Overall latency for the single nanosatellite. All values in \n
\r\n\tKey Features:
\r\n\t*Reviews the basics of plating technology including electroless and immersion technologies
\r\n\t*Covers microjoining and nanojoining processes in various device applications
\r\n\t*Examines applications of microjoining such as the wafer level packaging, biomedical research, medical implants etc.
Small (micro-, nano-, pico-) satellites and (micro-) unmanned aerial systems (UASs) are emerging technologies that have the potential to be of great academic and commercial use but only if a balance can be found between two diametrically opposed forces that act on their design: the desire, and need, for high performance and the desire to reduce costs. High performance, especially in state estimation, is necessary for these technologies to be advantageous over traditional aerospace systems in relevant applications.
\nThe desire to reduce the costs of these technologies has led to their miniaturisation and heavy use of commercial off-the-shelf (COTS) components so that some level of economy of scale may be achieved. Though both component and development costs can be reduced in this way, this approach, in turn, leads to a reduction in the resources available (e.g. electrical power, computing power and physical space) aboard those systems, impacting performance.
\nSpecialised hardware, e.g. application-specific integrated circuit (ASIC)- or field-programmable gate array (FPGA)-based systems, can achieve high performance, even for severely resource-constrained systems, but tends to increase the development complexity of these systems; in this way, using specialised hardware may reduce component costs and meet performance and miniaturisation requirements, while development costs are typically increased. This issue is illustrated in Figure 1, which depicts the balance between development complexity and performance for different embedded systems; greater complexity during the development process means that a greater investment in resources, personnel and time becomes necessary, which leads to higher development costs.
\nThe performance versus development complexity trade-off for different types of embedded systems.
Software approaches, e.g. microprocessor-based systems, generally have lower performance than specialised hardware but have much simpler, and thus cheaper, development processes. It is, however, possible to draw upon aspects of both hardware and software approaches and combine them into a hardware/software codesign. This codesign could deliver the high performance of specialised hardware but, by using software techniques, e.g. modularity or abstraction, could also alleviate some of the high development costs associated with such hardware. If this codesign approach is applied to a prolific state estimation algorithm, then the performance and miniaturisation requirements could be met, while keeping development costs low.
\nIn this chapter, a library containing a scalable, hardware/software (HW/SW) codesign of the unscented Kalman filter (UKF), based on an FPGA, is presented. The codesign is implemented as a fully parameterisable, self-contained ‘black box’ (which is often referred to as an IP core), which aims to minimise the necessary input from system designers when applying the codesign to a new application, such that overall development complexity is reduced.
\nThis chapter is a distillation of work first presented in [1]. The rest of this chapter is organised as follows: Section 2 provides background on relevant concepts, Section 3 outlines the proposed design, Section 4 describes the simulation model to verify the design and simulation results, Section 5 presents implementation results and Section 6 concludes the chapter.
\nHardware/software codesign is a design practice that is often used with system-on-a-chip (SoC) architectures. The term system on a chip comes from the field of very large-scale integration (VLSI) where individual hardware units or ‘black boxes’ (IP cores) that perform some dedicated function are arranged and connected together on a single ASIC chip. Typical SoCs may include a microcontroller or microprocessor core, DSPs, memories such as RAMs or ROMs, peripherals such as timers/counters, communication interfaces such as USB/UART, analog interfaces such as ADCs/DACs or other analog, digital, mixed-signal or RF hardware. Previously, each of these components may have had its own ASIC and was connected together on a PCB, but, in accordance with Moore’s law, resource densities of silicon chips have massively increased over time, so now these components are able to be integrated together on a single chip; an example SoC can be seen in Figure 2a.
\nExamples of system-on-a-chip architectures.
(a) Example of a typical system on a chip.
\n(b) An example of a target architecture for early hardware/software codesign implementations.
\nSoC designs for FPGAs have become more popular recently as the increase in resource densities allowed more complex logic to be implemented. The push towards SoCs on FPGAs is driven by the desire for greater autonomy in a variety of systems; the most obvious example is field robotics, but autonomous systems such as ‘smart’ rooms and satellites also have a need for a small form factor and high-performance computing solutions that the FPGA is well placed to deliver.
\nAs VLSI technology matured, designers began to see that the increase in development complexity for hardware or ASIC designs was impacting their ability to bring products to market quickly. The associated increase in the complexity of microprocessors led many designers to realise that these microprocessor units could be included into system designs and some of the functionality shifted to software to reduce their time to market. Microprocessors can be considered a SoC on their own, but they can also be included in much larger SoC designs, and this is where the idea of hardware/software codesign first began; reviews of the field by [2, 3, 4] give a comprehensive history of hardware/software codesign. A basic example of an architecture where hardware/software codesign may be appropriate is shown in Figure 2b.
\nThe extended Kalman filter (EKF) is, and has been, the most widespread method for nonlinear state estimation [5]. It has also become the de facto standard by which other methods are compared when analysing their performance. Various surveys of the field have noted that the EKF is ‘unquestionably dominant’ [6], ‘the workhorse’ of state estimation [7, 8] and the ‘most common’ nonlinear filter [9]. Despite some shortcomings, the relative ease of implementation and still-remarkable accuracy have propelled the EKF’s popularity.
\nHowever, more recently the unscented Kalman filter (UKF) [10] has been shown to perform much better than the EKF when the system models are ‘highly’ nonlinear [6, 7, 8, 9, 11]. While the EKF attempts to deal with non-linearities in the system model by using the Jacobian to linearise the system model, the UKF instead models the current state as a probability distribution with some mean and covariance. Following this, a deterministic sampling technique known as the unscented transform (UT) is applied. A set of points, called ‘sigma’ points, are drawn from the probability distribution, and each of them propagated through the nonlinear system models. The new mean and covariance of the transformed sigma points are then recovered to inform the new state estimate. The crucial aspect of the UT is that the sigma points are drawn deterministically, unlike random sampling methods like Monte Carlo algorithms, drastically reducing the number of points necessary to recover the ‘transformed’ mean and covariance.
\nConsider the general nonlinear system described for discrete time, \n
where \n
The augmented state vector has an associated augmented state covariance, \n
where \n
The choice of \n
Then, the vector sequence is expanded for \n
The actual sigma points are drawn, via a column-wise accumulation, from
where \n
The
The state and covariance are then predicted as
For the
The mean and covariance of the observation-transformed sigma points are calculated:
followed by the cross-covariance
and the Kalman gain
Finally, the current system state is estimated by
where \n
where the expression for the Kalman gain, Eq. (16), is substituted.
\nThe first exercise in the hardware/software codesign is to divide the UKF algorithm into two parts. For maximum performance, it is desirable for as much of the algorithm as possible to be implemented in hardware. However, to maintain portability, any part of the algorithm that is application-specific would be better implemented in software. This is so that the application-specific parts can make use of the faster and simpler development processes that using software entails. Reviewing the UKF algorithm, only the two system models, the
Apart from the two system models, the rest of the UKF can be viewed as, essentially, a series of matrix manipulations. The only changes to the rest of the UKF when either of the system models changes are the size of the vectors and matrices used in the UKF calculations. The sizes of these vectors and matrices are fixed for a particular formulation of the UKF, and so they can be treated as parameters that are set at synthesis. Fixing the parameters at synthesis means that only the bare minimum of hardware resources is needed, but the hardware can still be easily used for different applications with different vector/matrix sizes; rather than needing to redesign any functionality, the hardware can simply be synthesised with different parameters. Thus, the rest of the UKF can be designed and then used as a parameterisable, modular ‘black box’ (IP core), and implementing it for any given application only requires the appropriate selection of parameters.
