C: NA
Note. T: experimental group; C: control group; NA: unavailable; Freq: frequency; LoI: length of intervention; SAD: social anxiety disorder; SMI: serious mental illness; PTSD: post-traumatic stress disorder; ND: neurodevelopmental disorders; ADHD: attention-deficit/hyperactivity disorder; ASD: autism spectrum disorder; MDD: major depressive disorders. QLS: Quality of Life Scale; QLESS: Quality of Life Enjoyment and Satisfaction Scale; ADLS: Activity of Daily Living Scale; SLS: Satisfaction with Life Scale; PWS: Psychological Well-being Scale; MMSE: Mini-mental State Examination; BPRS: Brief Psychiatric Rating Scale; CSDD: Cornell Scale for Depression in Dementia; BDI: Beck Depression Inventory; GDS: Geriatric Depression Scale; PSS: Perceived Stress Scale; CDS: Calgary Depression Scale; SCAS: Spence Children’s Anxiety Scale; BAI: Beck Anxiety Inventory; LSAS: Liebowitz Social Anxiety Scale; CTQ: Childhood Trauma Questionnaire; SPSS: Severity of PTSD Symptoms Scale; PCL: PTSD Checklist; CBCL: Child Behaviour Checklist; WISC: Wechsler Intelligence Scale for Children; EMI: Ricketts’ Engagement, Maturity, and Innovativeness; SAI-R: Revised Spontaneity Assessment Inventory; CSCR: Child’s Skill Scale Rating; BRIEF-A: Behaviour Rating Inventory of Executive Function-Adult version; CBCL: Child Behaviour Checklist; QCST: Queendom Communication Skills Test; CSI: Communication Skills Inventory; BPSEIH: Bio-psycho-social Expressions of Incompatibility in Hospital; PACS: Parent-adolescent Communication Scale; SCS: Self-Compassion Scale; SEC: Self-esteem Scale; GSES: General Self-efficacy Scale; BAS: Body Appreciation Scale.
Sample sizes ranged from 5 to 114 participants, with age (mean + SD) ranging from 7.08 (1.53) to 82.62 (7.92); the majority of participants were female. Participants with trauma-related depression were included in five studies. Caregivers of children with neurodevelopmental disorders, cerebral palsy, or who were at risk were included in three studies. Two studies on children with attention-deficit/hyperactivity disorder have been conducted. Other studies included participants with social anxiety disorder, community-dwelling, epilepsy, chronic schizophrenia, hearing-impaired adolescents, and dementia patients.
The primary interventions included were psychodrama (12 studies) and drama therapy (4 studies). Other interventions, such as theatre performance, playback theatre, sociodrama, and theatre of the oppressed, were included. The majority of sessions were conducted once per week over 6–24 weeks, with durations of 1.5–2.5 h. In studies involving older and younger participants, however, shorter time periods (40–60 min) were allocated. In addition, a six-month study was conducted every two months for a duration of four days. Most of the interventions were conducted by occupational therapists, whereas instructors for the inpatient programme were clinical psychiatrists or specialists.
The outcome measures consisted of eight mental-health-related components that were administered as follows: quality of life in nine comparisons, psychological well-being in five comparisons, depression in seven comparisons, anxiety in three comparisons, trauma-related disorders in seven comparisons, cognitive functioning in four comparisons, communication skill in four comparisons, and self-regard in five comparisons. Regarding study design, twelve studies were accurately described as controlled trials, including five randomised controlled trials (RCTs), while thirteen were experimental studies with pre- and post-test groups.
Risks of bias were judged based on the Cochrane guidance. Regarding random sequence generation, four studies were deemed high-risk due to the absence of randomization procedures [ 50 , 52 , 65 , 70 ]. In terms of allocation concealment, three studies were judged high-risk reported no use of concealment in the allocation procedure [ 65 , 66 , 70 ]. Two studies [ 52 , 66 ] were evaluated as high risk regarding participants and personnel blinding. Meanwhile, the lack of blinding in outcome assessment led to a high risk classification for one study [ 50 ]. Except for four studies where the information was not reported [ 51 , 60 , 62 , 64 ], all studies were evaluated as low risk for incomplete outcome data due to the low dropout rate throughout the intervention. Regarding selective reporting, seventeen studies were rated as low risk, and the remaining eight studies were judged to be unclear. Concerning other biases, three studies did not identify the conflict of interest [ 56 , 58 , 72 ], one reported the author received research honoraria [ 52 ], and one indicated the authors were on the board of an entity supporting the research [ 69 ]. Figure 2 and Figure 3 display specific features.
Risk of bias graph for included studies.
Risk of bias summary for each included study [ 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 , 67 , 68 , 69 , 70 , 71 , 72 , 73 , 74 ].
All effects and heterogeneities for quality of life, psychological well-being, depression, anxiety, trauma-related disorders, communication skills, cognitive functioning, and self-regard were tested. The results are presented in Table 3 .
Effects and heterogeneity for comparisons between studies.
Effects | Heterogeneity | |||||
---|---|---|---|---|---|---|
Outcome | Study Design | SAMPLE SIZE | SMD (IV, Random, 95%CI) | I (%) | ||
Quality of life | Controlled group ( = 4) | 139 | 2.08 [−0.33, 4.49] | 0.09 | 96 | <0.00001 |
Pre/posttest group ( = 5) | 74 | 0.86 [0.06, 1.67] | 0.04 | 79 | 0.0002 | |
Total ( = 9) | 213 | 1.26 [0.33, 2.20] | 0.008 | 91 | <0.00001 | |
Psychological well-being | Controlled group ( = 4) | 202 | 1.69 [−0.45, 3.83] | 0.12 | 97 | <0.00001 |
Pre/posttest group ( = 1) | 6 | 0.46 [−0.69, 1.62] | 0.43 | - | - | |
Total ( = 5) | 208 | 1.40 [−0.32, 3.12] | 0.11 | 96 | <0.00001 | |
Depression | Controlled group ( = 3) | 166 | 1.17 [−0.35, 2.70] | 0.13 | 95 | <0.00001 |
Pre/posttest group ( = 4) | 59 | 0.42 [0.05, 0.78] | 0.03 | 0 | 0.82 | |
Total ( = 7) | 225 | 0.70 [−0.03, 1.42] | 0.03 | 85 | <0.00001 | |
Anxiety | Controlled group ( = 2) | 94 | 0.88 [−0.82, 2.58] | 0.31 | 93 | 0.0002 |
Pre/posttest group ( = 1) | 5 | 1.74 [0.16, 3.32] | 0.03 | - | - | |
Total ( = 3) | 99 | 1.10 [−0.24, 2.45] | 0.11 | 87 | 0.0004 | |
Trauma-related disorders | Controlled group ( = 1) | 46 | 0.14 [−0.46, 0.74] | 0.65 | - | - |
Pre/posttest group ( = 3) | 123 | 0.90 [0.52, 1.28] | <0.00001 | 36 | 0.21 | |
Total ( = 4) | 169 | 0.70 [0.23, 1.17] | 0.003 | 66 | 0.03 | |
Communication skills | Controlled group ( = 3) | 86 | 1.11 [−0.68, 2.90] | 0.22 | 92 | <0.00001 |
Pre/posttest group ( = 1) | 5 | 4.98 [1.91, 8.04] | 0.001 | - | - | |
Total ( = 4) | 91 | 1.76 [−0.06, 3.57] | 0.06 | 91 | <0.00001 | |
Cognitive functioning | Controlled group ( = 3) | 123 | 1.58 [0.62, 2.54] | 0.001 | 81 | <0.00001 |
Pre/posttest group ( = 4) | 66 | 3.47 [−1.02, 7.97] | 0.13 | 98 | 0.006 | |
Total ( = 7) | 189 | 2.50 [0.77, 4.23] | 0.005 | 96 | <0.00001 | |
Self-regard | Controlled group ( = 2) | 92 | 2.83 [−0.90, 6.56] | 0.14 | 96 | <0.00001 |
Pre/posttest group ( = 3) | 123 | 0.39 [0.14, 0.65] | 0.002 | 0 | 0.83 | |
Total ( = 5) | 215 | 1.40 [−0.06, 2.86] | 0.06 | 95 | <0.00001 |
A total of nine studies involving 213 participants provided the results of the meta-analysis regarding quality of life. On the basis of comparisons, significant difference in the use of drama-based intervention on quality of life was observed, with a considerable impact size (SMD = 1.26, 95% CI = 0.33 to 2.20, p = 0.008). However, the level of heterogeneity was substantial (I 2 = 91).
Psychological well-being was measured in five investigations with a total of 208 individuals. There was no statistically significant difference, and great heterogeneity (I 2 = 96) was displayed amongst studies. The effect size of the drama-based intervention was deemed to be substantial (SMD = 1.40, 95% CI −0.32 to 3.12, p = 0.11).
In seven investigations with 225 participants, the effect of a drama-based intervention for depression was evaluated. In the comparison of three controlled trials and four pre/post-test studies, significant differences were shown in favour of drama-based intervention in depression assessments (SMD = 0.70, 95% CI −0.03 to 1.42, p = 0.03). The I 2 value in this meta-analysis, however, was high (I 2 = 85).
Assessments of anxiety were included in three studies with a total sample size of 99. There were two controlled trials and one pre/post-test study in the comparison, revealing positive effect of drama-based intervention on anxiety but no statistically significant difference (SMD = 1.10, 95% CI −0.24 to 2.45, p = 0.11), with a high degree of heterogeneity (I 2 = 87) across studies.
To evaluate trauma-related disorders, four studies with 169 people were analysed. The comparison included one controlled trial and three pre/post-test investigations. Meta-analysis revealed a positive effect of drama-based intervention on trauma-related disorders (SMD = 0.70, 95% CI 0.23 to 1.17, p = 0.003), with a substantial heterogeneity (I 2 = 66).
