Research article

Empathy before entering practice: A qualitative study on drivers of empathy in healthcare professionals from the perspective of medical students

  • Received: 04 September 2023 Revised: 08 November 2023 Accepted: 09 November 2023 Published: 05 December 2023
  • Literature has shown that clinical empathy is important for good and effective patient care; however, research into the underlying precursors driving empathy is lacking. In this study, we aim to explore the motivating factors of empathy in healthcare professionals from the perspective of medical students. A grounded theory approach was employed to study the driving influences behind empathy in healthcare professionals. Focus Group Discussions comprising 21 English-speaking Year 4 medical students from Lee Kong Chian School of Medicine were conducted in August 2018. The results revealed four drivers of empathy and they are affective, cognitive, moral and individual valuation of empathy. A novel perspective on the motivation of empathy suggests that individual valuation of empathy plays a moderating role in both promoting and reducing empathetic behaviors. This proposes that effectiveness of empathetic behaviors founded upon genuine care might vary compared to those without it, which is consistent with current literature. We have shown that affective, cognitive and moral foundations of empathy are essential driving forces of empathy, with the valuation of empathy playing a major role in propelling empathetic behavior. In understanding the perceptions of empathy, interventions could work on accentuating the positive impacts of empathy in patient care, which might in turn, compel healthcare workers to display increased empathy for better patient care.

    Citation: Yun Ying Ho, Laurence Tan, Chou Chuen Yu, Mai Khanh Le, Tanya Tierney, James Alvin Low. Empathy before entering practice: A qualitative study on drivers of empathy in healthcare professionals from the perspective of medical students[J]. AIMS Medical Science, 2023, 10(4): 329-342. doi: 10.3934/medsci.2023026

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  • Literature has shown that clinical empathy is important for good and effective patient care; however, research into the underlying precursors driving empathy is lacking. In this study, we aim to explore the motivating factors of empathy in healthcare professionals from the perspective of medical students. A grounded theory approach was employed to study the driving influences behind empathy in healthcare professionals. Focus Group Discussions comprising 21 English-speaking Year 4 medical students from Lee Kong Chian School of Medicine were conducted in August 2018. The results revealed four drivers of empathy and they are affective, cognitive, moral and individual valuation of empathy. A novel perspective on the motivation of empathy suggests that individual valuation of empathy plays a moderating role in both promoting and reducing empathetic behaviors. This proposes that effectiveness of empathetic behaviors founded upon genuine care might vary compared to those without it, which is consistent with current literature. We have shown that affective, cognitive and moral foundations of empathy are essential driving forces of empathy, with the valuation of empathy playing a major role in propelling empathetic behavior. In understanding the perceptions of empathy, interventions could work on accentuating the positive impacts of empathy in patient care, which might in turn, compel healthcare workers to display increased empathy for better patient care.



    The interest for studying the theory of infinite systems of integral equations is based on the fact that the theory of infinite systems of integral equations is a branch of nonlinear analysis which has been applied in various fields of science and numerous applications. In fact, most physical and engineering problems are formed by infinite systems of integral equations, see for example [1,2,3,4]. The problem of the existence of solutions for infinite systems of integral equations plays a significant role in the investigation of these types of equations and it is important to apply original studies in our investigations (cf.[5,6,7]). In some papers, integral equations of Volterra type have been converted in the form of integral equations of Volterra-Stieltjes type and numerous results have been obtained on the existence of solutions of nonlinear integral equations (cf.[8,9]). The aim of this paper is to present some results on the existence of solutions for an infinite system of integral equations of Volterra-Stieltjes type of the form

    un(t,x)=Fn(t,s,f1(t,u(t,x))t0x0gn(t,s,x,y,u(t,x))dyg2(x,y)dsg1(t,s),(Tu)(t,x)0Vn(t,s,u(t,x))ds);u(t,x)={ui(t,x)}i=1,ui(t,x)BC(R+×R+,R), (1.1)

    where BC(R+×R+,R) is the space of all real functions u(t,x)=u:R+×R+R, which are defined, continuous and bounded on the set R+×R+ with a supremum norm u=sup{|u(t,x)|:(t,x)R+×R+}. The obtained results extend and generalize the results of [6,8,9] in the Banach spaces c0 and p. In our approach, this is done by applying the measure of noncompactness and Darbo fixed point theorem.

    In future, we apply some notations, definitions and preliminary facts to obtain our main results.

    For a bounded subset S of a metric space X, Kuratowski [10] defined the function α(S) by the formula

    α(S)=inf{δ>0:S=ni=1Si,diam(Si)δfor1in<},

    known as the Kuratowski measure of noncompactness. Another measure of noncompactness is the Hausdorff measure of noncompactness given by:

    χ(S)=inf{ε>0:ShasfinitenetinX}.

    Let E be a real Banach space with norm . and zero element θ. Besides, we suppose ¯X and Conv(X) denote the closure and convex hull of X, respectively. Moreover, let us denote by ME the family of all nonempty and bounded subsets of E and by NE its subfamily consisting of all relatively compact sets.

    Definition 1. [11] A mapping μ:ME[0,) is called a measure of noncompactness if it satisfies the following conditions:

    (1) The set Kerμ={XME:μ(X)=0} is nonempty and KerμNE.

    (2) XYμ(X)μ(Y).

    (3) μ(¯X)=μ(X).

    (4) μ(Conv(X))=μ(X).

    (5) μ(λX+(1λ)Y)λμ(X)+(1λ)μ(Y) for λ[0,1].