\nWhen it comes to designing hardware, there are three main considerations: the performance of the hardware (which may include data throughput, maximum clock frequency, etc.), the logic area (on-chip resources) used and the power consumption of the hardware. During development these considerations are usually at odds with each other—specifically performance is usually opposed by logic area and power consumption. In order to increase the performance of the design, additional resources often have to be used which, in turn, may increase the power consumption; these increases in resource/power cost may make the implementation infeasible for a given application. Due to these considerations, it is beneficial to give system designers the ability to scale resource use to the requirements of their particular application.
\nThe actual physical implementation of the hardware/software UKF on an FPGA can be seen in Figure 3. The hardware part is implemented as a stand-alone IP core, and the software part is implemented on a general-purpose microprocessor. The processor acts as the main controller which, in addition to implementing the system model software, controls the hardware IP core. The precise method of controlling the IP core is dependent on the design variation and is elaborated on in the following sections.
\nThe hardware/software partition on the FPGA.
The processor communicates with the IP core over some communication interface. Any intra-chip communication method would be sufficient and would be driven mostly by the requirements of the application; viable interfaces include point-to-point, bus or NoC interfaces. The IP core contains memory buffers at the interface in order to receive data from the processor as well as to temporarily store data that needs to be read by the processor. The communication interface is the same between all three variants, but the specifics of the memory buffers are not.
\nHere, the communication interface between the two parts is an AXI4 bus. All variants are implemented using single-precision arithmetic (IEEE-754); this gives a decent balance of dynamic range and resource usage which should be sufficient for the majority of applications. All hardware in the codesign is developed using the Verilog HDL, and all software in the codesign is developed using C. Although C is used here, in general, any type of software may be used as long as it contains the ability to interact with the communication interface connecting the hardware and software parts.
\nThe codesign utilises the main benefit of hardware implementations: wide parallelism. An increase in performance is gained by encapsulating certain parts of the major datapaths into a sub-module called a processing element (PE) and then using multiple instances of these PEs in parallel, allowing multiple elements of an algorithm to be calculated at once. The increase in resources used is not only for the extra processing elements but also in the additional overhead needed to deal with the parallel memory structure that is also necessary to feed to the parallel processing elements. The number of PEs used in the design is parameterisable, allowing for some trade-offs by the system designer between resources used and performance.
\nThe codesign logically separates the UKF algorithm into three parts, while on the hardware side, the IP core consists of the UKF hardware and a memory buffer which is attached to a communication (AXI4) bus; the top-level block diagram of the codesign can be seen in Figure 4. The memory buffer has a memory map that ensures that data are coherent between the processor and the IP core and also incorporate a control register which allows the IP core to be controlled. The control register allows the processor to reset or enable the IP core as a whole as well as start one of the core’s functional steps via a state machine; the control register also records the current state of the IP core. Data required by the IP core (e.g. transformed sigma points) must be placed in the memory buffer at the appropriate address by the processor before signalling the IP core to begin its calculations. The control register may be polled by the processor to control the IP core; alternatively, the core may also be configured with an optional interrupt line that may be attached to the processor’s interrupt controller or external interrupt lines.
\nTop-level block diagram.
The
Block diagram of the sig_gen step.
The memory prefetch and memory serialiser modules add a small amount of overhead to the
In addition to the matrix ‘square root’, the Cholesky decomposition is also used in the Kalman gain calculation which involves a matrix inversion (see Eq. (16)). Directly computing a matrix inversion is extremely computationally demanding; so rather than directly inverting the matrix, an algorithm called the matrix ‘right divide’ is used here. For positive definite matrices, this algorithm involves using the Cholesky decomposition to decompose the target matrix into a triangular form followed by forward elimination and then back substitution to solve the system; this sequence may be treated as solving a series of triangular linear equations meaning the same hardware can be reused for each operation [14]. The Cholesky decomposition of a target matrix \n
where \n
where \n
The recombination process is necessary because of the subsequent matrix multiply-add between the augmented covariance square root and the sigma weighting coefficient matrix (see Eq. (8)). The element-wise calculation for \n
where \n
Triangular linear equation solver.
The fused multiply-add module and feedback FIFO have been encapsulated to form an elementary block of hardware called a processing element (PE) which can be instantiated multiple times in parallel. The PE output to a demultiplexer, which ensures values, is passed to the subsequent calculations in the correct order. The latter calculations, after the demultiplexer, are not parallelised because these calculations require much fewer operations, and so parallelisation is not necessary.
\nThe matrix multiply-add datapath is a standard ‘naive’ element-wise multiplication and accumulation. However, the hardware to calculate one element is enclosed as one processing element, and additional PEs are added to handle calculations in parallel; the matrix multiply-add datapath can be seen in Figure 7. Each PE is responsible for calculating at least one row of the result matrix. The elements of the matrix to be added can simply be injected into the accumulation directly, instead of performing an additional matrix addition after a matrix multiplication.
\nMatrix multiply-add operation.
The
Block diagram of the predict step.
The processor may initiate a
Calculating the mean and covariance of the transformed sigma points is both very similar, meaning both can be calculated by the same datapath. Consider the calculation for the mean of the
This is a simple column-wise multiply-accumulation. Consider the calculation of the covariance:
The subtraction looks like it will cause inefficiencies in the datapath, similar to the division operation in the original Cholesky decomposition. However, let \n
This ‘sigma point residual’ matrix \n
This expression involves two multiplications followed by an accumulation; if these ‘sigma point residuals’ are calculated first with
Calculate mean/covariance operation. \n\nW\n\n refers the sigma point weights \n\n\nW\n0\n\n,\n\nW\n1\n\n\n.
The input to the datapath is either the transformed sigma points to calculate the mean or the residuals to calculate the covariance. The FIFO is used to skip the first multiplication when calculating the mean; the multiplexer selects which value is calculated.
\nThe
Block diagram of the update step.
As with the
To validate the implementation of the hardware/software UKF and demonstrate its effectiveness, an example application is presented. This demonstration emulates the attitude determination subsystem of a single, uncontrolled nanosatellite. It is envisioned that a system designer looking to use the HW/SW UKF in a new application simply formulates the UKF appropriately for that application, i.e. formulates the system models (1), (2) and sets the algorithm parameters. Then, once the UKF algorithm has been defined, the HW/SW codesign detailed in Section 3 can then be used to actually implement the UKF and accelerate its performance. The example application attempts to employ this process.
\nThe UKF was implemented using a number of methods for validation and comparison purposes. Once formulated, the UKF was first implemented in MATLAB (SW) to validate the design of the UKF algorithm. Next, the UKF was implemented again using the HW/SW codesign on an FPGA development board in order to validate the codesign. Finally, the UKF was implemented a third time in C (SW), but on the same FPGA development board, to provide a performance benchmark the HW/SW codesign could be compared to.
\nThe FPGA development board used was the Zedboard, featuring a Xilinx Zynq-7000 series XC7Z020, seen in Figure 11. The relevant features of the board are:
Dual ARM Cortex-A9 processor system (PS) @ 667 MHz
The equivalent of an Artix-7 device in programmable logic (PL)
AXI4 PS-PL interface
Zedboard development board used for two of the UKF implementations.
The HW/SW codesign was implemented for the 1 PE and 2 PE cases. The hardware part of the codesign, the IP core, was developed in Verilog and synthesised and implemented using Vivado 2014.1; basic arithmetic was implemented using floating point IP cores from Xilinx’s IP catalogue. All designs used a single-precision (IEEE 754–2008) number representation. The target synthesisable frequency for the IP core was 100 MHz, and the 2 PE case instantiated two processing elements for the whole design (i.e. each individual module had two processing elements). The software part of the codesign was implemented in C as bare-metal application on the processor system. The general-purpose AXI4 interface between the PS and the PL was used by the two parts to communicate with each other (@ 100 MHz as well). The C (SW) implementation of the UKF was a bare-metal application that used the GNU Scientific Library (GSL) for its vector and matrix manipulations. All software was compiled using the -O2 optimisation flag.