In four trials with a total of 86 participants, communication skills were assessed. The comparison included three controlled trials and one pre/post-test study. Meta-analysis found that drama-based intervention had a great impact on enhancing communication skills (SMD = 1.76, 95% CI −0.06 to 3.57), while there was no statistically significant difference ( p = 0.06), and the I 2 value was high (I 2 = 91).
Seven studies with 189 participants were used to measure cognitive functioning. There were three controlled trials and four pre/post-test studies in the comparison. Studies applying drama-based intervention on cognitive performance found the large impact size, with statistically significant difference (SMD = 2.50, 95% CI 0.77 to 4.23, p = 0.005). However, the level of heterogeneity was substantial in this meta-analysis (I 2 = 96).
Self-regard was measured using data from five studies with 215 participants. In the comparison, there were two controlled trials and three pre/post-test investigations. Meta-analysis revealed that drama-based intervention had no statistically significant effect on self-esteem (SMD = 1.40, 95% CI −0.06 to 2.86, p = 0.06), and the I 2 value was high (I 2 = 95).
Drama-based intervention had a positive effect with controlled groups on cognitive functioning (SMD = 1.58, 95% CI 0.62 to 2.54, p = 0.001). No statistically significant difference was observed between controlled groups on quality of life (SMD = 2.08, 95% CI −0.33 to 4.49, p = 0.09), psychological well-being (SMD = 1.69, 95% CI −0.45 to 3.83, p = 0.12), depression (SMD = 1.77, 95% CI −0.35 to 2.70, p = 0.13), trauma-related disorders (SMD = 0.14, 95% CI −0.46 to 0.74, p = 0.65), anxiety (SMD = 0.88, 95% CI −0.82 to 2.58, p = 0.31), communication skills (SMD = 1.11, 95% CI −0.68 to 2.90, p = 0.06), and self-regard (SMD = 2.83, 95% CI −0.90 to 6.56, p = 0.14). The largest positive effect size was self-regard, followed by quality of life, psychological well-being, depression, communication skills, cognitive functioning, anxiety, and trauma-related disorders. See Figure 4 .
Overall effectiveness of drama-based intervention with controlled groups.
Drama-based intervention with pre/post-test groups was effective to reduce depression (SMD = 0.42, 95% CI 0.05 to 0.78, p = 0.03), anxiety (SMD = 1.74, 95% CI 0.16 to 3.32, p = 0.03), and trauma-related disorder (SMD = 0.90, 95% CI 0.52 to 1.28, p < 0.0001). It is also effective to improve quality of life (SMD = 0.86, 95% CI 0.06 to 1.67, p = 0.04), communication skills (SMD = 4.98, 95% CI 1.91 to 8.04, p = 0.001), and self-regard (SMD = 0.39, 95% CI 0.14 to 0.65, p = 0.002). No statistically significant difference was observed between pre/post-test groups on psychological well-being (SMD = 0.46, 95% CI −0.69 to 1.62, p = 0.43) and cognitive functioning (SMD = 3.47, 95% CI −1.02 to 7.97, p = 0.13). The largest effect size was communication skills, followed by cognitive functioning, anxiety, trauma-related disorder, quality of life, psychological well-being, depression and self-regard. See Figure 5 .
Overall effectiveness of drama-based intervention with pre/post-test groups.
The symmetry of the funnel plot was utilised to determine the publication bias of the meta-analysis results [ 75 ].The funnel plot of standard errors by SMD was assessed according to its symmetry, and the results are presented in Figure 6 . The dotted line on each side of the figure represent the 95% confidence intervals. The middle line represents the effect of the meta-analysis as a whole. No apparent publication bias among the studies on quality of life, depression, anxiety, psychological well-being, cognitive functioning, trauma-related disorder, communication skills, and self-regard was observed, as indicated by visual observation of the funnel plots.
Funnel plots for visual assessment of the presence of publication bias.
This systematic review and meta-analysis evaluated studies that employed drama-based interventions to promote mental health and well-being in the COVID-19 and post-pandemic periods. A total of 25 studies representing 797 participants were identified. Overall, drama-based interventions were shown to have the most consistent favourable effect on trauma-related disorders, cognitive functioning, quality of life, and depression. Moreover, the study found that drama may be considerably beneficial but not significant in increasing psychological well-being and communication skills. Regarding the duration of drama-based intervention, except for two studies that employed 64 [ 55 ] and 72 weeks [ 56 ], the majority of the publications indicated that drama as a supplemental treatment was viable and acceptable with durations of 8–12 weeks.
In terms of forms and techniques of drama-based intervention, psychodrama (12 studies) and drama therapy (4 studies) were the most prevalent ones included. Other forms like theatre performance, playback theatre, theatre of the oppressed, and sociodrama were also included. The included studies found that the psychodrama had a statistically significant beneficial effect on lowering anxiety levels [ 50 , 62 , 74 ] and enhancing communication skills [ 51 , 64 ]. The playback theatre had the greatest effect on psychological well-being [ 58 ]. In addition, drama therapy was more effective than other cognitive functioning programmes applied in selected studies [ 54 , 61 ]. Furthermore, the findings revealed a positive psychological effect of organised short-term playback theatre involvement in community-dwelling older persons, indicating that the community drama may provide the elderly with an opportunity to enhance their existing well-being [ 58 ].
Initial results from the meta-analysis showed that drama-based interventions were effective in reducing symptoms of trauma-related disorders, according to the outcomes of four included studies. This is consistent with the finding of Yu et al. [ 74 ], who discovered that antidepressants combined with psychodrama were more effective at enhancing the coping style of patients with childhood traumatic depression than combined with a general health education intervention, thus providing a new clinical intervention option. In addition, Miguel and Pino-Juste [ 63 ] demonstrated that the psychodrama method (warming-up, action, and sharing) had a positive effect on domestic violence victims. Other two included studies added to the evidence that psychodrama is beneficial for reducing PTSD in inpatient substance abuse treatment patients [ 55 , 56 ]. It might be due to the fact that drama is more likely to assist individuals in expressing their difficulties, discovering their conflicts, and then confronting them [ 76 , 77 ]. The advantages were underlined in this review.
Meanwhile, the meta-analysis of seven studies discovered a statistically significant and favourable effect of drama-based interventions on cognitive functioning. For instance, the psychodrama technique may assist youngsters with attention deficit/hyperactivity disorder (ADHD) to reduce their aggressive behaviour and concentration difficulties [ 62 ]. Furthermore, drama therapy can be utilised as an effective intervention to lower the expenses of ADHD treatment, particularly for strengthening working memory in adolescents with ADHD [ 59 ]. Using a dramatic diary and monologue, cognitive-behavioral psychodrama group therapy promoted critical thinking and decreased defensiveness in inadequately guarded male adolescents [ 53 ]. This may be because of the way that drama encourages individuals to express repressed tensions and emotions in a safe environment by fostering spontaneity, inventiveness, and rational reasoning [ 54 , 78 ].
Moreover, nine studies included in the review demonstrated that drama-based intervention improved the quality of life. According with the findings of meta-analysis, the results of Vlotinou et al. [ 73 ] implied that drama activities (e.g., emotional expression, role-playing) may improve life quality of people with epilepsy by addressing their fear and loss of control. Besides, Simsek et al. [ 68 ] showed that quality of life of caregivers of children with cerebral palsy can be enhanced by increasing hope and self-confidence through warm-up, action, and sharing stages in psychodrama. Further research added to the findings that drama intervention fostered more favourable views towards the illness and social environment by gaining empathy and allowing participants to perceive themselves in diverse roles [ 63 , 67 ].
Additionally, the review confirmed the significance of drama-based intervention in the treatment of depression. In a meta-analysis, the statistical significance of seven investigations was determined. For instance, the included study by Sevi et al. [ 67 ] indicated that psychodrama sessions (e.g., dramatic games) helped alleviate depressive symptoms in patients with chronic schizophrenia by boosting sharing, group interaction, and a sense of belonging. Besides, the finding of Keisari et al. [ 58 ] showed that playback theatre, which integrates dramatic expression with the exploration of life stories in a group creative process, had a positive psychological effect in community-dwelling older adults with depressive psychological distress. Several studies have added to the evidence that drama improves mental health and reduces depressive symptoms through self-reflection and personal development. The drama programme provided therapeutic benefit and acted as a vehicle for the participants’ positive transformation [ 50 , 52 , 60 ].
It is also noted that the results suggested that drama-based intervention was beneficial but not statistically significant for enhancing psychological well-being. For example, a psychodrama programme improved the psychological balance of adolescents who had experienced a traumatic incident; the correlations showed increased psychological progress [ 71 ]. Furthermore, the results may point to the potential role of drama-based intervention in improving communication skills. This is consistent with the findings of Jang et al. [ 57 ], who discovered that the sociodrama programme improved parent–child communication for mothers of children with neurodevelopmental disorders. In accordance with additional findings [ 51 , 64 , 65 ], participants gained abilities via interpersonal interactions in the dramatic activities.
The review consists of twelve controlled groups, including five randomised controlled trials (RCTs), and thirteen experimental studies with pre- and post-testing. Depression, anxiety, trauma-related disorder, quality of life, communication skills, and self-regard were all positively affected by a drama-based intervention supported by pre/post-testing, whereas the overall effect of intervention with controlled trials had only positive effects on cognitive functioning. The current findings revealed that controlled groups were insufficient to demonstrate the efficacy of drama interventions on mental health and well-being. It suggested that additional well-designed controlled trials comparing experimental and control groups are required to evaluate the impact of drama-based interventions. More RCTs, particularly those with high-quality designs, were also called to provide causal explanations for the difference between pre- and post-values.
