Khalifeh et al. conducted a meta-analysis to evaluate the risk reduction of head and neck (HN) cancer following smoking cessation (1). The authors analyzed data from 65 studies, which had been published until June 2022. They were composed of 5 cohort and 60 case-control studies. Relative risks (RRs) (95% confidence intervals [CIs]) of former smokers compared with current smokers for HN cancer was 0.40 (0.35 to 0.46). By using 37 studies, RR (95% CI) per 10-year increase in smoking cessation was 0.47 (0.43 to 0.52). I present information from a prospective study, which presents a mortality risk.
Lee et al. reported the association between the duration of abstinence, overall and HN-specific mortality (2). Former smokers presented a significant risk reduction in HN-specific mortality, but there was no significant difference in the risk of noncancer mortality. Compared with current smokers, former smokers who quit >10 years before diagnosis presented the adjusted hazard ratios (95% CIs) of 0.72 (0.56 to 0.93) and 0.64 (0.46 to 0.91) for overall and HN-specific mortality. They emphasized that long-term abstinence over 10 years had a significant risk reduction in overall and HN-specific mortality. Although heterogeneity in each group of a meta-analysis was extremely high, risk assessment with incidence/prevalence may have some difficulties of data collections. Lee et al. conducted sensitivity analyses by the types of treatment, and radiation therapy only showed a signi...
Khalifeh et al. conducted a meta-analysis to evaluate the risk reduction of head and neck (HN) cancer following smoking cessation (1). The authors analyzed data from 65 studies, which had been published until June 2022. They were composed of 5 cohort and 60 case-control studies. Relative risks (RRs) (95% confidence intervals [CIs]) of former smokers compared with current smokers for HN cancer was 0.40 (0.35 to 0.46). By using 37 studies, RR (95% CI) per 10-year increase in smoking cessation was 0.47 (0.43 to 0.52). I present information from a prospective study, which presents a mortality risk.
Lee et al. reported the association between the duration of abstinence, overall and HN-specific mortality (2). Former smokers presented a significant risk reduction in HN-specific mortality, but there was no significant difference in the risk of noncancer mortality. Compared with current smokers, former smokers who quit >10 years before diagnosis presented the adjusted hazard ratios (95% CIs) of 0.72 (0.56 to 0.93) and 0.64 (0.46 to 0.91) for overall and HN-specific mortality. They emphasized that long-term abstinence over 10 years had a significant risk reduction in overall and HN-specific mortality. Although heterogeneity in each group of a meta-analysis was extremely high, risk assessment with incidence/prevalence may have some difficulties of data collections. Lee et al. conducted sensitivity analyses by the types of treatment, and radiation therapy only showed a significant risk reduction in mortality by smoking cessation and long-term quitting. Many factors might interact with prognosis, and caution should be paid to clinical outcomes in mortality study.
References
1. Khalifeh M, Ginex P, Boffetta P. Reduction of head and neck cancer risk following smoking cessation: a systematic review and meta-analysis. BMJ Open 2024;14(8):e074723.
2. Lee JJW, Kunaratnam V, Kim CJH, et al. Cigarette smoking cessation, duration of smoking abstinence, and head and neck squamous cell carcinoma prognosis. Cancer 2023;129(6):867-77.
Dear Editor,
I am writing in response to the article, “Association between sleep quality and uncertainty stress among healthcare professionals in hospitals in China,” recently published in BMJ Open. The study reveals the high prevalence of insomnia and uncertainty stress among healthcare workers, which is an important contribution. Furthermore, the use of validated tools such as the Athens Insomnia Scale (AIS) enhances the reliability of the findings, offering solid evidence for the urgent need to address healthcare workers’ mental well-being.
However, I would like to offer some additional suggestions that could make a further discussion.
Firstly, regional and hospital-level differences are important factors that cannot be overlooked. The study covers only three provinces, yet healthcare resources within these provinces vary significantly, which introduces potential variability in stress sources. For instance, tertiary hospitals in major cities, such as Hangzhou in Zhejiang province, often experience high levels of stress due to large patient volumes and complex cases. In contrast, healthcare professionals in less resourced areas, such as Lishui in Zhejiang province, are facing chronic stress from staff shortages and inadequate infrastructure. Understanding these regional disparities can provide a more detailed view of how healthcare environments influence sleep quality.
Secondly, the timing of data collection also affects the study’s findings. T...
Dear Editor,
I am writing in response to the article, “Association between sleep quality and uncertainty stress among healthcare professionals in hospitals in China,” recently published in BMJ Open. The study reveals the high prevalence of insomnia and uncertainty stress among healthcare workers, which is an important contribution. Furthermore, the use of validated tools such as the Athens Insomnia Scale (AIS) enhances the reliability of the findings, offering solid evidence for the urgent need to address healthcare workers’ mental well-being.
However, I would like to offer some additional suggestions that could make a further discussion.
Firstly, regional and hospital-level differences are important factors that cannot be overlooked. The study covers only three provinces, yet healthcare resources within these provinces vary significantly, which introduces potential variability in stress sources. For instance, tertiary hospitals in major cities, such as Hangzhou in Zhejiang province, often experience high levels of stress due to large patient volumes and complex cases. In contrast, healthcare professionals in less resourced areas, such as Lishui in Zhejiang province, are facing chronic stress from staff shortages and inadequate infrastructure. Understanding these regional disparities can provide a more detailed view of how healthcare environments influence sleep quality.