\nTo test the different UKF implementations, a simulator was constructed in MATLAB to model the nanosatellite’s motion; the details are given in Section 4.5. Simulated sensor measurements were generated from the nanosatellites’ motion and passed to each of the three UKF implementations, which act as the attitude determination subsystem. For the MATLAB implementation, the simulated measurements could be passed directly. For the HW/SW codesign and the C (SW) implementations, the simulated measurements were first exported to a C header which was included during compilation.
\nThe nanosatellite is modelled as a 1 U CubeSat. The attitude of the nanosatellite is represented by the unit quaternion \n
The kinematic equations for the satellite in terms of quaternions are given by
where \n
We consider a basic sensor set common on nanosatellites—a three-axis MEMS IMU including an accelerometer, gyroscope and magnetometer. We use the standard gyroscopic model for the gyroscope:
where \n
where \n
We use a dead-reckoning model and the gyroscopic data to predict the motion of the nanosatellite. However, it is necessary to account for the gyroscopic bias drift, so we estimate the current gyroscopic bias as well. Let the state vector be
The predict model, f, is then
where \n
The accelerometer and magnetometer data are used to correct for the gyroscopic bias, so the observation model, h, is
where \n
Collecting all the relevant terms, the initial augmented state vector is given by
and the initial augmented covariance is a diagonal matrix with diagonal terms:
The state vector length is \n
To generate the sensor measurements, the simulated motions were converted into the body frame via rotation matrix with 1–2-3 referring to roll-pitch-yaw, respectively:
It is assumed that the magnetometer is aligned with the x-axis (\n
The UKF was simulated in MATLAB environment as well as on the Zedboard development board. For the Zedboard implementations, the simulated sensor data set was loaded into the onboard memory (RAM) and the UKF simulated as if it were receiving data from the actual sensors. The data set used in all three implementations was the same. State estimates from the UKF were stored on the Zedboard for the duration of the simulation and then read back into MATLAB afterwards for analysis.
\nAll three implementations produced (within working precision) the simulation results in Figure 12a and b; these figures show the absolute attitude error (i.e. the difference between the UKF estimated attitude and the simulated ‘truth’) of the nanosatellite. In Figure 12a, the top graph shows the first tenth of a second of the simulation, highlighting early convergence of the filter to the truth from an initial noisy estimate. The bottom figure shows the first second of the simulation, highlighting the ability of the filter to maintain its accuracy (\n
Absolute attitude error.
(a) At the very beginning of the simulation.
\n(b) For the full simulation.
\nThese results demonstrate that there are no implementation issues when taking the UKF to a HW/SW codesign; the codesign, and IP core, is able to completely replicate software-based implementations of the UKF. The overall latency of the C (SW) implementation and the HW/SW codesign (serial and parallel) for the single nanosatellite case were measured using the ARMv7 Performance Monitoring Unit (PMU) and can be seen in Table 1. This overall latency is the time taken to complete one full iteration of the UKF (all steps). The 1 PE case offers a modest \n
\n | SW | \n1 PE | \n2 PE | \n
---|---|---|---|
Total | \n660 | \n363 | \n272 | \n
Overall latency for the single nanosatellite. All values in \n
Synthesis and implementation runs were targeted at the Zynq-7000 XC7Z045 at a target frequency of 100 MHz. Though the implementations of the example applications presented in Section 4 was for the Zynq-7000 XC7Z020, the codesign does not fit on this device for larger numbers of processing elements. In order to still compare implementation details, this larger device in the Zynq-7000 family is used instead. All the devices in the Zynq-7000 family feature the same processing system; the only difference for larger devices is the amount of programmable logic available.
\nResource utilisation of the device by the IP core is reported by Vivado post-implementation. The power analysis is done via the Xilinx Power Estimator (XPE) post-implementation; all power estimates exclude the device static power dissipation and the processing system power draw.
\nThe execution time (latency) for the hardware part is measured via behavioural simulation in Vivado Simulator, assuming a clock frequency of 100 MHz; this assumption was validated post-implementation for all designs. Though behavioural simulations are usually used for only functional verification, Vivado Simulator provides cycle-accurate execution times as long as timing assumptions made in the simulation are verified post-implementation. The entire IP core utilises synchronous logic and is on a single clock domain which makes confirming the proper distribution of the assumed clock signals, in this case 100 MHz, relatively straightforward.
\nThe execution time (latency) of the software part is measured via the ARMv7 Performance Monitoring Unit (PMU), which counts processor clock cycles between two epochs; because the number of processor clock cycles to perform a given task can vary, each measurement was conducted at least 10 times, and the average latency measured is reported here.
\nSynthesis results for a selection of different numbers of processing elements can be seen in Table 2. These results do not include the processor but do include the logic necessary for the AXI4 interface ports. The initial numbers of PEs were chosen to be multiples of the number of augmented state variables so that the major datapaths remained data efficient. Recall, for example, the matrix multiply-add datapath (Section 3.2.2); each PE calculates an entire row in the result matrix. If the number of PEs is not a multiple of the size of the matrix, then the last iteration of the calculations will not have enough data to fill all the PEs making the datapath slightly inefficient.
\nResource | \n1 PE | \n2 PE | \n5 PE | \n10 PE | \n
---|---|---|---|---|
FF | \n7668 (2) | \n14,286 (3) | \n27,311 (6) | \n48,714 (11) | \n
LUT | \n5764 (3) | \n15,158 (7) | \n29,500 (13) | \n53,427 (24) | \n
BRAM | \n16.5 (3) | \n36.5 (7) | \n62 (11) | \n109.5 (20) | \n
DSP48 | \n35 (4) | \n62 (7) | \n104 (12) | \n182 (20) | \n
Resource utilisation (% total) on the XC7Z045.
For low numbers of processing elements, the codesign utilises a relatively small percentage of the available resources. The XC7Z045 is a mid-range device in the Zynq-7000 series which means even the 10 PE case still only uses a quarter of the available LUTs. The codesign does not require a proportionally large amount of any one resource; in fact, the design uses a disproportionately smaller amount of FFs than other resources. This will allow easier integration into a full SoC, particularly if partially reconfigurable regions are used. Requiring too much of any one resource type can lead to placement and routing issues since resource on-chip locations are fixed by the manufacturer. This also implies that additional register stages could be added to major datapaths, which would increase the overall latency but could allow an increase in clock frequency as well. If the increase in clock frequency was greater than the increase in latency, the overall performance of the design would benefit.
\nA power consumption breakdown for the hardware IP core (i.e. excluding the processor) can be seen in Table 3. The power consumption for low numbers of PEs is reasonably low, due to the area efficiency design goals and the heavy utilisation of the FPGA clock that enable resources to disable modules that are not currently in use. For reference, the device static power consumption (@ 25°C) is \n
Resource | \n1 PE | \n2 PE | \n5 PE | \n10 PE | \n
---|---|---|---|---|
Clocks | \n38 | \n74 | \n136 | \n234 | \n
Signals | \n24 | \n83 | \n144 | \n261 | \n
Logic | \n23 | \n76 | \n126 | \n219 | \n
BRAM | \n51 | \n82 | \n112 | \n209 | \n
DSP | \n4 | \n6 | \n21 | \n52 | \n
Total | \n140 | \n336 | \n549 | \n975 | \n
Power consumption of the codesign. All values in mW.
