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2.2: Preference Schedules


To begin, we’re going to want more information than a traditional ballot normally provides. This ballot fails to provide any information on how a voter would rank the alternatives if their first choice was unsuccessful.

Preference ballot

A preference ballot is a ballot in which the voter ranks the choices in order of preference.

Example 1

A vacation club is trying to decide which destination to visit this year: Hawaii (H), Orlando (O), or Anaheim (A). Their votes are shown below:

(egin{array}{|l|l|l|l|l|l|l|l|l|l|l|}
hline & ext { Bob } & ext { Ann } & ext { Marv } & ext { Alice } & ext { Eve } & ext { Omar } & ext { Lupe } & ext { Dave } & ext { Tish } & ext { Jim }
hline 1^{ ext {st }} ext { choice } & mathrm{A} & mathrm{A} & mathrm{O} & mathrm{H} & mathrm{A} & mathrm{O} & mathrm{H} & mathrm{O} & mathrm{H} & mathrm{A}
hline 2^{mathrm{nd}} ext { choice } & mathrm{O} & mathrm{H} & mathrm{H} & mathrm{A} & mathrm{H} & mathrm{H} & mathrm{A} & mathrm{H} & mathrm{A} & mathrm{H}
hline 3^{mathrm{rd}} ext { choice } & mathrm{H} & mathrm{O} & mathrm{A} & mathrm{O} & mathrm{O} & mathrm{A} & mathrm{O} & mathrm{A} & mathrm{O} & mathrm{O}
hline
end{array})

Solution

These individual ballots are typically combined into one preference schedule, which shows the number of voters in the top row that voted for each option:

(egin{array}{|l|l|l|l|l|}
hline & 1 & 3 & 3 & 3
hline 1^{ ext {st }} ext { choice } & mathrm{A} & mathrm{A} & mathrm{O} & mathrm{H}
hline 2^{ ext {nd }} ext { choice } & mathrm{O} & mathrm{H} & mathrm{H} & mathrm{A}
hline 3^{ ext {rd }} ext { choice } & mathrm{H} & mathrm{O} & mathrm{A} & mathrm{O}
hline
end{array})

Notice that by totaling the vote counts across the top of the preference schedule we can recover the total number of votes cast: (1+3+3+3 = 10) total votes.


Modelling a Nurse Shift Schedule with Multiple Preference Ranks for Shifts and Days-Off

When it comes to nurse shift schedules, it is found that the nursing staff have diverse preferences about shift rotations and days-off. The previous studies only focused on the most preferred work shift and the number of satisfactory days-off of the schedule at the current schedule period but had few discussions on the previous schedule periods and other preference levels for shifts and days-off, which may affect fairness of shift schedules. As a result, this paper proposes a nurse scheduling model based upon integer programming that takes into account constraints of the schedule, different preference ranks towards each shift, and the historical data of previous schedule periods to maximize the satisfaction of all the nursing staff's preferences about the shift schedule. The main contribution of the proposed model is that we consider that the nursing staff’s satisfaction level is affected by multiple preference ranks and their priority ordering to be scheduled, so that the quality of the generated shift schedule is more reasonable. Numerical results show that the planned shifts and days-off are fair and successfully meet the preferences of all the nursing staff.

1. Introduction

Nurse-scheduling problem is a classical combinatorial optimization problem and has been shown to be NP-hard [1, 2]. The objective of the nurse-scheduling problem is to determine the rotating shifts of the nursing staff over a schedule period (weekly or monthly) [3]. A nurse schedule includes the work shifts and days-off of the nursing staff, ensuring that all the combinations of shifts and days-off meet the manpower requirements of each shift (including total number of staff members, daily minimum number of staff members, and number of senior staff members required), and at the same time the number of basic days-off of each staff member should be fulfilled [3].

