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Abstract Background does lasix decrease gfr lasix online canada. Empathy plays a role not only in pathophysiology but also in planning management strategies for alcohol dependence. However, few does lasix decrease gfr studies have looked into it.

No data are available regarding the variation of empathy with abstinence and motivation. Assessment based on cognitive does lasix decrease gfr and affective dimensions of empathy is needed.Aim. This study aimed to assess cognitive and affective empathy in men with alcohol dependence and compared it with normal controls.

Association of empathy with disease-specific variables, motivation, and does lasix decrease gfr abstinence was also done.Methods. This was a cross-sectional observational study conducted in the outpatient department of a tertiary care center. Sixty men with alcohol dependence and 60 healthy does lasix decrease gfr controls were recruited and assessed using the Basic Empathy Scale for cognitive and affective empathy.

The University of Rhode Island Change Assessment Scale was used to assess motivation. Other variables were does lasix decrease gfr assessed using a semi-structured pro forma. Comparative analysis was done using unpaired t-test and one-way ANOVA.

Correlation was does lasix decrease gfr done using Pearson's correlation test.Results. Cases with alcohol dependence showed lower levels of cognitive, affective, and total empathy as compared to controls. Affective and total empathy were higher in abstinent men does lasix decrease gfr.

Higher empathy correlates does lasix decrease gfr with lesser relapses. Abstinence and progression in motivation cycle is associated with remission in empathic deficits.Keywords. Abstinence, alcohol, empathy, motivationHow to cite this article:Nachane HB, Nadadgalli does lasix decrease gfr GV, Umate MS.

Cognitive and affective empathy in men with alcohol dependence. Relation with does lasix decrease gfr clinical profile, abstinence, and motivation. Indian J Psychiatry 2021;63:418-23How to cite this URL:Nachane HB, Nadadgalli GV, Umate MS.

Cognitive and does lasix decrease gfr affective empathy in men with alcohol dependence. Relation with clinical profile, abstinence, and motivation. Indian J Psychiatry [serial online] 2021 [cited does lasix decrease gfr 2022 Sep 20];63:418-23.

Available from. Https://www.indianjpsychiatry.org/text.asp?. 2021/63/5/418/328088 Introduction Alcohol dependence is as much a social challenge as it is a clinical one.[1] Clinicians have faced several challenges in helping subjects with alcohol dependence stay in treatment and maintain abstinence.[2] In substance abuse treatment, clients' motivation to change has often been the focus of both clinical interest and frustration.[3],[4] Motivation has been described as a prerequisite for treatment, without which the clinician can do little.[5] Similarly, lack of motivation has been used to explain the failure of individuals to begin, continue, comply with, and succeed in treatment.[6],[7] Treatment modalities have focused on various aspects of motivation enhancement â such as locus of control, social support, and networking.[8] Recent literature is focusing on the role empathy plays in pathogenesis and treatment seeking in alcohol dependence.[9] However, the way in which empathy is perceived has recently undergone drastic changes, specifically its role in both emotion processing and social interactions.[10]Broadly speaking, empathy is believed to be constituted of two components â cognitive and affective (or emotional).[9] Affective empathy (AE) deals with the ability of detecting and experiencing the others' emotional states, whereas cognitive empathy (CE) relates to perspective-taking ability allowing to understand and predict the other's various mental states (sometimes used synonymously with theory of mind).[11] Empathy constitutes an essential emotional competence for interpersonal relations and has been shown to be highly impaired in various psychiatric disorders including alcohol dependence.[9],[12] Empathy is crucial for maintaining interpersonal relations, which are frequently impaired in alcoholics and prove to be a source of frequent relapses.[9] However, research pertaining to empathy in alcohol has generated varied results.[9] Factors such as lapses, retaining in treatment, and abstinence have also been linked to subjects' empathy.[9],[13] However, few of these have assessed CE and AE separately.[9],[13] Previous literature has demonstrated that empathy correlates with the motivation to help others.[14] No study however addresses the role empathy may play in self-help, a crucial step in the management of alcohol dependence.

The present study was thus formulated, which aimed at comparing CE, AE, and total empathy (TE) between subjects of alcohol dependence and normal controls. Differences in CE, AE and TE with abstinence and stage of motivation were also assessed. We also correlated CE, AE, and TE with disease-specific variables.

Materials and Methods The present study is a cross-sectional observational study done in the outpatient psychiatric department of a tertiary care center. Ethical clearance was obtained from the institutional ethics committee (IEC/Pharm/RP/102/Feb/2019). The study was conducted over a period of 6 months (March 2019âAugust 2019) and purposive sampling method was used.

Sixty subjects, between the ages of 18â65 years, diagnosed with alcohol dependence as per the International Classification of Diseases-10 criteria were included in the study as cases. Subjects with comorbid psychiatric and medical disorders (four subjects) and those dependent on more than one substance (six subjects) were excluded. As all the available cases were male, the study was restricted to males.

Sixty normal healthy male controls who were not suffering from any medical or psychiatric illness (five subjects excluded) were recruited from the normal population (these were healthy relatives of patients attending our outpatient department). Subjects were explained about the nature of the study and written informed consent was obtained from them. A semi-structured pro forma was devised to include sociodemographic variables, such as age, marital status, family structure, education, and employment status and disease-specific variables in the cases, such as total duration of illness, number of relapses, number of hospital admissions, and family history of psychiatric illness/substance dependence.

The entire interview was completed in 20â30 min.InstrumentsThe Basic Empathy Scale for AdultsIt is a 20-item scale which was developed by Jolliffe and Farrington.[15] Each question is rated on a five point Likert type scale. We used the two-factor model where nine items assess CE (Items 3, 6, 9, 10, 12, 14, 16, 19, and 20) and 11 items assess AE (Items 1, 2, 4, 5, 7, 8, 11, 13, 15, 17, and 18). The total score gives TE, which can range from 20 (deficit in empathy) to 100 (high level of empathy).The University of Rhode Island Change Assessment Scale (URICA)This scale is based on the transtheoretical model of motivation given by Prochaska and DiClemente, which divides the readiness to change temporally into four stages.

Precontemplation (PC), contemplation (C), action (A), and maintenance (M).[16] The URICA is a 32-item self-report measure that grades responses on a 5-point Likert scale ranging from one (strong disagreement) to five (strong agreement). The subscales can be combined arithmetically (C + A + M â PC) to yield a second-order continuous readiness to change score that is used to assess readiness to change at entrance to treatment. Based on this score, the individual is classified into the stage of motivation (precontemplation, contemplation, action, and maintenance)Statistical analysisSPSS 20.0 software was used for carrying out the statistical analysis.

(IBM SPSS Statistics for Windows, Version 20.0, released 2011, Armonk, NY. IBM Corp.). Data were expressed as mean (standard deviation) for continuous variables and frequencies and percentages for categorical variables.

Comparative analyses were done using unpaired Student's t-test and one-way ANOVA with post hoc Bonferroni's test wherever appropriate. The correlation was done using Pearson's correlation test and point biserial correlation test for continuous and dichotomous categorical variables, respectively. The effect size was determined by calculating Cohen's d (d) for t-test, partial eta square (Î·p2) for ANOVA, and correlation coefficient (r) for Pearson's correlation/point biserial correlation test.

P <0.05 was considered statistically significant. Results A total of 120 subjects consisting of 60 cases and 60 controls who satisfied the inclusion and exclusion criteria were considered for the analysis. The mean age of cases was 40.80 (8.69) years, whereas that of controls was 39.02 (10.12) years.

About 80% of the cases and 88% of the controls were married. Only 58% of the cases and 57% of the controls were educated. Almost 80% of the cases versus 95% of the controls were employed at the time of assessment.

Majority of the cases (75%) and controls (83%) belonged to nuclear families. None of the sociodemographic variables varied significantly across cases and controls. Comparison of empathy between cases and controls using unpaired t-test showed cognitive (t(118) =2.59, P = 0.01), affective (t(118) =2.19, P = 0.03), and total empathy (t(118) =2.39, P = 0.02) to be significantly lower in cases [Table 1].

The analysis showed the difference to be most significant for CE (d = 0.48), followed by TE (d = 0.44), and then AE (d = 0.40), implying that it is CE that is most significantly lowered in men with alcohol dependence. [Table 2] shows the correlation between empathy and disease-related variables amng the cases using Pearson's correlation/point biserial correlation tests. Number of relapses negatively correlated with all three measures of empathy, most with CE (r = â0.42, P = 0.001), followed by TE (r = â0.39, P = 0.002) and least with AE (r = â0.31, P = 0.016).

This means that men with alcohol dependence who are more empathic tend to have lesser relapses. Having a family history of mental illness/substance use was seen to have a positive correlation with CE (r = 0.43, P = 0.001) and TE (r = 0.30, P = 0.02) but not AE (P = 0.17). As the coefficients of correlation for all the relations were <0.5, the strength of correlations in our sample was mildâmoderate.Table 2.

Relation of disease related variables with total empathy in casesClick here to viewMotivation and readiness to change was assessed in the cases using the URICA scale, which had a mean score of 8.78 (4.09). About 50% of the subjects were currently consuming alcohol (30 out of 60) and the remaining were completely abstinent. Comparing empathy scores among those subjects still consuming and those subjects completely abstinent using unpaired t-test [Figure 1] showed that abstinent patients had significantly higher AE (t(58) =2.72, mean difference = 5.10 [95% confidence interval [CI].

1.34â8.86], P = 0.009) and TE (t(58) =2.88, mean difference = 8.60 [95% CI. 2.63â14.57], P = 0.006) as compared to those still consuming but not CE (t(58) =1.93, mean difference = 2.83 [95% CI. 0.09â5.77], P = 0.058).

This difference was most marked in TE (d = 0.77), followed by AE (d = 0.71). Dividing the cases into their respective stages of motivation showed that 20 out of 60 (33%) subjects were in precontemplation stage, 10 out of 60 (17%) in contemplation stage and 30 out of 60 (50%) in action stage. None were seen to be in maintenance phase.

Using one-way ANOVA to assess the difference in empathy across the various stages of motivation [Table 3], it was found that AE (F (2,57) = 5.03, P = 0.01) and TE (F (2, 57) = 4.25, P = 0.02) varied across the motivation cycle but not CE (F (2,57) = 2.26, P = 0.11). Difference was more significant for affective empathy (Î·p2 = 0.15) as compared to total empathy (Î·p2 = 0.13), although a small one. In both cases of affective and total empathy, it can be seen that empathy increases gradually with each stage in motivation cycle [Figure 2].

However, using the post hoc Bonferroni test [Table 4] revealed that significant difference in both cases was seen between precontemplation and action stages only (P <. 0.05).Figure 1. Difference in cognitive, affective, and total empathy among dependent and abstinent subjects.

Comparison of cognitive, affective and total empathy in individual stages of motivation using post hoc Bonferroni testClick here to view Discussion Role of empathy in addictive behaviors is a pivotal one.[17] The present analysis shows that subjects dependent on alcohol lack empathic abilities as compared to healthy controls. This translates to both cognitive and affective components of empathy. Earlier research appears divided in this aspect.

