Critical to care Armstrong, Pat; Armstrong, Hugh; Scott-Dixon, Krista
Critical to care,
c2008, 20080628, 2008, 2008-01-01, 2008-06-14, 20080101
eBook
Who counts as a health care worker? The question of where we draw the line between health care workers and non-health care workers is not merely a matter of academic nicety or a debate without ...consequences for care. It is a central issue for policy development because the definition often results in a division among workers in ways that undermine care.
Critical to Careuses a wide range of evidence to reveal the contributions that those who provide personal care, who cook, clean, keep records, and do laundry make to health services. As a result of current reforms, these workers are increasingly treated as peripheral even though the research on what determines health demonstrates that their work is essential. The authors stress the invisibility and undervaluing of 'women's work' as well as the importance of context in understanding how this work is defined and treated.
Through a gendered analysis,Critical to Careestablishes a basis for discussing research, policy, and other actions in relation to the work of thousands of marginalized women and men every day.
The recent COVID-19 pandemic has raised the visibility of health care workers to the level of public heroes. We study this phenomenon by exploring how nonphysician health care workers, who ...traditionally believed they were invisible and undervalued, perceive their newfound elevated status during the pandemic. Drawing from a qualitative study of 164 health care workers, we find that participants interpreted the sudden visibility and social valorization of their work as temporary and treated it with skepticism, incredulity, and as devoid of genuinely transformative power. We seek to contribute to the recent call to develop novel approaches to understanding the contours of the paradoxical nature of invisibility in the workplace by offering insights into what makes "invisible" workers accept or reject publicly driven elevation in their sudden social valorization.
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CEKLJ, FFLJ, NUK, ODKLJ, PEFLJ, UPUK
•Commonly reported symptoms are headache, throat pain and lethargy.•A large number of healthcare workers report more than four symptoms.•Those with physical symptoms had higher rates of depression, ...anxiety, stress, PTSD.•Those with physical symptoms had higher mean scores in the IES-R, DASS subscales.•Association between physical symptoms and psychological outcomes may be bidirectional.
Since the declaration of the coronavirus 2019 (COVID-19) outbreak as pandemic, there are reports on the increased prevalence of physical symptoms observed in the general population. We investigated the association between psychological outcomes and physical symptoms among healthcare workers.
Healthcare workers from 5 major hospitals, involved in the care for COVID-19 patients, in Singapore and India were invited to participate in a study by performing a self-administered questionnaire within the period of February 19 to April 17, 2020. Healthcare workers included doctors, nurses, allied healthcare workers, administrators, clerical staff and maintenance workers. This questionnaire collected information on demographics, medical history, symptom prevalence in the past month, Depression Anxiety Stress Scales (DASS-21) and the Impact of Events Scale-Revised (IES-R) instrument. The prevalence of physical symptoms displayed by healthcare workers and the associations between physical symptoms and psychological outcomes of depression, anxiety, stress, and post-traumatic stress disorder (PTSD) were evaluated.
Out of the 906 healthcare workers who participated in the survey, 48 (5.3%) screened positive for moderate to very-severe depression, 79 (8.7%) for moderate to extremely-severe anxiety, 20 (2.2%) for moderate to extremely-severe stress, and 34 (3.8%) for moderate to severe levels of psychological distress. The commonest reported symptom was headache (32.3%), with a large number of participants (33.4%) reporting more than four symptoms. Participants who had experienced symptoms in the preceding month were more likely to be older, have pre-existing comorbidities and a positive screen for depression, anxiety, stress, and PTSD. After adjusting for age, gender and comorbidities, it was found that depression (OR 2.79, 95% CI 1.54–5.07, p = 0.001), anxiety (OR 2.18, 95% CI 1.36–3.48, p = 0.001), stress (OR 3.06, 95% CI 1.27–7.41, p = 0.13), and PTSD (OR 2.20, 95% CI 1.12–4.35, p = 0.023) remained significantly associated with the presence of physical symptoms experienced in the preceding month. Linear regression revealed that the presence of physical symptoms was associated with higher mean scores in the IES-R, DASS Anxiety, Stress and Depression subscales.