In general, there are a lot of types of work shifts and days-off in shift schedules. The most common ones include the 2-shift rotation (i.e., 12-hour day shift and 12-hour night shift) and the 3-shift rotation (i.e., 8-hour day shift, 8-hour evening shift, and 8-hour night shift). Regular days-off allow the nursing staff to rest, and each staff member is entitled to the same number of days-off [4–7]. Due to diverse personal lifestyles and different degrees of physical tolerance for continuous working days, the nursing staff usually have different preferences for work shifts and days-off.

The satisfaction of the nursing staff’s preference for work shifts and days-off enables them to take the proper rest to increase the quality of medical service and reduce medical cost of the hospital as well as risks of occupational hazard [8, 9]. Therefore, it has been an interesting problem in the recent works to take into consideration the nursing staff’s preferences in planning the schedule of work shifts and days-off and adopt maximization of satisfaction and minimization of penalty cost to evaluate the quality of the shift schedule with preferences [2, 10–13].

For example, as far as the hard constraints and soft constraints of the nurse shift schedule (including the nursing staff’s preferences and the demands of hospitals) are concerned, Hadwan et al. [2] aimed to minimize the penalty cost of a nurse schedule. Aickelin and Dowsland [11] applied a genetic algorithm to solve the nurse shift scheduling problem with the objective of minimizing the penalty cost for not fulfilling the preferences of the nursing staff. Maenhout and Vanhoucke [12] investigated the penalty costs with multiple constraints (including the nursing staff’s preferences and some specific combinations of work shifts and days-off). Topaloglu and Selim [13] considered a variety of uncertain factors in nurse shift scheduling to propose a fuzzy multiobjective integer programming model which takes into consideration the fuzziness of the objective and the nursing staff’s preferences.

From the literature, we discover that, in the penalty cost (or satisfaction) due to the nursing staff’s preferences in the objective function, all the previous works only focused on the most preferred work shift and the number of satisfactory days-off of the shift schedule at the current schedule period and further investigated neither different preference ranks (such as three ranks: good, normal, or bad) of the nursing staff toward different work shifts or planned days-off nor the number of times in which their preferences are satisfied in the previous shift schedules and days-off. Since the constraints of the schedule lead to the fact that the most preferred work shifts and days-off of each staff member cannot be fulfilled completely, we believe that if the penalty cost (or satisfaction level) due to preferences of the nursing staff does not consider different preference ranks and the historical data of previous schedules, the long-term fairness and justice of the nurse shift schedules is affected. For example, if each nursing staff member has three different preference ranks (good, normal, or bad) towards a 3-shift rotation, those scheduled to a bad work shift would have a larger preference penalty cost (or lower preference satisfaction level) as compared with those scheduled to work a normal shift and should be assigned a higher priority to their higher preference rank in their schedule at the next scheduling period.

In light of the above, this paper proposes a binary integer linear programming model for the nurse shift schedule with different levels of satisfaction preference and a different priority ordering of the nursing staff for planning their shift schedule. The objective of this model is to maximize the overall satisfaction level of the nursing staff towards their work shifts and days-off schedule. In addition, some common nurse-scheduling constraints are considered, including the limited number of nursing staff members, work shift limitation, and day-off limitation. Our mathematical model is capable of effectively helping schedule planners to design a nurse shift schedule that attempts to, within all scheduling constraints, satisfy the shift and day-off preferences of most of the nursing staff members in a fair manner and to achieve the highest overall satisfaction level.

The main contributions of this paper are stated as follows. In the proposed mathematical model for nurse schedule, the work shift and day-off preferences of the nursing staff are categorized into different levels and are then integrated to be solved. In addition, in the case, where the preferred number of shifts or days-off exceeds the actual shifts or days-off available (due to schedule constraints), a priority ordering mechanism of the nursing staff when planning their shift schedule is applied to solve the contradictory situations among their preferences.

The rest of this paper is organized as follows. Section 2 gives the literature review of our work. Section 3 first describes our concerned problem and then constructs its mathematical programming model. Section 4 gives a numeric example to analyze the performance of the shift schedule constructed by our mathematical model. Finally, a conclusion is made in Section 5.