Massey et al. Elucidated reduction in both CE and AE by behavioral, neuroanatomical, and self-report methods.[18] Impairment in affect processing system in alcohol dependence was cited as the reason behind the so-called âcognitive-affective dissociation of empathyâ in alcoholics, which resulted in a changed AE, with relatively intact CE.[9],[17] However, there is enough evidence to suggest the lack of social cognition, emotional cognition, and related cognitive deficits in alcohol-dependent subjects.[19] Cognitive deficits responsible for dampening of CE seen in addictions have been attributed to frontal deficits.[19] In fact, it is a combined deficit which leads to impaired social and interpersonal functioning in alcoholics.[20] Hence, our primary finding is in keeping with this hypothesis.Empathy may relate to various aspects of the psychopathological process.[21] Disorders have also been classified based on which aspect of empathy is deficient â cognitive, affective, or general.[21] On such a spectrum, alcohol dependence should definitely be classified as a general empathic deficit disorder. It is also known that within a disorder, the two components of empathy may show variation, depending upon various factors.[21] Addiction processes may have impulsivity, antisocial personality traits, externalizing behaviors, and internalizing behaviors as a part of their presentations, all factors which effect empathy.[22],[23] Hence, it is likely that difference in empathy could be attributable to these factors, even though it has been shown that empathy operates independent of them to impact the disease process.[18]Abstinence period is associated with several physiological and psychological changes and is a key experience in the life of patients with alcohol use disorder.[24] The present analysis shows that abstinence period is associated with higher empathy than the active phase of illness.

It has been demonstrated that empathy correlates significantly with abstinence and retention in treatment.[13],[23] A study has described improvement in empathy, attributable to personality changes with abstinence, in subjects following up for treatment in self-help groups.[13] A causative effect of improvement in empathy due to the 12-step program and abstinence has been hypothesized,[13] and our findings support this. Empathy is a key factor in motivation to help others and oneself when in distress. This suggests a role for it in motivation to quit and treatment seeking.

Yet still, few studies have made this assessment. Across the motivation cycle, we found that TE and AE were significantly higher for subjects in action phase than for precontemplation and contemplation phases. CE showed no significant changes.

Altered empathic abilities have been shown to impair future problem solving in social situations, thus impacting the prognosis of the illness.[25] Similarly, it also hampers treatment seeking in alcoholics. CE played a greater role in our sample as compared to AE, contrary to what most literature states.[26] This is furthered by the fact that CE and TE correlated with number of relapses and having a family history of mental illness in our subjects, whereas AE correlated with only number of relapses. Subjects with higher empathy had significantly lesser relapses, suggesting a role for empathy, particularly CE in maintaining abstinence, even though it is least likely to change.

This relation has been demonstrated by other researchers also.[13],[23] Having a positive family history of mental illness/addictions was associated with higher CE and TE. Genes have shown to influence development and dynamicity of empathy in healthy individuals and as genetics play a major role in heredity of addictions, levels of empathy may also vary accordingly.[21],[27] As AE did not show this relation, it appears CE and AE may not be âequally heritable.â However, more research in this area is needed.Our study was not without limitations. Factors such as premorbid personality and baseline empathy were not considered.

As all cases and controls were males, gender differences could not be assessed. We did not have any patients in the maintenance phase of motivation and hence this difference could not be assessed. It also might be more prudent to have a prospective study design wherein patients are followed throughout their motivation cycle to derive a more robust relation between empathy and motivation.

As our study was a cross-sectional study, it was not possible.To mention a few strengths, our analysis adds to the need for studying CE and AE separately, as they may impact different aspects of the illness and show varied dynamicity over the natural course of alcohol dependence owing to their difference in neural substrates.[28] While many risk factors for alcohol dependence are difficult if not impossible to change,[29] some components of empathy may be modifiable,[13] particularly AE. Abstinence is associated with an increase in AE and TE and thus empathy may be crucial in propelling an individual along the motivation cycle. Our analysis stands out in being one of the few to establish a relation between stages of motivation and components of empathy in alcohol dependence, which will definitely have further research and therapeutic implications.

Relapses are lesser in individuals with higher empathy and it is possible that those who relapse develop low empathy. The present analysis is associational and causality inference should be done with caution. Modalities of treatment which focus on empathy and its subsequent advancement, such as brief intervention and self-help groups, have met with ample success in clinical practice.[13],[31] Adding to existing factors that have proved successful for abstinence,[32] focusing on improving empathy at specific points in the motivation cycle (contemplation to action) may motivate individuals better to stay in treatment and reduce further relapses.Financial support and sponsorshipNil.Conflicts of interestThere are no conflicts of interest.

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Addiction 2002;97:633-45. 2.Willenbring ML. The past and future of research on treatment of alcohol dependence.

Alcohol Res Health 2010;33:55-63. 3.DiClemente CC. Conceptual models and applied research.

The ongoing contribution of the transtheoretical model. J Addict Nurs 2005;16:5-12. 4.Velasquez MM, Crouch C, von Sternberg K, Grosdanis I.

Motivation for change and psychological distress in homeless substance abusers. J Subst Abuse Treat 2000;19:395-401. 5.Beckman LJ.

An attributional analysis of Alcoholics Anonymous. J Stud Alcohol 1980;41:714-26. 6.Appelbaum A.

A critical re-examination of the concept of âmotivation for changeâ in psychoanalytic treatment. Int J Psychoanal 1972;53:51-9. 7.Miller WR.

Motivation for treatment. A review with special emphasis on alcoholism. Psychol Bull 1985;98:84-107.

8.Murphy PN, Bentall RP. Motivation to withdraw from heroin. A factor-analytic study.

Br J Addict 1992;87:245-50. 9.Maurage P, Grynberg D, NoÃ«l X, Joassin F, Philippot P, Hanak C, et al. Dissociation between affective and cognitive empathy in alcoholism.

A specific deficit for the emotional dimension. Alcohol Clin Exp Res 2011;35:1662-8. 10.de Vignemont F, Singer T.

The empathic brain. How, when and why?. Trends Cogn Sci 2006;10:435-41.

11.Reniers RL, Corcoran R, Drake R, Shryane NM, VÃ¶llm BA. The QCAE. A questionnaire of cognitive and affective empathy.

J Pers Assess 2011;93:84-95. 12.Martinotti G, Di Nicola M, Tedeschi D, Cundari S, Janiri L. Empathy ability is impaired in alcohol-dependent patients.

Am J Addict 2009;18:157-61. 13.McCown W. The relationship between impulsivity, empathy and involvement in twelve step self-help substance abuse treatment groups.

Br J Addict 1989;84:391-3. 14.Krebs D. Empathy and auism.

J Pers Soc Psychol 1975;32:1134-46. 15.Jolliffe D, Farrington DP. Development and validation of the basic empathy scale.

J Adolesc 2006;29:589-611. 16.McConnaughy EA, Prochaska JO, Velicer WF. Stages of change in psychotherapy.

Measurement and sample profiles. Psychol Psychother 1983;20:368-75. 17.Ferrari V, Smeraldi E, Bottero G, Politi E.

Addiction and empathy. A preliminary analysis. Neurol Sci 2014;35:855-9.

18.Massey SH, Newmark RL, Wakschlag LS. Explicating the role of empathic processes in substance use disorders. A conceptual framework and research agenda.

Drug Alcohol Rev 2018;37:316-32. 19.Uekermann J, Daum I. Social cognition in alcoholism.

A link to prefrontal cortex dysfunction?. Addiction 2008;103:726-35. 20.Uekermann J, Channon S, Winkel K, Schlebusch P, Daum I.

Theory of mind, humour processing and executive functioning in alcoholism. Addiction 2007;102:232-40. 21.Gonzalez-Liencres C, Shamay-Tsoory SG, BrÃ¼ne M.

Towards a neuroscience of empathy. Ontogeny, phylogeny, brain mechanisms, context and psychopathology. Neurosci Biobehav Rev 2013;37:1537-48.

22.Miller PA, Eisenberg N. The relation of empathy to aggressive and externalizing/antisocial behavior. Psychol Bull 1988;103:324-44.

23.McCown W. The effect of impulsivity and empathy on abstinence of poly-substance abusers. A prospective study.

Br J Addict 1990;85:635-7. 24.Pitel AL, Beaunieux H, Witkowski T, Vabret F, Guillery-Girard B, Quinette P, et al. Genuine episodic memory deficits and executive dysfunctions in alcoholic subjects early in abstinence.

Alcohol Clin Exp Res 2007;31:1169-78. 25.Thoma P, Friedmann C, Suchan B. Empathy and social problem solving in alcohol dependence, mood disorders and selected personality disorders.

Neurosci Biobehav Rev 2013;37:448-70. 26.Marinkovic K, Oscar-Berman M, Urban T, O'Reilly CE, Howard JA, Sawyer K, et al. Alcoholism and dampened temporal limbic activation to emotional faces.

Alcohol Clin Exp Res 2009;33:1880-92. 27.Smith A. Cognitive empathy and emotional empathy in human behavior and evolution.

Psychol Rec 2006;56:3-21. 28.Decety J, Jackson PL. A social-neuroscience perspective on empathy.

Curr Dir Psychol Sci 2006;15:54-8. 29.Tarter RE, Edwards K. Psychological factors associated with the risk for alcoholism.

Alcohol Clin Exp Res 1988;12:471-80. 30.Moyers TB, Miller WR. Is low therapist empathy toxic?.

Psychol Addict Behav 2013;27:878-84. 31.Heather N. Psychology and brief interventions.

Br J Addict 1989;84:357-70. 32.Cook S, Heather N, McCambridge J. Posttreatment motivation and alcohol treatment outcome 9 months later.

Findings from structural equation modeling. J Consult Clin Psychol 2015;83:232-7. Correspondence Address:Hrishikesh Bipin Nachane63, Sharmishtha, Tarangan, Thane West, Thane - 400 606, Maharashtra IndiaSource of Support.

None, Conflict of Interest. NoneDOI. 10.4103/indianjpsychiatry.indianjpsychiatry_1101_2 Figures [Figure 1], [Figure 2] Tables [Table 1], [Table 2], [Table 3], [Table 4].

Abstract Background where can i buy lasix. Empathy plays a role not only in pathophysiology but also in planning management strategies for alcohol dependence. However, few studies have looked where can i buy lasix into it. No data are available regarding the variation of empathy with abstinence and motivation. Assessment based on cognitive and where can i buy lasix affective dimensions of empathy is needed.Aim.

This study aimed to assess cognitive and affective empathy in men with alcohol dependence and compared it with normal controls. Association of empathy with disease-specific variables, motivation, and abstinence where can i buy lasix was also done.Methods. This was a cross-sectional observational study conducted in the outpatient department of a tertiary care center. Sixty men with alcohol dependence and 60 healthy controls were recruited and assessed using the Basic Empathy Scale for where can i buy lasix cognitive and affective empathy. The University of Rhode Island Change Assessment Scale was used to assess motivation.

Other variables were assessed using a semi-structured pro forma where can i buy lasix. Comparative analysis was done using unpaired t-test and one-way ANOVA. Correlation was where can i buy lasix done using Pearson's correlation test.Results. Cases with alcohol dependence showed lower levels of cognitive, affective, and total empathy as compared to controls. Affective and where can i buy lasix total empathy were higher in abstinent men.

Empathy varied across various stages of motivation, with a significant difference seen between precontemplation and action stages. Empathy correlated negatively with number of relapses and positively with family history of where can i buy lasix addiction.Conclusions. Empathy (both cognitive and affective) is significantly reduced in alcohol dependence. Higher empathy correlates where can i buy lasix with lesser relapses. Abstinence and progression in motivation cycle is associated with remission in empathic deficits.Keywords.

Abstinence, alcohol, empathy, motivationHow to cite this article:Nachane HB, Nadadgalli where can i buy lasix GV, Umate MS. Cognitive and affective empathy in men with alcohol dependence. Relation with clinical where can i buy lasix profile, abstinence, and motivation. Indian J Psychiatry 2021;63:418-23How to cite this URL:Nachane HB, Nadadgalli GV, Umate MS. Cognitive and affective empathy in men with alcohol where can i buy lasix dependence.