Several studies included in this review suggested drama-based intervention was feasible to cope with the COVID-19 pandemic. Consistent with the findings, Giacomucci et al. [ 56 ] discovered that people with active trauma from COVID-19 who participated in drama sessions reported a reduction in depression and PTSD symptoms. Notably, the COVID-19 social distancing decreased social contact engagement and may be risk factors for isolation, anxiety, and depression [ 79 ]. A number of included studies have provided solutions that allowed social connectedness through drama activities and generated the stimulating senses of connection and empathy in others [ 52 , 58 , 67 ], thereby enabling individuals to address issues of shared concern and increased their ability to embrace challenge in the pandemic and post-pandemic period. During quarantine, Cheung et al. [ 52 ] provided people with severe mental illness with online drama intervention via Zoom, which was considered a feasible strategy in the setting of the epidemic. This study constructed a convincing case for the usefulness of drama intervention in the digital space and proposed a novel strategy for dealing with pandemic realities.
In this study, the techniques of systematic review and meta-analysis were used to analyse the effects of drama on mental health and well-being of various populations during the COVID-19 and post-pandemic eras. This is the first review and meta-analysis to critically examine the evidence for the use of drama in mental health care. The findings of the selected studies provided crucial evidence of the effectiveness of drama-based intervention on mental health issues. This original review on the treatment of drama throughout individuals who required mental health care by different drama programmes provided more recent and comprehensive evidence-based recommendations.
The limitations of the study should be acknowledged. First, the literature search was restricted to the publications of the COVID-19 and the post-pandemic period (from December 2019 to October 2022); thus, some theoretically significant earlier contributions may have been overlooked. The number of included papers was modest, and several of the studies had small sample sizes, which may have compromised the reliability of the meta-analytic conclusions. Besides, a stratified analysis was not possible due to the extensive range of participant characteristics. Moreover, several studies in the present evidence base were conducted in quasi-experiment groups, which were inadequate to advance knowledge of the effects of drama-based intervention. Furthermore, despite the researchers’ best attempts, heterogeneity between studies could not be avoided.
This review and meta-analysis concludes that drama has the potential to improve mental health (e.g., trauma-related disorders) and well-being (e.g., psychological well-being), positioning it as a supplement to mental health care during and after the COVID-19 pandemic. Drama-based intervention is increasingly offered in healthcare settings as part of a variety of complementary therapies. Future research may examine the effects of drama-based interventions on individuals with post-COVID-19 pandemic trauma to better comprehend the correlations between drama activity and therapeutic effect. To further understand how drama interventions may be utilised as psychological prescriptions, it is recommended that future study compare drama intervention to other therapeutic treatments and/or compare different forms of drama programme. Moreover, telehealth and other technological advances may help improve the efficacy of drama intervention, which might be studied in the future.
We thank all the reviewers for their assistance and support.
This research received no external funding.
Conceptualization, L.J. and F.A.; methodology, L.J.; software, W.C.; validation, L.J., F.A. and W.C.; formal analysis, L.J. and W.C.; investigation, F.A.; data curation, W.C.; writing—original draft preparation, L.J.; writing—review and editing, F.A.; visualization, W.C.; supervision, F.A.; project administration, F.A.; funding acquisition, F.A. All authors have read and agreed to the published version of the manuscript.
Ethical review and approval were waived for this study, as this study is a systematic review of previously published studies.
Patient consent was waived, as this study is a systematic review of previously published studies.
Conflicts of interest.
The authors declare no conflict of interest.
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Did you know the PC was invented at Washington University?
Well, not that PC. The Programmed Console.
In the spring of 1965, Jerome R. Cox Jr. and Wesley A. Clark co-taught a graduate course in computer design in which teams of students designed working computers. One student, V.W. “Bill” Gerth, also wrote an interactive radiation treatment planning program. A demonstration piqued the interest of the Division of Research Resources at the National Institutes of Health (NIH), which subsequently directed funding to the Biomedical Computer Laboratory (BCL), a division of the School of Medicine, to further develop the concept.
Cox—who had founded BCL the previous spring—and colleagues in the Mallinckrodt Institute of Radiology went to work. He called the redesigned computer the Programmed Console, or PC, reflecting the unique way that users could interact directly with stored programs at a display console. Software was designed to enable radiologists to calculate the optimal position and intensity of radiation beams to treat a tumor, while minimizing damage to surrounding, healthy tissue. And with NIH support, BCL initiated a Radiation Treatment Planning (RTP) Project that supplied PCs to teams from six different institutions to evaluate and refine their use in radiation therapy over the course of several years.
Documents about the PC are among the many materials found in the recently processed papers of Dr. Jerome “Jerry” R. Cox Jr. (1925-2023). Acquired by the Becker Archives in 2022, this rich collection provides a window into Cox’s nearly five-decade career at Washington University, documenting his path-breaking work in biomedical computing and computer science and revealing a dedicated researcher, teacher, and advocate whose influence and impact extended far beyond the classroom.
Images excerpted from a BCL brochure explaining the research and training activities available to graduate students, circa 1965 (FC157-S13-ss01-B077-F05, Bernard Becker Medical Library Archives, Washington University in St. Louis).
A significant portion of the collection pertains to Cox’s tenure as director of BCL (1964-1975), when he played a pivotal role in Washington University’s journey toward becoming a leader in the application of computers to biomedicine. Cox had first joined the university’s faculty as a part-time assistant professor of electrical engineering in 1955, after accepting a position at the nearby Central Institute for the Deaf (CID). He moved on from CID to found BCL in April 1964. That same year, the LINC development team at MIT found itself in need a new institutional home, and Cox was instrumental in making sure they had one at Washington University. The LINC , or Laboratory INstrument Computer, was a small-for-its-time, mobile, and interactive computer designed with lab-based research in mind. The LINC team relocated to St. Louis in June 1964 and continued their work in the newly formed Computer Research Laboratory (CRL), which shared space with BCL on the Medical Campus. In 1967, with funding from a major NIH grant titled “A Resource for Biomedical Computing,” the Washington University Computer Laboratories (WUCL) formed around BCL and CRL’s successor, the Computer Systems Laboratory (CSL). Cox chaired WUCL until the completion of the grant in 1983. “Few laboratories in the nation,” a summary report noted, “have had as deep an impact on the evolution of computers in medicine and medical research as CSL and BCL.”
Another substantial portion of the collection documents Cox’s roles as the first chair of the Department of Computer Science (1975-1991) and as director of the Applied Research Laboratory (1991-1995). Much like his contributions to biomedical computing, Cox’s work on computer networking and the high-speed transmission of medical images during this time helped Washington University become a leader in those fields. It also prompted Cox to co-found Growth Networks Inc. in 1997, an effort to commercialize university-developed fast-packet chipset technology. Cisco Systems later acquired the successful company in 2000. Cox’s business ventures continued in 2007, when he founded Blendics, derived from Blended Integrated Circuit Systems. Blendics led to a cybersecurity spin-off, Q-Net Security Inc., in 2015. The collection contains a moderate amount of materials related to Cox’s entrepreneurial endeavors.
Cox’s writings and professional activities are also well-represented. In addition to manuscripts and drafts, the collection contains reprints of many of his published journal articles. Prominent among Cox’s professional activities was his role as co-founder and co-chair of Computers in Cardiology. The annual international conference brought together researchers applying computers to electrocardiography. Organizers also made sure attendees had a chance to explore the host cities. When Washington University hosted the gathering in 1976, the social calendar included a visit to the Missouri Botanical Gardens, a riverboat cruise, and a rooftop reception at the Chase Park Plaza Hotel. Cox served as co-chair until 1988, and the conference, now known as Computing in Cardiology , continues to be held today.
The Cox papers are open and accessible for research. In addition to the materials mentioned here, researchers can find administrative documents, correspondence, grant applications, research notes, patents, photographs, and more pertaining to his extensive work in auditory physiology, ECG analysis and processing, CT and PET scanning technologies, DNA mapping, information systems and database technologies, electronic radiology, digital communication networks, and asynchronous computing. The collection also contains a modest number of materials related to Cox’s personal life.
Certificate for U.S. Patent No. 3,217,321, Collision Avoidance System, November 9, 1965 (FC157-S06-B017-F10, Bernard Becker Medical Library Archives, Washington University in St. Louis). Cox’s work also led to patents related to tomography systems, video with high speed reconstruction and display of compressed images, and asynchronous computing.
Tampons from several brands that potentially millions of people use each month can contain toxic metals like lead, arsenic, and cadmium, a new study led by a UC Berkeley researcher has found.
Tampons are of particular concern as a potential source of exposure to chemicals, including metals, because the skin of the vagina has a higher potential for chemical absorption than skin elsewhere on the body. In addition, the products are used by a large percentage of the population on a monthly basis—50–80% of those who menstruate use tampons—for several hours at a time.
“Despite this large potential for public health concern, very little research has been done to measure chemicals in tampons,” said lead author Jenni A. Shearston , a postdoctoral scholar at the UC Berkeley School of Public Health and UC Berkeley’s Department of Environmental Science, Policy, & Management. “To our knowledge, this is the first paper to measure metals in tampons. Concerningly, we found concentrations of all metals we tested for, including toxic metals like arsenic and lead.”
Metals have been found to increase the risk of dementia, infertility, diabetes, and cancer. They can damage the liver, kidneys, and brain, as well as the cardiovascular, nervous, and endocrine systems. In addition, metals can harm maternal health and fetal development.
“Although toxic metals are ubiquitous and we are exposed to low levels at any given time, our study clearly shows that metals are also present in menstrual products, and that women might be at higher risk for exposure using these products,” said study co-author Kathrin Schilling , assistant professor at Columbia University Mailman School of Public Health.