Secondly, the timing of data collection also affects the study’s findings. The cross-sectional design captures data from a single point in time, limiting the study’s ability to account for seasonal workload fluctuations. Besides the covid-19 pandemic mentioned in the text, Temporal variations, such as increased patient admissions during specific seasons (e.g., flu season), can significantly influence healthcare providers' stress levels and sleep patterns (Arnedt, J. T., et al, 2005). Longitudinal data is essential to capture these seasonal trends accurately.
Lastly, the voluntary participation method introduces potential selection bias. Healthcare workers experiencing the highest levels of stress or fatigue may have been less likely to participate, skewing the results towards those with milder stress and better sleep patterns. This issue may be particularly pronounced during periods of increased hospital admissions, further complicating the study's findings.
In conclusion, the study offers very valuable insights, but future research should consider expanding the sample across more regions, employing longitudinal designs, and accounting for hospital-level disparities. These approaches would provide a deeper understanding of the complexities influencing healthcare workers’ well-being and guide more targeted interventions.
Reference:
Arnedt, J. T., Owens, J., Crouch, M., Stahl, J., & Carskadon, M. A. (2005). Neurobehavioral. Performance of Residents after Heavy Night Call vs after Alcohol Ingestion. JAMA, 294(9), 1025-1033. doi:10.1001/jama.294.9.1025
The initial mixed methods study as described in this published protocol (Hansen et al., 2021) had two components: a prospective quantitative and qualitative study. Since publication of this protocol, two changes were made from the described study design which occurred as a result of low recruitment in the prospective studies, and challenges related to accessing the study site for data collection throughout the COVID-19 pandemic due to Government enforced ‘lockdowns’. The ‘lockdowns prevented all non-essential access to the hospital and as a consequence further recruitment to the study was not possible. This rapid response outlines the required key changes to the study design, approved by the University of Newcastle Human Research Ethics Committee and the participating organisation.
The first change to the protocol involved the inclusion of a retrospective quantitative study which commenced on August 2, 2022. A file audit was conducted which included all women admitted to the study site between 01/01/2016 and 30/04/2021. These dates were chosen to allow the collection of five years of data preceding the commencement of the prospective study. Inclusion criteria included all women admitted to the study site during the study timeframe comprising women who did and who did not experience seclusion during their admission. Following ethical approval, a de-identified electronic list of women admitted during the study timeframe was provided to the first author from the study...
The initial mixed methods study as described in this published protocol (Hansen et al., 2021) had two components: a prospective quantitative and qualitative study. Since publication of this protocol, two changes were made from the described study design which occurred as a result of low recruitment in the prospective studies, and challenges related to accessing the study site for data collection throughout the COVID-19 pandemic due to Government enforced ‘lockdowns’. The ‘lockdowns prevented all non-essential access to the hospital and as a consequence further recruitment to the study was not possible. This rapid response outlines the required key changes to the study design, approved by the University of Newcastle Human Research Ethics Committee and the participating organisation.
The first change to the protocol involved the inclusion of a retrospective quantitative study which commenced on August 2, 2022. A file audit was conducted which included all women admitted to the study site between 01/01/2016 and 30/04/2021. These dates were chosen to allow the collection of five years of data preceding the commencement of the prospective study. Inclusion criteria included all women admitted to the study site during the study timeframe comprising women who did and who did not experience seclusion during their admission. Following ethical approval, a de-identified electronic list of women admitted during the study timeframe was provided to the first author from the study site’s Chief Health Information Manager. The electronic list contained the medical record number of women admitted, date of admission and date of birth. Data were collected on site by AH, using the medical record number. Data which included demographic and clinical information were collected from the women’s medical record and entered directly into Research Electronic Data Capture (REDCap) (Harris et al., 2019; Harris et al., 2009); as per the prospective study reported in this published protocol (Hansen et al., 2021). Where the woman experienced seclusion, data pertaining to the seclusion event (as described in the published protocol) were collected. Data storage and analysis are unchanged and accurate as reported in the published protocol (Hansen et al., 2021).
The second change to the study design relates to the low recruitment specifically in the qualitative component of the prospective study. This resulted in the pragmatic decision to present findings as a single case study, combining both the quantitative and qualitative data of the prospective study due to one person consenting to participate in an interview. The inclusion of the single case study supports a deep understanding of the case and the phenomenon of interest (Yin, 2018). In this single case the characteristics and experience of seclusion for a woman in a secure forensic hospital were analysed. Data collected for the single case study were the same as described in the published protocol (Hansen et al., 2021). The quantitative and qualitative data collected for the single case were linked and integrated for analysis, which enhanced the understanding of the woman’s experiences.
References
Hansen, A. C., Hazelton, M., Rosina, R., & Inder, K. J. (2021). Exploring the frequency, duration and experience of seclusion for women in a forensic mental health setting: a mixed-methods study protocol. BMJ Open, 11, e044261. https://doi-org.ezproxy.u-pec.fr/10.1136/bmjopen-2020-044261
Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research electronic data capture (REDCap)—A metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform 2009;42(2):377-81.
Harris PA, Taylor R, Minor BL, Elliott V, Fernandez M, O'Neal L, et al. The REDCap consortium: Building an international community of software platform partners. J Biomed Inform 2019;95.
