Conducting biomedical research using smartphones is a novel approach to studying health and disease that is only beginning to be meaningfully explored. Gathering large-scale, real-world data to track ...disease manifestation and long-term trajectory in this manner is quite practical and largely untapped. Researchers can assess large study cohorts using surveys and sensor-based activities that can be interspersed with participants' daily routines. In addition, this approach offers a medium for researchers to collect contextual and environmental data via device-based sensors, data aggregator frameworks, and connected wearable devices. The main aim of the SleepHealth Mobile App Study (SHMAS) was to gain a better understanding of the relationship between sleep habits and daytime functioning utilizing a novel digital health approach. Secondary goals included assessing the feasibility of a fully-remote approach to obtaining clinical characteristics of participants, evaluating data validity, and examining user retention patterns and data-sharing preferences. Here, we provide a description of data collected from 7,250 participants living in the United States who chose to share their data broadly with the study team and qualified researchers worldwide.
Background: Clinicians and patients now have a broad variety of antidepressants to choose from, due to an ever-growing pharmacopoeia. However, one of the most significant considerations preventing ...antidepressant use is their side effects, one of which is sexual dysfunction. This issue has a negative impact on the patient’s quality of life which can contribute to clinical non-adherence in long-term therapies.
Aims and Objectives: The objective of this research was to look into the characteristics of sexual dysfunction in married female antidepressant patients and patterns of sexual dysfunctions in female patients receiving antidepressants.
Materials and Methods: It was Cross-sectional observational study. The study was conducted in the department of Psychiatry, Patna Medical College and Hospital at Patna.The Departmental Research Committee accepted the report, and 50 patients were enrolled after receiving written informed consent. Purposive sampling was used to pick the sample for the analysis, which had a cross-sectional study. The women contacted were in the outpatient psychiatric care of the department of Psychiatry and had been diagnosed with depressive disorder during the study period June 2018 to February 2019.
Results: Seventy percent of patients were taking selective serotonin reuptake inhibitors (SSRIs), 20 % were taking tricyclic antidepressants (TCAs), and 10 % were taking other medications such as mirtazapine or desvenlafexine. Within six months, 44 % of patients were on therapy, and 22.0 % had been on treatment for more than two years. Patients taking Escitalopram (80 %) have less sexual activity than those taking Sertraline (66.7 %) or Fluoxetine (77.8 %), Patients observed a change in sexual activity in 58 percent of cases, a decrease in sexual desire in 70 % of cases (p=0.0009*), a slight decrease in 14 percent of cases, and a slight decrease in only 8 % of cases (p=0.0009). 18 % of patients reported a delay in orgasm, with 66 percent reporting a major delay, 8 % reporting a moderate delay, and 8 % reporting a slight delay (p=0.0001).
Conclusion: Our findings indicate that sexual dysfunction is common in married female patients taking antidepressants, and that antidepressants affect both aspects of sexual functioning.
Background: The link between hazardous types of illegal drug use and significant public health issues is a critical issue for national and international drug policy. There are several negative health ...effects connected with drug use, with the avoidance of both overdosefatalities and drug-related blood-borne diseases being of special importance. However, there has been an increasing understanding in recent decades that the existence of mental illnesses connected with drug use poses a significant barrier for public health interventions.
Aims and Objectives: • To investigate the trend of drug misuse in North Bihar Patients. • To determine the co-morbid & psychiatric medical illnesses.
Materials and Methods: It was a cross-sectional research conducted over a one-year period on 200 drug abusers from North Bihar and presenting at Patna Medical College in the Indian state of Bihar. Individuals from the sample were separated into two groups based on their age (<25 Years & >25 years) and gender. The pattern of drug abuse, as well as the mental and medical co-morbidities that were linked with it, were investigated in relation to age and gender.
Results: The sample size of the present study was 200 consisting of 183 males and 17 females. The total sample was analyzed separately with respect to age and sex. There were 55 patients below 25 years and 128 patients’ ≥ 25 years. The study found that 91.5% of substance abusers were males. Among the males, 48.6% were abusing alcohol and 19.1% were abusing polysubstance. 18.6% were intravenous drug abusers and 8.2% showed high risk behavior. Among the females, 29.4% of the female patients were abusing alcohol. The percentage of women abusing poly-substance was 35.3% and poly-substance and alcohol was 17.6%. The number of female patients involved in high-risk behavior was only 11.8%. Intravenous drug abuse and high-risk behavior was commoner in age group < 25 years than in the age group of >25 years. 17.5% received a psychiatric co-morbid diagnosis and 38.5% received a medical co-morbid diagnosis. The prevalence of schizophrenia and depression among male patients with mental co-morbidity was 63.3 % (n=19), with depression accounting for 6.7 % (n=2). On the other hand, only five female patients, were found to have mental co-morbidity.
Conclusion: The large number of young individuals taking intravenous drugs in north Bihar reflects the high level of human-to-human contact with bordering North-Eastern states and Nepal. The situation is critical, and immediate action is required.