Researchers evaluated levels of 16 metals (arsenic, barium, calcium, cadmium, cobalt, chromium, copper, iron, manganese, mercury, nickel, lead, selenium, strontium, vanadium, and zinc) in 30 tampons from 14 different brands. The metal concentrations varied by where the tampons were purchased (US vs. EU/UK), organic vs. non-organic, and store- vs. name-brand. However, they found that metals were present in all types of tampons; no category had consistently lower concentrations of all or most metals. Lead concentrations were higher in non-organic tampons but arsenic was higher in organic tampons.
Metals could make their way into tampons a number of ways: The cotton material could have absorbed the metals from water, air, soil, through a nearby contaminant (for example, if a cotton field was near a lead smelter), or some might be added intentionally during manufacturing as part of a pigment, whitener, antibacterial agent, or some other process in the factory producing the products.
“I really hope that manufacturers are required to test their products for metals, especially for toxic metals,” said Shearston. “It would be exciting to see the public call for this, or to ask for better labeling on tampons and other menstrual products.”
For the moment, it’s unclear if the metals detected by this study are contributing to any negative health effects. Future research will test how much of these metals can leach out of the tampons and be absorbed by the body; as well as measuring the presence of other chemicals in tampons.
Additional authors include: Kristen Upson of the College of Human Medicine, Michigan State University; Milo Gordon, Vivian Do, Olgica Balac, and Marianthi-Anna Kioumourtzoglou of Columbia University Mailman School of Public Health; and Khue Nguyen and Beizhan Yan of Lamont-Doherty Earth Observatory of Columbia University.
Funding was provided by the National Institute of Environmental Health Sciences; the National Heart, Lung, and Blood Institute; and the National Institute of Nursing Research.
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Published on 11.7.2024 in Vol 26 (2024)
Authors of this article:
1 Central Diagnostic Laboratory, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
2 Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
3 Department of Cardiology, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
4 Department of Nephrology and Hypertension, University Medical Center Utrecht, Utrecht, Netherlands
5 See Acknowledgements
Anna G M Zondag, MSc
Central Diagnostic Laboratory
University Medical Center Utrecht
Utrecht University
Heidelberglaan 100
Utrecht, 3584 CX
Netherlands
Phone: 31 631117922
Email: [email protected]
Background: Electronic informed consent (eIC) is increasingly used in clinical research due to several benefits including increased enrollment and improved efficiency. Within a learning health care system, a pilot was conducted with an eIC for linking data from electronic health records with national registries, general practitioners, and other hospitals.
Objective: We evaluated the eIC pilot by comparing the response to the eIC with the former traditional paper-based informed consent (IC). We assessed whether the use of eIC resulted in a different study population by comparing the clinical patient characteristics between the response categories of the eIC and former face-to-face IC procedure.
Methods: All patients with increased cardiovascular risk visiting the University Medical Center Utrecht, the Netherlands, were eligible for the learning health care system. From November 2021 to August 2022, an eIC was piloted at the cardiology outpatient clinic. Prior to the pilot, a traditional face-to-face paper-based IC approach was used. Responses (ie, consent, no consent, or nonresponse) were assessed and compared between the eIC and face-to-face IC cohorts. Clinical characteristics of consenting and nonresponding patients were compared between and within the eIC and the face-to-face cohorts using multivariable regression analyses.
Results: A total of 2254 patients were included in the face-to-face IC cohort and 885 patients in the eIC cohort. Full consent was more often obtained in the eIC than in the face-to-face cohort (415/885, 46.9% vs 876/2254, 38.9%, respectively). Apart from lower mean hemoglobin in the full consent group of the eIC cohort (8.5 vs 8.8; P =.0021), the characteristics of the full consenting patients did not differ between the eIC and face-to-face IC cohorts. In the eIC cohort, only age differed between the full consent and the nonresponse group (median 60 vs 56; P =.0002, respectively), whereas in the face-to-face IC cohort, the full consent group seemed healthier (ie, higher hemoglobin, lower glycated hemoglobin [HbA 1c ], lower C-reactive protein levels) than the nonresponse group.
Conclusions: More patients provided full consent using an eIC. In addition, the study population remained broadly similar. The face-to-face IC approach seemed to result in a healthier study population (ie, full consenting patients) than the patients without IC, while in the eIC cohort, the characteristics between consent groups were comparable. Thus, an eIC may lead to a better representation of the target population, increasing the generalizability of results.
The use of electronic informed consent (eIC) procedures in clinical research is increasing due to several benefits, including increased enrollment and improved efficiency, by reducing the need for on-site research staff and the associated paperwork [ 1 - 3 ]. eICs have the potential to improve the patient experience (eg, patient understanding and confidence) of the informed consent (IC) process, in part because of the ability to include digital multimedia [ 4 , 5 ]. Alternatively, concerns were raised about whether eIC forms are easily accessible to an elderly population and those with limited digital literacy [ 6 ], making it more difficult to assess whether the patient has fully understood the IC form, one of the requirements for a valid IC [ 7 ]. Standardized best practices for eIC procedures are still lacking [ 5 , 8 ].
In 2014, the University Medical Center (UMC) Utrecht in the Netherlands initiated the Utrecht Cardiovascular Cohort-CardioVascular Risk Management (UCC-CVRM) as a learning health care system (LHS). The UCC-CVRM LHS aims to improve uniform assessment and registration of cardiovascular risk indicators, based on Dutch national guidelines, in electronic health records (EHRs) for all patients referred to the UMC Utrecht for cardiovascular evaluation [ 9 ]. In an LHS, care and research are integrated in such a way that health care activities are continuously analyzed and the knowledge gained from these analyses is used to improve care by changing health care practices [ 10 ]. In the case of UCC-CVRM LHS, a traditional face-to-face IC procedure was used for blood sample storage in a biobank and the reuse of routine care data for scientific research purposes including linkage of data from EHRs to national registries [ 9 ]. In 2020, during the COVID-19 pandemic, the UCC-CVRM steering committee evaluated the study including the IC procedure [ 11 , 12 ]. In short, less than half of the patients who were invited to participate, 41.5% (2378/5730), provided written IC [ 12 ]. Next, patients who did consent differed in clinical characteristics from those nonconsenting or nonresponding, clearly leading to a selection of patients not representable for all eligible patients. For example, consenting patients had a lower cardiovascular disease burden than nonconsenting patients [ 11 , 12 ]. In addition, structured registration of cardiovascular risk management (CVRM) indicators in the EHR was worse compared with consenting patients. This selection is detrimental to an LHS, as the population included in the LHS may be less representative of the target population as a whole [ 11 , 12 ]. Finally, eligible patients were not invited, mainly because of the time-consuming and unsustainable IC procedure due to changes in personnel and changes in priorities during peak periods (eg, the COVID-19 pandemic) [ 13 ].
Therefore, the UCC-CVRM steering committee decided to alter the approach. Identification of eligible patients for the LHS was to be automated and CVRM data, to be assessed regularly in patients at higher cardiovascular risk, were extracted from structured fields in the EHR. To still enable the linkage of this patient information to data from national registries, general practitioners (GPs), and other hospitals, an eIC procedure was piloted. This study aims to evaluate the eIC procedure by studying the response to the IC form. In addition, we aim to assess whether the change in the IC procedure leads to a different study population by investigating potential differences in clinical characteristics between the response categories of the eIC compared with the former face-to-face IC procedure.
We used the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) statement as a reporting guideline for this study.
Patients visiting the UMC Utrecht for the first time for the evaluation of cardiovascular disease or risk factors were eligible for inclusion in the UCC-CVRM LHS. The full rationale of UCC-CVRM has been described elsewhere [ 9 ]. The eIC pilot was conducted between November 2021 and August 2022. During this period, all patients (18 years and older) visiting the cardiology outpatient clinic for first-time evaluation automatically received an email. This email notified these patients about UCC-CVRM and the associated eIC form that was available for completion in the UMC Utrecht patient portal. The IC procedures of the face-to-face IC and eIC are illustrated in Figure 1 . The full details eIC form presented to the patients in the patient portal are included in Multimedia Appendix 1 .
In both the face-to-face IC and the eIC forms, IC was asked for linkage with national registries, GPs, and other hospitals through the following two statements: (1) I consent to future requests to link with various international or national registries, such as the Central Bureau of Statistics (also known as Statistics Netherlands) where all causes of death are registered, the Dutch Cancer Registration (NKR), where all people with cancer are registered, the National Basic Registration of Hospital Care (LBZ), where all hospital admissions are registered, the Foundation for Pharmaceutical Statistics (SFK), where all people who use medicines are registered, and other regional and national registries. (2) I consent to the retrieval of my medical information from my GP, my pharmacy, and any other hospitals where I have been treated in the past.
We collected data from all patients aged 18 years or older referred to a cardiology outpatient clinic. We used the Utrecht Patient Oriented Database to collect data from the patients who participated in the eIC pilot, referred to as the “eIC cohort.” The Utrecht Patient Oriented Database comprises data on, among others, patient characteristics and laboratory tests for all patients treated at the UMC Utrecht since 2004 [ 14 ]. We collected routine care data related to the patient’s demographics and cardiovascular risk, namely blood pressure, BMI, and laboratory measurements (serum lipids, glycated hemoglobin [HbA 1c ], hemoglobin, and renal function). These data were also collected for the cardiology patients who were invited during the period in which a face-to-face IC procedure was in place, referred to as the “face-to-face IC cohort.” From the face-to-face IC cohort, only patients invited up until December 31, 2019, were included because the COVID-19 pandemic significantly hampered the face-to-face IC procedure.
All measurements were extracted from structured fields in the EHR. Blood pressure values were extracted from the EHR ±7 days from the date of the visit at the cardiology outpatient clinic. For other measurements, the closest value, within ±21 days of the visit date, was extracted. If no measurements were found within these cutoffs, the measurement was considered missing. An overview of missingness per variable is added as Multimedia Appendix 2 . Age was calculated by subtracting the date of the visit from the patient’s date of birth. The estimated glomerular filtration rate was calculated using the Chronic Kidney Disease Epidemiology Collaboration equation and used as a measure of renal function [ 15 ].