2. Literature Review

The nurse-scheduling problems have been solved by a variety of methods, which are mainly introduced by mathematical programming, heuristics, and others in this section.

First, the mathematical programming approaches for the nurse-scheduling problem are introduced. Maenhout and Vanhoucke [12] proposed an integrated analysis method to solve human resource planning and shift scheduling problem of nurses on the long run. Azaiez and Al Sharif [14] solved the nurse-scheduling problem with a 0-1 linear programming model, which takes into consideration the ratio of nurses working night shifts or having days-off on weekends and tries to avoid unnecessary overtime so that hospital costs can be reduced. Topaloglu [15] proposed a multiobjective programming model to tackle the nurse-scheduling problems of house physicians in the emergency room. Based on the AHP method, soft constraints in the model are weighted in accordance with their relative importance and this becomes the basis for weighting objective functions. Topaloglu [16] proposed a multiobjective scheduling model for planning the shifts of resident physicians, in which seniority of a resident physician is used for the weight setting. Empirical analysis showed that the model is far superior to the manual scheduling method in terms of efficiency and time-saving.

Beliën and Demeulemeester [17] proposed an integrated scheduling method for nurses and surgeons. They applied the branch-and-price method to perform integration, which is one of the most common methods to generate explicit solutions among the column generation techniques. Glass and Knight [18] identified four categories of nurse-scheduling problems and solved them with mixed-integer linear programming. Results showed that the optimal solutions were produced in all benchmarking examples within 30 minutes. The characteristic of this model is that it reduces the collection space based on the structure of the problem so that the problem-solving efficiency can be enhanced. Valouxis et al. [19] proposed a 2-stage solution to solve the nurse-scheduling problem, where the workload and days-off of each nurse are first determined before the shifts are planned.

Second, the heuristics for nurse-scheduling problems are introduced. Hadwan et al. [2] proposed a harmony search algorithm for the nurse-scheduling problem, which was tested in hospitals in Malaysia and was shown to be better than the genetic algorithm approach as well as most heuristic approaches. Aickelin and Dowsland [11] proposed an indirect genetic algorithm for the nurse-scheduling problem, in which a chromosome encoding is performed recombination is conducted with a heuristic approach evolution is conducted via mixed-crossover to locate better solutions. The method has been tested and was found to be superior to some of the already published Tabu search methods.

Tsai and Li [20] proposed a 2-stage programming model to analyze and solve the nurse-scheduling problem, in which days-off are planned in the first stage, and then shifts are determined in the second stage. The two stages were then analyzed with a genetic algorithm. Sadjadi et al. [21] proposed a mixed-integer nonlinear programming model to randomly plan shift schedules, in which the demand for human resource is considered a variable and is based on a certain probability distribution. Then, the authors applied the GA and Taguchi method to solve the nurse-scheduling problem. Gutjahr and Rauner [22] proposed ant colony optimization to solve dynamic regional nurse-scheduling problem in a public hospital in Vienna, Austria. Upon verification via simulation experiments, the model was shown to be superior to a greedy assignment algorithm.

Finally, except for the above two methods, some other solutions for the nurse-scheduling problem are introduced. Lü and Hao [23] proposed adaptive neighborhood search (ANS) for the nurse-scheduling problem, which performs a neighborhood search and changes based on three different levels of intensity and change. The approach was tested on 60 examples and the results were quite impressive. M. V. Chiaramonte and L. M. Chiaramonte [24] proposed to use a competitive agent-based negotiation algorithm for the nurse-scheduling problem, which aims to maximize preferences of nurses and minimize the costs. Vanhoucke and Maenhout [25] proposed a set of complexity indicators for the nurse-scheduling problem, which can indicate the complexity of the problem and automatically come up with a simulation solution that meets the level of complexity of the problem. They can be used as the baseline analysis to compare the performance of different approaches.