Relation with clinical profile, abstinence, and motivation. Indian J Psychiatry [serial online] 2021 [cited where can i buy lasix 2022 Sep 20];63:418-23. Available from. Https://www.indianjpsychiatry.org/text.asp?. 2021/63/5/418/328088 Introduction Alcohol dependence is as much a social challenge as it is a clinical one.[1] Clinicians have faced several challenges in helping subjects with alcohol dependence stay in treatment and maintain abstinence.[2] In substance abuse treatment, clients' motivation to change has often been the focus of both clinical interest and frustration.[3],[4] Motivation has been described as a prerequisite for treatment, without which the clinician can do little.[5] Similarly, lack of motivation has been used to explain the failure of individuals to begin, continue, comply with, and succeed in treatment.[6],[7] Treatment modalities have focused on various aspects of motivation enhancement â such as locus of control, social support, and networking.[8] Recent literature is focusing on the role empathy plays in pathogenesis and treatment seeking in alcohol dependence.[9] However, the way in which empathy is perceived has recently undergone drastic changes, specifically its role in both emotion processing and social interactions.[10]Broadly speaking, empathy is believed to be constituted of two components â cognitive and affective (or emotional).[9] Affective empathy (AE) deals with the ability of detecting and experiencing the others' emotional states, whereas cognitive empathy (CE) relates to perspective-taking ability allowing to understand and predict the other's various mental states (sometimes used synonymously with theory of mind).[11] Empathy constitutes an essential emotional competence for interpersonal relations and has been shown to be highly impaired in various psychiatric disorders including alcohol dependence.[9],[12] Empathy is crucial for maintaining interpersonal relations, which are frequently impaired in alcoholics and prove to be a source of frequent relapses.[9] However, research pertaining to empathy in alcohol has generated varied results.[9] Factors such as lapses, retaining in treatment, and abstinence have also been linked to subjects' empathy.[9],[13] However, few of these have assessed CE and AE separately.[9],[13] Previous literature has demonstrated that empathy correlates with the motivation to help others.[14] No study however addresses the role empathy may play in self-help, a crucial step in the management of alcohol dependence.

A link between an alcoholic's empathy and motivation is lacking. It is imperative to highlight changes in empathy with changes in motivation, over and above the dichotomy of abstinence and dependence.Detailed understanding of empathy, or a lack thereof, and its fate during the natural course of the illness, particularly with each step of the motivation cycle, will prove fruitful in planning better strategies for alcohol dependence. This will, in turn, lead to better handling of its social consequences and reduction in its burden on society and healthcare. The present study was thus formulated, which aimed at comparing CE, AE, and total empathy (TE) between subjects of alcohol dependence and normal controls. Differences in CE, AE and TE with abstinence and stage of motivation were also assessed.

We also correlated CE, AE, and TE with disease-specific variables. Materials and Methods The present study is a cross-sectional observational study done in the outpatient psychiatric department of a tertiary care center. Ethical clearance was obtained from the institutional ethics committee (IEC/Pharm/RP/102/Feb/2019). The study was conducted over a period of 6 months (March 2019âAugust 2019) and purposive sampling method was used. Sixty subjects, between the ages of 18â65 years, diagnosed with alcohol dependence as per the International Classification of Diseases-10 criteria were included in the study as cases.

Subjects with comorbid psychiatric and medical disorders (four subjects) and those dependent on more than one substance (six subjects) were excluded. As all the available cases were male, the study was restricted to males. Sixty normal healthy male controls who were not suffering from any medical or psychiatric illness (five subjects excluded) were recruited from the normal population (these were healthy relatives of patients attending our outpatient department). Subjects were explained about the nature of the study and written informed consent was obtained from them. A semi-structured pro forma was devised to include sociodemographic variables, such as age, marital status, family structure, education, and employment status and disease-specific variables in the cases, such as total duration of illness, number of relapses, number of hospital admissions, and family history of psychiatric illness/substance dependence.

Empathy was assessed using the Basic Empathy Scale for Adults for both cases and controls and motivation was assessed in the cases using the University of Rhode Island Change Assessment Scale (URICA). The scales were translated into the vernacular languages (Hindi and Marathi) and the translated versions were used. The scales were administered by a single rater in one sitting. The entire interview was completed in 20â30 min.InstrumentsThe Basic Empathy Scale for AdultsIt is a 20-item scale which was developed by Jolliffe and Farrington.[15] Each question is rated on a five point Likert type scale. We used the two-factor model where nine items assess CE (Items 3, 6, 9, 10, 12, 14, 16, 19, and 20) and 11 items assess AE (Items 1, 2, 4, 5, 7, 8, 11, 13, 15, 17, and 18).

The total score gives TE, which can range from 20 (deficit in empathy) to 100 (high level of empathy).The University of Rhode Island Change Assessment Scale (URICA)This scale is based on the transtheoretical model of motivation given by Prochaska and DiClemente, which divides the readiness to change temporally into four stages. Precontemplation (PC), contemplation (C), action (A), and maintenance (M).[16] The URICA is a 32-item self-report measure that grades responses on a 5-point Likert scale ranging from one (strong disagreement) to five (strong agreement). The subscales can be combined arithmetically (C + A + M â PC) to yield a second-order continuous readiness to change score that is used to assess readiness to change at entrance to treatment. Based on this score, the individual is classified into the stage of motivation (precontemplation, contemplation, action, and maintenance)Statistical analysisSPSS 20.0 software was used for carrying out the statistical analysis. (IBM SPSS Statistics for Windows, Version 20.0, released 2011, Armonk, NY.

IBM Corp.). Data were expressed as mean (standard deviation) for continuous variables and frequencies and percentages for categorical variables. Comparative analyses were done using unpaired Student's t-test and one-way ANOVA with post hoc Bonferroni's test wherever appropriate. The correlation was done using Pearson's correlation test and point biserial correlation test for continuous and dichotomous categorical variables, respectively. The effect size was determined by calculating Cohen's d (d) for t-test, partial eta square (Î·p2) for ANOVA, and correlation coefficient (r) for Pearson's correlation/point biserial correlation test.

Almost 80% of the cases versus 95% of the controls were employed at the time of assessment. Majority of the cases (75%) and controls (83%) belonged to nuclear families. None of the sociodemographic variables varied significantly across cases and controls. Comparison of empathy between cases and controls using unpaired t-test showed cognitive (t(118) =2.59, P = 0.01), affective (t(118) =2.19, P = 0.03), and total empathy (t(118) =2.39, P = 0.02) to be significantly lower in cases [Table 1]. The analysis showed the difference to be most significant for CE (d = 0.48), followed by TE (d = 0.44), and then AE (d = 0.40), implying that it is CE that is most significantly lowered in men with alcohol dependence.

[Table 2] shows the correlation between empathy and disease-related variables amng the cases using Pearson's correlation/point biserial correlation tests. Number of relapses negatively correlated with all three measures of empathy, most with CE (r = â0.42, P = 0.001), followed by TE (r = â0.39, P = 0.002) and least with AE (r = â0.31, P = 0.016). This means that men with alcohol dependence who are more empathic tend to have lesser relapses. Having a family history of mental illness/substance use was seen to have a positive correlation with CE (r = 0.43, P = 0.001) and TE (r = 0.30, P = 0.02) but not AE (P = 0.17). As the coefficients of correlation for all the relations were <0.5, the strength of correlations in our sample was mildâmoderate.Table 2.

0.09â5.77], P = 0.058). This difference was most marked in TE (d = 0.77), followed by AE (d = 0.71). Dividing the cases into their respective stages of motivation showed that 20 out of 60 (33%) subjects were in precontemplation stage, 10 out of 60 (17%) in contemplation stage and 30 out of 60 (50%) in action stage. None were seen to be in maintenance phase. Using one-way ANOVA to assess the difference in empathy across the various stages of motivation [Table 3], it was found that AE (F (2,57) = 5.03, P = 0.01) and TE (F (2, 57) = 4.25, P = 0.02) varied across the motivation cycle but not CE (F (2,57) = 2.26, P = 0.11).

Difference was more significant for affective empathy (Î·p2 = 0.15) as compared to total empathy (Î·p2 = 0.13), although a small one. In both cases of affective and total empathy, it can be seen that empathy increases gradually with each stage in motivation cycle [Figure 2]. However, using the post hoc Bonferroni test [Table 4] revealed that significant difference in both cases was seen between precontemplation and action stages only (P <. 0.05).Figure 1. Difference in cognitive, affective, and total empathy among dependent and abstinent subjects.

Data expressed as mean (standard deviation)Click here to viewFigure 2. Cognitive, affective, and total empathy in cases across precontemplation, contemplation, and action stages of motivation. Data expressed as mean (standard deviation)Click here to viewTable 4. Comparison of cognitive, affective and total empathy in individual stages of motivation using post hoc Bonferroni testClick here to view Discussion Role of empathy in addictive behaviors is a pivotal one.[17] The present analysis shows that subjects dependent on alcohol lack empathic abilities as compared to healthy controls. This translates to both cognitive and affective components of empathy.

Earlier research appears divided in this aspect. Massey et al. Elucidated reduction in both CE and AE by behavioral, neuroanatomical, and self-report methods.[18] Impairment in affect processing system in alcohol dependence was cited as the reason behind the so-called âcognitive-affective dissociation of empathyâ in alcoholics, which resulted in a changed AE, with relatively intact CE.[9],[17] However, there is enough evidence to suggest the lack of social cognition, emotional cognition, and related cognitive deficits in alcohol-dependent subjects.[19] Cognitive deficits responsible for dampening of CE seen in addictions have been attributed to frontal deficits.[19] In fact, it is a combined deficit which leads to impaired social and interpersonal functioning in alcoholics.[20] Hence, our primary finding is in keeping with this hypothesis.Empathy may relate to various aspects of the psychopathological process.[21] Disorders have also been classified based on which aspect of empathy is deficient â cognitive, affective, or general.[21] On such a spectrum, alcohol dependence should definitely be classified as a general empathic deficit disorder. It is also known that within a disorder, the two components of empathy may show variation, depending upon various factors.[21] Addiction processes may have impulsivity, antisocial personality traits, externalizing behaviors, and internalizing behaviors as a part of their presentations, all factors which effect empathy.[22],[23] Hence, it is likely that difference in empathy could be attributable to these factors, even though it has been shown that empathy operates independent of them to impact the disease process.[18]Abstinence period is associated with several physiological and psychological changes and is a key experience in the life of patients with alcohol use disorder.[24] The present analysis shows that abstinence period is associated with higher empathy than the active phase of illness. It has been demonstrated that empathy correlates significantly with abstinence and retention in treatment.[13],[23] A study has described improvement in empathy, attributable to personality changes with abstinence, in subjects following up for treatment in self-help groups.[13] A causative effect of improvement in empathy due to the 12-step program and abstinence has been hypothesized,[13] and our findings support this.

Empathy is a key factor in motivation to help others and oneself when in distress. This suggests a role for it in motivation to quit and treatment seeking. Yet still, few studies have made this assessment. Across the motivation cycle, we found that TE and AE were significantly higher for subjects in action phase than for precontemplation and contemplation phases. CE showed no significant changes.

Thus, it appears that AE is more amenable to change and instrumental in motivation enhancement. Treatment modalities for dependence should inculcate methods addressing empathy, especially AE as this would be more beneficial. It is also possible that these patients may innately have higher empathy and hence are motivated to quit alcohol, as has been previously demonstrated.[9]It is clear that in adults who have developed alcohol dependence, deficits in empathic processing remit in recovery and this finding is crucial to optimize long-term outcomes and minimize the likelihood of relapse. Altered empathic abilities have been shown to impair future problem solving in social situations, thus impacting the prognosis of the illness.[25] Similarly, it also hampers treatment seeking in alcoholics. CE played a greater role in our sample as compared to AE, contrary to what most literature states.[26] This is furthered by the fact that CE and TE correlated with number of relapses and having a family history of mental illness in our subjects, whereas AE correlated with only number of relapses.