Yin, RK. Case study research and applications: Design and methods. Sixth edition. SAGE Publications, Inc.; 2018.
We recently read “Barriers and facilitators to use of digital health tools by healthcare practitioners and their patients, before and during the COVID-19 pandemic: a multimethods study,” which explores the critical question of how healthcare professionals adopt and use digital health technologies (DHTs).
The authors’ examination of barriers to DHT access and use on organisational and individual levels was a particularly valuable finding for their future implementation. We found the observation that some healthcare professionals (HCPs) acted as gatekeepers for patients’ access to DHTs particularly compelling. This highlights the importance of addressing biases and assumptions about the type of patients who could use and benefit from DHTs, to avoid unintentionally increasing digital health inequity. While this was not the primary focus of the study, we believe it is an important finding that should be further explored to understand how HCPs made such judgments and how they compare with patients’ perceptions. Understanding the underlying factors shaping professionals’ assumptions may provide a deeper understanding of the barriers to using digital tools. Additionally, it would have been interesting to further investigate usage patterns within the participants' geographic regions. The characteristics of these regions (e.g. socioeconomic status, demographics, digital access levels) may be associated with different adoption rates of DHTs by profe...
We recently read “Barriers and facilitators to use of digital health tools by healthcare practitioners and their patients, before and during the COVID-19 pandemic: a multimethods study,” which explores the critical question of how healthcare professionals adopt and use digital health technologies (DHTs).
The authors’ examination of barriers to DHT access and use on organisational and individual levels was a particularly valuable finding for their future implementation. We found the observation that some healthcare professionals (HCPs) acted as gatekeepers for patients’ access to DHTs particularly compelling. This highlights the importance of addressing biases and assumptions about the type of patients who could use and benefit from DHTs, to avoid unintentionally increasing digital health inequity. While this was not the primary focus of the study, we believe it is an important finding that should be further explored to understand how HCPs made such judgments and how they compare with patients’ perceptions. Understanding the underlying factors shaping professionals’ assumptions may provide a deeper understanding of the barriers to using digital tools. Additionally, it would have been interesting to further investigate usage patterns within the participants' geographic regions. The characteristics of these regions (e.g. socioeconomic status, demographics, digital access levels) may be associated with different adoption rates of DHTs by professionals. Exploring these regional differences could provide valuable socioeconomic context to inform future implementation strategies and more equitable access to DHTs.
We believe the authors’ decision to conduct additional research to understand how barriers and facilitators may have shifted due to the COVID-19 pandemic strengthened the study. It also raised our curiosity about how these barriers and facilitators may have continued to change throughout the pandemic. Data collected from HCPs at the start of the pandemic (July-August 2020) might not provide the most up-to-date insight into the evolving role of these tools. The burden on healthcare services increased exponentially while DHTs and their implementation simultaneously improved in each subsequent lockdown [1,2]. Notably, while healthcare services had begun using digital tools before the pandemic, the change was generally slow. The pandemic accelerated this transformation in Scotland, where healthcare consultations rapidly shifted from face-to-face to videoconferencing, with video appointments increasing from 20,000 in mid-2020 to over 1 million in July 2021 [1]. Future research could build on this study to generate additional insights into how the pandemic has altered HCPs’ access to and use of DHTs now that the pandemic's peak has passed.
Some research has suggested that, from a patient perspective, elevated public interest levels in digital health during the Covid-19 pandemic were not sustained [3]. Potential reasons for this include digital infrastructure and competency issues [3] and barriers to systems integration and trust [4]. This highlights the importance of understanding how barriers for HCPs to access and uptake of DHTs intersect with barriers experienced by patients. This study highlights HCPs’ perspectives of patients’ barriers; future research could generate additional insights by exploring barriers from patients’ perspectives and identifying areas of alignment and misalignment. This will be a necessary step in training HCPs in the use of DHTs with patients in a way that does not increase health inequity and digital exclusion.
References
1 Fang ML, Walker M, Wong KLY, et al. Future of digital health and community care: Exploring intended positive impacts and unintended negative consequences of COVID-19. Healthc Manage Forum. 2022;35:279–85. doi: 10.1177/08404704221107362
2 Newman KL, Jeve Y, Majumder P. Experiences and emotional strain of NHS frontline workers during the peak of the COVID-19 pandemic. Int J Soc Psychiatry. 2022;68:783–90. doi: 10.1177/00207640211006153
3 van Kessel R, Kyriopoulos I, Wong BLH, et al. The effect of the COVID-19 pandemic on digital health-seeking behavior: Big data interrupted time-series analysis of Google Trends. J Med Internet Res. 2023;25:e42401. doi: 10.2196/42401
4 Peek N, Sujan M, Scott P. Digital health and care: emerging from pandemic times. BMJ Health Care Inform. 2023;30:e100861. doi: 10.1136/bmjhci-2023-100861
We have read the article by Murray et al interestingly, the article was engaging and thought provoking [1]. With the advancements of digitalization technology in the health sector, diabetes care and management have also experienced modifications and betterment. Various newer technologies cater to individual conditions & needs and provide personalized treatment. Device-based technologies such as continuous glucose monitoring (CGM) linked to closed-loop insulin delivery systems, insulin pumps, and wearable devices linked with mobile apps have made the self-management of diabetes possible regularly. The web assisted interventions can be an asset for diabetes management in a developing country like India where the number of people with diabetes are currently is around 40.9 million and is expected to rise to 69.9 million by 2025 unless urgent preventive steps are taken [2]. The prevalence in the recent report by the Indian Council of Medical Research- India Diabetes (ICMR-INDIAB) study was observed to be 11.4% [3]. The scenario in the tribal population of India is more or less similar as the diabetes prevalence in tribal areas was observed to be from 0.7-10.1% [4] which is an alarming figure, but still, a systematic tribe-wise prevalence data is meager. Also, land alienation, lack of health management infrastructure, low connectivity, and technological challenges add up to their condition. While various technologies are challenging to implement due to electricity, network...