We presented the yield for both the eIC and face-to-face IC cohort as counts and the percentages of patients who, (1) consented to the linkage of their data with their GP, pharmacy, and other hospitals, and linkage with national registries (ie, “full consent”); (2) did not consent for the linkage of their data with their GP, pharmacy, and other hospitals, nor to the linkage with national registries (ie, “nonconsent”); (3) consented to only 1 of the 2; and (4) the percentage of patients who did not respond at all or provided an answer for only 1 of the 2 statements (ie, “nonresponse”). Due to the limited number of observations in some IC response groups (n<25), especially in the eIC cohort, other than the full consent (n=1291) and nonresponse (n=1477) group, further analyses were restricted to the full consent and nonresponse group only.
To assess differences in patient groups, characteristics of the patients with full consent were stratified by cohort (ie, eIC cohort vs face-to-face IC cohort). As a supplement, we also explored the characteristics of the nonresponders by cohort. Finally, we assessed the differences in patient characteristics between the response categories within each cohort (ie, full consent versus nonresponse).
Clinical characteristics were presented as means with corresponding SDs, medians with corresponding interquartile ranges, or counts and percentages, as appropriate. To quantify differences in characteristics between cohorts, or response categories within cohorts, we performed multivariable linear regression analyses, adjusted for age, categorized into 4 categories with an approximately equal number of observations (18 to 47, 48 to 60, 61 to 70, and 71 to 95 years old), and sex. The assumptions of linear regression (eg, approximate normal distribution of the error terms, homoscedasticity of errors) were assessed. Where needed, we used the Box-Cox method to estimate the most appropriate transformation of the dependent variable to stabilize the variance and improve the accuracy of our estimations [ 16 ]. Similarly, multivariable linear regression was used to assess the difference in age (as a continuous variable) between groups, adjusted for sex. Multivariable logistic regression was used to assess the difference in sex between the groups (ie, between the 2 cohorts and between the response categories within each cohort), adjusted for age (categorized into 4 categories with an approximately equal number of observations). As a sensitivity analysis, we repeated the adjusted regression analyses with age as a continuous variable, to assess whether the categorization led to different results.
We used the Bonferroni correction to reduce the risk of a type I error resulting from the multiple tests [ 17 ]. Thus, the α that we considered as cutoff, .05, was divided by the number of analyses (N=13) performed per comparison. Therefore, a P value ≤.0038 was considered statistically significant.
All statistical analyses were performed using R software (version 4.0.5; The R Foundation) [ 18 ].
We obtained an additional ethical waiver (number 19/641) from the Research Ethics Committee Utrecht to examine the characteristics of patients in all IC response categories. Patients who objected to the use of their clinical data for research purposes via the UMC Utrecht opt-out procedure were excluded from this study. Data were pseudonymized and the patients did not receive any compensation for their participation in this study.
In total, 3139 patients participated in this study, of whom 885 (28.2%) participated in the eIC pilot cohort and 2254 (71.8%) in the face-to-face IC cohort ( Multimedia Appendix 3 ). Of all patients from the eIC cohort, 49.9% (442/885) completed the eIC form, 50.1% (443/885) did not respond. Of all patients who completed the eIC form, we obtained full consent for linkage with GPs, hospitals, and national registries from 93.9% (415/442) of the patients. In the face-to-face IC cohort, 54.1% (1220/2254) of all patients completed the IC form, and 45.9% (1034/2254) patients did not respond. The percentage of responding patients with full consent was higher in the eIC cohort as compared with the face-to-face IC cohort (415/442, 93.9% vs 876/1220, 71.8%, respectively).
Overall, fully consenting patients had similar patient characteristics ( Table 1 ). Adjusted for sex and age, the eIC cohort had lower hemoglobin levels and higher HbA 1c levels than the face-to-face IC cohort, reaching the multiple testing threshold for statistical significance for hemoglobin ( P =.0021).
Similarly, we compared the (clinical) characteristics of the nonresponding patients between cohorts, shown in Multimedia Appendix 4 . Adjusted for sex, the nonresponders of the eIC cohort were significantly younger and had, adjusted for age and sex, lower c-reactive protein values than the nonresponders of the face-to-face cohort. No other differences were observed.
Variable | Full consent | value | |||||
eIC (n=415) | F2F IC (n=876) | ||||||
Age (years), median (IQR) | 60.0 (48.0-70.0) | 61.0 (50.0-69.0) | .2529 | ||||
Male | 237 (57.1) | 476 (54.3) | — | ||||
Female | 178 (42.9) | 400 (45.7) | .3239 | ||||
BMI (kg/m ), mean (SD) | 26.6 (5.2) | 26.7 (5.7) | .8981 | ||||
SAP (mm Hg), mean (SD) | 132.1 (19.4) | 137.6 (19.6) | .0586 | ||||
Hemoglobin (mmol/L), mean (SD) | 8.5 (1.4) | 8.8 (0.9) | .0021 | ||||
HbA (mmol/mol), median (IQR) | 37.5 (34.0-44.0) | 37.0 (34.0-40.0) | .0454 | ||||
Cholesterol (mmol/L), mean (SD) | 4.8 (1.2) | 5.1 (1.3) | .1266 | ||||
HDL -cholesterol (mmol/L), mean (SD) | 1.3 (0.4) | 1.4 (0.4) | .0676 | ||||
LDL -cholesterol (mmol/L), mean (SD) | 2.7 (1.1) | 2.9 (1.1) | .1086 | ||||
Triglycerides (mmol/L), median (IQR) | 1.7 (1.1-2.6) | 1.6 (1.0-2.1) | .3023 | ||||
CRP (mg/L), median (IQR) | 2.0 (0.5-10.0) | 2.6 (1.1-8.5) | .6666 | ||||
Creatinine (µmol/L), median (IQR) | 76.0 (64.2-94.0) | 74.0 (64.0-88.0) | .7760 | ||||
eGFR CKD-EPI (mL/min/1.73 m ), mean (SD) | 83.3 (23.1) | 84.5 (22.3) | .7068 |
a eIC: electronic informed consent.
b F2F IC: face-to-face informed consent.
c Reference group.
d SAP: systolic arterial blood pressure.
e HbA 1c : glycated hemoglobin.
f HDL: high-density lipoprotein.
g LDL: low-density lipoprotein.
h CRP: c-reactive protein.
i eGFR CKD-EPI: estimated glomerular filtration rate calculated using the Chronic Kidney Disease Epidemiology Collaboration equation.
Within each cohort, we assessed whether there were differences in characteristics between the response categories (ie, full consent vs nonresponse). In the eIC cohort, the nonresponse group was significantly younger than the full consent group ( Table 2 ). Other than that, the clinical characteristics of the full consent group were similar to those of the nonresponse group.
More differences were found between the response categories of the face-to-face IC cohort. Adjusted for age and sex, patients in the full consent group had higher hemoglobin, but lower HbA 1c and c-reactive protein values than the nonresponse group ( Table 3 ).
Variable | Full consent (n=415) | Nonresponse (n=443) | value | |
Age (years), median (IQR) | 60.0 (48.0-70.0) | 56.0 (28.0-72.0) | .0002 | |
Male | 237 (57.1) | 222 (50.1) | — | |
Female | 178 (42.9) | 221 (49.9) | .0420 | |
BMI (kg/m ), mean (SD) | 26.6 (5.2) | 26.0 (4.9) | .3673 | |
SAP (mm Hg), mean (SD) | 132.1 (19.4) | 130.4 (19.6) | .4168 | |
Hemoglobin (mmol/L), mean (SD) | 8.5 (1.4) | 8.4 (1.3) | .2397 | |
HbA (mmol/mol), median (IQR) | 37.5 (34.0-44.0) | 37.5 (34.0-40.2) | .1940 | |
Cholesterol (mmol/L), mean (SD) | 4.8 (1.2) | 4.6 (1.5) | .2852 | |
HDL -cholesterol (mmol/L), mean (SD) | 1.3 (0.4) | 1.2 (0.5) | .3371 | |
LDL -cholesterol (mmol/L), mean (SD) | 2.7 (1.1) | 2.6 (0.9) | .9304 | |
Triglycerides (mmol/L), median (IQR) | 1.7 (1.1-2.6) | 1.4 (1.1-2.0) | .4167 | |
CRP (mg/L), median (IQR) | 2.0 (0.5-10.0) | 3.0 (0.5-12.0) | .5922 | |
Creatinine (µmol/L), median (IQR) | 76.0 (64.2-94.0) | 79.0 (64.0-100.5) | .0897 | |
eGFR CKD-EPI (mL/min/1.73 m ), mean (SD) | 83.3 (23.1) | 82.0 (30.7) | .1103 |
a Reference group.
b SAP: systolic arterial blood pressure.
c HbA 1c : glycated hemoglobin.
d HDL: high-density lipoprotein.
e LDL: low-density lipoprotein.
f CRP: c-reactive protein.
g eGFR CKD-EPI: estimated glomerular filtration rate calculated using the Chronic Kidney Disease Epidemiology Collaboration equation.