Our study demonstrates a significant association between the prevalence of physical symptoms and psychological outcomes among healthcare workers during the COVID-19 outbreak. We postulate that this association may be bi-directional, and that timely psychological interventions for healthcare workers with physical symptoms should be considered once an infection has been excluded.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Background
Resilience can be defined as the maintenance or quick recovery of mental health during or after periods of stressor exposure, which may result from a potentially traumatising event, ...challenging life circumstances, a critical life transition phase, or physical illness. Healthcare professionals, such as nurses, physicians, psychologists and social workers, are exposed to various work‐related stressors (e.g. patient care, time pressure, administration) and are at increased risk of developing mental disorders. This population may benefit from resilience‐promoting training programmes.
Objectives
To assess the effects of interventions to foster resilience in healthcare professionals, that is, healthcare staff delivering direct medical care (e.g. nurses, physicians, hospital personnel) and allied healthcare staff (e.g. social workers, psychologists).
Search methods
We searched CENTRAL, MEDLINE, Embase, 11 other databases and three trial registries from 1990 to June 2019. We checked reference lists and contacted researchers in the field. We updated this search in four key databases in June 2020, but we have not yet incorporated these results.
Selection criteria
Randomised controlled trials (RCTs) in adults aged 18 years and older who are employed as healthcare professionals, comparing any form of psychological intervention to foster resilience, hardiness or post‐traumatic growth versus no intervention, wait‐list, usual care, active or attention control. Primary outcomes were resilience, anxiety, depression, stress or stress perception and well‐being or quality of life. Secondary outcomes were resilience factors.
Data collection and analysis
Two review authors independently selected studies, extracted data, assessed risks of bias, and rated the certainty of the evidence using the GRADE approach (at post‐test only).
Main results
We included 44 RCTs (high‐income countries: 36). Thirty‐nine studies solely focused on healthcare professionals (6892 participants), including both healthcare staff delivering direct medical care and allied healthcare staff. Four studies investigated mixed samples (1000 participants) with healthcare professionals and participants working outside of the healthcare sector, and one study evaluated training for emergency personnel in general population volunteers (82 participants). The included studies were mainly conducted in a hospital setting and included physicians, nurses and different hospital personnel (37/44 studies).
Participants mainly included women (68%) from young to middle adulthood (mean age range: 27 to 52.4 years). Most studies investigated group interventions (30 studies) of high training intensity (18 studies; > 12 hours/sessions), that were delivered face‐to‐face (29 studies). Of the included studies, 19 compared a resilience training based on combined theoretical foundation (e.g. mindfulness and cognitive‐behavioural therapy) versus unspecific comparators (e.g. wait‐list). The studies were funded by different sources (e.g. hospitals, universities), or a combination of different sources. Fifteen studies did not specify the source of their funding, and one study received no funding support.
Risk of bias was high or unclear for most studies in performance, detection, and attrition bias domains.
At post‐intervention, very‐low certainty evidence indicated that, compared to controls, healthcare professionals receiving resilience training may report higher levels of resilience (standardised mean difference (SMD) 0.45, 95% confidence interval (CI) 0.25 to 0.65; 12 studies, 690 participants), lower levels of depression (SMD −0.29, 95% CI −0.50 to −0.09; 14 studies, 788 participants), and lower levels of stress or stress perception (SMD −0.61, 95% CI −1.07 to −0.15; 17 studies, 997 participants). There was little or no evidence of any effect of resilience training on anxiety (SMD −0.06, 95% CI −0.35 to 0.23; 5 studies, 231 participants; very‐low certainty evidence) or well‐being or quality of life (SMD 0.14, 95% CI −0.01 to 0.30; 13 studies, 1494 participants; very‐low certainty evidence). Effect sizes were small except for resilience and stress reduction (moderate). Data on adverse effects were available for three studies, with none reporting any adverse effects occurring during the study (very‐low certainty evidence).
Authors' conclusions
For healthcare professionals, there is very‐low certainty evidence that, compared to control, resilience training may result in higher levels of resilience, lower levels of depression, stress or stress perception, and higher levels of certain resilience factors at post‐intervention.