A breakdown of the execution time (latency) of different modules can be seen in Table 4. The design spends a large amount of the time propagating the sigma points through the two system models. The majority of the time spent by the design is actually in these system models, making the software part the main bottleneck. Looking at the sigma point propagation process a little closer, however, the latency of reading the sigma points from the memory buffer and of writing the transformed points back to the memory buffer was 116 μs. The actual calculation of the system models took a mere 21 μs. So, the bottleneck is actually the speed of the AXI4 port in transferring data between the processor and the memory buffer. Using a higher-performance communication, bus or other techniques such as direct memory access (DMA) ports may alleviate this issue, but intra-chip communication methods are beyond the scope of this chapter.
\n\n | SW | \n1 PE | \n2 PE | \n5 PE | \n10 PE | \n
---|---|---|---|---|---|
Sig. gen. | \n— | \n— | \n92 | \n61 | \n51 | \n
System model | \n52 | \n137 | \n137 | \n137 | \n137 | \n
Predict | \n522 | \n170 | \n13 | \n8.5 | \n6.5 | \n
Update | \n87 | \n56 | \n30 | \n21 | \n17 | \n
Total | \n660 | \n363 | \n272 | \n228 | \n212 | \n
Latency of each stage for the codesign. System models encompass propagation through both the
For the hardware part, the majority of time is spent in the
In this chapter, a scalable FPGA-based implementation of the unscented Kalman filter was presented. The proposed design balances development effort/complexity with performance, combining the advantages of both the traditional software approach and hardware approaches to create a design that system designers can easily use in a potentially wide variety of applications. Simulation and physical implementation results of the codesign were presented. The demonstration application simulated the attitude determination system of an uncontrolled nanosatellite, and the physical implementation was performed on the Xilinx XC7Z045.
\nWouldn’t the world be a better place if there were no limits to sacrifice? Most people will answer yes to this question. When it comes to organ transplantation, can this fact occasionally contradict primum non nocere, “first, do no harm”, which is the basic doctrine of medicine. Although selfishness is rarely accepted as a strategy for the benefit of the group, in evolutionary formulation, altruism benefits the group and selfishness interferes with altruism. While the living donor benefits the person who needs organ transplantation, they assume a group of life risks in advance. In this case, assessments will be multi-layered. Can the recipient’s physician take a paternalistic approach to the benefit of their patient? How much risk can the donor take with the thought of benefiting another person? How should the decision of the potential donor to donate organs be handled? How should the organ donation decision based on their altruistic approach be evaluated within the scope of autonomy? Do the risks undertaken by the donor mean that they will be harmed? It is of course possible to augment the number of questions, but the need for organ transplantation is increasing every other day. The number of donors does not match the needs, and this increases the need for organs every other day and causes the waiting lists for organs to get longer. Due to the scarcity of cadaver donations especially in some countries, organ transplantation, including kidney transplantation, is performed mainly from living donors.
With the increasing need for organs, organ transplantation from living donors, who are relatives of the recipient or not, is becoming more common, and even scientific studies on organ and tissue transplantation present living organ donors as an alternative to long-term dialysis treatment [1].
In justification of transplantation procedures with organs obtained from living donors, one has to be genuinely volunteer and to give informed consent under free will. Saving an individual’s life and donating living organs can be a commendable option. However, to make sure the utility reaches its aim, a balance must be maintained between the utility provided to the sick person and the cost that the person taking an altruistic approach will pay. It should be essential to minimize the damage and maximize the possible utility in organ transplantation practice.
Various ethical statements suggest that the individual should voluntarily donate organs of their free will by giving informed consent, the donation should be exempt from exploitation and pressure, the donor should have the freedom to withdraw from the donation process at any time, and that the transplant team should make sure that the donor’s decision to donate is voluntary and not manipulated. The correct definition of volunteering is an issue of practical importance. The answer to the question of how donors’ volunteering should be properly assessed is far from a resolution today. Although standards about informing donors and how to control the information they understand have been developed (for example, the US Medicare Program), an empirical assessment standard of whether the decision to donate is voluntary is not developed enough to meet the relevant ethical norms [2]. One of the most important studies on the topic is the one carried out by Al-Khader. This study aimed to develop a scoring and rating system for assessing the volunteering of potential living donors [3]. In light of, a scoring and grading model was proposed in our country too, to determine the volunteering of living donors in kidney transplantation [1].
The assessment of potential donors’ willingness to volunteer for organ donation, which is basically a difficult process, handles issues, such as motivation to donate, social status and family ties, economic status, relationship with the recipient, evidence of volunteering, and proof of a financial reward. Various ethical guidelines on organ transplantation from living donors have been developed around the world. One of the first ethical guidelines suggested is “Consensus Statement on the Live Organ Donor” [4]. In the light of this guideline, other ethical guidelines for the assessment of living donors have been developed [5].
When living donors want to donate organs, it is important to determine whether they are really volunteers or whether they are subject to a relationship of interest or control over their volunteering. It is an ethical and legal requirement for the donor to donate of their free will and by fully volunteering. The creation of a measurement tool on organ transplant volunteering is considered to be important in terms of the value and non-instrumentalization of human beings.
Contrary to the expectations of transplant surgeons, the use of living donors in countries, such as Turkey, Saudi Arabia, or South Korea is increasing every other day, resulting in more transplants from living donors than cadavers [6].
Nowadays, with the acceptance of cross organ transplants and living organ donations from non-relatives, the issue of volunteering and altruism of volunteers has become much more important. Lack of a standard approach to these issues is one of the biggest problem areas.
Utility of organ transplantation is available to the recipient under all circumstances. Health business is a utilitarian business. For this reason, utility fits the basic philosophy of healthcare very well. However, no matter how the individual’s actions are conditioned to positive and beneficial results, negative and undesirable consequences may accompany these beneficial results as well. In the context of doing no harm, one of the main topics that need to be addressed is who or what is responsible for the damage, if any, and the other is assessment of the damage. Undoubtedly, balancing the benefit and harm is of particular importance for high-risk healthcare providers.
Morality requires that we do not only avoid harming people and regard them as autonomous but also contribute to the well-being of other people. This is expressed under the title of “utility”. Apart from avoiding harming others, people should take positive steps to help other people. The utility can be examined under the “positive utility” heading, which refers to the action of the subject to provide some benefits to others, and utility, which requires the subject to establish a balance between benefits, risks, and costs to achieve the best overall results [7]. Regarding our subject, it is necessary to talk about the utility and saving duty for the specific (i.e. for certain people) rather than the general benefit.
General utility targets all persons regardless of special relationships. The utility specific to persons emerging as a result of moral relationships, contracts, and special ties usually applies to certain persons, such as our children, friends, parties to the contract, or patients. Although the idea that we have an obligation to all people is controversial, almost everyone agrees with the idea that we have an obligation to act for the benefit of the people with whom we have special relationships [7].
Beauchamp and Childress argues that the “duty to save” requires an obligation to provide a prima facie utility if all of the following conditions are met, even if close moral relationships based on specific agreements or family and friendship ties are excluded.
Person Y is at risk of serious loss or damage to his life, health, or other fundamental interests.
The action of person X (alone or in the relevant chain of actions) is necessary to prevent this loss or damage.
The action of person X (alone or in combination with other actions) will most likely prevent this loss or damage.
Person X will not put himself/herself at any critical risk, cost, or burden by performing this action.
The expected benefits for person Y outweigh the damage, cost, or burden that person X may face [7].
In the light of these evaluations of Beauchamp and Childress, the 4th condition constitutes the debate on whether living donors who have a special contract for organ transplantation or have family and friendship ties have an obligatory saving mission. If we do not consider a person’s donation of a kidney as “a critical risk, cost, or burden”, then we put potential living donors under obligatory duty to save. Putting the living donor, who will only have moral gains, under the direct obligation of compulsory saving would be a point in contradiction with the concept of volunteering. Also, another issue to discuss is which of the individuals who meet these conditions and have a family, friend, or special contractual relationships with the recipient will fulfill this obligation first.