    (6) If {Xn} is a sequence of closed sets from ME such that Xn+1Xn for n=1,2, and limnμ(Xn)=0, then n=1Xn is nonempty.

    We will apply the following theorem as the main tool in our investigations.

    Theorem 1. (Darbo[12]) Let C be a nonempty, bounded, closed and convex subset of a Banach space E and T:CC be a continuous mapping. Assume that there exists a constant K[0,1) such that μ(TX)Kμ(X) for any nonempty subset X of C, where μ is a measure of noncompactness defined in E. Then T has at least a fixed point in C.

    Samadi [13] extended Darbo's fixed point theorem as follows.

    Theorem 2. Let C be a nonempty bounded, closed and convex subset of a Banach space E. Assume T:CC be a continuous operator satisfying

    θ(μ(X))+f(μ(T(X)))f(μ(X)) (2.1)

    for all nonempty subsets X of C, where μ is an arbitrary measure of noncompactness defined in E and (θ,f)Δ=. Then T has a fixed point in C.

    In Theorem 2, Δ is the set of all pairs (θ,f) satisfying the following:

    (Δ1) θ(tn)0 for each strictly increasing sequence {tn};

    (Δ2) f is strictly increasing function;

    (Δ3) for each sequence {αn} of positive numbers, limnαn=0 if and only if limnf(αn)=.

    (Δ4) If {tn} is a decreasing sequence such that tn0 and θ(tn)<f(tn)f(tn+1), then we have n=1tn<.

    We know that the Hausdorff measure of noncompactness χ in the Banach space p can be defined as follows:

    χ(B)=limn{supxB{Σknxkp}1p}, (2.2)

    where BMp and x=(xk)p. For the Banach space (c0,.c0), the Hausdorff measure of noncompactnes χ is given by (cf. Definition 1):

    χ(B)=limn{supuB{maxknuk}}, (2.3)

    where BMc0 and u=(uk)c0.

    Now, we recall some basic facts concerning the concept of the variation of a function (cf.[14,15]).

    Assume that f is a real function defined on the interval [a,b]. The variation of the function f will be denoted by baf. If baf is finite, the function f has bounded variation on the interval [a,b]. Similarly, if g:[a,b]×[c,d]R is a real function of two variables, then the variation of the function tg(t,s) on the interval [p,q][a,b] will be denoted by qs=pg(t,s). Analogously, we can define qt=pg(t,s). Assume that f and g are two real functions defined on the interval [a,b], then under appropriate conditions we can define the Steiltjes integral baf(t)dg(t) of the function f with respect to the function g. If the integral baf(t)dg(t) is finite, then f is Stieltjes integrable on the interval [a,b].

    The following lemmas will be applied in our investigations.

    Lemma 1. If f is Stieltjes integrable on the interval [a,b] with respect to a function g of bounded variation, then

    |baf(t)dg(t)|ba|f(t)|d(tag).

    Lemma 2. Let f1 and f2 be Stieltjes integrable functions on the interval [a,b] with respect to a nondecreasing function g such that f1(t)f2(t) for t[a,b]. Then,

    baf1(t)dg(t)baf2(t)dg(t).

    In this section, as an application of Theorem 2, the existence of solutions for the infinite system (1.1) is studied in the spaces p and c0. First, we show that infinite system (1.1) has a solution that belongs to the space p.

    We consider the following conditions:

    (H1)Fn:R+×R+×R×RR is continuous and there exist positive real numbers τ>0 such that

    |Fn(t,s,x1,y1)Fn(t,s,x2,y2)|peτ(|x1x2|p+|y1y2|p),

    for all t,sR+ and x1,x2,y1,y2R. Moreover, we have

    limiΣi=1|Fi(t,s,0,0)|p=0,N1=Σi=1|Fi(t,s,0,0)|p.

    (H2)f1:R+×RR is continuos with f0=suptR+|f(t,0)| and there exist positive real numbers τ>0 such that

    |f1(t,u(t,x))f1(t,v(t,x))|peτu(t,x)v(t,x)p,|f1(t,u(t,x))|peτu(t,x)p.

    for all t,xR+ and u(t,x)={ui(t,x)}i=1,v(t,x)={vi(t,x)}i=1p.

    (H3)T:BC(R+×R+,p)BC(R+×R+,R) is a continuos operator such that

    |(Tu)(t,x)(Tv)(t,x)|u(t,x)v(t,x)p,|(Tu)(t,x)|1.

    for all u,vBC(R+×R+,p) and t,xR+.

    (H4) For any fixed t>0 the function sgi(t,s) has a bounded variation on the interval [0,t] and the function tts=0gi(t,s) is bounded over R+.

    (H5)gn:R+×R+×R+×R+×RR is continuous and there exist continuous functions an:R+×R+R+ such that

    |gn(t,s,x,y,u(t,x))|an(t,s),limtΣn1t0|gn(t,s,x,y,u(t,x))gn(t,s,x,y,v(t,x))|dstq=0g1(t,q)=0,φk=sup{Σnk[|t0x0gn(t,s,x,y,u(t,x))dyg2(x,y)dsg1(t,s)|];t,s,x,yR+,u(t,x)R}.

    Moreover, assume that

    A=sup{Σn=1t0an(t,s)dssp=0g1(t,p),tR+},G=sup{xy=0g2(x,y);xR+},limkφk=0.