From the above literature review, it can be found that many works did not explore the preference ranks of the nursing staff towards each shift rotation or day-off. In addition, the preferred shift and day-off are not given any priority ordering according to the previous scheduling periods. Based on this, this paper proposes a mathematical programming model for the nurse-scheduling problem in order to produce a preliminary shift schedule that can fulfill the needs of practical work and at the same time satisfy most nursing staff members.

3. Methodology

In this section, we construct a mathematical model to plan the shift rotation and day-off based on the preference ranks of the nursing staff. The construction process of the mathematical model includes description of the problem, identification of the satisfaction level of the nursing staff, and the development of the mathematical model.

3.1. Problem Description

In this subsection, we explain the actual work scenario inside the hospital and then the problems encountered when planning for a shift schedule.

We first describe the work scenario, which includes the structure and constraints of shift schedule, combination of the nursing staff, and the preference ranks of the nursing staff towards each shift rotation and days-off. Consider a shift schedule for a 2-week work in which the shifts of a day start at 0:00 AM and the hospital runs on a 3-shift rotation: a day shift (8:00 AM

4:00 PM), an evening shift (4:00 PM

0:00 AM), and a night shift (0:00 AM

8:00 AM). Note that only regular days-off are planned in the schedule.

The planned schedule has some constraints on shift rotations: each nursing staff member is only assigned to a fixed type of shift within each schedule period the number of nursing staff members required for each shift is fixed (after deducting the number of nursing staff members on regular days-off) each person should have at least an 8-hour rest before continuing on to the next shift. Note that the constraint of a fixed shift for each staff member is reasonable since, in practice, in order to ensure that the nursing staff enjoy the health with fixed work and rest, some hospitals assign each nursing staff member a fixed work shift type for all working days of the scheduling period. In addition, the planned schedule has some constraints on days-off: the total number of days-off of each nursing staff member within the schedule period is the same, and each nursing staff member is entitled to at least one day-off each week. The maximum number of the nursing staff members is allowed to be on day-off, and the number of senior staff members working in each shift each day are known and flexible.

As for composition of the nursing staff, the qualified nursing staff members are categorized into junior and senior staff members, where the staff members with at least 2 years of nursing working experience are considered senior, and those below 2 years, junior. Also, all the nursing staff are full time. When the total number of staff members is insufficient to cover all the shifts, the concerned department has to hire new staff members to fill this shortage in manpower. Outsourcing nursing staff members from other departments is not allowed.

Lastly, the nursing staff are asked to rank their preferences for each shift and day- off, which are called preference ranks. The preference ranks of each shift are classified into three types: “good,” “normal,” and “bad” shifts. The preference ranks of days-off are classified into “good” and “bad” days-off based on the “preferred” and “not preferred” days-off, respectively. Note that each staff member has a fixed number of days-off within each schedule period. Therefore, we assume that there may be more than one “good” day-off and no further rank is made among all the “good” days-off.

As the nursing staff have rather diverse preferences, they are asked to fill out a preference form before the schedule is formulated so that the schedule planner has adequate information about the staff’s preferences for shifts and days-off and the total number of the nursing staff preferring each shift or day-off. In the preference form, the preference ranks of shifts are expressed in a numerical ordering: 1 indicates “good” (most preferred), 2 indicates “normal,” and 3 indicates “bad” (least preferred). The preference ranks of days-off are expressed as follows: 1 indicates “good” (preferred) while 3 indicates “bad” (not preferred). Note that the numbers of the preference ranks for shifts and days-off are three (i.e., 1, 2, and 3 for good, normal, and bad, resp.) and two (i.e., good and bad), respectively. We assume that the good and bad preference ranks for shifts and days-off are corresponded with each other. Therefore, we let the good and bad preference ranks for days-off be 1 and 3, respectively.