It should be noted that the obligation to save is at the core of why living organ donors mostly donate organs to their relatives (family, friends, relatives, etc.). Even if the conditions stated by Beauchamp & Childress are met, it is a matter of debate whether we have an obligation to save people we do not know, especially in terms of organ transplantation. The fact that people hesitate to donate living organs to patients they do not know can be shown as evidence of this matter. Expecting such a sacrifice from the whole society will not go beyond pursuing a high ideal.
Balancing the duties of providing utility and doing no harm with the principles of respect for autonomy and justice is accepted as essential [8]. This balance requires the determination of the capacity and autonomy of living organ donors and the careful examination of the stages that require their voluntary consent.
In this context, the volunteering of living donors who want to give a “new life” to their family, friend, or someone they do not know as a living organ donor should be determined well, and the special utility action of the person should be ethically assessed within the concept of obligation to save.
The majority of scientists studying living organ donation ethics have reached a consensus on the issue that giving a certain level of harm to competent volunteers to save another person’s life requires that a valid consent for the donation is available, living organ donation provides a general positive balance of harm and benefit that cannot be achieved in a way that is less damaging to donors and recipients, and that the donation does not lead to significant and long-term morbidity or mortality of the donor.
Altruism, which is also a piece of modesty, is the ability of a person to prefer someone else’s purposes and desires over their own purposes and desires. Altruism, which is the most important factor underlying the expression of volunteering, is one of the basic principles of organ transplantation.
Although there are partial similarities in the assessment of potential organ donors, there are regional differences in how assessments are carried out. The criteria explaining who is allowed to donate and who will be disqualified as a donor also differ.
Family members who make an organ donation will benefit from a successful organ transplant operation to their loved ones, which can be effective in the risk and benefit discussion during the approval process. It may be necessary to limit the sacrifice allowed. For example, while we do not accept a living heart donor for obvious reasons, we know that most donors can live with a single kidney.
It is difficult to predict whether a particular organ donation is an altruistic act because while most recipients benefit from the transplant, the recipient may be in a worse condition if an organ is rejected or the operation fails. As an altruistic action/practice is judged by the outcome, it is difficult to pre-operationally determine whether any special donation proposal is acceptable. Altruism is one of the basic principles of organ transplantation. In organ transplantation;
altruistic action must be an action that leads to an outcome,
the action should be directly linked to the aim,
the action should aim at enhancing another person’s well-being or quality of life,
if the person wants to take action for another person, the result of the action, whether it is bad or it generates negative consequences in the long run, will not decrease the altruistic nature of that action [9].
Merriam-Webster dictionary defines altruism as unselfish respect and commitment to the well-being of others [10]. The Contemporary Turkish Dictionary of the Turkish Language Association defines the concept of altruism as “the state of being altruistic, selflessness”. The synonyms of altruist and altruism are given as selfless and selflessness. According to the same dictionary, an altruist is a person who tries to be useful to someone else without pursuing any personal benefits [11].
The word altruism is derived from the word alter, which comes from Latin meaning “other”. In the 1830s, Auguste Comte used this word as a general term to mean “care for others”. While altruism often points out to sparing thought for another, people can self-sacrifice due to environmental pressure while taking an altruistic approach. While volunteering and personal preference come to the fore in altruism, it may be possible for the person to act as a donor even if they are not willing. If a person acts with completely altruistic motives, that is, if the self-seeking motives are completely absent, we can define this action as a “pure” state of altruism. We must be careful to distinguish purely altruistic behavior from self-sacrificing behavior: the former does not pursue personal gains, while the latter involves some loss. Altruism is the opposite of egoism. However, the person who transcends egoism can be altruistic. A person, not who takes action in a situation where their interests are not harmed at all, but who does what is necessary in a situation that touches their own interests or who can do what should be done and act fairly will be altruistic.
Sacrifice can be seen as a manifestation of individual autonomy. In this case, it is necessary to accept a certain risk in advance. It is unavoidable that the operation to be performed to remove the transplantable graft is risky even if the donor’s health is excellent. The short-term mortality risk for living kidney donors is roughly the same as the risk taken by any patient under general anesthesia. People take risks in their daily lives, which are far greater than the risks often imposed by donor surgery, with little or no direct benefit to their health. The risk of damage from kidney donation is much less compared to the many risks we all face in daily life. Therefore, if both the donor and the recipient are informed about the risks of the surgery, the long-term outcomes of the donation, and the forecast of factors that may affect the success of the transplant, the living organ donation will not push the limits of an acceptable sacrifice.
Schopenhauer mentions denial of the will, silencing the ego, and transcending egoism, which are essential for the existence of freedom, justice, and love in the world and says that this can occur in two ways: by gaining knowledge of the suffering of others or by the person’s own great suffering. Schopenhauer says that the vast majority of those who deny the will achieve it in the latter way; not only by the acquisition of knowledge but also by the experience of pain. According to Kant I, the fact that action or the will at the basis of the action is determined by the self-love of maxims makes that action unethical. Therefore, it would not be wrong to say that morality and freedom can only be achieved when the person who determines the actions does not have desires and tendencies [8].
If a social behavior decreases the appropriateness of the organism performing the behavior but increases the suitability of others, it is considered an altruistic behavior. Although the concept of altruism was first introduced within the discipline of sociology, today it is frequently used in fields, such as sociology, psychology, theology, and education. Definitions of altruism handled in different perspectives and different disciplines naturally vary, too. In almost all disciplines, altruism is not understood as showing helping behavior without an expectation of personal reward or benefit. Should altruism be understood as the individual’s consideration of well-being of others as much as his/her own or as seeing the well-being of others above his/her own? If a person sees others’ well-being over/before his/her own, he/she will be seen to be sacrificing for others without expecting a response. When altruistic behavior is shown with the expectation of gaining benefit from the person sacrificing, this situation may sometimes appear in the form of cooperation or showing off.
Since the altruism in question here is realized with the expectation of self-interest, this situation is based on mutual altruism, and it can be said that altruism is a kind of strategy that aims to gain respect in society. Gaining public reputation and the desire to benefit from the new opportunities that society offers to them can also support this type of behavior. The person who acts altruistically in the latter form of altruistic behavior, which is based on volunteering without any expectation of benefit, and where the motivation to live for others is dominant, does not seek reward, and deterrent effects do not influence him/her in any way. It should not be forgotten that in the domain between these two views regarding altruism, a spiritual gain to be obtained from the person who has sacrificed will be dominant. It is in this domain that one’s moral gains in return for altruistic behavior are called theological and moral altruism [12].
The most important factor that distinguishes altruism from other purposive behaviors such as “helping” and “obeying social rules” is that the altruist sacrifices something from themselves and takes on a burden depending on their behaviors. This burden distinguishes altruistic behavior from individual behavior, such as “benevolent” or “kind, manners”. The behavior of the altruist, which emerges in social life and is “for the benefit of someone else but brings harm to themselves”, varies by the conditions, the cause that leads to the behavior, and the behavior process. For this reason, the concept of altruism also swings between Kropotkin’s understanding of absolute altruism [13] and mutual altruism approaches based on expectations.
Pro-social behaviors include behaviors that may be for the benefit of another person or a group, which are shown without being under pressure and voluntarily. Bierhoff [14] distinguishes helping behavior, pro-social behavior, and altruistic behavior as follows. Helping is a broad term covering all types of interpersonal support. Pro-social behavior is a rather narrower concept than helping because the action is intended to improve the status of the recipient, and the recipient is not an institution but a person. Altruism, on the other hand, is pro-social behavior, which means that with an additional restriction, the motivation of the person who helps is determined by perspective acquisition and empathy.