    (H6)Vn:R+×R+×RR is a continuous function and there exists continuous function k:R+×R+R+ such that the function sk(t,s) is integrable over R+ and the following conditions hold:

    |Vn(t,s,u(t,x))|k(t,s)|un(t,x)|p,|Vn(t,s,u(t,x))Vn(t,s,v(t,x)||un(t,x)vn(t,x)|pk(t,s).

    for all t,s,xR+ and u,vp. Moreover, assume that

    M=suptR+0k(t,s)ds.

    (H7) There exists a positive solution r0 such that

    22pe2τrp0(GA)p+22peτfp0(GA)p+2peτrp0Mp+2pN1rp0,

    Moreover, assume that 2pM<1.

    Theorem 3. Under the assumptions (H1)(H7), Eq (1.1) has at least one solution u(t,x)={ui(t,x)}i=1 in the space p.

    Proof. Let us define the operator G on BC(R+×R+,p) by

    (Gu)(t,x)={Fn(t,s,f1(t,u(t,x))t0x0gn(t,s,x,y,u(t,x))dyg2(x,y)dsg1(t,s),(Tu)(t,x)0Vn(t,s,u(t,x))ds)}.

    In view of our assumptions, for all t,xR+, we get

    (Gu)(t,x)pp=Σi=1|Fi(t,s,f1(t,u(t,x))t0x0gi(t,s,x,y,u(t,x))dyg2(x,y)dsg1(t,s),(Tu)(t,x)0Vi(t,s,u(t,x))ds)|p2pΣi=1|Fi(t,s,f1(t,u(t,x))t0x0gi(t,s,x,y,u(t,x))dyg2(x,y)dsg1(t,s),(Tu)(t,x)0Vi(t,s,u(t,x))ds)Fi(t,s,0,0)|p+2pΣi=1|Fi(t,s,0,0)|p2pΣi=1[eτ|f1(t,u(t,x))t0x0gi(t,s,x,y,u(t,x))dyg2(x,y)dsg1(t,s)|p+eτ|(Tu)(t,x)0Vi(t,s,u(t,x))ds|p]+2pΣi=1|Fi(t,s,0,0)|p22peτΣi=1(|f1(t,u(t,x))f1(t,0)|p)×(t0x0|gi(t,s,x,y,u(t,x))|dyyq=0g2(x,q)sp=0dsg1(t,p))p+22peτΣi=1|f1(t,0)|p(t0x0|gi(t,s,x,y,u(t,x))|dyyq=0g2(x,q)sp=0dsg1(t,p))p+2peτ(0k(t,s)ds)pΣi=1|ui(t,x)|p+2pΣi=1|Fi(t,s,0,0)|p22pe2τu(t,x)pp(GA)p+22peτ(f0)p(GA)p+2peτMpu(t,x)pp+2pN1. (3.1)

    Thus, by applying the last estimates and assumption (H7) one can easily seen that G maps ¯Br0 into itself, where

    ¯Br0={uBC(R+×R+,p);uBC(R+×R+,p)r0}.

    Next, we prove that the operator G is a continuous operator on the Ball ¯Br0. For this, take ε>0 arbitrarily and u(t,x)={ui(t,x)}i=1,v(t,x)={vi(t,x)}i=1¯Br0 with uvBC(R+×R+,p)<ε. Acordingly, taking into account our assumptions, for (t,x)R+×R+ we have

    (Gu)(t,x)(Gv)(t,x)ppΣi=1eτ|f1(t,u(t,x))t0x0gi(t,s,x,y,u(t,x))dyg2(x,y)dsg1(t,s)f1(t,v(t,x))t0x0gi(t,s,x,y,v(t,x))dyg2(x,y)dsg1(t,s)|p+Σi=1eτ|(Tu)(t,x)0Vi(t,s,u(t,x))ds(Tv)(t,x)0Vi(t,s,v(t,x))ds|p. (3.2)

    On the other hand, we have

    |f1(t,u(t,x))t0x0gi(t,s,x,y,u(t,x))dyg2(x,y)dsg1(t,s)f1(t,v(t,x))t0x0gi(t,s,x,y,v(t,x))dyg2(x,y)dsg1(t,s)|p2p|f1(t,u(t,x))f1(t,v(t,x))|p×(t0x0|gn(t,s,x,y,u(t,x))|dyyp=0g2(x,p)dstq=0g1(t,q))p+2p|f1(t,v(t,x))|p(t0x0|gn(t,s,x,y,u(t,x))gn(t,s,x,y,v(t,x))|dyyp=0g2(x,p)dstq=0g1(t,q))peτ2pu(t,x)v(t,x)p(xy=0g2(x,y)|t0an(t,s)dstq=0g1(t,q))p+2p|f1(t,v(t,x))|p(xy=0g2(x,y)t0|gn(t,s,x,y,u(t,x))gn(t,s,x,y,v(t,x))|dstq=0g1(t,q))peτ2pu(t,x)v(t,x)p(GAi)p+2pGp|f1(t,v(t,x))(t0|gi(t,s,x,y,u(t,x))gi(t,s,x,y,v(t,x))|dstq=0g1(t,q))p. (3.3)

    Further, by applying our assumptions, we arrive that

    |(Tu)(t,x)0Vi(t,s,u(t,x))ds(Tv)(t,x)0Vi(t,s,v(t,x))ds|p2p|(Tu)(t,x)0Vi(t,s,u(t,x))ds(Tv)(t,x)0Vi(t,s,u(t,x))ds|p+2p|(Tv)(t,x)0Vi(t,s,u(t,x))ds(Tv)(t,x)0Vi(t,s,v(t,x))ds|p2pu(t,x)v(t,x)pp|ui(t,x)|pMp+Mp|ui(t,x)vi(t,x)|p. (3.4)