We have read the article by Murray et al interestingly, the article was engaging and thought provoking [1]. With the advancements of digitalization technology in the health sector, diabetes care and management have also experienced modifications and betterment. Various newer technologies cater to individual conditions & needs and provide personalized treatment. Device-based technologies such as continuous glucose monitoring (CGM) linked to closed-loop insulin delivery systems, insulin pumps, and wearable devices linked with mobile apps have made the self-management of diabetes possible regularly. The web assisted interventions can be an asset for diabetes management in a developing country like India where the number of people with diabetes are currently is around 40.9 million and is expected to rise to 69.9 million by 2025 unless urgent preventive steps are taken [2]. The prevalence in the recent report by the Indian Council of Medical Research- India Diabetes (ICMR-INDIAB) study was observed to be 11.4% [3]. The scenario in the tribal population of India is more or less similar as the diabetes prevalence in tribal areas was observed to be from 0.7-10.1% [4] which is an alarming figure, but still, a systematic tribe-wise prevalence data is meager. Also, land alienation, lack of health management infrastructure, low connectivity, and technological challenges add up to their condition. While various technologies are challenging to implement due to electricity, network connectivity, infrastructure, and storage facilities, some technologies can be implemented easily with the joint approach of primary health care staff, governmental & non-governmental organizations, and people with diabetes themselves. The situation demands a tailored multifaceted approach for implementing the technological-based remedies in tribal settings of India as it will increase the quality of life in these areas.
The web-based interventions like virtual group assessment (VGA), clinical decision support system (CDSS) can hold promise in diabetes management in tribal setting, which can get the population access to health expert in the fields even after sitting in a remote location. Clinical decision support systems can become a vital tool for improving diabetes care in tribal settings as it uses data analytics and computational power to determine relevant patterns from patients' medication history and glycemic records [5]. Then create personalized prescription strategies for their individual needs. For VGA, the primary health care workers (Accredited Social Health Activist (ASHA), Anganwadi workers (AWW) of tribal settings can be provided with the computers or equivalent devices and with their help the concerned people can directly consult the expert health care groups [6]. As technology continues to advance the future of diabetes management is moving toward solutions that are user-centred and effective.
Implementing web-based interventions is challenging in tribal settings as it has language and cultural barriers, as technology may be unfamiliar or culturally mismatched, requiring extensive education and community engagement. It will be helpful if the interface could be designed in local languages. Ministry of Tribal Affairs, Government of India has also shown its concern about impowering the digitalization in tribal groups through Digital India scheme. [7] Also, training camps and awareness programs can be organised by the local health staff and administration to make the interface familiar to the population. Given these multifaceted challenges, a holistic and culturally sensitive approach, taking into account the unique needs and circumstances of tribal areas, is imperative to ensure the successful integration of web-based interventions in diabetes management.
1. Murray E, Sweeting M, Dack C, Pal K, Modrow K, Hudda M, Li J, Ross J, Alkhaldi G, Barnard M, Farmer A, Michie S, Yardley L, May C, Parrott S, Stevenson F, Knox M, Patterson D. Web-based self-management support for people with type 2 diabetes (HeLP-Diabetes): randomised controlled trial in English primary care. BMJ Open. 2017 Sep 27;7(9):e016009. doi: 10.1136/bmjopen-2017-016009.
2. Pradeepa, R., & Mohan, V. (2021). Epidemiology of type 2 diabetes in India. Indian Journal of Ophthalmology, 69(11), 2932-2938. doi: 10.4103/ijo.IJO_1627_21.
3. Anjana, R. M., Unnikrishnan, R., Deepa, M., Pradeepa, R., Tandon, N., Das, A. K., ... & Mohan, V. (2023). Metabolic non-communicable disease health report of India: the ICMR-INDIAB national cross-sectional study (ICMR-INDIAB-17). The Lancet Diabetes & Endocrinology, 11(7), 474-489. doi: 10.1016/S2213-8587(23)00119-5.
4. Shriraam, V., Mahadevan, S., & Arumugam, P. (2021). Prevalence and Risk Factors of Diabetes, Hypertension, and Other Non-Communicable Diseases in a Tribal Population in South India. Indian Journal of Endocrinology and Metabolism, 25(4), 313-319. doi: 10.4103/ijem.ijem_298_21.
5. Singh K, Chakma T, Shrivastava S. Type 1 Diabetes Management Among Tribes: How Virtual Group Appointments Approach May Be Beneficial. J Diabetes Sci Technol. 2023 Jul;17(4):1121-1122. doi: 10.1177/19322968231170889.
6. Singh K, Chakma T, Nagwanshi A, Shrivastava S. Can the Clinical Decision Support System Untangle the Difficulties in the Diabetes Management of Indian Tribes? J Diabetes Sci Technol. 2024 Mar;18(2):526-527. doi: 10.1177/19322968231222488.