In the actual work scenario, each nursing staff member has different preference ranks for shifts and days-off, markedly increasing the computing time and difficulty to formulate a shift schedule. Also, a lot of constraints for schedule make it impossible for all the staff members to work their preferred shifts and have their preferred days-off. Therefore, it is important to formulate a preliminary shift schedule recommendation so that schedule planners can perform necessary and flexible adjustments on the recommended schedule, reducing the difficulty and workload of manpower planning.

3.2. Preference Satisfaction of Shifts and Days-Off

This subsection discusses the satisfaction of the preference ranks of shifts and days-off, which is called preference satisfaction. This paper aims to maximize the overall shifts and days-off preference satisfaction of the nursing staff. There are different preference ranks of shifts and days-off, and the preference satisfaction increases with the preference ranks. The more the number of preferred shifts and days-off is satisfied, the higher the overall satisfaction level towards the shift schedule will be.

However, due to the constraints on shifts and days-off, not all the preferred shifts and days-off could be satisfied. For the staff members not scheduled to their preferred shifts or days-off for consecutive schedule periods, if their preferences in the next schedule are satisfied with a higher priority, then their preference satisfaction must be higher. Therefore, in designing the preference satisfaction, the past schedules are reviewed first (to count the number of times in which a preferred shift of an individual is satisfied in the past few schedule periods) and the weights of preferred shifts and days-off of each nursing staff member are calculated before the current schedule is formulated. Note that the staff member with a larger preference weight must be scheduled with a higher priority order. Then, based on these two weighted values, the preference satisfaction of work shifts and days-off of the current schedule can be calculated.

3.3. Mathematical Model

In this subsection, a binary integer linear programming model is constructed, which aims to maximize the overall preference satisfaction of the nursing staff towards the shift schedule by taking into consideration the preference ranks of the nursing staff for different work shifts and days-off, despite the constraints of manpower, shifts, and days-off.

3.3.1. Symbols

: Index of a nursing staff member

: Set of the nursing staff (i.e.,

: Set of shift types (i.e., note that = <1 (day shift), 2 (evening shift), 3 (night shift)>in this paper)

: Set of days-off (i.e., note that

: Set of preference ranks of shifts, =

: Set of preference ranks of days-off, =

: Number of the past schedule periods considered

: Coefficient of the most preferred shift, > 1

: Total number of days-off of each staff member within the schedule period, > 1

: The variable to identify whether staff member is senior, =

: The preference weight of staff member for work shift

: The preference weight of staff member for day-off

: The base of preference weight ( = 2 in this paper)

: Preference satisfaction of staff member in working shift : Preference satisfaction of staff member in taking day

: Preference rank of staff member for shift within the schedule period, : Preference rank of staff member for taking day off within the schedule period,

: In the recent periods, the number of times in which staff member has been assigned to the shift of preference rank ,

: In the recent periods, the number of times in which staff member has been assigned to the day-off of preference rank ,

: Preference score for being assigned to the shift of preference rank ,

: Preference score for being assigned to the day-off of preference rank ,

: Manpower demand in shift on day

: Lower bound of the required number of senior staff members in shift on day

: The maximum number of staff members allowed to have day-off in shift on day

: Whether staff member worked shift in the previous schedule periods,

: Whether staff member had day-off in shift on day in the previous schedule periods, <0 (no), 1 (yes)>.

Decision Variable : Whether staff member is scheduled for shift , <0 (off shift), 1 (on shift)>. : Whether staff member is scheduled for day-off in shift on day , <0 (off shift), 1 (on shift)>.


Creating a Joint Custody Schedule

Custody can be physical, legal, or both. When parents share joint legal custody, they both have a say in major decisions regarding the child's life, such as education, religious upbringing, and ​medical care. When parents have joint physical custody, their children spend time living in each of their homes, although it doesn't necessarily have to be an exact 50/50 split. ​

These six joint custody schedules provide for almost equal time for the kids with both parents. You can tweak and adjust the schedules to meet your family's unique needs.

It's important to settle on a routine that works for everyone and takes into consideration both parents’ work schedules, your kids' ages, their school schedules, extracurricular​​ activities, and even driving considerations if you live more than 30 miles apart.