Subjects with higher empathy had significantly lesser relapses, suggesting a role for empathy, particularly CE in maintaining abstinence, even though it is least likely to change. This relation has been demonstrated by other researchers also.[13],[23] Having a positive family history of mental illness/addictions was associated with higher CE and TE. Genes have shown to influence development and dynamicity of empathy in healthy individuals and as genetics play a major role in heredity of addictions, levels of empathy may also vary accordingly.[21],[27] As AE did not show this relation, it appears CE and AE may not be âequally heritable.â However, more research in this area is needed.Our study was not without limitations. Factors such as premorbid personality and baseline empathy were not considered. As all cases and controls were males, gender differences could not be assessed.

We did not have any patients in the maintenance phase of motivation and hence this difference could not be assessed. It also might be more prudent to have a prospective study design wherein patients are followed throughout their motivation cycle to derive a more robust relation between empathy and motivation. As our study was a cross-sectional study, it was not possible.To mention a few strengths, our analysis adds to the need for studying CE and AE separately, as they may impact different aspects of the illness and show varied dynamicity over the natural course of alcohol dependence owing to their difference in neural substrates.[28] While many risk factors for alcohol dependence are difficult if not impossible to change,[29] some components of empathy may be modifiable,[13] particularly AE. Abstinence is associated with an increase in AE and TE and thus empathy may be crucial in propelling an individual along the motivation cycle. Our analysis stands out in being one of the few to establish a relation between stages of motivation and components of empathy in alcohol dependence, which will definitely have further research and therapeutic implications.

Conclusions Empathic deficits in alcohol dependence are well established, being more for CE than AE although both being affected. Even though psychotherapeutic approaches have hitherto targeted therapist's empathy,[30] we suggest that a detailed understanding of patient's empathy is equally crucial in the management. Increment in AE and TE is seen with abstinence and improvement in subject's motivation. Relapses are lesser in individuals with higher empathy and it is possible that those who relapse develop low empathy. The present analysis is associational and causality inference should be done with caution.

Modalities of treatment which focus on empathy and its subsequent advancement, such as brief intervention and self-help groups, have met with ample success in clinical practice.[13],[31] Adding to existing factors that have proved successful for abstinence,[32] focusing on improving empathy at specific points in the motivation cycle (contemplation to action) may motivate individuals better to stay in treatment and reduce further relapses.Financial support and sponsorshipNil.Conflicts of interestThere are no conflicts of interest. References 1.Caetano R, Cunradi C. Alcohol dependence. A public health perspective. Addiction 2002;97:633-45.

2.Willenbring ML. The past and future of research on treatment of alcohol dependence. Alcohol Res Health 2010;33:55-63. 3.DiClemente CC. Conceptual models and applied research.

The ongoing contribution of the transtheoretical model. J Addict Nurs 2005;16:5-12. 4.Velasquez MM, Crouch C, von Sternberg K, Grosdanis I. Motivation for change and psychological distress in homeless substance abusers. J Subst Abuse Treat 2000;19:395-401.

5.Beckman LJ. An attributional analysis of Alcoholics Anonymous. J Stud Alcohol 1980;41:714-26. 6.Appelbaum A. A critical re-examination of the concept of âmotivation for changeâ in psychoanalytic treatment.

Int J Psychoanal 1972;53:51-9. 7.Miller WR. Motivation for treatment. A review with special emphasis on alcoholism. Psychol Bull 1985;98:84-107.

8.Murphy PN, Bentall RP. Motivation to withdraw from heroin. A factor-analytic study. Br J Addict 1992;87:245-50. 9.Maurage P, Grynberg D, NoÃ«l X, Joassin F, Philippot P, Hanak C, et al.

Dissociation between affective and cognitive empathy in alcoholism. A specific deficit for the emotional dimension. Alcohol Clin Exp Res 2011;35:1662-8. 10.de Vignemont F, Singer T. The empathic brain.

How, when and why?. Trends Cogn Sci 2006;10:435-41. 11.Reniers RL, Corcoran R, Drake R, Shryane NM, VÃ¶llm BA. The QCAE. A questionnaire of cognitive and affective empathy.

J Pers Assess 2011;93:84-95. 12.Martinotti G, Di Nicola M, Tedeschi D, Cundari S, Janiri L. Empathy ability is impaired in alcohol-dependent patients. Am J Addict 2009;18:157-61. 13.McCown W.

The relationship between impulsivity, empathy and involvement in twelve step self-help substance abuse treatment groups. Br J Addict 1989;84:391-3. 14.Krebs D. Empathy and auism. J Pers Soc Psychol 1975;32:1134-46.

15.Jolliffe D, Farrington DP. Development and validation of the basic empathy scale. J Adolesc 2006;29:589-611. 16.McConnaughy EA, Prochaska JO, Velicer WF. Stages of change in psychotherapy.

Measurement and sample profiles. Psychol Psychother 1983;20:368-75. 17.Ferrari V, Smeraldi E, Bottero G, Politi E. Addiction and empathy. A preliminary analysis.

Neurol Sci 2014;35:855-9. 18.Massey SH, Newmark RL, Wakschlag LS. Explicating the role of empathic processes in substance use disorders. A conceptual framework and research agenda. Drug Alcohol Rev 2018;37:316-32.

19.Uekermann J, Daum I. Social cognition in alcoholism. A link to prefrontal cortex dysfunction?. Addiction 2008;103:726-35. 20.Uekermann J, Channon S, Winkel K, Schlebusch P, Daum I.

Theory of mind, humour processing and executive functioning in alcoholism. Addiction 2007;102:232-40. 21.Gonzalez-Liencres C, Shamay-Tsoory SG, BrÃ¼ne M. Towards a neuroscience of empathy. Ontogeny, phylogeny, brain mechanisms, context and psychopathology.

Neurosci Biobehav Rev 2013;37:1537-48. 22.Miller PA, Eisenberg N. The relation of empathy to aggressive and externalizing/antisocial behavior. Psychol Bull 1988;103:324-44. 23.McCown W.

The effect of impulsivity and empathy on abstinence of poly-substance abusers. A prospective study. Br J Addict 1990;85:635-7. 24.Pitel AL, Beaunieux H, Witkowski T, Vabret F, Guillery-Girard B, Quinette P, et al. Genuine episodic memory deficits and executive dysfunctions in alcoholic subjects early in abstinence.

Alcohol Clin Exp Res 2007;31:1169-78. 25.Thoma P, Friedmann C, Suchan B. Empathy and social problem solving in alcohol dependence, mood disorders and selected personality disorders. Neurosci Biobehav Rev 2013;37:448-70. 26.Marinkovic K, Oscar-Berman M, Urban T, O'Reilly CE, Howard JA, Sawyer K, et al.

Alcoholism and dampened temporal limbic activation to emotional faces. Alcohol Clin Exp Res 2009;33:1880-92. 27.Smith A. Cognitive empathy and emotional empathy in human behavior and evolution. Psychol Rec 2006;56:3-21.

28.Decety J, Jackson PL. A social-neuroscience perspective on empathy. Curr Dir Psychol Sci 2006;15:54-8. 29.Tarter RE, Edwards K. Psychological factors associated with the risk for alcoholism.

Alcohol Clin Exp Res 1988;12:471-80. 30.Moyers TB, Miller WR. Is low therapist empathy toxic?. Psychol Addict Behav 2013;27:878-84. 31.Heather N.

Psychology and brief interventions. Br J Addict 1989;84:357-70. 32.Cook S, Heather N, McCambridge J. Posttreatment motivation and alcohol treatment outcome 9 months later. Findings from structural equation modeling.

J Consult Clin Psychol 2015;83:232-7. Correspondence Address:Hrishikesh Bipin Nachane63, Sharmishtha, Tarangan, Thane West, Thane - 400 606, Maharashtra IndiaSource of Support. None, Conflict of Interest. NoneDOI. 10.4103/indianjpsychiatry.indianjpsychiatry_1101_2 Figures [Figure 1], [Figure 2] Tables [Table 1], [Table 2], [Table 3], [Table 4].

What should I watch for while using Lasix?

Visit your doctor or health care professional for regular checks on your progress. Check your blood pressure regularly. Ask your doctor or health care professional what your blood pressure should be, and when you should contact him or her. If you are a diabetic, check your blood sugar as directed.

You may need to be on a special diet while taking Lasix. Check with your doctor. Also, ask how many glasses of fluid you need to drink a day. You must not get dehydrated.

You may get drowsy or dizzy. Do not drive, use machinery, or do anything that needs mental alertness until you know how this drug affects you. Do not stand or sit up quickly, especially if you are an older patient. This reduces the risk of dizzy or fainting spells. Alcohol can make you more drowsy and dizzy. Avoid alcoholic drinks.

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Buy lasix for horses

Choice is view website probably one buy lasix for horses of the most often discussed areas in bioethics, alongside the related concepts of informed consent and autonomy. It is generally, prima facie, portrayed as a good buy lasix for horses thing. In healthcare, the 2000s saw the UK Prime Minister Tony Blair pursue the buy lasix for horses âChoice Agendaâ where, âAs capacity expands, so choice will grow.

Choice will fundamentally change the balance of power in the NHS.â1 In a consumerist society giving consumers more choice is seen as desirable. However, choice is not a good in itself, giving buy lasix for horses people more choice in certain situations can be problematic. I.e.

Consumerism drives economic growth and this has a detrimental effect on the environment. And increasing the range of choices a patient is offered is often not the best way to improve the quality of healthcare provision.2 The assumptions behind the valuing of choice need careful unpacking and this Issue of the Journal of Medical Ethics includes papers that explore choice in a number of areas.This Issue's Editorâs choice is Tom Walkerâs âThe Value of Choiceâ,3 which puts forward a suggestion for the importance of the symbolic value of choice. There are a number of ways of categorising the value of choice in healthcare.

One account sees choice as valuable because it is by choosing that individuals make their life their own. Another account sees choice as valuable for instrumental reasons, people are generally, assuming they are sufficiently informed, the best judge of their own best interests. Walker argues for an additional third reason, the symbolic value of choice, originally proposed by Scanlon.

This sees choice as valuable because being given the option to choose, whether or not one takes it up, not the act of choosing is what makes choice valuable. Being offered the option to choose has a âcommunicative roleâ in that it communicates that the person has standing and, for certain types of choice, being denied the opportunity to choose, âcan be both demeaning and stigmatising.â Walker states that denying someone the opportunity to choose in certain circumstances does not communicate anything untoward, and he goes to explore how we might determine when not allowing someone a choice would be demeaning. Here he stresses the importance of context in making this determination, it is not fixed by the features of a patient, but what being âallowedâ or âdeniedâ the opportunity to make a choice reveals about the healthcare professionalâs view of the patient.

ÂIt communicates that they either see those patients as competent and equal members of society, or that they do not.â Denying a patient the opportunity to choose an ineffective treatment, for example, does not communicate a negative judgement. Walker says his account, âis intended to supplement existing accounts, not replace them. Because choice is valuable for more than one reason no single account can capture everything that matters.âThe importance of pointing to the context of the choice is highlighted in Walkerâs paper and it is only through careful examination of the context of that offering that we can determine if, in fact, this is an area where choice should be offered and to whom.

Such an examination is carried out in Cameron Beattieâs paper,4 which considers the High Court review of service provision at the youth-focussed gender identity Tavistock Clinic. Beattie disagrees with the High Courtâs view that it is âhighly unlikelyâ that under-13s, and âdoubtfulâ that 14â15 years old, can be competent to consent to puberty blocker therapy for gender dysphoria. Beattie argues that having puberty blocker therapy is a choice that minors should be given the opportunity to make.