    Combining (3.2), (3.3) and (3.4), we conclude that

    (Gu)(t,x)(Gv)(t,x)ppΣi=1e2τ2pu(t,x)v(t,x)pp(GAi)p+2pGpeτ|f1(t,v(t,x))|p(Σi=1t0|gi(t,s,x,y,u(t,x))gi(t,s,x,y,v(t,x))|dstq=0g1(t,q))p+Σi=1|ui(t,x)|peτ2pMpu(t,x)v(t,x)|pp+eτ2pMpΣi=1|ui(t,x)vi(t,x)|p. (3.5)

    Using (H5), there exists T>0 such that for t>T, we get

    Σi=1t0|gi(t,s,x,y,u(t,x))gi(t,s,x,y,v(t,x))|dstq=0g1(t,q)<ε.

    Hence, by (3.5), we conclude that

    (Gu)(t,x)(Gv)(t,x)pp2pe2τuvpBC(R+×R+,p)(GA)p+2pGpεpeτv(t,x)pp+2pMpeτuvpBC(R+×R+,p)u(t,x)pp+eτ2pMpuvpBC(R+×R+,p). (3.6)

    For t[0,T] we have

    (Gu)(t,x)(Gv)(t,x)pp2pe2τuvpBC(R+×R+,p)(GA)p+v(t,x)pp2pGpω(g,ε)peτ+2pMpeτuvpBC(R+×R+,p)u(t,x)pp+eτ2pMpuvpBC(R+×R+,p), (3.7)

    where

    ω(g,ε)=sup{Σn=1|gn(t,s,x,,y,u)gn(t,s,x,y,v)|;(t,s)Δ1,(x,y)Δ2,u,vp,uvBC(R+,R+,p)<ε},Δ1={(t,s)R2;stT},Δ2={(x,y)R2;yxT}.

    and ω(g,ε)0 as ε0. Consequently, G is continuous on the ball ¯Br0. To finish the proof, we prove that the condition (2.1) of Theorem 2 is fulfilled. Let X be a nonempty and bounded subset of the ball ¯Br0. Assume that

    (Hn)(u)=f1(t,u(t,x))t0x0gn(t,s,x,y,u(t,x))dyg2(x,y)dsg1(t,s),(Dn)(u)=(Tu)(t,x)0Vn(t,s,u(t,x))ds.

    Thus, by applying our assumptions, we infer that

    χp(G(X))(t,x)=limn[supu(t,x)X{Σkn|Fk(t,s,(Hk)(u),(Dk)(u))|p}1p]=limn[supu(t,x)X{Σkn|Fk(t,s,(Hk)(u),(Dk)(u))Fk(t,s,0,0)+Fk(t,s,0,0)|p}1p]2peτlimn[supu(t,x)X{Σkn{|(Hk)(u)|p+|(Dk)(u)|p}}1p]2peτlimn[supu(t,x)X{Σkn{eτu(t,x)ppφn+Mp|uk(t,x)|p}1p]=2peτMlimn[supu(t,x)X{Σkn|uk(t,x)|p}1p]. (3.8)

    Hence,

    χp(G(X))(t,x))2peτMlimn[supu(t,x)X{Σkn|uk(t,x)|p}1p]. (3.9)

    Consequently,

    sup(t,x)R+×R+χp(G(X))(t,x))=χBC(R+×R+,p)(GX)sup(t,x)R+×R+2peτMlimn[supu(t,x)X{Σkn|uk(t,x)|p}1p].

    By passing to logarithms, we get

    ln(χBC(R+×R+,p))(GX))+τln(χBC(R+×R+,p)(X)) (3.10)

    Now applying Theorem 2 with f(t)=ln(t) and θ(t)=τ, we obtain that G has a fixed point and the proof is completed.

    Example 1. Now, we investigate the following system of integral equations:

    un(t,x)=(eτtn)1p2sin((etτ)1psin(u(t,x)p)2×t0x0arctan(12n×e3t+s8+|x|+|y|+|un(t,x)|)ex1+y2e2xet1+t2dyds+cos(11+u(t,x)lp)0es1+t8sin(|un(t,x)|)ds); (3.11)

    Observe that Eq (3.11) is a special case of the infinite system (1.1) if we put

    Fn(t,s,x,y)=(eτtn)1p2sin(x+y),gn(t,s,x,y,u(t,x))=arctan(12n×e3t+s8+|x|+|y|+|un(t,x)|),f1(t,u(t,x))=(etτ)1psin(u(t,x)p)2,an(t,s)=12ne3t+s,g1(t,s)=set1+t2,g2(x,y)=arctan(yex),Vn(t,s,u(t,x))=es1+t8sin(|un(t,x)|),k(t,s)=es1+t8,(Tu)(t,x)=cos(11+u(t,x)lp).

    Thus, it is easily seen that Fn and f1 satisfy assumptions (H1) and (H2) with N1=0 and f0=0. Further, the operator T satisfies hypothesis (H3). To justify assumption (H5), let t,sx,yR+ and u,up. Then, we have

    |gn(t,s,x,y,u(t,x))|12ne3t+s=an(t,s).