Variable | Full consent (n=876) | Nonresponse (n=1034) | value | |
Age, median (IQR) | 61.0 (50.0-69.0) | 61.0 (48.0-71.0) | .9461 | |
Male | 476 (54.3) | 552 (53.4) | — | |
Female | 400 (45.7) | 482 (46.6) | .7859 | |
BMI (kg/m ), mean (SD) | 26.7 (5.7) | 26.2 (5.5) | .1063 | |
SAP (mm Hg), mean (SD) | 137.6 (19.6) | 136.3 (22.0) | .1093 | |
Hemoglobin (mmol/L), mean (SD) | 8.8 (0.9) | 8.3 (1.2) | <.0001 | |
HbA (mmol/mol), median (IQR) | 37.0 (34.0-40.0) | 38.0 (34.0-42.0) | .0001 | |
Cholesterol (mmol/L), mean (SD) | 5.1 (1.3) | 5.0 (1.4) | .4493 | |
HDL -cholesterol (mmol/L), mean (SD) | 1.4 (0.4) | 1.3 (0.4) | .0898 | |
LDL -cholesterol (mmol/L), mean (SD) | 2.9 (1.1) | 2.9 (1.1) | .2754 | |
Triglycerides (mmol/L), median (IQR) | 1.6 (1.0-2.1) | 1.6 (1.0-2.4) | .0435 | |
CRP (mg/L), median (IQR) | 2.6 (1.1-8.5) | 8.1 (2.0-38.2) | <.0001 | |
Creatinine (µmol/L), median (IQR) | 74.0 (64.0-88.0) | 75.0 (63.0-92.0) | .4361 | |
eGFR CKD-EPI (mL/min/1.73 m ), mean (SD) | 84.5 (22.3) | 81.3 (29.0) | .0946 |
We repeated the regression analyses adjusted for sex and age. In these regression analyses, age was maintained continuous instead of categorized, to assess whether the categorization of age led to different results. The results were similar ( Multimedia Appendix 5 ).
We showed that by using an eIC in an LHS, patients more often provided full consent to link their data to national registries, GPs, and other hospitals compared with a face-to-face IC procedure. The clinical characteristics of patients with full consent remained largely similar after changing the IC procedure to an eIC. Except for age, we did not find any differences between the response categories of the eIC cohort, whereas in the face-to-face cohort, several differences were found. These differences potentially suggest a higher (cardiovascular) disease burden in the nonresponse group compared with the full consent group, indicative of a potentially more pronounced selection in the face-to-face approach.
A possible explanation for the differences in characteristics between the response categories in the face-to-face cohort is that patients may have been too ill or frail to attend the physical appointment with the research nurse to discuss and sign the IC form, resulting in nonresponse. The inability to attend the appointment was probably less of an issue in the eIC cohort, as patients were able to access the eIC form remotely. The finding suggests that the use of eIC results in a study population (ie, those who give full consent) that is more representative of the full target population. Our findings agree with a previous study showing that providing computer-based clinical study information leads to more willingness to participate [ 19 ], as the increased willingness to participate is consistent with the higher full consent rates found in the eIC group compared with the face-to-face IC group in our study.
Concerns have been raised about whether consent given via an eIC is truly an “informed” consent [ 8 ]. According to the principles of the Declaration of Helsinki [ 7 ], potential participants must be adequately informed about various aspects of the study, such as its purpose, sources of funding, the anticipated benefits and potential risks, and the right to refuse or withdraw consent to participate without giving a reason [ 7 ]. According to previous research, comprehension assessment is more challenging when an eIC procedure is used as there is no direct interaction between the potential participant and researcher [ 6 ]. As a result, patients might provide consent without fully understanding what they are consenting to, or, conversely, patients may be less likely to consent because of the lack of personal interaction with the researcher or clinician, especially those who were already doubtful about participating in the first place. However, our findings indicate that the latter might not have been the case in our pilot study, as we observed a higher percentage of patients with full consent in the eIC cohort compared with the face-to-face IC cohort.
Another frequently mentioned concern is that studies using an eIC procedure could become inaccessible to patients who lack the digital literacy needed to access and understand the eIC form [ 6 ]. In 2021, the Netherlands had the highest percentage (ie, 79%) of 17- to 74-year-olds with at least basic digital skills in Europe [ 20 ]. Therefore, incomprehension of the eIC due to limited digital literacy may appear less of an issue in our study. However, the percentage of persons with basic digital skills varied considerably by age, with older people being less literate [ 20 ]. A sensitivity analysis showed that the age distribution of responding patients was similar between the eIC and the face-to-face approach ( Multimedia Appendix 6 ), indicating that the eIC was not less accessible than the face-to-face IC for certain age groups. However, accessibility may be an issue for geriatric patients, who are generally older than cardiology patients and often have geriatric syndromes that sometimes affect comprehension and literacy [ 21 ]. These syndromes generally make it difficult to obtain IC from the elderly [ 21 ]. eIC could, therefore, also be seen as an opportunity. Unlike paper-based ICs, multiple formats can be used to inform the patient about the purpose of the eIC and to provide technical support, for example, by using instructional videos or audio. The use of multiple formats in IC forms for the elderly has been recommended by, among others, Barron et al [ 22 ]. Furthermore, UCC-CVRM’s eIC form is available in UMC Utrecht’s long-existing patient portal. In the portal, patients have the opportunity to, among others, ask questions to their clinician via an e-consult, which can be used if parts of the eIC are unclear [ 23 ]. Another possibility would be a hybrid format, allowing patients who prefer correspondence by regular mail to respond using a paper-based IC form. However, it is questionable whether this would be helpful and it would negate the positive aspects of the eIC highlighted in this study (eg, less pronounced selection).
Since July 2022, eICs have been permitted in the Netherlands when certain conditions are met [ 24 ]. A total of 6 conditions are described in the guideline written by the Central Committee on Research Involving Human Subjects (Centrale Commissie Mensgebonden Onderzoek) and the Dutch Association of Medical Research Ethics Committees (Nederlandse Vereniging voor Medisch-Ethische toetsingscommissies) [ 25 ]. The most important conditions are (1) eIC must be appropriate for the study, meaning that the study is associated with low potential risk and burden for the patient, (2) the eIC process must be sufficiently reliable and confidential, guaranteed by an electronic system that is compliant to the Dutch General Data Protection Regulation (UAVG in Dutch) and ensures the validity of the electronic signatures, and (3) the eIC procedure must be described in the study protocol [ 24 , 25 ]. The implementation of an eIC seems appropriate in the case of the UCC-CVRM, as no potential risk or burden for the patient is involved. Furthermore, in the eIC of the UCC-CVRM, data security, identity verification, and the validity of the electronic signature are ensured by the Dutch digital ID, an identification method for accessing web-based services [ 26 ]. Regarding the third condition, an amendment to the UCC-CVRM approach, including the eIC, was submitted and approved by the Research Ethics Committee.
Based on the results of our study, the use of eIC to obtain IC might be a sustainable and adequate way to enable researchers to link with national registries, GPs, and other hospitals. The use of the eIC seemed to have resulted in a population with consent that is more similar to the target population compared with the face-to-face IC, which is of great importance in an LHS. Results from the LHS would be more generalizable to the target population, namely to all patients at higher cardiovascular risk. Yet, one may argue whether ≈50% response to both the electronic and face-to-face IC for an LHS approach is sufficient. In addition, it should be noted that the extractability of CVRM indicators from structured fields in the EHR was much lower in the eIC cohort compared with the face-to-face IC cohort. Groenhof et al [ 13 ] showed that the former, protocolized, face-to-face UCC-CVRM approach led to more systematic registration of the cardiovascular risk profile in the EHR, which had a positive effect on CVRM guideline adherence in consenting patients, compared with the situation before UCC-CVRM was introduced [ 13 ]. The substantial missingness in the eIC cohort of our study may suggest that these improvements are at risk when the approach is automated, as deviations from the initial protocol are made, potentially leading to suboptimal CVRM in clinical care.
Exploring the views and experiences of patients could help to further improve the eIC form. Therefore, we recommend further qualitative research into the accessibility and understandability of eICs used for similar purposes and in similar settings as the UCC-CVRM LHS from a patient’s perspective.
To the best of our knowledge, we are among the first to investigate the differences in clinical patient characteristics between response categories of an eIC compared with those of a traditional face-to-face IC, specifically in the context of a cardiovascular LHS in a large sample of patients. Our uniqueness, however, limits the ability to compare our findings to the literature, as most research on eIC has focused on user perspectives, experiences, and the ethical considerations of eICs. For example, Chen et al [ 5 ] showed that in most included studies, participants had a better understanding of the information when using an eIC compared with a traditional paper-based face-to-face IC, while others found no difference [ 5 ]. Nevertheless, they [ 5 ] and others [ 2 , 6 , 27 ] indicated that face-to-face interaction should remain part of the IC process, especially for more complex and higher-risk studies. However, as the UCC-CVRM LHS is not a complex or high-risk study, the face-to-face interaction may be less necessary. Furthermore, the nonresponders in the eIC cohort may not be fully comparable to the nonresponders in the face-to-face IC cohort because, in the eIC cohort, patients received the eIC after their appointment at the cardiology outpatient clinic, whereas in the face-to-face IC cohort, cardiology patients were identified as eligible and received information about the UCC-CVRM LHS prior to their appointment. This means that patients who, for example, canceled their appointment at the last minute would still be included in the face-to-face cohort as nonresponders. It may be that patients who did not attend their appointment at all had different characteristics to those who attended but did not respond to the eIC, potentially affecting the validity of the comparisons made. Finally, the eIC form was piloted in the patient population of the cardiology outpatient clinic only. Although our results indicated that there were only minor differences (ie, hemoglobin) between patients providing full consent using the eIC compared with the face-to-face IC, it remains to be seen whether this would still be the case after implementation of the eIC in other clinical departments.
To conclude, our findings suggest that using an eIC may lead to a better representation of the target population by consenting patients. This increases the generalizability of results from studies using the data collected within the LHS from consenting patients.