Background: Breast cancer related Lymphedema (BCRL) in the respective arm is a common but serious negative sequel of breast cancer management. Risk factors include dissection of Axillary lymph nodes ...and irradiation of Regional lymph nodes. Nearly 20% of patients receiving treatment of breast cancer develop this complication and it has a negative impact on quality of life of the patient. Objective: Current study aims to equip the medical professionals with all the details needed for prevention, early detection, intervention and management of this hazardous late treatment related complication. Material and Methods: Total 350 breast cancer patients (with their consent) treated at Government Cancer Hospital, Indore in the Radiotherapy and Oncology Department, in period from January 2019till December 2021, with chest wall radiotherapy following subsequent hormonal therapy, as needed. Patients then analysed for occurrence of lymphedema. Subsequently, efforts were given for finding out the correlation between lymphedema and related treatment modality like adjuvant radiotherapy following definitive surgery with number of excised lymph nodes and number of involved lymph nodes, chemotherapy, hormonal therapy, subjective co-morbid condition (obesity, diabetes mellitus and high blood pressure). Results: Current study demonstrate a significant correlation of adjuvant radiotherapy, including progressive involvement of the lymph node stations, with radical or conservative breast surgery with lymph node dissection represents a statistically significant risk factor, with relative risk, RR=1.49 (95% CI=0.72–3.05), p<0.001. Subsequent increase in number of dissected lymph nodes shown a risk factor with statistical significance as relative risk for more than 25 removed lymph nodes, demonstrated significant risk of lymphedema than for 16-25 removed lymph nodes. Other analysed risk factors, which did not influence lymphedema development like, associated chemotherapy, hormonal therapy or presence of co-morbid illnesses. Conclusions: Arm lymphedema is a late sequel associated with carcinoma breast treatment using radiation or surgery, and quite capricious occurrence that can happen years after axillary clearance surgery. With the use of sentinel node sampling, could reduce the need of frank axillary clearance by showing either involvement of lymph node in axilla, so as to manage only by radiotherapy. That significantly reduces the risk of lymphedema from 16% with axillary clearance to 5% without dissection. Keywords: Lymphedema, Breast cancer, Risk factors, Axillary lymph node
Background: In India, women are twice more likely to become caregivers than men. The quality of life (QOL) is the ability level to which an individual is healthy and able to enjoy life.
Aims and ...Objective: To assess and compare QOL among homemaker women and working women giving care to patients suffering from psychiatric illnesses.
Materials and Methods: This hospital-based, cross-sectional study was conducted on the caregivers who were recruited from out-door patient department of Psychiatry department of Patna Medical College and Hospital, Patna from January 1, 2021, to June 31, 2021. Women who were 30–55 years old, working or homemakers, and who were taking care of psychiatric patients diagnosed with Schizophrenia and Bipolar affective disorder of either sex. Caregivers were first degree relatives of patients. The estimated sample size was 140 (Group 1=70 homemaker women and Group 2=70 working women). Sociodemographic data were recorded using Sociodemographic Performa 1 and QOL was assessed using World Health Organization (WHO)-QoL-BREF.
Results: WHO-QOL domain mean score for physical, psychological, social, and environmental of Group 1 was 12.42, 11.60, 12.24, 12.62 whereas 14.46, 13.28, 11.28, and 12.28 of Group 2 with statistically significant difference (P<0.05).
Conclusion: In physical and psychological domain of QoL, working women scores were better than homemakers. QOL in working women caregivers was better than homemakers’ caregivers in social and environmental domains but statistically non-significant.
Suboptimal adherence to data collection procedures or a study intervention is often the cause of a failed clinical trial. Data from connected sensors, including wearables, referred to here as ...biometric monitoring technologies (BioMeTs), are capable of capturing adherence to both digital therapeutics and digital data collection procedures, thereby providing the opportunity to identify the determinants of adherence and thereafter, methods to maximize adherence.
We aim to describe the methods and definitions by which adherence has been captured and reported using BioMeTs in recent years. Identifying key gaps allowed us to make recommendations regarding minimum reporting requirements and consistency of definitions for BioMeT-based adherence data.
We conducted a systematic review of studies published between 2014 and 2019, which deployed a BioMeT outside the clinical or laboratory setting for which a quantitative, nonsurrogate, sensor-based measurement of adherence was reported. After systematically screening the manuscripts for eligibility, we extracted details regarding study design, participants, the BioMeT or BioMeTs used, and the definition and units of adherence. The primary definitions of adherence were categorized as a continuous variable based on duration (highest resolution), a continuous variable based on the number of measurements completed, or a categorical variable (lowest resolution).
Our PubMed search terms identified 940 manuscripts; 100 (10.6%) met our eligibility criteria and contained descriptions of 110 BioMeTs. During literature screening, we found that 30% (53/177) of the studies that used a BioMeT outside of the clinical or laboratory setting failed to report a sensor-based, nonsurrogate, quantitative measurement of adherence. We identified 37 unique definitions of adherence reported for the 110 BioMeTs and observed that uniformity of adherence definitions was associated with the resolution of the data reported. When adherence was reported as a continuous time-based variable, the same definition of adherence was adopted for 92% (46/50) of the tools. However, when adherence data were simplified to a categorical variable, we observed 25 unique definitions of adherence reported for 37 tools.