7. Kapoor, Naval & Maurya, Ashutosh & Raman, Raghu & Govind, Kumar & Nedungadi, Prema. (2021). Digital India eGovernance Initiative for Tribal Empowerment: Performance Dashboard of the Ministry of Tribal Affairs. 10.1007/978-981-16-0882-7_92.
The recent paper “Profiles of health literacy and digital health literacy in clusters of hospitalised patients: a single-centre, cross-sectional study” generates insights into the health literacy characteristics of patients. We commend the authors for their efforts to enhance health equity by examining the types of patients who may require additional health literacy support when hospitalised. The authors’ comprehensive analysis of both health literacy and digital health literacy offers a strong foundation for future research, particularly in enhancing health equity by identifying vulnerable populations in hospital settings. This rapid response aims to emphasise two key areas of the analysis where further elaboration could enhance the study's quality and insights: the potential influence of the study's context on the findings and the practical implications of the generated clusters.
Health literacy refers to an individual’s ability to maintain health through knowledge, self-management, and collaboration with health professionals [1]. The paper defines health and digital health literacy as involving “access, understanding, appraisal, and use” of health information. The measurement tools reflect this broad perspective. Data was collected from a single clinical setting, and while the authors note limited generalisability, more discussion on the influence of contextual factors would have been helpful. The field would benefit from further c...
The recent paper “Profiles of health literacy and digital health literacy in clusters of hospitalised patients: a single-centre, cross-sectional study” generates insights into the health literacy characteristics of patients. We commend the authors for their efforts to enhance health equity by examining the types of patients who may require additional health literacy support when hospitalised. The authors’ comprehensive analysis of both health literacy and digital health literacy offers a strong foundation for future research, particularly in enhancing health equity by identifying vulnerable populations in hospital settings. This rapid response aims to emphasise two key areas of the analysis where further elaboration could enhance the study's quality and insights: the potential influence of the study's context on the findings and the practical implications of the generated clusters.
Health literacy refers to an individual’s ability to maintain health through knowledge, self-management, and collaboration with health professionals [1]. The paper defines health and digital health literacy as involving “access, understanding, appraisal, and use” of health information. The measurement tools reflect this broad perspective. Data was collected from a single clinical setting, and while the authors note limited generalisability, more discussion on the influence of contextual factors would have been helpful. The field would benefit from further consideration of the social context of health decision-making and the communication skills of health professionals [2]. Profiling patients in a setting and circumstance likely to influence responses to the measurement tools employed directly suggests the authors’ broad agreement with this view. The paper could further build on its contribution by exploring health literacy as an enduring individual capacity and a more context-dependent and dynamic construct. Including a description of the digital infrastructure in the study’s setting could have provided valuable insights into how this context influenced the findings. This would offer implications for broader applications. The work lays a strong foundation for understanding health literacy, which future research can expand upon by incorporating these additional contextual factors.
The impact of the findings could be enhanced by improving the visualisation of the clusters and providing a more detailed explanation of their practical implications. Visual representations, such as radar charts and cluster plots, can facilitate more efficient interpretation of findings. The six clusters could also be labelled with memorable names to make them more accessible and easier to recall. The diverse health literacy and digital health literacy profiles of hospitalised patients highlight the need for tailored interventions. The practical application of the findings may be further strengthened by directly linking the profile of each cluster to interventions in healthcare settings. For instance, visual aids (e.g., picture-based education) are impactful for people with low health literacy [3–5]. In this case, the clusters with low health literacy and digital health literacy identified from this study might benefit from suggested tailored educational materials.
This study offers important insights into the health and digital literacy profiles of hospitalised patients, which emphasise the need for tailored interventions. Considering contextual factors like digital infrastructure could deepen understanding. Improving the visualisation of clusters and connecting them to practical healthcare interventions would enhance the findings. Building on the six clusters identified in this study, future research could expand on these clusters by creating predictive models to optimise resource allocation and improve patient care.
References
[1] Liu C, Wang D, Liu C, Jiang J, Wang X, Chen H, et al. What is the meaning of health literacy? A systematic review and qualitative synthesis. Fam Med Community Health 2020;8:e000351.
[2] McKenna VB, Sixsmith J, Barry MM. The relevance of context in understanding health literacy skills: Findings from a qualitative study. Health Expect 2017;20:1049–60.
[3] Sudore RL, Schillinger D. Interventions to improve care for patients with limited health literacy. J Clin Outcomes Manag 2009;16:20–9.
[4] Park J, Zuniga J. Effectiveness of using picture-based health education for people with low health literacy: An integrative review. Cogent Med 2016;3:1264679.
[5] Mbanda N, Dada S, Bastable K, Ingalill G-B, Ralf W S. A scoping review of the use of visual aids in health education materials for persons with low-literacy levels. Patient Educ Couns 2021;104:998–1017.
I feel that this study leaves me with a sense of being on safari to
catch a glimpse of the 'Big Five' - as a health professional from South
Africa I recognize that it is only but interesting to note the first world
trends in pre-eclampsia, but it does not provide any sustainable short or
long term treatment modalities, where it is so urgently required.
Hypertension during pregnancy has been attributed to one of t...
I feel that this study leaves me with a sense of being on safari to
catch a glimpse of the 'Big Five' - as a health professional from South
Africa I recognize that it is only but interesting to note the first world
trends in pre-eclampsia, but it does not provide any sustainable short or
long term treatment modalities, where it is so urgently required.