The paucity of medium‐ or long‐term data, heterogeneous interventions and restricted geographical distribution limit the generalisability of our results. Conclusions should therefore be drawn cautiously. The findings suggest positive effects of resilience training for healthcare professionals, but the evidence is very uncertain. There is a clear need for high‐quality replications and improved study designs.
Healthcare workers, who are at the forefront of the fight against COVID-19, are particularly susceptible to physical and mental health consequences such as anxiety and depression. The aim of this ...umbrella review of meta-analyses is to determine the prevalence of anxiety and depression among healthcare workers during the COVID-19 pandemic.
Using relevant keywords, data resources including PubMed, Scopus, Web of Science, Cochrane, ProQuest, Science Direct, Google Scholar and Embase were searched to obtain systematic reviews and meta-analyses reporting the prevalence of anxiety and depression among healthcare workers during the COVID-19 pandemic from the beginning of January to the end of October 2020. The random effects model was used for meta-analysis, and the I2 index was employed to assess heterogeneity among studies. Data was analyzed using STATA 14 software.
In the primary search, 103 studies were identified, and ultimately 7 studies were included in the umbrella review. The results showed that the overall prevalence of anxiety and depression among healthcare workers during the COVID-19 pandemic was 24.94% (95% CI: 21.83–28.05, I2 = 0.0%, P = 0.804) and 24.83% (95% CI: 21.41–28.25, I2 = 0.0%, P = 0.897), respectively.
This umbrella review shows that the prevalence of anxiety and depression is relatively high among healthcare workers during the COVID-19 pandemic. Healthcare workers should be provided with resources to minimize this risk.
•During pandemic, healthcare workers are susceptible to mental disorders.•Healthcare workers showed high prevalence of anxiety and depression.•Healthcare workers should be educated how to cope with mental health disorders.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
COVID-19 affected our mental health as well as our physical health. In this study, the anxiety and hopelessness levels of healthcare workers and non-healthcare workers and the factors affecting them ...were evaluated in Turkey. Beck Hopelessness Scale and State-Trait Anxiety Inventory (STAI) was applied online to participants. Totally 2156 individuals were included in the study and 52.0% (n:1121) of them are healthcare workers. The hopelessness and state anxiety levels of healthcare workers were higher than non-healthcare workers. Nurses' hopelessness levels are higher than doctors, and state anxiety levels are higher than both doctors and other healthcare workers. Anxiety and hopelessness levels were higher in women, those living with a high-risk individual at home during the pandemic, those who had difficulty in caring for their children, and those whose income decreased. Anxiety levels are an important predictor of hopelessness. The increase in anxiety levels explained 28.9% of the increase in hopelessness levels. Increased working hours is one of the important factors affecting anxiety. As a conclusion, healthcare workers were more affected psychologically in the COVID-19 pandemic compared to the society. Nurses were affected more than other healthcare workers. It is important to identify the factors affecting anxiety, hopelessness, and individuals who may be more psychologically affected during the pandemic. An important contribution can be made to the protection of public health by ensuring that psychosocial interventions for high-risk groups are planned in advance.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Healthcare workers (HCWs) are at the frontline of the COVID-19 pandemic and identified as a priority target group for COVID-19 vaccines. We aimed to determine COVID-19 vaccine acceptance rate in HCWs ...in France.
We conducted an anonymous survey from 26th March to 2nd July 2020. The primary endpoint was the intention to get vaccinated against COVID-19 if a vaccine was available.
Two-thousand and forty-seven HCWs answered the survey; women accounted for 74% of respondents. Among respondents, 1.554 (76.9%, 95% confidence interval 75.1–78.9) would accept a COVID-19 vaccine. Older age, male gender, fear about COVID-19, individual perceived risk and flu vaccination during previous season were associated with hypothetical COVID-19 vaccine acceptance. Nurses and assistant nurses were less prone to accept vaccination against COVID-19 than physicians. Vaccine hesitancy was associated with a decrease in COVID-19 vaccine acceptance. Flu vaccine rate was 57.3% during the previous season, and 54.6% of the respondents had the intention to get a flu vaccine during the next season.