We recommend that quantitative, nonsurrogate, sensor-based adherence data be reported for all BioMeTs when feasible; a clear description of the sensor or sensors used to capture adherence data, the algorithm or algorithms that convert sample-level measurements to a metric of adherence, and the analytic validation data demonstrating that BioMeT-generated adherence is an accurate and reliable measurement of actual use be provided when available; and primary adherence data be reported as a continuous variable followed by categorical definitions if needed, and that the categories adopted are supported by clinical validation data and/or consistent with previous reports.
Abstract
Most people with mental health disorders cannot receive timely and evidence-based care despite billions of dollars spent by healthcare systems. Researchers have been exploring using digital ...health technologies to measure behavior in real-world settings with mixed results. There is a need to create accessible and computable digital mental health datasets to advance inclusive and transparently validated research for creating robust real-world digital biomarkers of mental health. Here we share and describe one of the largest and most diverse real-world behavior datasets from over two thousand individuals across the US. The data were generated as part of the two NIMH-funded randomized clinical trials conducted to assess the effectiveness of delivering mental health care continuously remotely. The longitudinal dataset consists of self-assessment of mood, depression, anxiety, and passively gathered phone-based behavioral data streams in real-world settings. This dataset will provide a timely and long-term data resource to evaluate analytical approaches for developing digital behavioral markers and understand the effectiveness of mental health care delivered continuously and remotely.
In this paper, a new socially assistive robot (SARs) called HBS-1.2 is presented, which uses 6-ply twisted and coiled polymer (TCP) artificial muscles in its hand to perform physical tasks. The ...utilization of 6-ply TCP artificial muscles in a humanoid robot hand is a pioneering advancement, offering cost effective, lightweight, and compact solution for SARs. The robot is designed to provide safer human–robot interaction (HRI) while performing physical tasks. The paper explains the procedures for fabrication and testing of the 6-ply TCP artificial muscles, along with improving the actuation response by using a Proportional-Integral-Derivative (PID) control method. Notably, the robot successfully performed a vision-based pick and place experiment, showing its potential for use in homecare and other settings to assist patients who suffer from neurological diseases like Alzheimer’s disease. The study also found an optimal light intensity range between 34 to 108 lumens/m2, which ensures minimal variation in calculated distance with 95% confidence intervals for robust performance from the vison system. The findings of this study have important implications for the development of affordable and accessible robotic systems to support elderly patients with dementia, and future research should focus on further improving the use of TCP actuators in robotics.
Smartphones are increasingly used in health research. They provide a continuous connection between participants and researchers to monitor long-term health trajectories of large populations at a ...fraction of the cost of traditional research studies. However, despite the potential of using smartphones in remote research, there is an urgent need to develop effective strategies to reach, recruit, and retain the target populations in a representative and equitable manner.
We aimed to investigate the impact of combining different recruitment and incentive distribution approaches used in remote research on cohort characteristics and long-term retention. The real-world factors significantly impacting active and passive data collection were also evaluated.
We conducted a secondary data analysis of participant recruitment and retention using data from a large remote observation study aimed at understanding real-world factors linked to cold, influenza, and the impact of traumatic brain injury on daily functioning. We conducted recruitment in 2 phases between March 15, 2020, and January 4, 2022. Over 10,000 smartphone owners in the United States were recruited to provide 12 weeks of daily surveys and smartphone-based passive-sensing data. Using multivariate statistics, we investigated the potential impact of different recruitment and incentive distribution approaches on cohort characteristics. Survival analysis was used to assess the effects of sociodemographic characteristics on participant retention across the 2 recruitment phases. Associations between passive data-sharing patterns and demographic characteristics of the cohort were evaluated using logistic regression.
We analyzed over 330,000 days of engagement data collected from 10,000 participants. Our key findings are as follows: first, the overall characteristics of participants recruited using digital advertisements on social media and news media differed significantly from those of participants recruited using crowdsourcing platforms (Prolific and Amazon Mechanical Turk; P<.001). Second, participant retention in the study varied significantly across study phases, recruitment sources, and socioeconomic and demographic factors (P<.001). Third, notable differences in passive data collection were associated with device type (Android vs iOS) and participants' sociodemographic characteristics. Black or African American participants were significantly less likely to share passive sensor data streams than non-Hispanic White participants (odds ratio 0.44-0.49, 95% CI 0.35-0.61; P<.001). Fourth, participants were more likely to adhere to baseline surveys if the surveys were administered immediately after enrollment. Fifth, technical glitches could significantly impact real-world data collection in remote settings, which can severely impact generation of reliable evidence.
Our findings highlight several factors, such as recruitment platforms, incentive distribution frequency, the timing of baseline surveys, device heterogeneity, and technical glitches in data collection infrastructure, that could impact remote long-term data collection. Combined together, these empirical findings could help inform best practices for monitoring anomalies during real-world data collection and for recruiting and retaining target populations in a representative and equitable manner.
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