In principle, children of that age could be competent to make the decision and that the decision is no more complex than other medical decisions that Gillick competence has conventionally been applied to. Children of this age fall into what Walker calls a âtransitionalâ group, âOf particular importance here is the extent to which societal features mean members of some groups find it particularly hard to be recognised as competent and equal members of society. That includes members of groups subject to discriminationâ¦.It also includes those who are in what we might call transitional groups such as teenagers struggling to be recognised as competent.â In the case of denying puberty blockers, the symbolic value of choice is clear.The paper by Zeljka Buturovic5 examines the debate over young childless women requesting sterilisation.

There has been a discussion in the literature that critiques doctorsâ hesitancy to accede to this type of request and Buturovic argues against these criticisms. The argument is that rather than a doctorâs refusal to sterilise a young childless woman or putting up obstacles to this being examples of, variously, inconsistency, paternalism, pronatalist bias and discrimination, it is understandable that doctors should be reluctant to follow this unusual request, and such hesitancy is of potential benefit to the young woman. This hesitancy can act as a filter for women who are not seriously committed to sterilisation.

This, in essence, is the opposite argument to Beattieâs paper, that the barriers put up to prevent people exercising their choice in this case are warranted. Young childless women should have their choice scrutinised and if necessary delayed so that it can be ascertained if the choice is a genuine one, and âto weed out (the) confused and uncommitted.â Ultimately, that choice should be available for young childless woman, but it is a choice, given its long-term consequences and likely lack of reversibility, that should be carefully considered.These papers show that choice is a contextually based, complex and multi-facetted concept and approaches such as Walkerâs, give us tools to think more carefully about the value of choice and what that means in particular situations. A consideration of choice is not complete without thinking about the effects of our choices on others, and this needs to be at the forefront of any ethical analysis.

The âchoice-agendaâ can often be a proxy for an individualistic conception of personal responsibility and a construction of the âgoodâ of the choice as being solely about that individualâs right to exercise a choice, rather than a more nuanced consideration of the wider, or even limited, effects of that choice on others. Although we have well-worn ways of thinking about harm â harm to others and liberty limiting principles6 â how the exercising of individual choice might harm others is often debatable and unclear, and political with a small and large P!. For instance, in July 2021 Boris Johnson, the UK prime minister, announced that mask wearing would now be one of personal choice.

The government would end the legal obligation to wear a face covering, âWe will move away from legal restrictions and allow people to make their own informed decisions about how to manage the lasix.â Johnson went on to say. ÂGuidance will suggest where you might choose to do so - especially when cases are rising and where you come into contact with people you don't usually meet in enclosed spaces, such as obviously crowded public transport.â7 This mandate for âfreedom-dayâ was criticised in a number of letters in high ranking medical journals,8 9 arguing, âThe narrative of âcaution, vigilance, and personal responsibilityâ is an abdication of the governmentâs fundamental duty to protect public health. ÂPersonal responsibilityâ does not work in the face of an airborne, highly contagious infectious disease.

Infectious diseases are a matter of collective, rather than individual, responsibility.â8 In this case, someoneâs personal choice to not wear a mask on public transport, where social distancing is impossible, conflicts with someone elseâs choice to travel to work as safely as they can. As the critics of this policy and work in public health ethics notes, one personâs choice can have a significant detrimental effect on others, and in situations like this, such as this mask wearing example, where not allowing choice, that is maintaining the legally mandated requirement to wear a face mask (unless there are reasons for an exemption), is an ethically acceptable restriction on âpersonal choice.â In Walkerâs terminology disallowing this choice it is not demeaning or stigmatising, as it applies to everyone, and does not fail to recognise any particular person or group as equal members of society.Choice is often portrayed as a good thing like parenthood and apple pie and the use of choice by politicians to whip up support and bolster their political agendas, as shown by the examples of Blair and Johnson, shows the rhetorical power of the concept. But to really address in what circumstances choices should be offered, to whom and what type of choice, we need theoretical tools to help us understand and be attentive to the wider implications and the papers in this Issue help us to do that.Ethics statementsPatient consent for publicationNot applicable.Ethics approvalThis study does not involve human participants.IntroductionLarge-scale, international data sharing opens the door to the study of so-called âBig Dataâ, which holds great promise for improving patient-centred care.

Big Data health research is envisioned to take precision medicine to the next level through increased understanding of disease aetiology and phenotypes, treatment effects, disease management and healthcare expenditure.1 However, lack of public trust is proven to be detrimental to the goals of data sharing.2 The case of care.data in the UK offers a blatant example of a data sharing initiative gone awry. Criticism predominantly focused on limited public awareness and lack of clarity on the goals of the programme and ways to opt out.3 Citizens are becoming increasingly aware and critical of data privacy issues, and this warrants renewed investments to maintain public trust in data-intensive health research. Here, we use the term data-intensive health research to refer to a practice of grand-scale capture, (re)use and/or linkage of a wide variety of health-related data on individuals.Within the European Union (EU), the recently adopted General Data Protection Regulation (GDPR) (EU 2016/679) addresses some of the concerns the public may have with respect to privacy and data protection.

One of the primary goals of the GDPR is to give individuals control over their personal data, most notably through consent.4 Other lawful grounds for the processing of personal data are listed, but it is unclear how these would exactly apply to scientific research. Legal norms remain open to interpretation and thus offer limited guidance to researchers.5 6 In Recital 33, the GDPR actually mentions that additional ethical standards are necessary for the processing of personal data for scientific research. This indicates a recognised need for entities undertaking activities likely to incite public unease to go beyond compliance with legal requirements.7 Complementary ethical governance then becomes a prerequisite for securing public trust in data-intensive health research.A concept that could be of use in developing ethical governance is that of a âsocial license to operateâ.7 The social license captures the notion of a mandate granted by society to certain occupational groups to determine for themselves what constitutes proper conduct, under the condition that such conduct is in line with societyâs expectations.

The term âsocial licenseâ was first used in the 1950s by American sociologist Everett Hughes to address relations between professional occupations and society.8 The concept has been used since to frame, for example, corporate social responsibility in the mining industry,9 governance of medical research in general8 and of data-intensive health research more specifically.7 10 As such, adequate ethical governance then becomes a precondition for obtaining a social license for data sharing activities.Key to an informed understanding of the social license is identifying the expectations society may hold with regard to sharing of and access to health data. Here, relevant societal actors are the subjects of Big Data health research, constituting both patients and the general public. Identification of patientsâ and public views and attitudes allows for a better understanding of the elements of a socially sanctioned governance framework.

We know of the existence of research papers that have captured these views using quantitative or qualitative methods or a combination of both. So far, systematic reviews of the literature have limited their scope to citizens of specific countries,11 12 qualitative studies only13 or the sharing of genomic data.14 Therefore, we performed an up-to-date narrative review of both quantitative and qualitative studies to explore predominant patient and public views and attitudes towards data sharing for health research.MethodsWe searched the literature databases PubMed (MEDLINE), Embase, Scopus and Google Scholar in April 2019 for publications addressing patientsâ and public views and attitudes towards the use of health data for research purposes. Synonyms of the following terms (connected by âANDâ) were used to search titles and/or abstracts of indexed references.

Research (See box 1 and online supplementary appendix 1). To merit inclusion, an article had to report results from an original research study (qualitative, quantitative or mixed methods) on attitudes of individuals regarding use of data for health research. We restricted eligibility to records published in English and studies performed between 2009 and 2019.

We chose 2009 as a lower limit because we assume that patientsâ and public perspectives might have changed substantially with increasing awareness and use of digital (health) technologies. Systematic reviews and meta-analyses synthesising the empirical literature on this topic also qualified for review. Reports from stakeholder meet-ups and workshops were eligible as long as they included patients or the public as participants.

Since we were only interested in empirical evidence, expert opinion and publications merely advocating for the inclusion of patientsâ and public views in Big Data health research were excluded. Studies that predominantly reported on views of other stakeholdersâsuch as clinicians, researchers, policy makers or industryâwere excluded. Articles reporting on conference proceedings, or views regarding (demographic) data collection in low or middle income countries or for public health and care/quality improvement were not considered relevant to this review.

Despite our specific interest in data sharing within the European context, we broadened eligibility criteria to include studies performed in the USA, Canada, Australia and New Zealand. Additional articles were identified through consultation with experts and review of references in the manuscript identified through the literature database searches. Views and attitudes of patients and the public were identified from selected references and reviewed by means of thematic content analysis.Supplemental materialBox 1 Key search terms(patient* OR public OR citizen*)AND(attitude* OR view* OR perspective* OR opinion* OR interview* OR qualitative* OR questionnaire* OR survey*)AND(âdata sharingâ OR âdata accessâ OR âdata transferâ)ANDResearchResultsStudy characteristicsSearches in PubMed (MEDLINE), Embase, Scopus and Google Scholar resulted in a total of 1153 non-unique records (see online supplementary appendix 1).

We identified 27 papers for review, including 12 survey or questionnaire studies (quantitative), 8 interview or focus group studies (qualitative), 1 mixed methods study and 6 systematic reviews (see table 1). Most records were excluded because they were not relevant to our research question or because they did not report on findings from original (empirical) research studies. Ten studies reported on views of patients, 11 on views of the public/citizens and 6 studies combined views of patients, research participants and the public.View this table:Table 1 Study characteristicsWillingness to share data for health researchReviewed papers suggest widespread support for the sharing of data for health research.Four systematic reviews synthesising the views of patients and the public report that willingness for data to be linked and shared for research purposes is high11â14 and that people are generally open to and understand the benefits of data sharing.15Outpatients from a German university hospital who participated in a questionnaire study (n=503) expressed a strong willingness (93%) to give broad consent for secondary use of data,16 and 93% of a sample of UK citizens with Parkinsonâs disease (n=306) were willing to share their data.17 Wide support for sharing of data internationally18 19 and in multicentre studies20 was reported among patient participants.

Goodman et al found that most participants in a sample of US patients with cancer (n=228) were willing to have their data made available for âas many research studies as possibleâ.21 Regarding the use of anonymised healthcare data for research purposes, a qualitative study found UK rheumatology patients and patient representatives in support of data sharing (n=40).22Public respondents in survey studies recognised the benefits of storing electronic health information,23 and 78.8% (n=151) of surveyed Canadians felt positive about the use of routinely collected data for health research.24 The majority (55%) of a sample of older Swiss citizens (n=40) were in favour of placing genetic data at disposal for research.25 Focus group discussions convened in the UK showed that just over 50% of the members of the Citizens Council of The National Institute for Health and Care Excellence (NICE) said they would have no concerns about NICE using anonymised data derived from personal care records to evaluate treatments,26 and all participants in one qualitative study were keen to contribute to the National Healthcare Service (NHS)-related research.27Motivations to share dataPatients and public participants expressed similar reasons and motivations for their willingness to share data for health research, including contributing to advancements in healthcare, returning incurred benefits and the hope of future personal health benefits (tables 2â4).View this table:Table 2 Patientsâ views and attitudes towards the sharing of health data for researchView this table:Table 3 Public views and attitudes towards the sharing of health data for researchView this table:Table 4 Patientsâ and public views and attitudes towards the sharing of health data for researchIn the two systematic reviews that addressed this topic, sharing data for âthe common goodâ or âthe greater goodâ was identified as one of the most prevalent motivations.12 14For patients specifically, to help future patients or people with similar health problems was an important reason.14 16 One survey study conducted among German outpatients found that 72% listed returning their own benefits incurred from research as a driver for sharing clinical data.16 Patients with rare disease were also motivated by âgreat hope and trustâ in the development of international databases for health research.19 Among patients, support of research in general,16 the value attached to answering âimportantâ research questions,20 and a desire to contribute to advancements in medicine14 were prevalent reasons in favour of data sharing. Ultimately, the belief that data sharing could lead to improvements in health outcome and care was reported.20Only one original study research paper addressed public motivations. This study found that older citizens mentioned auistic reasons and the greater good in a series of interviews as reasons to share genetic data for research.25 In these interviews, citizens expressed no expectations of an immediate impact or beneficial return but ultimately wanted to help the next generation.Perceived benefits of data sharingPatients and the public perceive that data sharing could lead to better patient care through improved diagnosis and treatment options and more efficient use of resources.