    Since g1s=et1+t2>0, then sq=0g1(t,q)=g1(t,s)g1(t,0)=set1+t2. Consequently, we have

    limtt0an(t,s)dssq=0g1(t,q)=limtt012ne3t+s(et1+t2)ds=limt12ne2t+s1+t2|t0=0

    Inconsequence,

    limtΣn1t0|gn(t,s,x,y,u(t,x))gn(t,s,x,y,v(t,x))|dstq=0g1(t,q)=0,A=sup{Σi=1t0an(t,s)dssp=0g1(t,s),tR+},φk=sup{Σnk[t0x0gn(t,s,x,y,u(t,x))dyg2(x,y)dsg1(t,s)];t,s,x,yR+,u(t,x)p}G(e2t1+t2et1+t2)Σnk12n.

    So, φk0. On the other hand the function Vn(t,s,u(t,x))=es1+t8sin(|un(t,x)|) verifies assumption (H6) with k(t,s)=es1+t8 and M=1. To show that the functions g1 and g2 satisfy assumption (H4), let first note that the functions g1 and g2 are increasing on every interval of the form [0,t] and g2 is bounded on the triangle 2. Consequently, the function yg2(x,y) has bounded variation on the interval [0,x] and we have

    xy=0g2(x,y)=g2(x,y)g2(x,0)=g2(x,y)π4.

    So, Gπ4. We can take G=π4. Consequently, all conditions of Theorem 3 are satisfied and Theorem 3 implies that the infinite system (3.11) has at least one solution which belongs to the space p.

    Now the existence of solutions of the system (1.1) is studied in the space c0. In this case, we need the following assumptions.

    (D1)Fn:R+×R+×R×RR is continuous and there exist positive real numbers τ>0 such that

    |Fn(t,s,x1,y1)Fn(t,s,x2,y2)|eτ(|x1x2|+|y1y2|),

    for all t,sR+ and x1,x2,y1,y2R. Moreover, assume that

    limi|Fi(t,s,0,0)|=0,M1=sup{|Fi(t,s,0,0)|;t,sR+,i1}.

    (D2)f1:R+×RR is continuous with f0=suptR+|f(t,0)| and there exist positive real numbers τ>0 such that

    |f1(t,u(t,x))f1(t,v(t,x))|eτsupn1{|ui(t,x)vi(t,x)|;in},|f1(t,u(t,x))|eτsupn1{|ui(t,x)|;in}

    for all t,xR+ and u(t,x)={ui(t,x)},v(t,x)={vi(t,x)}c0

    (D3)T:BC(R+×R+,c0)BC(R+×R+,R) is a continuous operator such that

    |(Tu)(t,x)(Tv)(t,x)|supn1{|ui(t,x)vi(t,x)|;in},|(Tu)(t,x)|1.

    for all u,vBC(R+×R+,c0) and t,xR+.

    (D4) For any fixed t>0 the function sgi(t,s) has a bounded variation on the interval [0,t] and the functions tts=0gi(t,s) are bounded on R+. Moreover, for arbitrarily fixed T>0 the function wwz=0gi(w,z) is continuous on the interval [0,T] for i=1,2.

    (D5)gn:R+×R+×R+×R+×RR is continuous and there exist continuous functions an:R+×R+R+ such that

    |gn(t,s,x,y,u(t,x))|an(t,s),limtt0|gn(t,s,x,y,u(t,x))gn(t,s,x,y,v(t,x))|dstq=0g1(t,q)=0,

    for all t,s,x,yR+ and u,vR. Moreover, assume that

    limnt0an(t,s)dssp=0g1(t,p)=0,A=sup{t0an(t,s)dssp=0g1(t,p);nN},G=sup{xy=0g2(x,y);xR+},G1=sup{wz=0g1(w,z);w[0,T]}.

    where T>0 is arbitrarily fixed.

    (D6)Vn:R+×R+×RR is a continuous function and there exists continuous function k:R+×R+R+ such that the function sk(t,s) is integrable over R+ and the following conditions hold:

    |Vn(t,s,u(t,x))|k(t,s)supn1{|ui(t,x)|;in},|Vn(t,s,u(t,x))Vn(t,s,v(t,x)|supn1{|ui(t,x)vi(t,x);in}k(t,s).

    for all t,s,xR+ and u,vc0. Moreover, assume that

    M=suptR+0k(t,s)ds<1,e2τGA+f0GAeτ+Meτ+Meτ<1.

    Theorem 4. Under assumptions (D1)(D6), the infinite system (1.1) has at least one solution u(t)={ui(t,x)}i=1 belonging to the space c0.

    Proof. Define the operator G on the space BC(R+×R+,c0) as

    (Gu)(t,x)={Fn(t,s,f1(t,u(t,x))t0x0gn(t,s,x,y,u(t,x))dyg2(x,y)dsg1(t,s),(Tu)(t,x)0Vn(t,s,u(t,x))ds)}

    where t,xR+. We show that

    ¯Br0={uBC(R+×R+,c0);uBC(R+×R+,c0)r0}

    is G-invariant where i=1,2,... and t,xR+. Assume that

    (Hn)(u)=t0x0gn(t,s,x,y,u(t,x))dyg2(x,y)dsg1(t,s),(Dn)(u)=(Tu)(t,x)0Vn(t,s,u(t,x))ds.

    For arbitrarily fixed (t,x)R+×R+, we have

    (Gu)(t,x)c0=supn1|Fn(t,s,(Hn)(u),(Dn)(u))|supn1[|Fn(t,s,f1(t,u(t,x))(Hn)(u),(Dn)(u))Fn(t,s,0,0)|+|Fn(t,s,0,0)|]supn1[eτ|(f1(t,u(t,x))Hn)(u)|+eτ|(Dn)(u)|]+supn1|Fn(t,s,0,0)|supn1[eτ(|f1(t,u(t,x))f1(t,0)|+|f1(t,0)|)(|Hn)(u)|+eτu(t,x)|c0M]supn1[e2τ{|ui(t,x)|;in}GA+f0GAeτ+eτu(t,x)c0M(e2τGA+eτf0GA+Meτ)u(t,x)c0.