Hypertension during pregnancy has been attributed to one of the top
five causes of maternal deaths in South Africa (Blaauw and Penn-Kekana,
2010). The South African Health Review, 2010, admits that despite an
increase in antenatal care coverage and skilled birth attendance, maternal
mortality is still on the rise (Blaauw and Penn-Kekana, 2010). While other
interventions like low dose asprin and multi-vitamin supplementation do
play a role, in this study elective delivery before the due date was one
of the primary causes attributed to the trend in the decrease of pre-
eclampsia. I am not convinced that elective caesarean sections is the
ideal, as this method of delivery may contribute to other causes of
morbidity and mortality, not to mention increased costs of surgical
delivery, especially in the African setting.
The abovementioned article makes some valuable contributions to the
understanding of international trends in pre-eclampsia. However, once
again it raises the issue of what we interpret as 'international'. My
concern about these trends being acknowledged as international is that the
study takes place across borders but it does not necessarily apply to the
global context.
The study lacks inclusion of developing nations, and thus does not
take in consideration the countries urgently seeking solutions, in their
urgency to reach Millenium Development Goals and reduce maternal mortality
(MDGs 4 and 5). I would urge that cognizance be taken of the location of
the countries used in the study.
References:
Blaauw, D & Penn-Kekana, M. 2010. In: Fonn, S., Padarath, A.
South African Health Review. Durban: Health Systems Trust. Available
online: http://www.hst.org.za/publications/876
Monden and Smits raise a valid point that "the countries that reached
a certain e(0) first are not the most equal countries at that level of
e(0)" [1]. We do not dispute this. In fact, we performed a similar
analysis in the supporting material (Figure S4) [2]. At each e(0) level,
our figure compared the life disparity level of e(0) leaders to the
average life...
Monden and Smits raise a valid point that "the countries that reached
a certain e(0) first are not the most equal countries at that level of
e(0)" [1]. We do not dispute this. In fact, we performed a similar
analysis in the supporting material (Figure S4) [2]. At each e(0) level,
our figure compared the life disparity level of e(0) leaders to the
average life disparity level of all other countries in the HMD, separately
for men and women. For some e(0) levels, the life disparity of the e(0)
leader was higher than average, for other levels it was lower. Overall,
there was no clear trend. Thus we concluded: "While leaders are the first
to reduce premature mortality, thereby reducing life disparity, laggards
on average follow with similar reductions in life disparity alongside life
expectancy increases."
While we find no clear difference between the life expectancy leaders
and the laggards, the Figure 1 of M&S indicates that leaders have higher
lifespan inequality on average at each life expectancy level. These
differences are likely stemming from differences in datasets. M&S use a
mixture of life tables from various sources including published papers,
the WHO life table database, the HLTD and the HMD [3]. Some of these life
tables are abridged, while others are full. Some would have been exposed
to data smoothing, others not. Our life tables are drawn entirely from
the Human Mortality Database [4]. This database has high data quality
inclusion criteria and follows strict protocols to ensure a good level of
comparability. Thus it could be that when more countries are included
into the analysis, instead of laggards having similar life disparity
levels to leaders, they in fact have lower levels of life disparity. Or
this simply could be a data artefact.
Nevertheless, neither result would dispute our main finding, which is
that life expectancy leaders have low life disparity levels in any given
year. This is because the life expectancy leaders are at the frontier of
reducing premature mortality, which also reduces life disparity. As we
concluded: "It is not a question of either long life or low disparity:
countries can achieve both by averting premature deaths". We fully agree
with M&S that further research should explore the paths that life
expectancy laggards can take to reduce inequality to levels even lower
than those achieved earlier by the leaders. There is no reason to think
that this is not possible.
References:
[1] Monden C, Smits J. Life expectancy record holders not most equal
if compared within life expectancy levels. BMJOpen eLetter 7 Sept 2012:
http://bmjopen.bmj.com.ezproxy.u-pec.fr/content/1/1/e000128.full/reply#bmjopen_el_6407
[2] Vaupel JW, Zhang Z, Van Raalte A.A. Life expectancy and
disparity: an international comparison of life table data. BMJ Open
2011;1:e000128 doi:10.1136/bmjopen-2011-000128. [See supplementary
material: http://bmjopen.bmj.com.ezproxy.u-pec.fr/content/suppl/2011/08/03/bmjopen-2011-
000128.DC1/SupplementaryMaterial.pdf]
[3] The full list of data sources can be found at
www.lengthoflife.org.
[4] Human Mortality Database. University of California, Berkeley
(USA), and Max Planck Institute for Demographic Research (Germany).
http://www.mortality.org.
Data files that support this article are available at the Dryad
repository:
BMJ open Access MHRA Field Safety Notices 2006_2010
MHRA Field safety notices_FDA 19_5_11
When using this data, please cite the original article and the Dryad
data package. The data package should be cited as follows:
Heneghan C, Thompson M, Billingsley M, Cohen D (2011) Data from:
Medical-device recalls in the UK and the device-regulation process:
retrospective review of safety notices and alerts. Dryad Digital
Repository. doi:10.5061/dryad.585t4
In this article KR Smith makes three important points in the
conclusion. Firstly, that it may be useful for the General Medical Council to clarify the extent to which Complementary and
Alternative Medicine (CAM) should be incorporated into the curriculum.