Intention to get vaccinated against COVID-19 reached 75% in HCWs with discrepancies between occupational categories. COVID-19 pandemic had no positive effect on flu vaccine acceptance rate.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
The authors propose reinvigorating and extending the traditional social history beyond its narrow range of risk behaviors to enable clinicians to address negative health outcomes imposed by social ...determinants of health. In this Perspective, they outline a novel, practical medical vulnerability assessment questionnaire that operationalizes for clinical practice the social science concept of “structural vulnerability.” A structural vulnerability assessment tool designed to highlight the pathways through which specific local hierarchies and broader sets of power relationships exacerbate individual patients’ health problems is presented to help clinicians identify patients likely to benefit from additional multidisciplinary health and social services. To illustrate how the tool could be implemented in time- and resource-limited settings (e.g., emergency department), the authors contrast two cases of structurally vulnerable patients with differing outcomes. Operationalizing structural vulnerability in clinical practice and introducing it in medical education can help health care practitioners think more clearly, critically, and practically about the ways social structures make people sick. Use of the assessment tool could promote “structural competency,” a potential new medical education priority, to improve understanding of how social conditions and practical logistics undermine the capacities of patients to access health care, adhere to treatment, and modify lifestyles successfully. Adoption of a structural vulnerability framework in health care could also justify the mobilization of resources inside and outside clinical settings to improve a patient’s immediate access to care and long-term health outcomes. Ultimately, the concept may orient health care providers toward policy leadership to reduce health disparities and foster health equity.
Therapist drift occurs when clinicians fail to deliver the optimum evidence-based treatment despite having the necessary tools, and is an important factor in why those therapies are commonly less ...effective than they should be in routine clinical practice. The research into this phenomenon has increased substantially over the past five years. This review considers the growing evidence of therapist drift. The reasons that we fail to implement evidence-based psychotherapies are considered, including our personalities, knowledge, emotions, beliefs, behaviours and social milieus. Finally, ideas are offered regarding how therapist drift might be halted, including a cognitive-behavioural approach for therapists that addresses the cognitions, emotions and behaviours that drive and maintain our avoidance of evidence-based treatments.
•We consider the recent evidence that therapist drift is a common phenomenon in psychological therapies.•We consider the reasons that therapist drift takes place.•A cognitive-behavioural approach to overcoming therapist drift is outlined.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
Implicit biases involve associations outside conscious awareness that lead to a negative evaluation of a person on the basis of irrelevant characteristics such as race or gender. This review examines ...the evidence that healthcare professionals display implicit biases towards patients.
PubMed, PsychINFO, PsychARTICLE and CINAHL were searched for peer-reviewed articles published between 1st March 2003 and 31st March 2013. Two reviewers assessed the eligibility of the identified papers based on precise content and quality criteria. The references of eligible papers were examined to identify further eligible studies.
Forty two articles were identified as eligible. Seventeen used an implicit measure (Implicit Association Test in fifteen and subliminal priming in two), to test the biases of healthcare professionals. Twenty five articles employed a between-subjects design, using vignettes to examine the influence of patient characteristics on healthcare professionals' attitudes, diagnoses, and treatment decisions. The second method was included although it does not isolate implicit attitudes because it is recognised by psychologists who specialise in implicit cognition as a way of detecting the possible presence of implicit bias. Twenty seven studies examined racial/ethnic biases; ten other biases were investigated, including gender, age and weight. Thirty five articles found evidence of implicit bias in healthcare professionals; all the studies that investigated correlations found a significant positive relationship between level of implicit bias and lower quality of care.
The evidence indicates that healthcare professionals exhibit the same levels of implicit bias as the wider population. The interactions between multiple patient characteristics and between healthcare professional and patient characteristics reveal the complexity of the phenomenon of implicit bias and its influence on clinician-patient interaction. The most convincing studies from our review are those that combine the IAT and a method measuring the quality of treatment in the actual world. Correlational evidence indicates that biases are likely to influence diagnosis and treatment decisions and levels of care in some circumstances and need to be further investigated. Our review also indicates that there may sometimes be a gap between the norm of impartiality and the extent to which it is embraced by healthcare professionals for some of the tested characteristics.
Our findings highlight the need for the healthcare profession to address the role of implicit biases in disparities in healthcare. More research in actual care settings and a greater homogeneity in methods employed to test implicit biases in healthcare is needed.
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