Pros and cons of a 2-2-5-5 schedule

  • Your child is able to spend time with both parents each week.
  • Your child doesn't go a long time without seeing a parent.
  • The schedule is consistent and fairly easy to remember.
  • Parents have equal time so there may be less fighting about the schedule.
  • This is a shared parenting schedule, so both parents provide daily caregiving.
  • This schedule can work very well if parents have nontraditional work schedules.
  • This schedule can work well for younger children who aren't in school.
  • There are frequent exchanges which the parents must remember and keep track of.
  • One parent may have the child every weekend.
  • Your child changes homes frequently and may struggle with adapting.
  • Since your child will spend weekdays in both parents' homes, the parents must communicate about school and activities.
  • The parents must live relatively close to each other.
  • If the child is in school, both parents must live close to the school.

State preferences for joint physical custody

Many states have laws that give preference for joint physical custody. Courts in these states will order joint physical custody as the default unless a parent can prove that it would be harmful to the child.

Look at your state custody guidelines to find out what your court prefers. Some states require that both parents have a minimum amount of time with the child in order for the arrangement to be labeled joint physical custody. Other states simply require both parents to have substantial and frequent contact with the child.


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Questions to Ask Yourself if You Are Considering a 2-2-3 Arrangement

If you are still trying to decide whether a 2-2-3 visitation schedule could work for you and your spouse, be sure to consider its implications on both you and your children. Here are just a few of the guiding questions you should answer before adopting this visitation plan:

  • Are weekly transitions going to be stressful for you, because you will have to interact with your spouse?
  • Will your children have a hard time switching parents at such a high rate?
  • Is anyone involved too busy to cope with this schedule? Am I ready to commit to this change?
  • Am I willing to put forth the time and money to make sure my children have weekly interactions with both parents?
  • Do my children need weekly interactions to feel loved and safe?
  • Will this schedule improve or hinder my children’s mental and emotional development?
  • Will my spouse and I be able to work as a team, rather than undermining each other or fighting in front of the children?

After you have considered the answers to these questions, you might decide that a 2-2-3 visitation schedule is right for you, or you could choose a different route. Remember, this arrangement might not work for you, even though it works for some divorced parents. As long as you are primarily considering the wellbeing of your children and yourself throughout your decision, you will find a plan that works for everyone.


5 CFR § 6.2 - Schedules of excepted positions.

OPM shall list positions that it excepts from the competitive service in Schedules A, B, C, D, E, and F, which schedules shall constitute parts of this rule, as follows:

Schedule A. Positions other than those of a confidential or policy-determining character for which it is not practicable to examine shall be listed in Schedule A.

Schedule B. Positions other than those of a confidential or policy-determining character for which it is not practicable to hold a competitive examination shall be listed in Schedule B. Appointments to these positions shall be subject to such noncompetitive examination as may be prescribed by OPM.

Schedule C. Positions of a confidential or policy-determining character normally subject to change as a result of a Presidential transition shall be listed in Schedule C.

Schedule D. Positions other than those of a confidential or policy-determining character for which the competitive service requirements make impracticable the adequate recruitment of sufficient numbers of students attending qualifying educational institutions or individuals who have recently completed qualifying educational programs. These positions, which are temporarily placed in the excepted service to enable more effective recruitment from all segments of society by using means of recruiting and assessing candidates that diverge from the rules generally applicable to the competitive service, shall be listed in Schedule D.

Schedule E. Position of administrative law judge appointed under 5 U.S.C. 3105. Conditions of good administration warrant that the position of administrative law judge be placed in the excepted service and that appointment to this position not be subject to the requirements of 5 CFR, part 302, including examination and rating requirements, though each agency shall follow the principle of veteran preference as far as administratively feasible.

Schedule F. Positions of a confidential, policy-determining, policy-making, or policy-advocating character not normally subject to change as a result of a Presidential transition shall be listed in Schedule F. In appointing an individual to a position in Schedule F, each agency shall follow the principle of veteran preference as far as administratively feasible.