Secondly, he suggests that current CAM education appears to exist
primarily as a means of educating future doctors on the modalities that
their patients may use or reque...
In this article KR Smith makes three important points in the
conclusion. Firstly, that it may be useful for the General Medical Council to clarify the extent to which Complementary and
Alternative Medicine (CAM) should be incorporated into the curriculum.
Secondly, he suggests that current CAM education appears to exist
primarily as a means of educating future doctors on the modalities that
their patients may use or request. And thirdly, he observes that some
forms of pedagogy arguably risk students assimilating CAM advocacy in an
uncritical fashion. These conclusions are pertinent in a country such as
Kenya where a large proportion of the population use CAM partly due to
culture and tradition and partly due to inability to afford conventional
medicine. At the same time the teaching of complementary and alternative
medicine to health professionals is far from fully developed with varying
curriculum content and teaching and learning methods on the one hand, and
the ongoing debate on CAM integration in health care, on the other. There
is also acknowledgement of the changes which may need to be effected in
order to improve medical education with regard to CAM which in turn will
have effect its full inclusion safety and the efficacy in the healthcare
system.
It is true that guidance from the regulatory authority in relation to
teaching CAM in health professional schools will be necessary. However, in
addition this should be in the context of a structured needs assessment
incorporating key stakeholders including input of conventional medical
practitioners, CAM practitioners, the faculty, students, and the
community (the consumers of CAM). I also agree with the author that CAM
education should address more than preparing the future health service
practitioners to respond to patient requests. The students need to be
prepared to critically think and engage CAM practitioners and literature
as well as also be prepared to make informed to choice on the benefits of
CAM for their own personal consumption self-awareness and self-care.
Thus, apart from lectures and other didactic approaches opportunities to
experience CAM personally, particularly mind-body approaches and stress
management, as part of self-care should provide to student opportunity for
experiential learning. The students who learn the fundamentals of self-awareness and self-care will also be better able to teach their patients
to care for themselves. Therefore medical education should include
opportunities to experience CAM approaches, such as meditation and
relaxation therapy, for students who personally may benefit from these
approaches during their stressful journey through health professionals
training. The faculty will also understand first-hand the importance of
experiential learning and how this initiative in CAM could actually
advance learning in terms of broader issues, such as improved patient-provider communication, and heightened student and faculty self-awareness
and self-care while also addressing personal biases in clinical
interactions, personal health and wellness, or training in mind-body
interventions.
Khalifeh et al. conducted a meta-analysis to evaluate the risk reduction of head and neck (HN) cancer following smoking cessation (1). The authors analyzed data from 65 studies, which had been published until June 2022. They were composed of 5 cohort and 60 case-control studies. Relative risks (RRs) (95% confidence intervals [CIs]) of former smokers compared with current smokers for HN cancer was 0.40 (0.35 to 0.46). By using 37 studies, RR (95% CI) per 10-year increase in smoking cessation was 0.47 (0.43 to 0.52). I present information from a prospective study, which presents a mortality risk.
Lee et al. reported the association between the duration of abstinence, overall and HN-specific mortality (2). Former smokers presented a significant risk reduction in HN-specific mortality, but there was no significant difference in the risk of noncancer mortality. Compared with current smokers, former smokers who quit >10 years before diagnosis presented the adjusted hazard ratios (95% CIs) of 0.72 (0.56 to 0.93) and 0.64 (0.46 to 0.91) for overall and HN-specific mortality. They emphasized that long-term abstinence over 10 years had a significant risk reduction in overall and HN-specific mortality. Although heterogeneity in each group of a meta-analysis was extremely high, risk assessment with incidence/prevalence may have some difficulties of data collections. Lee et al. conducted sensitivity analyses by the types of treatment, and radiation therapy only showed a signi...
Show MoreDear Editor,
I am writing in response to the article, “Association between sleep quality and uncertainty stress among healthcare professionals in hospitals in China,” recently published in BMJ Open. The study reveals the high prevalence of insomnia and uncertainty stress among healthcare workers, which is an important contribution. Furthermore, the use of validated tools such as the Athens Insomnia Scale (AIS) enhances the reliability of the findings, offering solid evidence for the urgent need to address healthcare workers’ mental well-being.
However, I would like to offer some additional suggestions that could make a further discussion.
Firstly, regional and hospital-level differences are important factors that cannot be overlooked. The study covers only three provinces, yet healthcare resources within these provinces vary significantly, which introduces potential variability in stress sources. For instance, tertiary hospitals in major cities, such as Hangzhou in Zhejiang province, often experience high levels of stress due to large patient volumes and complex cases. In contrast, healthcare professionals in less resourced areas, such as Lishui in Zhejiang province, are facing chronic stress from staff shortages and inadequate infrastructure. Understanding these regional disparities can provide a more detailed view of how healthcare environments influence sleep quality.
Secondly, the timing of data collection also affects the study’s findings. T...
Show MoreThe initial mixed methods study as described in this published protocol (Hansen et al., 2021) had two components: a prospective quantitative and qualitative study. Since publication of this protocol, two changes were made from the described study design which occurred as a result of low recruitment in the prospective studies, and challenges related to accessing the study site for data collection throughout the COVID-19 pandemic due to Government enforced ‘lockdowns’. The ‘lockdowns prevented all non-essential access to the hospital and as a consequence further recruitment to the study was not possible. This rapid response outlines the required key changes to the study design, approved by the University of Newcastle Human Research Ethics Committee and the participating organisation.