The proportion of healthy adults who are potentially able to donate kidneys is greater than the number of deaths under conditions that comply with a donation. The number of people willing to donate instead is limited. It is not surprising that a healthy person may be reluctant to undergo surgery without clinical benefit, and some donors in most countries donate to family or close friends. Some factors affecting this situation, such as the number of people waiting for transplantation and the benefits of organ donation, can be presented through various channels, and this can highlight the person in terms of donation. Some organ donation campaigns have featured individual ‘case studies’, which are sometimes called ‘stories of hope’ that tell the story of people awaiting a transplant and describing their situation and highlight the benefits a transplant can provide. The use of case studies aims to motivate and address people to take action to help others and create empathy by making the human impact of organ deficiency clearer.
The empathic-altruism hypothesis, widely described and proven in the psychological literature, suggests that empathic anxiety for another can lead to altruistic motivation to improve the well-being of the other [15].
Traditionally, altruism refers to a situation where one takes action for the benefit of another even when self-sacrifice is required. Therefore, altruism shows up with actions since goodwill and good thoughts are alone not enough. One goal of this action should include helping another person. If the well-being of the other person is an unintentional or secondary result of an action that one takes to improve one’s own well-being, this action is not altruistic. Altruism does not change according to circumstances. Considering these characteristics, altruistic people are those who have a feeling of caring/considering other people.
There is no widely accepted classification of the types of altruism; however, two types of altruism, normative and hedonistic, are mentioned in some studies. While normative altruism can emerge through moral intuition, non-moral social rules, or logic, hedonistic altruism emphasizes that the individual finds a value in their perception of the situation where other individuals’ distress decreases, they are better off, or they are happier [16].
Ethical altruism is based on the principle that altruism is a virtue, even an obligation. Some might argue that people are always generous and altruistic. This view may apply to a sole advocate of ethical altruism. At this point, the person expressing opinion actually advocates psychological altruism. It is worth noting the consequences of pure altruism-related behaviors based on the fact that everyone accepts the assumption of desiring very little for themselves and very much for others by one’s voluntary sacrifice of their own pleasure to give pleasure to others. All those who behave in this way should not have thoughts for themselves as the giver, nor for others as the recipient, when considered not only as the waiver but as the acceptor of what has been renounced. A sense of compassion that is worrisome for others, willingly self-victimizing to benefit others, cannot be achieved without thinking that those who victimize themselves by giving something to others expect a benefit from it [17].
Moral altruism is based on rewarding the altruistic and punishing those who are not altruistic [18].
Kin altruism is defined as the situation where an individual jeopardizes their own safety to increase the survival chance of other people with genetic or blood ties in the same family [19].
Generally, the living donor is an adult family member whose first-degree relative has terminal stage renal disease. Their experience provides them with insight into the challenges of kidney disease and transplantation. Individuals, motivated by altruism when they choose to donate kidneys after thinking for a long time about risks and benefits, can be emotionally unsettled, and even if they believe they are acting with a desire to help, their ability to act autonomously and without coercion may be endangered.
When the priority of the family concerning organ donation is considered in the blood tie theory, the emergence of altruistic behavior is explained by kin relationships. The individual behaves more altruistically towards their close relatives who carry the same genes, such as mother vs. child, and siblings vs. siblings, compared to other individuals. As the blood ties decrease, the desire to tolerate harm for altruistic behavior or the likelihood of the emergence of altruistic behavior decreases. The reason for this is that human beings have gone through a psychological evolution process in a way that motivates them to spare even their lives in order for their own genes to be permanent. Thus, a person who has close relations to an altruistic individual can survive through the behavior of this altruistic relative.
Partial altruism, which means the individual shares their assets with others, also constitutes an example of altruism approaches, especially in organ transplantation. While doing a favor to others, the person may have sometimes thought of obtaining financial gains from this behavior.
Living donors without a genetic link are increasingly used worldwide, and various approaches support the application. Donors who are not genetically linked to the recipient and who are emotionally connected to the patient and motivated by a desire to help, without an expectation of any material gains can be examples of partial altruism. Many psychological studies show people behave more altruistically towards their friends who have strong emotional bonds with compared to others even though they have no kin relationship. In a meta-analysis investigating factors related to organ donation [20], it was found that education, religion, knowledge, attitude, social influence, altruism, and family positively affected organ donation and that fear of death and the fear of organ donation negatively impacted it.
Pro-social behavior has been suggested by some social scientists as the opposite of anti-social behavior and has been defined as a behavior done with autonomous and free will that benefits others. According to Batson, there are two types of pro-social behavior: egocentric and other-centered. In egocentric pro-social behavior, the person expects to be rewarded or escape from any negativity for the positive behavior to another, while in other-centered pro-social behavior, the only goal of the person is to be helpful to the person to whom the positive behavior is directed, and there is no personal expectation in return for this behavior [21]. While this type of behavior is specified as altruistic behavior, one of the best examples of this is organ donation after death. A person cannot benefit from donating their organs after death.
In a study on the phenomenon of altruistic behavior, titled “An investigation on epistemological problems”, Yeşilkaya approaches the subject with a three-color classification. The view claiming that altruism is based on the expectation of gaining a benefit from the person or the community that receives the sacrifice is characterized by the “black” metaphor, and the view claiming that this kind of sacrifice is made without expecting any return from any source is characterized by the “white” metaphor. However, when the research on this subject is examined, a third, “gray”, understanding, which makes the epistemological blurriness that already exists more thought-provoking, stands out. The study points out that this hybrid approach, which makes the subject relatively more complicated, differs completely from the “black” view in terms of from whom or where to expect the return of altruistic behavior, but reveals clearer boundaries than the “white” view. As a matter of fact, although this understanding accepts that altruistic behavior is realized with an expectation, it is seen that the addressee of this expectation is based on the understanding that it is not the person or the community that receives the sacrifice but a completely different motivator and a different source of power. In other words, according to the “gray” view, it is accepted that there is an expectation that motivates the individual to act altruistically as in the “black” view, and it is essential not to expect a return from the person who is the subject of the sacrifice as emphasized by the “white” view. That is, the person acts voluntarily [22].
Some critical points can be mentioned when talking about altruism. Some studies have shown that personality is not effective in attitudes towards organ donation, but altruistic nature affects attitudes towards it [23].
People who volunteer to be a living donor with a completely altruistic attitude, without expecting anything in return, make a great sacrifice. Whether the approach of donors is really altruistic in organ transplantation requires a good ethical evaluation.
Cognitive framework and processing, religious beliefs and expectations, worldview, empathy, and self-perception determine the altruistic approach. The meaning conveyed by a statement can be defined as the cognitive meaning as the type of meaning that stands directly opposite to the emotional meaning that reveals people’s feelings and emotional responses. In the cognitive framework and processing, the process involving the knowing activity with intellectual knowledge refers to activities, such as thinking, grasping, and reasoning and mental behaviors, such as symbolization, belief, and problem-solving [24].
Religious assessment is an assessment of depth, sophistication, and holiness. Religion is a matter of hearing certain things, believing in them, and engaging in certain voluntary activities according to them.
When studies conducted with living donors are examined, it is stated that religious beliefs cause a strong motivation in the donation of kidneys in relatives and non-relative donors. The donation decision of the donor must be examined in detail. Minimal risk to the donor and maximal benefit to the recipient should be the primary objective. The weight of religious elements in the altruistic approach should also be determined.
World view: It is the body of beliefs, thoughts, and attitudes of an individual or a group of people about humanity, future, or similar matters. The most powerful element for donors has been identified as “helping others”. Whether the recipient is a relative or not, the donor believes that there will be an increase in self-respect by donating organs.