Rather, acceptance seemed to decrease if data sharing was financially motivated, and if people did not know how and with whom their data would be shared.First, individuals often opposed data sharing if it was motivated by financial gain or profit20 or if the data were shared with commercial/private companies.14 15 In one large pan-European survey (n=20â882), respondents were found to be strongly averse to health insurance companies and private sector pharmaceutical companies viewing their data.23 Second, lack of understanding and awareness around the use of data was viewed as a barrier to data sharing.15 22 Third, lack of transparency and controllability in releasing data were mentioned as factors compromising public trust in data sharing activities.14 22Factors affecting willingness to share dataA wide range of factors were identified from the literature that impacted individualsâ willingness to share data for health research, including geographical factors, age, individual-specific and research-specific characteristics.Geographical factorsMcCormack et al found that European patientsâ expressions of trust and attitudes to risk were often affected by the regulatory and cultural practices in their home countries, as well as by the nature of the (rare) disease the patient participant had.18 Shah et al conducted a survey among patients in four Northern European countries (n=855) and found a significant association between country and attitudes towards sharing of deidentified data.34 Interestingly, Dutch respondents were less likely to support sharing of their deidentified data compared with UK citizens.AgeAmong a sample of surveyed patients with Parkinsonâs disease (UK), a significant association was found between higher age and increased support for data sharing.17 According to a study based on semistructured interviews with older Swiss citizens, generational differences impacted willingness to share.25 With respect to public attitudes towards data sharing, findings of one systematic review suggest that males and older people are more likely to consent to sharing their medical data.27 A systematic review by Shabani et al suggests that patient and public participants with higher mean age are substantially less worried about privacy and confidentiality than other groups.14Individual-specific characteristicsA systematic review into patientsâ and public perspectives on data sharing in the USA suggests that individuals from under-represented minorities are less willing to share data.11 A large multisite survey (n=13â000) among the US public found that willingness to share was associated with self-identified white race, higher educational attainment and lower religiosity.31 In another systematic review, race, gender, age, marital status and/or educational level all seemed to influence how people perceived sensitivity of genomic data and the sharing thereof.14 However, a UK study among patients with Parkinsonâs disease found no clear relationship between data sharing and the number of years diagnosed, sex, medication class or health confidence.17Factors that clearly positively affected attitudes towards data sharing were perceptions of the (public) benefits and value of the research,13 20 fewer concerns and fewer information needs,31 and higher trust in and reputation of individuals or organisations conducting and/or overseeing data sharing.12â14 35 Conversely, willingness decreased with higher privacy and confidentiality concerns11 and higher distrust of the government as an oversight body for (genetic) research data.35Research-specific characteristicsPrivacy measures increased peopleâs willingness to share their data for health research, such as removal of social security numbers (90%, n=3516) and insurance ID (82%, n=3516), the sharing of only summary-level or aggregate data20 and deposition of data in a restricted access online database.29 Expressions of having control over what data are shared and with whom positively affected attitudes towards data sharing.34 In one study, being asked for consent for each study made participants (81%) feel ârespected and involvedâ, and 74% agreed that they would feel that they âhad controlâ.14 With respect to data sharing without prospective consent, participants became more accepting after being given information about the research processes and selection bias.27 Less support was observed for data sharing due to financial incentives25 and, more specifically, if data would be shared with private companies, such as insurance or pharmaceutical companies.11 25Conditions for sharingWidespread willingness to share data for health research very rarely led to participantsâ unconditional support. Studies showed agreement on the following conditions for responsible data sharing. Value, privacy, minimising risks, data security, transparency, control, information, trust, responsibility and accountability.ValueOne systematic review found that participants found it important that the research as a result of data sharing should be in the publicâs interest and should reflect participantsâ values.15 The NICE Citizens Council advocated for appropriate systems and good working practices to ensure a consistent approach to research planning, data capture and analysis.26Privacy, risks and data securityThe need to protect individualsâ privacy was considered paramount11 14 21 34 and participants often viewed deidentification of personal data as a top privacy measure.11 24 30 36 One survey among US patients with cancer found that only 20% (n=228) of participants found linkage of individuals with their deidentified data acceptable for return of individual health results and to support further research.21 Secured access to databases was considered an important measure to ensure data security in data sharing activities.30 34 A systematic review of participantsâ attitudes towards data sharing showed that people established risk minimisation as another condition for data sharing.15 Findings by Mazor et al suggest that patients only support studies that offer value and minimise security risks.20Transparency and controlConditions regarding transparency were information about how data will be shared and with whom,14 35 the type of research that is to be performed, by whom the research will be performed,16 information on data sharing and monitoring policies and database governance,35 conditions framing access to data and data access agreements,24 28 30 and any partnerships with the pharmaceutical industry.19 More generally, participants expressed the desire to be involved in the data sharing process,35 to be notified when their data are (re)used and to be informed of the results of studies using their data.15 Spencer et al identified use of an electronic interface as a highly valued means to enable greater control over consent choices.22 When asked about the use of personal data for health research by the NHS, UK citizens were typically willing to accept models of consent other than the ones they would prefer.37 Acceptance of consent models with lower levels of individual control was found to be dependent on a number of factors, including adequate transparency, control over detrimental use and commercialisation, and the ability to object, particularly to any processing considered to be inappropriate or particularly sensitive.37Information and trustOne systematic review identified trust in the ability of the original institution to carry out the oversight tasks as a major condition for responsible data sharing.14 Appropriate education and information about data sharing was thought to include public campaigns to inform stakeholders about Big Data32 and information communicated at open days of research institutions (such as NICE) to ensure people understand what their data are being used for and to reassure them that personal data will not be passed on or sold to other organisations.26 The informed consent process for study participation was believed to include information about the fact that individualsâ data could potentially be shared,15 30 the objectives of data sharing and (biobank) research, the studyâs data sharing plans,29 governance structure, logistics and accountability.33Responsibility and accountabilityParticipants often placed the responsibility for data sharing practices on the shoulders of researchers.

Secondary use of data collected earlier for scientific research was viewed to require a data access committee that involves a researcher from the original research project, a clinician, patient representative and a participant in the original study.36 Researchers of the original study were required to monitor data used by other researchers.36 In terms of accountability, patient and public groups in Italy (n=280) placed high value on sanctions for misuse of data.30 Information on penalties or other consequences of a breach of protection or misuse was considered important by many.31 35DiscussionIn this study, we narratively reviewed 27 papers on patientsâ and public views on and attitudes towards the use of health data for scientific research. Studies reported a widespreadâthough conditionalâsupport for the linkage and sharing of data for health research. The only outlier seems to be the finding that just over half (n=25) of the NICE Citizens Council answered ânoâ to the question whether they had any concerns if NICE used anonymised data to fill in the gaps if NICE was not getting enough evidence in âthe usual waysâ.26 However, we hasten to point out that the question about willingness to share is different from the question whether people have concerns or not.

In addition, after a 2-day discussion meeting Council members were perhaps more sensitised to the potential concerns regarding data sharing. Therefore, we suggest that the way and context within which questions are phrased may influence the answers people give.Overall, people expressed similar motivations to share their data, perceived similar benefits (despite some variation between patients and citizens), yet at the same time displayed a range of concerns, predominantly relating to confidentiality and data security, awareness about access and control, and potential harms resulting from these risks. Both patient and public participants conveyed that certain factors would increase or reduce their willingness to have their data shared.

For example, the presence of privacy-protecting measures (eg, data deidentification and the use of secured databases) seemed to increase willingness to share, as well as transparency and information about data sharing processes and responsibilities. The identified views and attitudes appeared to come together in the conditions stipulated by participants. Value, privacy and confidentiality, minimising risks, data security, transparency, control, information, trust, responsibility and accountability.In our Introduction, we mentioned that identifying patientsâ and public views and attitudes allows for a better understanding of the elements of a socially sanctioned governance framework.

In other words, what work should our governance framework be doing in order to obtain a social license?. This review urges researchers and institutions to address peopleâs diverse concerns and to make an effort to meet the conditions identified. Without these conditions, institutions lack trustworthiness, which is vital for the proceedings of medicine and biomedical science.

As such, a social license is not a ânice to haveâ but a âneed to haveâ. Our results also confirm that patients and the public indeed care about more than legal compliance alone, and wish to be engaged through information, transparency and control. This work supports the findings of a recent systematic review into ethical principles of data sharing as specified in various international ethical guidelines and literature.38 What this body of research implies is considerable diversity of values and beliefs both between and within countries.The goal of this narrative review was to identify the most internationally dominant, aggregated patient and public views about the broad topic of data sharing for health research.

We deliberately opted for the methodology of a narrative review rather than a systematic review. Most narrative reviews deal with a broad range of issues to a given topic rather than addressing a particular topic in depth.39 This means narrative reviews may be most useful for obtaining a broad perspective on a topic, and that they often are less useful in generating quantitative answers to specific clinical questions. However, because narrative reviews do not require specification of the search and selection strategy and the way of critically appraising literature can be variable, the connection between evidence generated by narrative reviews and (clinical) recommendations is less rigorous and risk of bias exists.

For example, there is a difference between sharing of routinely collected health data versus secondary use of health data collected for research purposes. And we can only make loose assumptions about potential differences between patient and public views.In addition, we should mention that this work is centred around studies conducted in Western countries as the whole Big Data space and literature is dominated by Western countries, higher socioeconomic status and Caucasians. However, most of the disease burden globally and within countries is most probably not represented in the âBig Dataâ and so we have to stress the lack of generalisability to large parts of the world.Nevertheless, we believe our findings point towards essential elements of a governance framework for data sharing for health research purposes.

If we are to conclude that the identified conditions ought to act as the pillars of a governance framework, the next step is to identify how these conditions could be practically operationalised. For example, if people value information, transparency and control, what type of consent is most likely to valorise these conditions?. And what policy for returning research results would be desirable?.

Once we know what to value, we can start thinking about the ways to acknowledge that value. A new challenge arising here, however, is what to do when people hold different or even conflicting values or preferences. Discrete choice experiments could help to test peopleâs preferences regarding specific topics, such as preferred modes of informed consent.

Apart from empirical work, conceptual analysis is needed to clarify how public trust, trustworthiness of institutions and accountability are interconnected.ConclusionThis narrative review suggests widespreadâthough conditionalâsupport among patients and the public for data sharing for health research. Despite the fact that participants recognise actual or potential benefits of health research, they report a number of significant concerns and related conditions. We believe identified conditions (eg, social value, data security, transparency and accountability) ought to be operationalised in a value-based governance framework that incorporates the diverse patient and public values, needs and interests, and which reflects the way these same conditions are met, to strengthen the social license for Big Data health research.Ethics statementsPatient consent for publicationNot required.AcknowledgmentsWe thank Susanne LÃ¸gstrup (European Heart Network) and Evert-Ben van Veen (Medlaw) for their valuable feedback during various stages in drafting the manuscript..