    Consequently,

    Guu(t,x)c0 (4.1)

    By applying (4.1), one can easily seen that G maps the ball ¯Br0 into itself. Next, the continuity property of the operator G will be proved on the ball ¯Br0. Let u,vBr0 and ε>0 such that uvBC(R+×R+,c0)<ε. Thus for all t,xR+, we have

    (Gu)(t,x)(Gv)(t,x)c0=supn1|Fn(t,s,f1(t,u(t,x))Hn(u),(Dnu))Fn(t,s,f1(t,v(t,x))Hn)(v),(Dnv))|supn1{eτ|f1(t,u(t,x))Hn)(u)f1(t,v(t,x))Hn)(v)|+eτ|(Dn)(u)(Dn)(v)|}. (4.2)

    Besides, we have

    |f1(t,u(t,x))Hn)(u)f1(t,v(t,x))Hn)(v)|2pGAeτsupn1{|ui(t,x)vi(t,x)|;in}+2peτGsupn1{|vi(t,x)|;in}×t0|gn(t,s,x,y,u(t,x))gn(t,s,x,y,v(t,x))ds(tq=0g1(t,q). (4.3)

    By assumption (D5), there exists T>0 such that for t>T, we have

    t0|gn(t,s,x,y,u(t,x))gn(t,s,x,y,v(t,x))|ds(tq=0g1(t,q)<ε.

    Further, the assumptions (D3) and (D6) give us the following eastimates

    |(Tu)(t,x)0Vn(t,s,u(t,x))ds(Tv)(t,x)0Vn(t,s,v(t,x))ds|Mu(t,x)v(t,x)c0u(t,x)c0+|(Tv)(t,x)|0|Vn(t,s,u(t,x))Vn(t,s,v(t,x))|dsMu(t,x)v(t,x)c0u(t,x)c0+Mu(t,x)v(t,x)c0. (4.4)

    Applying (4.2), (4.3) and (4.4), we have

    (Gu)(t,x)(Gv)(t,x)c02pe2τGAsupn1{|ui(t,x)vi(t,x)|;in}+2pe2τGsupn1{|vi(t,x)|;in}ε+MuvBC(R+×R+,c0)+M(u(t,x)c0)uvBC(R+×R+,c0)2pe2τGAε+2peτGv(t,x)c0ε+eτMε+Meτu(t,x)c0)ε. (4.5)

    For t[0,T], we have

    (Gu)(t,x)(Gv)(t,x)c02pe2τGAsupn1{|ui(t,x)vi(t,x)|;in}+2peτGsupn1{|ui(t,x);in}G1ω(gn,ε)+Muvc0+MuBC(R+×R+,c0)uvBC(R+×R+,c0)eτGAε+eτGG1v(t,x)c0ω(gn,ε)+Mε+MuBC(R+×R+,c0)ε, (4.6)

    where

    ω(gn,ε)=sup{|gn(t,s,x,y,u(t,x))gn(t,s,x,y,v(t,x))|;(t,s)Δ1,(x,y)Δ2,u,vR;uvBC(R+×R+,c0)<ε}.

    Moreover, in light of the continuity of V on 1×2×R, we have ω(gn,ε)0. Now, combining (4.5) and (4.6) implies that G is continuous on the Ball ¯Br0. In what follows let X be a nonempty subset of the ball ¯Br0, In view of the formula (2.3) and our assumptions, we have

    χc0(GX)(t,x)=limn{supuX(maxin|Fi(t,s,(Hi)(u),(Di)(u)|)}limn{supuX(maxin|Fi(t,s,(Hi)(u),(Di)(u)|)Fi(t,s,0,0)|+|Fi(t,s,0,0)|}limn{supuX(maxin(eτ|(Hi)(u)|+eτ|(Di)(u)|))}limn{supuX(maxin(eτ|f1(t,u(t,x))f1(t,0)|(Hi)(u)|+eτ|f1(t,0)|(Hi)(u)|+eτ|(Di)(u)|))}limn{supuX(maxin(e2τsupn1{|ui(t,x);in}GA+f0GA+eτsupn1{|ui(t,x);in}M)}.

    Consequently,

    χBC(R+×R+,c0)(GX)Meτsup(t,x)R+×R+limn{supuX(maxin|ui(t,x)|)}.

    As, M<1, by passing to logarithms, we have

    τ+ln(χBC(R+×R+,c0)(GX))ln(χBC(R+×R+,c0)(X))).

    Thus all conditions of Theorem 2 hold true with f(t)=ln(t) and θ(t)=τ and by Theorem 2 there exists {ui(t,x)}i=1c0 such that

    un(t,x)=Fn(t,s,f1(t,u(t,x))t0x0gn(t,s,x,y,u(t,x))dyg2(x,y)dsg1(t,s),(Tu)(t,x)0Vn(t,s,u(t,x))ds). (4.7)

    Hence, the proof is completed.

    Example 2.

