [Journal of Gerontological Nursing, 49(7), 5-8.].

PMID:37379044 | DOI:10.3928/00989134-20230615-02

J Cataract Refract Surg. 2023 Jun 26. doi: 10.1097/j.jcrs.0000000000001246. Online ahead of print.

ABSTRACT

PURPOSE: To compare the postoperative endothelial cell counts of EVO-ICLs with a central hole (V4c and V5) and laser vision correction surgery (LASIK or PRK).

SETTING: OOO Eye Center, OOO, South Korea.

DESIGN: Retrospective, observational, and paired contralateral study.

METHODS: We retrospectively reviewed 62 eyes of 31 patients who underwent EVO-ICL with a central hole implantation in one eye (pIOL group) and laser vision correction in the contralateral eye (LVC group) to correct refractive errors. Central endothelial cell density (ECD), percentage of hexagonal cells (HEX), coefficient of variation in cell size (CV), and adverse events were evaluated for at least three years. The endothelial cells were observed using a non-contact specular microscope.

RESULTS: All surgeries were performed, without complications during the follow-up period. The mean ECD loss values compared with the preoperative measurements were 6.65% and 4.95% during the 3 years after pIOL and LVC, respectively. There was no significant difference in ECD loss compared to the preoperative values (paired t-test, P = 0.188) between the two groups. No significant loss in ECD was observed at any time point. The pIOL group showed higher HEX (P = 0.018) and lower CV (P = 0.006) values than the LVC group at the last visit.

CONCLUSION: According to our experience, EVO-ICL with a central hole implantation was a safe and stable vision correction method. Moreover, it did not induce statistically significant changes in ECD 3 years postoperatively compared with LVC. However, further long-term follow-up studies are required to confirm these results.

PMID:37379027 | DOI:10.1097/j.jcrs.0000000000001246

J Cataract Refract Surg. 2023 Jun 27. doi: 10.1097/j.jcrs.0000000000001251. Online ahead of print.

NO ABSTRACT

PMID:37379022 | DOI:10.1097/j.jcrs.0000000000001251

J Vis. 2023 Jun 1;23(6):13. doi: 10.1167/jov.23.6.13.

ABSTRACT

Clinical trials typically analyze multiple endpoints for signals of efficacy. To improve signal detection for treatment effects using the high-dimensional data collected in trials, we developed a hierarchical Bayesian joint model (HBJM) to compute a five-dimensional collective endpoint (CE5D) of contrast sensitivity function (CSF) and visual acuity (VA). The HBJM analyzes row-by-row CSF and VA data across multiple conditions, and describes visual functions across a hierarchy of population, individuals, and tests. It generates joint posterior distributions of CE5D that combines CSF (peak gain, peak frequency, and bandwidth) and VA (threshold and range) parameters. The HBJM was applied to an existing dataset of 14 eyes, each tested with the quantitative VA and quantitative CSF procedures in four Bangerter foil conditions. The HBJM recovered strong correlations among CE5D components at all levels. With 15 qVA and 25 qCSF rows, it reduced the variance of the estimated components by 72% on average. Combining signals from VA and CSF and reducing noises, CE5D exhibited significantly higher sensitivity and accuracy in discriminating performance differences between foil conditions at both the group and test levels than the original tests. The HBJM extracts valuable information about covariance of CSF and VA parameters, improves precision of the estimated parameters, and increases the statistical power in detecting vision changes. By combining signals and reducing noise from multiple tests for detecting vision changes, the HBJM framework exhibits potential to increase statistical power for combining multi-modality data in ophthalmic trials.

PMID:37378989 | DOI:10.1167/jov.23.6.13

JAMA Psychiatry. 2023 Jun 28. doi: 10.1001/jamapsychiatry.2023.1691. Online ahead of print.

ABSTRACT

IMPORTANCE: Tobacco smoking drives markedly elevated cardiovascular disease risk and preventable death in persons with serious mental illness, and these risks are compounded by the high prevalence of overweight/obesity that smoking cessation can exacerbate. Guideline-concordant combined pharmacotherapy and behavioral smoking cessation treatment improves abstinence but is not routinely offered in community settings, particularly to those not seeking to quit smoking immediately.

OBJECTIVE: To determine the effectiveness of an 18-month pharmacotherapy and behavioral smoking cessation intervention incorporating weight management and support for physical activity in adults with serious mental illness interested in quitting smoking within 1 or 6 months.

DESIGN, SETTING, AND PARTICIPANTS: This was a randomized clinical trial conducted from July 25, 2016, to March 20, 2020, at 4 community health programs. Adults with serious mental illness who smoked tobacco daily were included in the study. Participants were randomly assigned to intervention or control, stratified by willingness to try to quit immediately (within 1 month) or within 6 months. Assessors were masked to group assignment.

INTERVENTIONS: Pharmacotherapy, primarily varenicline, dual-form nicotine replacement, or their combination; tailored individual and group counseling for motivational enhancement; smoking cessation and relapse prevention; weight management counseling; and support for physical activity. Controls received quitline referrals.

MAIN OUTCOME AND MEASURES: The primary outcome was biochemically validated, 7-day point-prevalence tobacco abstinence at 18 months.

RESULTS: Of the 298 individuals screened for study inclusion, 192 enrolled (mean [SD] age, 49.6 [11.7] years; 97 women [50.5%]) and were randomly assigned to intervention (97 [50.5%]) or control (95 [49.5%]) groups. Participants self-identified with the following race and ethnicity categories: 93 Black or African American (48.4%), 6 Hispanic or Latino (3.1%), 90 White (46.9%), and 9 other (4.7%). A total of 82 participants (42.7%) had a schizophrenia spectrum disorder, 62 (32.3%) had bipolar disorder, and 48 (25.0%) had major depressive disorder; 119 participants (62%) reported interest in quitting immediately (within 1 month). Primary outcome data were collected in 183 participants (95.3%). At 18 months, 26.4% of participants (observed count, 27 of 97 [27.8%]) in the intervention group and 5.7% of participants (observed count, 6 of 95 [6.3%]) in the control group achieved abstinence (adjusted odds ratio [OR], 5.9; 95% CI, 2.3-15.4; P < .001). Readiness to quit within 1 month did not statistically significantly modify the intervention’s effect on abstinence. The intervention group did not have significantly greater weight gain than the control group (mean weight change difference, 1.6 kg; 95% CI, -1.5 to 4.7 kg).

CONCLUSIONS AND RELEVANCE: Findings of this randomized clinical trial showed that in persons with serious mental illness who are interested in quitting smoking within 6 months, an 18-month intervention with first-line pharmacotherapy and tailored behavioral support for smoking cessation and weight management increased tobacco abstinence without significant weight gain.

TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT02424188.

PMID:37378972 | DOI:10.1001/jamapsychiatry.2023.1691