Choice is probably one of the most often discussed useful reference areas in bioethics, alongside the related concepts of informed consent where can i buy lasix and autonomy. It is generally, prima facie, portrayed as a good thing where can i buy lasix. In healthcare, the 2000s saw the UK Prime Minister Tony Blair pursue the âChoice where can i buy lasix Agendaâ where, âAs capacity expands, so choice will grow. Choice will fundamentally change the balance of power in the NHS.â1 In a consumerist society giving consumers more choice is seen as desirable.

However, choice is not where can i buy lasix a good in itself, giving people more choice in certain situations can be problematic. I.e. Consumerism drives economic growth and this has a detrimental effect on the environment. And increasing the range of choices a patient is offered is often not the best way to improve the quality of healthcare provision.2 The assumptions behind the valuing of choice need careful unpacking and this Issue of the Journal of Medical Ethics includes papers that explore choice in a number of areas.This Issue's Editorâs choice is Tom Walkerâs âThe Value of Choiceâ,3 which puts forward a suggestion for the importance of the symbolic value of choice.

There are a number of ways of categorising the value of choice in healthcare. One account sees choice as valuable because it is by choosing that individuals make their life their own. Another account sees choice as valuable for instrumental reasons, people are generally, assuming they are sufficiently informed, the best judge of their own best interests. Walker argues for an additional third reason, the symbolic value of choice, originally proposed by Scanlon.

Walker says his account, âis intended to supplement existing accounts, not replace them. Because choice is valuable for more than one reason no single account can capture everything that matters.âThe importance of pointing to the context of the choice is highlighted in Walkerâs paper and it is only through careful examination of the context of that offering that we can determine if, in fact, this is an area where choice should be offered and to whom. Such an examination is carried out in Cameron Beattieâs paper,4 which considers the High Court review of service provision at the youth-focussed gender identity Tavistock Clinic. Beattie disagrees with the High Courtâs view that it is âhighly unlikelyâ that under-13s, and âdoubtfulâ that 14â15 years old, can be competent to consent to puberty blocker therapy for gender dysphoria.

Beattie argues that having puberty blocker therapy is a choice that minors should be given the opportunity to make. In principle, children of that age could be competent to make the decision and that the decision is no more complex than other medical decisions that Gillick competence has conventionally been applied to. Children of this age fall into what Walker calls a âtransitionalâ group, âOf particular importance here is the extent to which societal features mean members of some groups find it particularly hard to be recognised as competent and equal members of society. That includes members of groups subject to discriminationâ¦.It also includes those who are in what we might call transitional groups such as teenagers struggling to be recognised as competent.â In the case of denying puberty blockers, the symbolic value of choice is clear.The paper by Zeljka Buturovic5 examines the debate over young childless women requesting sterilisation.

Young childless women should have their choice scrutinised and if necessary delayed so that it can be ascertained if the choice is a genuine one, and âto weed out (the) confused and uncommitted.â Ultimately, that choice should be available for young childless woman, but it is a choice, given its long-term consequences and likely lack of reversibility, that should be carefully considered.These papers show that choice is a contextually based, complex and multi-facetted concept and approaches such as Walkerâs, give us tools to think more carefully about the value of choice and what that means in particular situations. A consideration of choice is not complete without thinking about the effects of our choices on others, and this needs to be at the forefront of any ethical analysis. The âchoice-agendaâ can often be a proxy for an individualistic conception of personal responsibility and a construction of the âgoodâ of the choice as being solely about that individualâs right to exercise a choice, rather than a more nuanced consideration of the wider, or even limited, effects of that choice on others. Although we have well-worn ways of thinking about harm â harm to others and liberty limiting principles6 â how the exercising of individual choice might harm others is often debatable and unclear, and political with a small and large P!.

For instance, in July 2021 Boris Johnson, the UK prime minister, announced that mask wearing would now be one of personal choice. The government would end the legal obligation to wear a face covering, âWe will move away from legal restrictions and allow people to make their own informed decisions about how to manage the lasix.â Johnson went on to say. ÂGuidance will suggest where you might choose to do so - especially when cases are rising and where you come into contact with people you don't usually meet in enclosed spaces, such as obviously crowded public transport.â7 This mandate for âfreedom-dayâ was criticised in a number of letters in high ranking medical journals,8 9 arguing, âThe narrative of âcaution, vigilance, and personal responsibilityâ is an abdication of the governmentâs fundamental duty to protect public health. ÂPersonal responsibilityâ does not work in the face of an airborne, highly contagious infectious disease.

Criticism predominantly focused on limited public awareness and lack of clarity on the goals of the programme and ways to opt out.3 Citizens are becoming increasingly aware and critical of data privacy issues, and this warrants renewed investments to maintain public trust in data-intensive health research. Here, we use the term data-intensive health research to refer to a practice of grand-scale capture, (re)use and/or linkage of a wide variety of health-related data on individuals.Within the European Union (EU), the recently adopted General Data Protection Regulation (GDPR) (EU 2016/679) addresses some of the concerns the public may have with respect to privacy and data protection. One of the primary goals of the GDPR is to give individuals control over their personal data, most notably through consent.4 Other lawful grounds for the processing of personal data are listed, but it is unclear how these would exactly apply to scientific research. Legal norms remain open to interpretation and thus offer limited guidance to researchers.5 6 In Recital 33, the GDPR actually mentions that additional ethical standards are necessary for the processing of personal data for scientific research.

This indicates a recognised need for entities undertaking activities likely to incite public unease to go beyond compliance with legal requirements.7 Complementary ethical governance then becomes a prerequisite for securing public trust in data-intensive health research.A concept that could be of use in developing ethical governance is that of a âsocial license to operateâ.7 The social license captures the notion of a mandate granted by society to certain occupational groups to determine for themselves what constitutes proper conduct, under the condition that such conduct is in line with societyâs expectations. The term âsocial licenseâ was first used in the 1950s by American sociologist Everett Hughes to address relations between professional occupations and society.8 The concept has been used since to frame, for example, corporate social responsibility in the mining industry,9 governance of medical research in general8 and of data-intensive health research more specifically.7 10 As such, adequate ethical governance then becomes a precondition for obtaining a social license for data sharing activities.Key to an informed understanding of the social license is identifying the expectations society may hold with regard to sharing of and access to health data. Here, relevant societal actors are the subjects of Big Data health research, constituting both patients and the general public. Identification of patientsâ and public views and attitudes allows for a better understanding of the elements of a socially sanctioned governance framework.

Views. Data sharing. Research (See box 1 and online supplementary appendix 1). To merit inclusion, an article had to report results from an original research study (qualitative, quantitative or mixed methods) on attitudes of individuals regarding use of data for health research.

We restricted eligibility to records published in English and studies performed between 2009 and 2019. We chose 2009 as a lower limit because we assume that patientsâ and public perspectives might have changed substantially with increasing awareness and use of digital (health) technologies. Systematic reviews and meta-analyses synthesising the empirical literature on this topic also qualified for review. Reports from stakeholder meet-ups and workshops were eligible as long as they included patients or the public as participants.

Additional articles were identified through consultation with experts and review of references in the manuscript identified through the literature database searches. Views and attitudes of patients and the public were identified from selected references and reviewed by means of thematic content analysis.Supplemental materialBox 1 Key search terms(patient* OR public OR citizen*)AND(attitude* OR view* OR perspective* OR opinion* OR interview* OR qualitative* OR questionnaire* OR survey*)AND(âdata sharingâ OR âdata accessâ OR âdata transferâ)ANDResearchResultsStudy characteristicsSearches in PubMed (MEDLINE), Embase, Scopus and Google Scholar resulted in a total of 1153 non-unique records (see online supplementary appendix 1). We identified 27 papers for review, including 12 survey or questionnaire studies (quantitative), 8 interview or focus group studies (qualitative), 1 mixed methods study and 6 systematic reviews (see table 1). Most records were excluded because they were not relevant to our research question or because they did not report on findings from original (empirical) research studies.

Ten studies reported on views of patients, 11 on views of the public/citizens and 6 studies combined views of patients, research participants and the public.View this table:Table 1 Study characteristicsWillingness to share data for health researchReviewed papers suggest widespread support for the sharing of data for health research.Four systematic reviews synthesising the views of patients and the public report that willingness for data to be linked and shared for research purposes is high11â14 and that people are generally open to and understand the benefits of data sharing.15Outpatients from a German university hospital who participated in a questionnaire study (n=503) expressed a strong willingness (93%) to give broad consent for secondary use of data,16 and 93% of a sample of UK citizens with Parkinsonâs disease (n=306) were willing to share their data.17 Wide support for sharing of data internationally18 19 and in multicentre studies20 was reported among patient participants. Goodman et al found that most participants in a sample of US patients with cancer (n=228) were willing to have their data made available for âas many research studies as possibleâ.21 Regarding the use of anonymised healthcare data for research purposes, a qualitative study found UK rheumatology patients and patient representatives in support of data sharing (n=40).22Public respondents in survey studies recognised the benefits of storing electronic health information,23 and 78.8% (n=151) of surveyed Canadians felt positive about the use of routinely collected data for health research.24 The majority (55%) of a sample of older Swiss citizens (n=40) were in favour of placing genetic data at disposal for research.25 Focus group discussions convened in the UK showed that just over 50% of the members of the Citizens Council of The National Institute for Health and Care Excellence (NICE) said they would have no concerns about NICE using anonymised data derived from personal care records to evaluate treatments,26 and all participants in one qualitative study were keen to contribute to the National Healthcare Service (NHS)-related research.27Motivations to share dataPatients and public participants expressed similar reasons and motivations for their willingness to share data for health research, including contributing to advancements in healthcare, returning incurred benefits and the hope of future personal health benefits (tables 2â4).View this table:Table 2 Patientsâ views and attitudes towards the sharing of health data for researchView this table:Table 3 Public views and attitudes towards the sharing of health data for researchView this table:Table 4 Patientsâ and public views and attitudes towards the sharing of health data for researchIn the two systematic reviews that addressed this topic, sharing data for âthe common goodâ or âthe greater goodâ was identified as one of the most prevalent motivations.12 14For patients specifically, to help future patients or people with similar health problems was an important reason.14 16 One survey study conducted among German outpatients found that 72% listed returning their own benefits incurred from research as a driver for sharing clinical data.16 Patients with rare disease were also motivated by âgreat hope and trustâ in the development of international databases for health research.19 Among patients, support of research in general,16 the value attached to answering âimportantâ research questions,20 and a desire to contribute to advancements in medicine14 were prevalent reasons in favour of data sharing. Ultimately, the belief that data sharing could lead to improvements in health outcome and care was reported.20Only one original study research paper addressed public motivations. This study found that older citizens mentioned auistic reasons and the greater good in a series of interviews as reasons to share genetic data for research.25 In these interviews, citizens expressed no expectations of an immediate impact or beneficial return but ultimately wanted to help the next generation.Perceived benefits of data sharingPatients and the public perceive that data sharing could lead to better patient care through improved diagnosis and treatment options and more efficient use of resources.