The first change to the protocol involved the inclusion of a retrospective quantitative study which commenced on August 2, 2022. A file audit was conducted which included all women admitted to the study site between 01/01/2016 and 30/04/2021. These dates were chosen to allow the collection of five years of data preceding the commencement of the prospective study. Inclusion criteria included all women admitted to the study site during the study timeframe comprising women who did and who did not experience seclusion during their admission. Following ethical approval, a de-identified electronic list of women admitted during the study timeframe was provided to the first author from the study...
Show MoreDear Editor,
We recently read “Barriers and facilitators to use of digital health tools by healthcare practitioners and their patients, before and during the COVID-19 pandemic: a multimethods study,” which explores the critical question of how healthcare professionals adopt and use digital health technologies (DHTs).
The authors’ examination of barriers to DHT access and use on organisational and individual levels was a particularly valuable finding for their future implementation. We found the observation that some healthcare professionals (HCPs) acted as gatekeepers for patients’ access to DHTs particularly compelling. This highlights the importance of addressing biases and assumptions about the type of patients who could use and benefit from DHTs, to avoid unintentionally increasing digital health inequity. While this was not the primary focus of the study, we believe it is an important finding that should be further explored to understand how HCPs made such judgments and how they compare with patients’ perceptions. Understanding the underlying factors shaping professionals’ assumptions may provide a deeper understanding of the barriers to using digital tools. Additionally, it would have been interesting to further investigate usage patterns within the participants' geographic regions. The characteristics of these regions (e.g. socioeconomic status, demographics, digital access levels) may be associated with different adoption rates of DHTs by profe...
Show MoreWe have read the article by Murray et al interestingly, the article was engaging and thought provoking [1]. With the advancements of digitalization technology in the health sector, diabetes care and management have also experienced modifications and betterment. Various newer technologies cater to individual conditions & needs and provide personalized treatment. Device-based technologies such as continuous glucose monitoring (CGM) linked to closed-loop insulin delivery systems, insulin pumps, and wearable devices linked with mobile apps have made the self-management of diabetes possible regularly. The web assisted interventions can be an asset for diabetes management in a developing country like India where the number of people with diabetes are currently is around 40.9 million and is expected to rise to 69.9 million by 2025 unless urgent preventive steps are taken [2]. The prevalence in the recent report by the Indian Council of Medical Research- India Diabetes (ICMR-INDIAB) study was observed to be 11.4% [3]. The scenario in the tribal population of India is more or less similar as the diabetes prevalence in tribal areas was observed to be from 0.7-10.1% [4] which is an alarming figure, but still, a systematic tribe-wise prevalence data is meager. Also, land alienation, lack of health management infrastructure, low connectivity, and technological challenges add up to their condition. While various technologies are challenging to implement due to electricity, network...
Show MoreDear Editor,
The recent paper “Profiles of health literacy and digital health literacy in clusters of hospitalised patients: a single-centre, cross-sectional study” generates insights into the health literacy characteristics of patients. We commend the authors for their efforts to enhance health equity by examining the types of patients who may require additional health literacy support when hospitalised. The authors’ comprehensive analysis of both health literacy and digital health literacy offers a strong foundation for future research, particularly in enhancing health equity by identifying vulnerable populations in hospital settings. This rapid response aims to emphasise two key areas of the analysis where further elaboration could enhance the study's quality and insights: the potential influence of the study's context on the findings and the practical implications of the generated clusters.
Health literacy refers to an individual’s ability to maintain health through knowledge, self-management, and collaboration with health professionals [1]. The paper defines health and digital health literacy as involving “access, understanding, appraisal, and use” of health information. The measurement tools reflect this broad perspective. Data was collected from a single clinical setting, and while the authors note limited generalisability, more discussion on the influence of contextual factors would have been helpful. The field would benefit from further c...
Show MoreI feel that this study leaves me with a sense of being on safari to catch a glimpse of the 'Big Five' - as a health professional from South Africa I recognize that it is only but interesting to note the first world trends in pre-eclampsia, but it does not provide any sustainable short or long term treatment modalities, where it is so urgently required.
Hypertension during pregnancy has been attributed to one of t...
Alyson A. van Raalte, James W. Vaupel, Zhen Zhang
Monden and Smits raise a valid point that "the countries that reached a certain e(0) first are not the most equal countries at that level of e(0)" [1]. We do not dispute this. In fact, we performed a similar analysis in the supporting material (Figure S4) [2]. At each e(0) level, our figure compared the life disparity level of e(0) leaders to the average life...
Data files that support this article are available at the Dryad repository:
BMJ open Access MHRA Field Safety Notices 2006_2010 MHRA Field safety notices_FDA 19_5_11
When using this data, please cite the original article and the Dryad data package. The data package should be cited as follows:
Heneghan C, Thompson M, Billingsley M, Cohen D (2011) Data from: Medical-device recalls in the UK an...
In this article KR Smith makes three important points in the conclusion. Firstly, that it may be useful for the General Medical Council to clarify the extent to which Complementary and Alternative Medicine (CAM) should be incorporated into the curriculum. Secondly, he suggests that current CAM education appears to exist primarily as a means of educating future doctors on the modalities that their patients may use or reque...
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