The Utrecht Cardiovascular Cohort-Cardiovascular Risk Management (UCC-CVRM) is primarily financed by the University Medical Center (UMC) Utrecht (contact information of UCC-CVRM is [email protected]). AGMZ was supported by a grant from the European Union’s Horizon 2020 research and innovation program (grant agreement number 101017331; ODIN). MJH and RvdG were supported by the ZonMw, ETHMIRE project (grant agreement number 91217027). The funding sources were not involved in the design of the study, the analysis and interpretation of the data, the writing of the manuscript, and the decision to submit the manuscript for publication. Members of the UCC-CVRM study group were the following: GJ de Borst, Department of Vascular Surgery; ML Bots (chair), Julius Center for Health Sciences and Primary Care; M Hollander, Julius Center for Health Sciences and Primary Care; MH Emmelot, Department of Geriatrics; PA de Jong, Department of Radiology; AT Lely, Department of Obstetrics/Gynecology; HM Nathoe, Department of Cardiology; IE Hoefer, Central Diagnostic Laboratory; NP van der Kaaij, Department of Cardiothoracic Surgery; YM Ruigrok, Department of Neurology; and MC Verhaar, Department of Nephrology and Hypertension, FLJ Visseren, Department of Vascular Medicine, University Medical Center Utrecht and Utrecht University.
AGMZ, HMN, WWvS, MLB, SH, and RWMV contributed to the conceptualization of the project. AGMZ, RWMV, SH, WWvS, and MLB contributed to the methodology of the project. AGMZ analyzed the data and drafted the manuscript. AGMZ, MJH, RvdG, HMN, WWvS, MLB, SH, and RWMV contributed substantially to the interpretation of the data. The final manuscript was critically reviewed and edited by all authors. Approval of the final manuscript was obtained by all authors.
None declared.
The electronic informed consent form as presented in the patient portal of the UMC (University Medical Center) Utrecht (translated from Dutch to English).
Missingness per variable in count and percentage, by cohort and informed consent response strata.
Yield (ie, response to the informed consent invitation), by type of informed consent. eIC: electronic informed consent; GP: general practitioner.
Differences between patients who did not respond, by cohort, adjusted for age and sex.
Results of the sensitivity analysis in which age is treated as a continuous variable instead of categorical variable.
Age distribution of patients who completed the informed consent form, stratified by cohort.
cardiovascular risk management |
electronic health record |
electronic informed consent |
general practitioner |
glycated hemoglobin |
informed consent |
learning health care system |
Strengthening the Reporting of Observational Studies in Epidemiology |
Utrecht Cardiovascular Cohort-Cardiovascular Risk Management |
University Medical Center |
Edited by A Mavragani; submitted 29.11.23; peer-reviewed by CMJ Wong, H Kondylakis; comments to author 28.02.24; revised version received 15.04.24; accepted 10.05.24; published 11.07.24.
©Anna G M Zondag, Marieke J Hollestelle, Rieke van der Graaf, Hendrik M Nathoe, Wouter W van Solinge, Michiel L Bots, Robin W M Vernooij, Saskia Haitjema, UCC-CVRM study group. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 11.07.2024.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research (ISSN 1438-8871), is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.
The dotted vertical line indicates the Dobbs v Jackson Women’s Health Organization decision.
eTable. Diagnosis and Billing Codes Used to Identify Tubal Ligation, Vasectomy, and Encounters for Evaluation and Management (E&M)
Data Sharing Statement
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Ellison JE , Brown-Podgorski BL , Morgan JR. Changes in Permanent Contraception Procedures Among Young Adults Following the Dobbs Decision. JAMA Health Forum. 2024;5(4):e240424. doi:10.1001/jamahealthforum.2024.0424
© 2024
On June 24, 2022, the US Supreme Court’s decision in Dobbs v Jackson Women’s Health Organization overturned the constitutional right to abortion, permitting states to further restrict or ban abortion care. As of January 2024, 21 states have done so. 1 This structural barrier to exercising control over pregnancy and childbearing will indirectly affect contraceptive decision-making.
Early research has documented increased demand for permanent contraception in the months following Dobbs , including tubal sterilization and vasectomy. 2 , 3 This change may reflect fears of restricted access to abortion and/or contraception. However, no research, to our knowledge, has evaluated the differential effect of Dobbs on permanent contraception among men relative to women or among younger adults who are more likely to have an abortion and to experience sterilization regret. 4 , 5 We therefore evaluated changes in tubal ligation and vasectomy following Dobbs among younger adults.
We used data from the TriNetX platform for this cross-sectional study. These continuously updated medical record data are largely from academic medical centers and affiliated clinics in all 4 US census regions. We used an interrupted time series study design, fitting seasonally adjusted segmented autoregressive models to assess level and slope changes in procedure rates before (January 1, 2019, to May 31, 2022) and after (June 1, 2022, to September 30, 2023) Dobbs . Sensitivity analyses with a truncated pre- Dobbs observation window (April 1, 2021, to May 31, 2022) were conducted using Stata, version 17.1 (StataCorp LLC). This research was deemed exempt from review and the need for informed consent by the Boston University Institutional Review Board owing to the use of deidentifed patient data. We followed the ( STROBE ) reporting guideline.
Using monthly aggregate counts of tubal ligations and vasectomies, we calculated rates per 100 000 person-months among female and male patients aged 18 to 30 years. Individuals with an encounter for evaluation and management each month and no permanent contraception documented previously were included in the denominator. Visits for evaluation and management, tubal sterilization, and vasectomy procedures were identified using Current Procedural Terminology and International Statistical Classification of Diseases, Tenth Revision codes (eTable in Supplement 1 ). Two-sided P < .05 indicated statistical significance.
Observed permanent contraception procedure rates, estimates, and seasonally adjusted models for 22 063 348 person-months (36.9% male and 63.1% female) are presented in the Figure . Prior to Dobbs , the monthly permanent contraception rate increased by 2.84 and 1.03 procedures per 100 000 person-months among female and male patients, respectively ( Table ). Dobbs was associated with an immediate level increase of 58.02 procedures and 5.31 procedures per month among female patients. Among male patients, it was associated with a level increase of 26.99 procedures and no significant change in the number of procedures per month. Findings were robust to sensitivity analyses.
We observed an abrupt increase in permanent contraception procedures among adults aged 18 to 30 years following Dobbs . The increase in procedures for female patients was double that for male patients. These patterns offer insights into the gendered dynamics of permanent contraceptive use and may reflect the disproportionate health, social, and economic consequences of compulsory pregnancy on women and people with the capacity to become pregnant.
This study has several limitations. The TriNetX platform does not capture state or health care organization identifiers. We were therefore unable to assess the potential outcomes of state abortion policy or account for changes in the sample attributable to fluctuations in the organizations contributing data over the study period. Additionally, our findings do not provide insight into the differential experiences of Black, Indigenous, Hispanic, disabled, immigrant, and low-income women, who disproportionately encounter interference and coercion in their contraceptive decision-making. 6
The abrupt increase in permanent contraception rates may indicate a policy-induced change in contraceptive preferences. Dobbs may have also increased a sense of urgency among individuals who were interested in permanent contraception before the decision. Changes in contraceptive decision-making must be considered to understand the short- and long-term implications of Dobbs on reproductive autonomy.
Accepted for Publication: February 7, 2024.
Published: April 12, 2024. doi:10.1001/jamahealthforum.2024.0424
Correction: This article was corrected on May 10, 2024, to correct the y-axis label in the Figure.
Open Access: This is an open access article distributed under the terms of the CC-BY License . © 2024 Ellison JE et al. JAMA Health Forum .
Corresponding Author: Jacqueline E. Ellison, PhD, 130 De Soto St, Pittsburgh, PA 15261 ( [email protected] ).
Author Contributions: Dr Ellison had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Concept and design: Ellison, Morgan.
Acquisition, analysis, or interpretation of data: All authors.
Drafting of the manuscript: Ellison, Brown-Podgorski.
Critical review of the manuscript for important intellectual content: All authors.
Statistical analysis: Ellison, Morgan.
Administrative, technical, or material support: Ellison, Morgan.
Supervision: Ellison.
Conflict of Interest Disclosures: None reported.
Data Sharing Statement: See Supplement 2 .
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by North Carolina State University
A new paper on the many ways wildfires affect people and the planet makes clear that as fires become more intense and frequent, the urgency for effective and proactive fire science grows. By addressing these challenges, the fire research community aims to better protect our planet and its inhabitants.
The paper appears in the Zenodo research repository.
Fire is a natural part of life on Earth, sustaining healthy and balanced ecosystems worldwide. But human activity and a changing climate are rapidly shifting both the frequency and severity of wildfire events, creating new risks to human and environmental health.
Recently, a group of scientists from 14 countries and across several disciplines—physical and social sciences, mathematics, statistics, remote sensing, fire communication and art, operational fire science , and fire management—gathered to discuss rapid changes in fire regimes and identify pathways to address these challenges.
The experts identified three grand challenges for fire science in the coming decades: understanding the role of fire in the carbon cycle , fire and extreme events , and the role of humans in fire.
"If we want to improve the assessment of future fire impacts on people and the planet, we need to start with a better understanding of how climate, land cover changes, and human land management practices drive fire distribution and severity in the coming decades," says Douglas Hamilton, assistant professor of marine, earth and atmospheric science at North Carolina State University.
Hamilton, together with Morgane Perron of University Brest, France and Joan Llort of the Barcelona Supercomputing Centre, Spain, initiated the working group FLARE (which stands for Fire Science Learning AcRoss the Earth System).
To address the grand challenges, the scientists identified three pressing research priorities: understanding the net carbon balance of fire, developing rapid response tools for wildfire events, and understanding fire's impact on society, especially marginalized and underrepresented populations.
The first priority, understanding the net carbon balance of fire, refers to understanding how fire's carbon release, ecological recovery from fire, climate change , ocean biology, and ice melt all interact and affect the Earth's carbon balance.
"Wildfires can significantly affect the global carbon cycle," says Chantelle Burton, senior climate scientist at the Met Office UK. "Fires in ecosystems that store large amounts of carbon, such as peatlands, permafrost and forests, can release vast quantities of CO 2 into the atmosphere. However, where that carbon ultimately ends up and its impact on future warming are harder to determine. Incorporating accurate fire-related carbon fluxes into Earth System Models is crucial for predicting climate outcomes and informing mitigation strategies, and it will require us to bring together experts from across the fire sciences."