    Nowweinvestigateun(t,x)=etsτn35arctan(eτΣkn|uk(t,x)|1+k2)(Hn)(u)+7(Dn)(u) (4.8)

    on the space c0. Taking

    (Dn)(u)=e100Σknsin(|uk(t,x)|)(1+k2)0etsnΣkn|uk(t,x)|10n(1+k2)ds,(Hn)(u)=t0x0arctan(es+t2n8+|u(t,x)|)e2t1+t2×ex1+y2e2xdyds,Fn(t,s,x,y)=eτtsn35x+7y,f1(t,u(t,x))=arctan(eτΣkn|uk(t,x)|1+k2),gn(t,s,x,y,u(t,x))=arctan(es+t2n8+|u(t,x)|),g1(t,s)=se2t1+t2,g2(x,y)=arctan(yex),Vn(t,s,u(t,x))=etsnΣkn|uk(t,x)|10n(1+k2),k(t,s)=ets,(Tu)(t,x)=e100Σknsin(|uk(t,x)|)(1+k2)nN,

    in the system (1.1), the system of integral Eq (4.8) is obtained. Note that the functions Fn and f1 satisfy conditions (D1) and (D2). Indeed, we have

    |Fn(t,x1,y1)Fn(t,x2,y2)|=eτnt[|35x1+7y135x1+7y1|]eτ[35x1+7y15x27y2]eτ[35x1x2+7y1y2|]eτ[|x1x2|+|y1y2|],M1=0,limnFn(t,s,0,0)=0,|f1(t,u(t,x))|supn1{|ui(t,x)|;in},|f1(t,u(t,x))f1(t,v(t,x))|supn1{|ui(t,x)||vi(t,x);in}

    Also, it can easily be seen that the operator T satisfies assumption (D3) and

    |(Tu)(t,x)|e100π26supn1{|ui(t,x)|;in},|(Tu)(t,x)(Tv)(t,x)|eτπ26supn1{|ui(t,x)vi(t,x)|;in}.

    Moreover, since g1s=e2t1+t2>0, so g1 is increasing and we have

    sq=0g1(t,q)=g1(t,s)g1(t,0)=g1(t,s)=se2t1+t2>0

    Consequently,

    |gn(t,s,x,y,u(t,x))|es+t2n,limtt0|gn(t,s,x,y,u(t,x))gn(t,s,x,y,v(t,x))|dstq=0g1(t,q) 2limtt0et+se2t1+t2ds=0

    Again, we have

    yq=0g2(x,y)=g2(x,y)g2(x,0)=g2(x,y)π4,limnt0an(t,s)dssq=0g1(t,q)=limn2n(11+t2et1+t2)=0.

    So, G=π4 and A<. On the other hand the function Vn(t,s,u(t,x))=etsnΣkn|uk(t,x)|10n(1+k2) verifies assumption (D6) with k(t,s)=ets and M=1. By applying the continuity of the function hwz=0gi(h,z) on the interval [0,T] we can take G1=sup{wz=0g1(w,z):w[0,T]} where T>0 is arbitrarily fixed. Thus all conditions of Theorem 4 are satisfied and by applying Theorem 4, infinite system (4) has at least one solution in the space c0

    We studied the existence of solutions for an infinite system of integral equations of Volterra-Stieltjes type of the following form in the Banach sequence spaces p and c0 via the techniques of measures of noncompactness and Darbo's fixed point theorem.

    un(t,x)=Fn(t,s,f1(t,u(t,x))t0x0gn(t,s,x,y,u(t,x))dyg2(x,y)dsg1(t,s),(Tu)(t,x)0Vn(t,s,u(t,x))ds);u(t,x)={ui(t,x)}i=1,ui(t,x)BC(R+×R+,R),

    where BC(R+×R+,R) is the space of all real functions u(t,x)=u:R+×R+R, which are defined, continuous and bounded on the set R+×R+ with a supremum norm u=sup{|u(t,x)|:(t,x)R+×R+}. Some examples in the Banach sequence spaces p and c0 are also given to ascertain the usefulness of our main result.

    Research of the author M. Mursaleen was supported by SERB Core Research Grant, DST, New Delhi, under grant NO. EMR/2017/000340.

    All authors declare no conflicts of interest in this paper.



    Funding



    This work was supported by Geriatric Education and Research Institute's Intramural fund (reference number GERI1616).

    Conflict of interest



    All authors declare no conflicts of interest in this paper.