Patients seem to also value the potential of (direct) personal health benefits.Two systematic reviews reported on perceived benefits of data sharing for health research purposes. Howe et al mentioned perceived benefits to research participants or the immediate community, benefits to the public and benefits to research and science.15 Shabani et al also listed accelerating research advancement and maximising the value of resources as perceived benefits.14Surveyed patients perceived that data sharing could help their doctor âmake better decisionsâ about their health (94%, n=3516)28 or result in an increased chance of receiving personalised health information (n=228).21In the original studies reviewed, advantages and potential benefits of data sharing were generally recognised by public and patient participants.22 29 Data sharing was believed to enable the study of long-term treatment effects and rare events, as well as the study of large numbers of people,24 to improve diagnosis25 and treatment quality,20 23 as well as to stimulate innovation30 and identify new treatment options.25 A cross-sectional online survey among patient and citizen groups in Italy (n=280) also identified the perception that data sharing could reduce waste in research.30Perceived risks of data sharingThe most significant risks of data sharing were perceived to results from breaches of confidentiality, commercial use and potential abuse of the data.Systematic reviews report on patientsâ and public concerns about confidentiality in general,13 15 sometimes linked to the risk of reidentification,14 concerns about a party's competence in keeping data secure,12 and concerns that personal information could be mined from genomic data.14 A systematic review by Stockdale et al identified concerns among the public (UK and Ireland) about the motivation a party might have to use the data.14Patients in a UK qualitative study (n=40) perceived âdetrimentalâ consequences of data âfalling into the wrong handsâ, such as insurance companies.22 Respondents from the online patient community PatientsLikeMe were fearful of health data being âstolen by hackersâ (87%, n=3516).28Original research studies flagged data security and privacy as major public concerns.16 18 20 25 26 29â32 More specifically, many studies found that participants worried about who would have access to the data and about risk of misuses or abuses.13 15 18 25 27 33 A large pan-European survey among respondents from 27 EU member states revealed public concerns about different levels of access by third parties (48.9%â60.6%, n=20â882).23 Overall, reviewed papers suggest that patients and the public are concerned about the use of their data for commercial purposes.14 27 For example, the NICE Citizens Council expressed concerns about the potential for data to be sold to other organisations and used for profit and for purposes other than research.26 The Citizens Council also highlighted the need for transparency about how data are used and how it might be used in the future and for ensuring the research is conducted according to good scientific practice and that data are used to benefit society. Concerns about control and ownership of data were identified13 33 and about re-use of data for purposes that participants do not agree on.30 Fear of discrimination, stigmatisation, exploitation or other repercussions as a consequence of data being shared was widely cited by individuals.14 15 18Barriers to share dataStudies showed that patients and the public rarely mention barriers to data sharing in absolute terms. Rather, acceptance seemed to decrease if data sharing was financially motivated, and if people did not know how and with whom their data would be shared.First, individuals often opposed data sharing if it was motivated by financial gain or profit20 or if the data were shared with commercial/private companies.14 15 In one large pan-European survey (n=20â882), respondents were found to be strongly averse to health insurance companies and private sector pharmaceutical companies viewing their data.23 Second, lack of understanding and awareness around the use of data was viewed as a barrier to data sharing.15 22 Third, lack of transparency and controllability in releasing data were mentioned as factors compromising public trust in data sharing activities.14 22Factors affecting willingness to share dataA wide range of factors were identified from the literature that impacted individualsâ willingness to share data for health research, including geographical factors, age, individual-specific and research-specific characteristics.Geographical factorsMcCormack et al found that European patientsâ expressions of trust and attitudes to risk were often affected by the regulatory and cultural practices in their home countries, as well as by the nature of the (rare) disease the patient participant had.18 Shah et al conducted a survey among patients in four Northern European countries (n=855) and found a significant association between country and attitudes towards sharing of deidentified data.34 Interestingly, Dutch respondents were less likely to support sharing of their deidentified data compared with UK citizens.AgeAmong a sample of surveyed patients with Parkinsonâs disease (UK), a significant association was found between higher age and increased support for data sharing.17 According to a study based on semistructured interviews with older Swiss citizens, generational differences impacted willingness to share.25 With respect to public attitudes towards data sharing, findings of one systematic review suggest that males and older people are more likely to consent to sharing their medical data.27 A systematic review by Shabani et al suggests that patient and public participants with higher mean age are substantially less worried about privacy and confidentiality than other groups.14Individual-specific characteristicsA systematic review into patientsâ and public perspectives on data sharing in the USA suggests that individuals from under-represented minorities are less willing to share data.11 A large multisite survey (n=13â000) among the US public found that willingness to share was associated with self-identified white race, higher educational attainment and lower religiosity.31 In another systematic review, race, gender, age, marital status and/or educational level all seemed to influence how people perceived sensitivity of genomic data and the sharing thereof.14 However, a UK study among patients with Parkinsonâs disease found no clear relationship between data sharing and the number of years diagnosed, sex, medication class or health confidence.17Factors that clearly positively affected attitudes towards data sharing were perceptions of the (public) benefits and value of the research,13 20 fewer concerns and fewer information needs,31 and higher trust in and reputation of individuals or organisations conducting and/or overseeing data sharing.12â14 35 Conversely, willingness decreased with higher privacy and confidentiality concerns11 and higher distrust of the government as an oversight body for (genetic) research data.35Research-specific characteristicsPrivacy measures increased peopleâs willingness to share their data for health research, such as removal of social security numbers (90%, n=3516) and insurance ID (82%, n=3516), the sharing of only summary-level or aggregate data20 and deposition of data in a restricted access online database.29 Expressions of having control over what data are shared and with whom positively affected attitudes towards data sharing.34 In one study, being asked for consent for each study made participants (81%) feel ârespected and involvedâ, and 74% agreed that they would feel that they âhad controlâ.14 With respect to data sharing without prospective consent, participants became more accepting after being given information about the research processes and selection bias.27 Less support was observed for data sharing due to financial incentives25 and, more specifically, if data would be shared with private companies, such as insurance or pharmaceutical companies.11 25Conditions for sharingWidespread willingness to share data for health research very rarely led to participantsâ unconditional support.

Studies showed agreement on the following conditions for responsible data sharing. Value, privacy, minimising risks, data security, transparency, control, information, trust, responsibility and accountability.ValueOne systematic review found that participants found it important that the research as a result of data sharing should be in the publicâs interest and should reflect participantsâ values.15 The NICE Citizens Council advocated for appropriate systems and good working practices to ensure a consistent approach to research planning, data capture and analysis.26Privacy, risks and data securityThe need to protect individualsâ privacy was considered paramount11 14 21 34 and participants often viewed deidentification of personal data as a top privacy measure.11 24 30 36 One survey among US patients with cancer found that only 20% (n=228) of participants found linkage of individuals with their deidentified data acceptable for return of individual health results and to support further research.21 Secured access to databases was considered an important measure to ensure data security in data sharing activities.30 34 A systematic review of participantsâ attitudes towards data sharing showed that people established risk minimisation as another condition for data sharing.15 Findings by Mazor et al suggest that patients only support studies that offer value and minimise security risks.20Transparency and controlConditions regarding transparency were information about how data will be shared and with whom,14 35 the type of research that is to be performed, by whom the research will be performed,16 information on data sharing and monitoring policies and database governance,35 conditions framing access to data and data access agreements,24 28 30 and any partnerships with the pharmaceutical industry.19 More generally, participants expressed the desire to be involved in the data sharing process,35 to be notified when their data are (re)used and to be informed of the results of studies using their data.15 Spencer et al identified use of an electronic interface as a highly valued means to enable greater control over consent choices.22 When asked about the use of personal data for health research by the NHS, UK citizens were typically willing to accept models of consent other than the ones they would prefer.37 Acceptance of consent models with lower levels of individual control was found to be dependent on a number of factors, including adequate transparency, control over detrimental use and commercialisation, and the ability to object, particularly to any processing considered to be inappropriate or particularly sensitive.37Information and trustOne systematic review identified trust in the ability of the original institution to carry out the oversight tasks as a major condition for responsible data sharing.14 Appropriate education and information about data sharing was thought to include public campaigns to inform stakeholders about Big Data32 and information communicated at open days of research institutions (such as NICE) to ensure people understand what their data are being used for and to reassure them that personal data will not be passed on or sold to other organisations.26 The informed consent process for study participation was believed to include information about the fact that individualsâ data could potentially be shared,15 30 the objectives of data sharing and (biobank) research, the studyâs data sharing plans,29 governance structure, logistics and accountability.33Responsibility and accountabilityParticipants often placed the responsibility for data sharing practices on the shoulders of researchers. Secondary use of data collected earlier for scientific research was viewed to require a data access committee that involves a researcher from the original research project, a clinician, patient representative and a participant in the original study.36 Researchers of the original study were required to monitor data used by other researchers.36 In terms of accountability, patient and public groups in Italy (n=280) placed high value on sanctions for misuse of data.30 Information on penalties or other consequences of a breach of protection or misuse was considered important by many.31 35DiscussionIn this study, we narratively reviewed 27 papers on patientsâ and public views on and attitudes towards the use of health data for scientific research. Studies reported a widespreadâthough conditionalâsupport for the linkage and sharing of data for health research.

The only outlier seems to be the finding that just over half (n=25) of the NICE Citizens Council answered ânoâ to the question whether they had any concerns if NICE used anonymised data to fill in the gaps if NICE was not getting enough evidence in âthe usual waysâ.26 However, we hasten to point out that the question about willingness to share is different from the question whether people have concerns or not. In addition, after a 2-day discussion meeting Council members were perhaps more sensitised to the potential concerns regarding data sharing. Therefore, we suggest that the way and context within which questions are phrased may influence the answers people give.Overall, people expressed similar motivations to share their data, perceived similar benefits (despite some variation between patients and citizens), yet at the same time displayed a range of concerns, predominantly relating to confidentiality and data security, awareness about access and control, and potential harms resulting from these risks. Both patient and public participants conveyed that certain factors would increase or reduce their willingness to have their data shared.

This review urges researchers and institutions to address peopleâs diverse concerns and to make an effort to meet the conditions identified. Without these conditions, institutions lack trustworthiness, which is vital for the proceedings of medicine and biomedical science. As such, a social license is not a ânice to haveâ but a âneed to haveâ. Our results also confirm that patients and the public indeed care about more than legal compliance alone, and wish to be engaged through information, transparency and control.

This work supports the findings of a recent systematic review into ethical principles of data sharing as specified in various international ethical guidelines and literature.38 What this body of research implies is considerable diversity of values and beliefs both between and within countries.The goal of this narrative review was to identify the most internationally dominant, aggregated patient and public views about the broad topic of data sharing for health research. We deliberately opted for the methodology of a narrative review rather than a systematic review. Most narrative reviews deal with a broad range of issues to a given topic rather than addressing a particular topic in depth.39 This means narrative reviews may be most useful for obtaining a broad perspective on a topic, and that they often are less useful in generating quantitative answers to specific clinical questions. However, because narrative reviews do not require specification of the search and selection strategy and the way of critically appraising literature can be variable, the connection between evidence generated by narrative reviews and (clinical) recommendations is less rigorous and risk of bias exists.

This is something to take into account in this study. A risk of bias assessment was not possible due to the heterogeneity of the findings. We acknowledge that our methodological choices may have affected the discriminative power or granularity of our findings. For example, there is a difference between sharing of routinely collected health data versus secondary use of health data collected for research purposes.

And we can only make loose assumptions about potential differences between patient and public views.In addition, we should mention that this work is centred around studies conducted in Western countries as the whole Big Data space and literature is dominated by Western countries, higher socioeconomic status and Caucasians. However, most of the disease burden globally and within countries is most probably not represented in the âBig Dataâ and so we have to stress the lack of generalisability to large parts of the world.Nevertheless, we believe our findings point towards essential elements of a governance framework for data sharing for health research purposes. If we are to conclude that the identified conditions ought to act as the pillars of a governance framework, the next step is to identify how these conditions could be practically operationalised. For example, if people value information, transparency and control, what type of consent is most likely to valorise these conditions?.

And what policy for returning research results would be desirable?. Once we know what to value, we can start thinking about the ways to acknowledge that value. A new challenge arising here, however, is what to do when people hold different or even conflicting values or preferences. Discrete choice experiments could help to test peopleâs preferences regarding specific topics, such as preferred modes of informed consent.

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