However, those who accept the help, that is, organ recipients, may feel guilty and indebted. They do not want their donors to be harmed. Feeling guilty about what we do or do not do, say or do not say is another way of wasting time unnecessarily [1].
Patients in need of kidney transplantation experience a long and troublesome process. It seems that most of the donors have witnessed this process. For most donors, not being a donor in this shared life would be ‘heartbreaking’ for the recipient.
Besides, the fact that the dialysis process reaches an intolerable position and the reflection of this in words motivates the donor to apply to a transplant center as quickly as possible.
Taking the altruistic approach as a basis in organ donation; for example, the kidney may have been reserved for
a loved one or a relative within the scope of direct donation,
anyone on the general waiting list, or
a recipient that has already been qualified.
The donors’ actions can be based on individual autonomy and an altruistic approach. Undoubtedly, regarding the decision expressed, in addition to the freedom and decision-making competence expressed by Beauchamp and Childress, the interviews about the choice in terms of the donor, as emphasized by Appelbaum and Grisso, the information provided, awareness of the current situation, and the information given should be reviewed and the deficiencies - if any - must be completed [1].
The word ‘voluntary’ comes from the Old French word ‘voluntaire’, which was derived from ‘voluntarius’, whose Latin root is ‘voluntas’. The root of the word ‘voluntary’ is ‘voluntas’, meaning ‘will’ in Latin, which means that the individual undertakes a task with their own will and wish. On the other hand, as the Oxford English Dictionary states, what is ‘voluntary’ is a phenomenon that is ‘not restricted or reminded or suggested by someone else’s assistance’. ‘Volunteer’ is also used for ‘deliberate action’ and when it is used for gifts, it means giving freely or spontaneously to another person [25].
Volunteer in the current Turkish Dictionary of the Turkish Language Association is defined as “a person who willingly undertakes to do a job without any obligation”. In the context of consent, “volunteering” refers to the right of a person to make personal decisions independent of the influence of any internal and external factors. In the Dictionary of Bioethics Terms, volunteering is defined as the situation of a person who decides to do a job with their free will and does it without waiting for anything in return. In volunteering, there should not be any force, obligation, or pressure that drives a person. Respect for individual autonomy is the basis of volunteering. Volunteering is considered an ethical basis in medicine, especially in organ transplantation [8]. Ethically, volunteering is one of the basic elements of informed consent. The “volunteer person” must have the characteristics of the person authorized to give informed consent (sound mind) defined by law. Volunteering should be analyzed in the presence of appropriate and adequate information and the absence of psychological coercion and external pressure. From this point of view, we see that the conditions related to volunteering are in parallel with the conditions required for autonomous action [1]. Not only do medical or psychosocial factors play a role in the selection process by living donors, but every medical professional, lawyer or ethicist agrees that the decision to donate must be voluntary and informed. However, proving the determination of volunteering is not always easy; it requires intense effort. For the consent to be meaningful, the process must also be carried out in a meaningful way. In other words, consent must be voluntary. This is not a surprising statement and everyone agrees that volunteering is important. However, it should not be forgotten that volunteering is a concept that can be quickly overlooked and create a dangerous situation in the daily practice of medicine.
Although organ donations from living donors are commendable, it should not be forgotten that they are considered voluntary. For living donors to make sure they do not make inappropriate decisions within their own values and views on self-sacrifice, risk, or similar topics, transplant teams need to present the criteria they use to select living donors to the community. For policies and practices supporting living donations to be morally acceptable, they should not turn into a means of influence or pressure [7]. In this sense, the concept of volunteering or the opposite, reluctance, is important.
In the evaluation of whether a person is a volunteer for organ donation, there are signs that appear not only in words but also in behaviors and give us clues in determining volunteering; for example, the donor comes for the tests alone, tries to learn the results, does not lean his head forward when the organ donation decision is made, or insists on being a donor, etc. [26]. But what exactly is volunteering?
Stating that the action of a voluntary person is the product of the will of the person acting in the light of the concepts of knowledge, freedom, and volunteering, Babor divides volunteering into thirteen types or degrees. In terms of organ transplantation, it is necessary to examine perfect/imperfect, direct/indirect, and positive/negative volunteering concepts. Perfect volunteering is defined as an action taken with full knowledge and consent. Imperfect volunteering is the opposite of this concept, and there are flaws in both knowledge and consent. Direct volunteering expresses a voluntary action that is desired as an end in itself. In indirect volunteering, on the other hand, the action is not an end in itself but is desired as an anticipated result or sequence of action. Positive volunteering mentions the volunteering present in performing an action, while in negative volunteering, the person avoids the action [27]. For the person’s action to be considered voluntary in organ donation, it should be an action that includes all characteristics of perfect, direct, and positive volunteering.
In an ethical guide prepared for the assessment of living organ donors, the evaluation of whether the person is a volunteer or not is checked from 10 different angles. The guide addresses issues, such as potential donor’s psycho-social status, financial status, relationship with the transplant candidate, the reason for donation, the conditions under which the decision has been made and by whom the potential donor is asked to donate, the convenience of the potential donor to refuse the donation request, the comfort of the potential donor near other family members, proof of material reward for the donation, willingness and motivation of the potential donor, and the imbalance of power between the potential living donor and the recipient [28].
The concept of volunteering may be affected by some positive and negative factors. In this sense, it is useful to look at these factors.
The “gift” that the recipient receives from the donor free of charge, which has no physical or symbolic equivalent by nature, is so extraordinary that as a result, the donor, recipient, and their families may find themselves in a mutual creditor-debtor spiral. Such a situation also describes the importance of volunteering in organ donation. It is essential for the organ donor to donate in full volunteering and to be completely free from negative factors. Also, informed consent for organ transplantation requires sufficient information sharing for both the patient and the organ and tissue donor and communication that is free from coercion and threat, does not involve persuasion, and does not aim to manipulate the decision.
It is clear that there is a non-altruistic motivation if the person requests a reward for a donation. However, the fact that such a demand has accompanying elements does not mean that the donation is motivated by altruism and that it involves an altruistic approach. One of the three pillars of autonomy is that the individual is far from influences that control them. In other words, for the action to be autonomous, the person should not be in a situation that prevents their self-management either by internal or external forces. However, not all effects on the person by others are controlling. In this section, controlling concepts will be discussed.
Evaluating the determinants of attitudes towards organ removal from the dead, willingness to donate, and donor behavior in a systematic review of 33 published studies, Wakefield et al. emphasizes that individuals’ attitudes towards donation are complex due to differences in social norms, existing laws, and interactions between beliefs and individual factors in each country [29].
However, apart from these regional and personal differences, there are factors that affect donation positively and negatively. A study shows that the team, which will talk to the family of the deceased during the donation process, should reassure the family with their linguistic and cognitive abilities and show their emotions, which has a significant effect on whether the family is a donor [30].
Although organ donation is apparently supported by society, the level of organ donation is very low. Psychological factors that affect the person’s decisions to become a donor also play a role in this complexity. They have also led to the need to understand how people predict or inhibit the desire to become organ donors. In a study conducted by Morgan et al., it has been shown that the perceived benefits of organ donation play an effective role in the decision-making process [31]. The volunteer choices of potential donors (e.g., women in strong patriarchal cultures) who do not understand that they are an autonomous moral person, act as expected, and never dare to reject are undermined by persuasion, encouragement, and pressure.