    [1] Hojat M, Mangione S, Nasca TJ, et al. (2004) An empirical study of decline in empathy in medical school. Med Educ 38: 934-941. https://doi.org/10.1111/j.1365-2929.2004.01911.x
    [2] Bellini LM, Baime M, Shea JA (2002) Variation of mood and empathy during internship. JAMA 287: 3143-3146. https://doi.org/10.1001/jama.287.23.3143
    [3] Hojat M, Vergare MJ, Maxwell K, et al. (2009) The devil is in the third year: A longitudinal study of erosion of empathy in medical school. Acad Med 84: 1182-1191. https://doi.org/10.1097/ACM.0b013e3181b17e55
    [4] Bellini LM, Shea JA (2005) Mood change and empathy decline persist during three years of internal medicine training. Acad Med 80: 164-167. https://doi.org/10.1097/00001888-200502000-00013
    [5] Riess H, Kelley JM, Bailey RW, et al. (2012) Empathy training for resident physicians: A randomized controlled trial of a neuroscience-informed curriculum. J Gen Intern Med 27: 1280-1286. https://doi.org/10.1007/s11606-012-2063-z
    [6] Wündrich M, Schwartz C, Feige B, et al. (2017) Empathy training in medical students—A randomized controlled trial. Med Teach 39: 1096-1098. https://doi.org/10.1080/0142159X.2017.1355451
    [7] Zhou YC, Tan SR, Tan CGH, et al. (2021) A systematic scoping review of approaches to teaching and assessing empathy in medicine. BMC Med Educ 21: 292. https://doi.org/10.1186/s12909-021-02697-6
    [8] Decety J (2020) Empathy in medicine: What it is, and how much we really need it. Am J Med 133: 561-566. https://doi.org/10.1016/j.amjmed.2019.12.012
    [9] Koblar S, Cranwell M, Koblar S, et al. (2018) Developing empathy: Does experience through simulation improve medical-student empathy?. Med Sci Educ 28: 31-36. https://doi.org/10.1007/s40670-017-0488-z
    [10] Chen A, Hanna JJ, Manohar A, et al. (2018) Teaching empathy: the implementation of a video game into a psychiatry clerkship curriculum. Acad Psychiatry 42: 362-365. https://doi.org/10.1007/s40596-017-0862-6
    [11] Patel S, Pelletier-Bui A, Smith S, et al. (2019) Curricula for empathy and compassion training in medical education: A systematic review. PloS One 14: e0221412. https://doi.org/10.1371/journal.pone.0221412
    [12] Noordman J, Post B, van Dartel AAM, et al. (2019) Training residents in patient-centred communication and empathy: evaluation from patients, observers and residents. BMC Med Educ 19: 128. https://doi.org/10.1186/s12909-019-1555-5
    [13] Hojat M, Gonnella JS, Nasca TJ, et al. (2002) Physician empathy: definition, components, measurement, and relationship to gender and specialty. Am J Psychiatry 159: 1563-1569. https://doi.org/10.1176/appi.ajp.159.9.1563
    [14] Fragkos KC, Crampton PES (2020) The effectiveness of teaching clinical empathy to medical students: A systematic review and meta-analysis of randomized controlled trials. Acad Med 95: 947-957. https://doi.org/10.1097/ACM.0000000000003058
    [15] Quince T, Thiemann P, Benson J, et al. (2016) Undergraduate medical students' empathy: current perspectives. Adv Med Educ Pract 7: 443-455. https://doi.org/10.2147/AMEP.S76800
    [16] Hojat M (2009) Ten approaches for enhancing empathy in health and human services cultures. J Health Hum Serv Adm 31: 412-450.
    [17] Tan L, Le MK, Yu CC, et al. (2021) Defining clinical empathy: a grounded theory approach from the perspective of healthcare workers and patients in a multicultural setting. BMJ Open 11: e045224. https://doi.org/10.1136/bmjopen-2020-045224
    [18] Batt-Rawden SA, Chisolm MS, Anton B, et al. (2013) Teaching empathy to medical students: An updated, systematic review. Acad Med 88: 1171-1177. https://doi.org/10.1097/ACM.0b013e318299f3e3
    [19] Kelm Z, Womer J, Walter JK, et al. (2014) Interventions to cultivate physician empathy: A systematic review. BMC Med Educ 14: 219. https://doi.org/10.1186/1472-6920-14-219
    [20] Shapiro J (2008) Walking a mile in their patients' shoes: empathy and othering in medical students' education. Philos Ethics Humanit Med 3: 10. https://doi.org/10.1186/1747-5341-3-10
    [21] Watling CJ, Lingard L (2012) Grounded theory in medical education research: AMEE Guide No. 70. Med Teach 34: 850-861. https://doi.org/10.3109/0142159X.2012.704439
    [22] Heath H, Cowley S (2004) Developing a grounded theory approach: A comparison of Glaser and Strauss. Int J Nurs Stud 41: 141-150. https://doi.org/10.1016/s0020-7489(03)00113-5
    [23] Clarke V, Braun V (2012) Thematic analysis, In: Cooper H, Camic PM, Long DL, et al. Editors, APA handbook of research methods in psychology, Vol. 2. Research designs: Quantitative, qualitative, neuropsychological, and biological, Washington: American Psychological Association, 57-71 https://doi.org/10.1037/13620-004
    [24] Nanyang Technological University, Our Pedagogy. Singapore Nanyang Technological University, (2023) Available from: www.ntu.edu.sg/medicine/education/bachelor-of-medicine-and-bachelor-of-surgery-(mbbs)/our-pedagogy. Accessed 27 Nov. 2023
    [25] Batson CD, Lishner DA, Stocks EL (2010) The empathy-altruism hypothesis, In: Schroeder DA, Graziano WG, Auhors, The Oxford Handbook of Prosocial Behavior, Oxford: Oxford Academic, 259-281 https://doi.org/10.1093/oxfordhb/9780195399813.013.023
    [26] Batson CD (2010) Behavioral consequences of empathy-induced altruism. In: Batson CD, Auhtor, Altruism in Humans, Oxford: Oxford Academic, 59-80 https://doi.org/10.1093/acprof:oso/9780195341065.003.0004
    [27] Tseng WT, Lin YP (2016) “Detached concern” of medical students in a cadaver dissection course: A phenomenological study. Anat Sci Educ 9: 265-271. https://doi.org/10.1002/ase.1579
    [28] Halpern J (2003) What is clinical empathy?. J Gen Intern Med 18: 670-674. https://doi.org/10.1046/j.1525-1497.2003.21017.x
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    17. Yue Li, Qian Zhao, Haijing Sun, Yichuan Shao, Yong Wang, Research on the SEGDC‐UNet electron microscope image segmentation algorithm based on channel attention mechanism, 2025, 0022-2720, 10.1111/jmi.13394
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