The second priority, developing rapid response tools for wildfire events, refers to developing tools for more timely and responsive answers to critical questions during extreme fire events and providing an annual report on key policy and media questions.
"Our observational, statistical, and modeling tools for assessing and projecting fire are improving rapidly, but the problem of extreme fires always remains one step ahead of us," says Douglas Kelley, fire scientist at the UK Centre for Ecology & Hydrology (UKCEH). "To catch up, we need our tools to provide quick, robust answers to critical questions about climate impact, human causation, affected communities, and future risks. These answers need to be communicated clearly to non-specialists when they are most needed."
The third priority aims to explore how fires affect marginalized and underrepresented communities, emphasizing Indigenous populations and environmental justice.
"So how should we be using all the tools at our disposal to improve measurements and help create better models for predicting the downstream effects of each fire?" Hamilton asks. "And once we do that, how do we best communicate these findings to our communities? We wanted to create a roadmap for science, so that our collaborations focus on getting these answers faster than at present."
A main goal in the white paper is to be able to improve fire modeling, predictability, and mitigation on both regional and global scales, but Hamilton also hopes that FLARE will aid in fostering transdisciplinary science and in recruiting future fire scientists. "There simply are not enough scientists in this field to do the work," Hamilton says.
Sebastian Diez from Universidad del Desarrollo, Chile and part of International Global Atmospheric Chemistry's (IGAC) Early Career Committee further emphasizes the importance of global collaboration. "Researchers from the Global South face unique challenges that require locally adapted solutions," Diez says. "Strengthening research capabilities and resources in less affluent regions is imperative to effectively address the transdisciplinary challenges of fire science."
"Fire has always been there in the Earth system. What's new is how it is being affected by and affecting humans in the context of wider planetary change," says Sophie Hebden, Future Earth. "By bringing together the different global research networks of Future Earth, we were able to address these challenges across research silos and outline a transdisciplinary research agenda for the global fire community."
As fire events become more intense and frequent, the urgency for effective and proactive fire science grows. FLARE's next steps are to address these challenges collectively, as a unified fire research community, to better protect our planet and its inhabitants.
Provided by North Carolina State University
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COMMENTS
The medical drama that health science students watched most was The Good Doctor, one of the newest medical dramas (available since 2017). This series shows the life of a young autistic physician with savant syndrome who is starting his residency in surgery, and it includes many situations that involve bioethical issues [ 21 ].
Grey' s Anatomy Grey's Anatomy is an American medical drama television series. It follows the lives of interns, resi-. dents and their mentors in the ctional Seattle Grace-Mercy W est Hospital ...
Background Medical dramas have been popular since their inception, especially among medical students. We hypothesized that the recent increase in the availability of TV medical series through online streaming platforms has probably changed health science students' viewing habits as well as the representation of bioethical conflicts and health professionals. Methods We invited undergraduate ...
2 Center for Research on Media, Technology, and Health, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213, USA. ... One time paper survey: P, B - Effect of viewership on patient perception of physicians and patient-physician interaction ... Medical drama watching was a significant, positive predictor of fatalistic beliefs ...
Medical drama has been one of television's (TV's) most popular genres since its inception in the 1960s. 1 Even though the fact that the vast majority of TV medical dramas are produced in the United States and are centered on the American healthcare system, they are viewed globally. 2 In addition, the growing popularity of online platforms, also known as subscription video-on-demand services ...
This paper aims to boost quantitative research in the field of media studies, first considering a comparative and data-driven study of the narrative features in the US medical TV series, one of ...
The current paper analyzed data that were collected over the 36-month period between January 2007 and December 2009 because they included questions about medical drama watching. Among those who were randomly selected and recruited to participate, about 28% of the respondents (between 19 and 34%) showed a willingness to participate and join as ...
Heavier viewers of medical dramas, compared to lighter viewers, also tend to take a more fatalistic perspective about cancer. Theoretical implications for cultivation theory and practical implications for health policy makers and drama producers are discussed.
This paper aims to boost quantitative research in the field of media studies, first considering a comparative and data-driven study of the narrative features in the US medical TV series, one of the most popular and longest-running genres on global television. ... Medical drama is a narrative genre that has been one of the most popular products ...
ABSTRACT. Based on genre theory, this quantitative content analysis compares physician portrayals, behaviors, and patient-centered communication practices in 2,658 scenes from medical drama (Grey's Anatomy), comedy (Scrubs), and reality (New York Med) shows.Significant differences among the programs' portrayals of television doctors notwithstanding, the overall results indicate that Black ...
3 Medical drama under investigation. Research on American medical dramas has been carried out both on a national and international level: from studies regarding TV genres on, researchers focused on the different aspects that have sparked interest on these products. Starting from issues related to TV genre, necessary to contextualize the medical ...
As Joseph Turow details in his institutional analysis of the medical drama genre, the AMA checked scripts for medical accuracy, but also to ensure that the programs presented an exclusively positive image of the modern physician. See, Turow J. Playing Doctor: Television, Storytelling, and Medical Power. New York, NY: Oxford University Press; 1989.
The study suggests that perceived realism of and trust in physicians in medical dramas mediate the relationship between medical drama viewing and medical trust, with health literacy moderating this cultivation process. Implications and future research directions are discussed.
Recent papers in Medical Drama. Top Papers; Most Cited Papers; Most Downloaded Papers; ... The aim of the article is exploratory, and it highlights the need for future research, as the potential of Netflix's EE seems the greatest when compared to other platforms analyzed. Netflix has the largest number of contents featuring cancer, and these ...
Five medical K-dramas (General Hospital 2 / 종합병원2 (2009), Brain / 브레인(2011), The Third Hospital / 제3의병원(2012), Medical Top Team메디컬탑팀(2013) and Doctor Stranger닥터이방인(2014)) are selected for qualitative analysis, to explore different ways in which the creative content industry reflects genuine Korean cultural beliefs, moral values, political attitudes and ...
Viewers of medical dramas expect the same medical treatment as is depicted on television (Ye & Ward, 2010). For example, one study found that most viewers of medical dramas anticipate his/her physician to be smart, attractive, and friendly (Chory-Assad & Tamborini, 2010). Such portrayals provide an interesting research opportunity to discover the
Abstract and Figures. This study was planned to evaluate that a lecture employing medical drama could motivate students to have an interest in the professionalism of healthcare personnel, which ...
Background: Medical dramas have been popular since their inception, especially among medical students. We hypothesized that the recent increase in the availability of TV medical series through online streaming platforms has probably changed health science students' viewing habits as well as the representation of bioethical conflicts and health professionals.
Multiple studies have also shown that television profoundly influences how we think about physicians. "Heavy viewers of medical dramas compared to light viewers perceived doctors to be more unethical, tense, and inconsiderate," the authors of a 2003 paper reported. This may be expected in situations where people have limited access to ...
In this paper, meta-analysis is employed to investigate the effect of drama as an intervention on mental health and well-being. ... Future research may examine the effects of drama-based interventions on individuals with post-COVID-19 pandemic trauma to better comprehend the correlations between drama activity and therapeutic effect. To further ...
Psychodrama and drama therapy are organized health professions where credentialed professionals intentionally employ experiential drama processes and techniques to ameliorate health and well-being within a therapeutic relationship. These drama-based therapies are used for mental health treatment across a range of clients and in various healthcare settings. The aims of this systematic review ...
The Cox papers are open and accessible for research. In addition to the materials mentioned here, researchers can find administrative documents, correspondence, grant applications, research notes, patents, photographs, and more pertaining to his extensive work in auditory physiology, ECG analysis and processing, CT and PET scanning technologies, DNA mapping, information systems and database ...
"To our knowledge, this is the first paper to measure metals in tampons. Concerningly, we found concentrations of all metals we tested for, including toxic metals like arsenic and lead." Metals have been found to increase the risk of dementia, infertility, diabetes, and cancer.
We used a random sample of 16 million patients (2006-2020) from the PharMetrics Plus for Academics database (IQVIA), a large health claims database that captures 93% of all outpatient prescriptions and physician diagnoses in the US through the International Classification of Diseases, Ninth Revision (ICD-9) or ICD-10. In our cohort study, we included new users of semaglutide or liraglutide, 2 ...
Medical drama as an md-narrative is an important venue to be used in the teaching of biomedical ethics. . The use of medical drama in teaching enhances emotional engagement, cognitive development, and moral imagination which allow for a more ethically sensitive student in training. .
Background: Electronic informed consent (eIC) is increasingly used in clinical research due to several benefits including increased enrollment and improved efficiency. Within a learning health care system, a pilot was conducted with an eIC for linking data from electronic health records with national registries, general practitioners, and other hospitals.
These continuously updated medical record data are largely from academic medical centers and affiliated clinics in all 4 US census regions. We used an interrupted time series study design, fitting seasonally adjusted segmented autoregressive models to assess level and slope changes in procedure rates before (January 1, 2019, to May 31, 2022 ...
A rare allergy to meat; seeking gentler treatment for hydrocephalus; new bladder cancer therapy: Upstate Medical University's HealthLink on Air for Sunday, July 14, 2024 A certain type of tick bite can trigger a rare reaction to red meat, explains public health researcher Jamie Romeiser, PhD .
There is still much discussion surrounding the place of the humanities within the undergraduate medical and health sciences curricula. Whilst a large amount of educational research focuses on the cognitive and psycho-motor domains of learning, seeking the most appropriate ways of teaching, learning and assessment, less attention is paid to the more difficult to define affective domain.
The paper appears in the Zenodo research repository.. Fire is a natural part of life on Earth, sustaining healthy and balanced ecosystems worldwide. But human activity and a changing climate are ...