In determining whether an action is autonomous, the two most important conditions require that the person fully understands the issue and is not under control. There is a gradual transition from total freedom to total control for the status of both understanding and being free of controlling influences. This transition involves the scales that reveal the “autonomous actions” and “non-autonomous actions” domains. By considering these domains and thresholds for specific purposes, the boundary between “autonomous enough” and “not autonomous enough” can be carefully determined [7]. There are some factors, such as requests, family, or legal obligations, in making personal decisions. But there are also some factors other than these factors that will directly affect the person’s ability to act autonomously. All of these factors are detrimental to the autonomy of the person and aim at taking the person under control.
Informed consent is the most important issue in ensuring the autonomy of the person. Instead of reading standard forms, each individual’s unique needs for information should be taken into account with a “customized” approach. It would not be wrong to state that the dignity and value of the human being, the principle of autonomy, and legal aspects of organ transplantation should be addressed for each person in the informed consent form [32].
Concepts such as sacrifice, compassion, interest, renunciation, loyalty, reliability, concern, respect and justice, empathy, and emotional ties are among the positive factors that affect volunteering. Besides, the altruistic nature of the person is an important issue that requires research on its own among positive factors.
Volunteering is essential for autonomous action. External control over an individual’s actions weakens the voluntary nature of the actions. Such effects can be grouped under three main categories, namely, persuasion, coercion, and manipulation. If we detail these concepts, we can better evaluate the negative factors affecting volunteering.
Persuasion is the effort or process of encouraging people to change their current beliefs, values, or attitudes, or to gain new ones. This extremely complex process may be based on rational discussions or messages or it may include a method that addresses irrational desires or needs [33]. The process of persuasion is typically analyzed in terms of who said what, how, and with what effect, and expresses whether any attitude changes have occurred [34]. Valapour explains persuasion as influencing by using reasoning and states that when the person is persuaded, they freely accept the effect; therefore, they think it is an ethically acceptable action and that it does not undermine the voluntary nature of the person and they regard it as compatible with autonomous actions [35]. Hançerlioğlu handles the concept of persuasion under the heading of “deceiving” and defines it as “making something accepted with mental evidence or making someone believe” [36]. However, it is seen that the meaning of the concept of “volunteering” has not been fully understood. There are also studies showing that people’s attitudes towards organ donation can be changed with persuasion and manipulation techniques [37].
Persuasion arises as a result of the reasoning offered to a person to believe something is worth believing. Inviting people to be reasonable and addressing people’s feelings are different situations [7]. In summary, persuasion is the process of making a person believe something that they did not believe at the outset.
Hançerlioğlu states that pressure leads to a situation that prevents free development naturally and socially and that it prevents free behavior [36]. Budak defines pressure as forcing the person to act one way or another and as excessive or stress-causing expectations from the person and states that what is felt as pressure changes depending on the person or education level [33].
Coercion exists when a person poses a credible and serious threat of harm or coercion in an attempt to control another person. Whether the pressure will occur or not depends on how the target person will receive this threat, and this response varies from person to person. Coercion occurs when the perpetrator behind a person’s actions is not their own free will and their conscious behavior about areas in which they are knowledgeable ceases to be autonomous when they receive a credible threat [7]. It is the pressure that causes a person to act contrary to their will under a threat of harm. The threat of harm is an essential component of the concept of coercion, and a forced action reflects someone else’s choices, not one’s own choices, as it is based on a credible threat. Therefore, decisions made under coercion and actions carried out are not autonomous.
Following the coercion, the person makes their own decision. Therefore, although it is said that this, in a sense, is an autonomous choice and should be stated as a voluntary act, this kind of volunteering is volunteering that is not perfect, indirect, and negative. Therefore, as mentioned at the beginning, it is not a desired situation for organ donation. In terms of organ donation, the decision to be made after coercion, pressure or threat is not an autonomous and consensual choice.
Coercion entails a real, convincing, and intended threat that pushes a person into unwanted action and pushes his autonomy out of self-control. In this sense, threat involves applying force to a person to do something or to restrict their freedom. In principle, threat requires a genuine, reliable, intended, and willing orientation [26]. In these concepts, which we generally express, there is a use of physical or psychological force against the autonomy of the person. The plan of bringing the person to the level to do the desired thing lies at the heart of applying pressure, threat, force, and coercion.
Studies on the psychosocial effect of living kidney donation indicate that many living donors believe that the decision to donate is not a real choice and that they feel compelled to donate [38, 39]. In a similar study conducted in the USA, 40% of the donors who donated living organs between 2002 and 2005 reported that they felt some pressure to donate [40]. Understanding volunteer donation only as the absence of coercion will indicate a narrow meaning as it does not cover more sophisticated interventions such as persuasion and manipulation. In this sense, it is necessary to examine the concept of manipulation among the negative factors that affect volunteering.
The concept of manipulation increasingly plays a central role in debates about free will and moral responsibility. Manipulation is essentially the orientation of the person to do what the manipulator wants by means other than persuasion or coercion. In this sense, manipulation encompasses some forms of influence that are neither persuasion nor coercion/threat/force. The most likely type of manipulation in healthcare is informational. It is the presentation of information in such a way that the person is directed to do what the manipulator wants by understanding the situation differently. In this sense, informational manipulation is also against autonomy. Hiding certain information, telling lies, or exaggerating the meaning or importance of certain information to make people believe in unfounded things are the kinds of actions that can harm autonomous choices.
Manipulation is the deliberate and successful influence on the available choices one can make, either by non-coercively altering or by changing one’s perception of those choices. “Being manipulated” is subjective in nature and depends on the person’s reaction [35]. If the living donor accepts surgical intervention because of its benefits, they must also accept the possible risks. This is not a manipulative situation [26].
It is a fact that some living organ donors are also manipulated with financial support. Besides, due to the paternalistic approach of the physician to their recipient patient, they may attempt to manipulate the living donor candidate to affect their willingness. The assessment of the living donor candidate by a different transplant team is necessary so that the manipulation that may occur can be evaluated.
Organ transplantation is not an issue limited to health. It is also a field of both law and ethics as a medical practice surrounded by social, cultural and value problems which have challenging solution. The applicability of every medical practice in the clinic is within the limits determined by the law, and there are laws that vary by countries regarding organ transplantation. The fact that concepts such as human rights, right to health, human value, bodily integrity, and quality of life are predominantly handled within philosophy is also a guide in the preparation of existing legal texts. One of the main points that everyone agrees on is the value of life and that it is an inalienable personality right. The right to life is defined as the existence of a healthy and complete body and the ability to continue lives by protecting them against potential threats and dangers. The right to life is also directly linked to human dignity. While the material aspect of the right to life is expressed with the content of protecting the bodily integrity of the person and not being exposed to bad behavior, living under humane living conditions also emphasizes the spiritual aspect of the right in question. Debates about organ transplantation arise between the right to life and the right to determine one’s own future. For example, obtaining a kidney from a potential donor is very important in saving the life of the terminal kidney patient who will die. Without harming the bodily functions, the living donor will use their ethical right to give up their organ that is valuable for them but can also be lived without. In this context, medical evaluations of the donor and the recipient alone will not be enough. It is also necessary to examine how altruistic behavior leads to volunteerism. For people to live a good life they have determined for themselves, they must not interfere with the autonomy of others. Especially, it is necessary to evaluate carefully whether the living donors in the family donate with a mission to save or because they are really volunteers. Saving lives can be a commendable option when one can be sure of the willingness of living donors. If we accept that voluntary donation is a moral and legal requirement, the issues of persuasion, coercion, force, lack of financial incentives, and manipulation and non-instrumentalization of individuals need to be addressed in a more systematic and detailed manner. The scales to be used to determine the volunteering in organ transplantation will contribute to the informed consent processes of health professionals, as well as basing the right to determine one’s own future and right to life on the self-worth of the individual.
If you are associated with any of the institutions in our list below, you can apply to receive OA publication funds by following the instructions provided in the links.
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