Contents

Murray's system of human needs has influenced the making of personality tests for years. [2] By incorporating his theory into personality testing, one can determine how one may act in a specific situation, as an employee, student, parent. The list goes on and on. Following is an overview on Murray's theory.

American psychologist Henry Murray developed a theory of personality that was organized in terms of motives, presses, and needs. Murray described a need as a potentiality or readiness to respond in a certain way under certain given circumstances.

Theories of personality based upon needs and motives suggest that our personalities are a reflection of behaviors controlled by needs. While some needs are temporary and changing, other needs are more deeply seated in our nature. According to Murray, these psychogenic needs function mostly on the unconscious level, but play a major role in our personality. [3]

The Personality Research Form and the Jackson Personality Inventory are also structured personality tests based on Murray's theory of needs but were constructed slightly differently than the EPPS in hopes of increasing validity. [2]

The 15 personality variable scales Edit

On the EPPS there are nine statements used for each scale. Social Desirability ratings have been done for each item, and the pairing of items attempts to match items of approximately equal social desirability. Fifteen pairs of items are repeated twice for the consistency scale.

  1. Achievement : A need to accomplish tasks well
  2. Deference: A need to conform to customs and defer to others
  3. Order: A need to plan well and be organized
  4. Exhibition: A need to be the center of attention in a group
  5. Autonomy: A need to be free of responsibilities and obligations
  6. Affiliation: A need to form strong friendships and attachments
  7. Intraception: A need to analyze behaviors and feelings of others
  8. Succorance: A need to receive support and attention from others
  9. Dominance: A need to be a leader and influence others
  10. Degradation: A need to accept blame for problems and confess errors to others
  11. Nurturance: A need to be of assistance to others
  12. Change: A need to seek new experiences and avoid routine
  13. Endurance: A need to follow through on tasks and complete assignments
  14. Heterosexuality: A need to be associated with and attractive to members of the opposite sex
  15. Aggression: A need to express one's opinion and be critical of others [4]

(Edwards, 1959/1985) [ citation needed ]

Test Consistency Edit

The inventory consists of 225 pairs of statements in which items from each of the 15 scales are paired with items from the other 14 plus the other fifteen pairs of items for the optional consistency check. This leaves the total number of items (14x15) at 210. Edwards has used the last 15 items to offer the candidate the same item twice, using the results to calculate a consistency score. [4] The result will be considered valid if the consistency checks for more than 9 out of 15 paired items. Within each pair, the subjects choose one statement as more characteristic of themselves, reducing the social desirability factor of the test. Due to the forced choice, the EPPS is an ipsative test, [2] the statements are made in relation to the strength of an individual's other needs. Hence, like personality, it is not absolute. Results of the test are reliable, although there are doubts about the consistency scale.

The manual reports studies comparing the EPPS with the Guilford Martin Personality Inventory and the Taylor Manifest Anxiety Scale. Other researchers have correlated the California Psychological Inventory, the Adjective Check List, the Thematic Apperception Test, the Strong Vocational Interest Blank, and the MMPI with the EPPS. In these studies there are often statistically significant correlations among the scales of these tests and the EPPS, but the relationships are usually low-to-moderate and sometimes are difficult for the researcher to explain. Since the MMPI is still actively used today on a worldwide basis as a major brand test this comparison might be the most interesting to study.

The EPPS has been designed primarily for personal counselling, but has found its way into recruitment as well. The EPPS is very suitable for these purposes..

The inter-correlations of the variables measured by EPPS are quite low. It indicates that the variables being measured are relatively independent and the schedule is quite reliable. [4]

The EPPS has been published for a long period of time through The Psychological Corporation, now known as Harcourt Assessment. In 2002 the worldwide publishing rights have been returned by Harcourt to the Allen L. Edwards Living Trust. Internationally there is a translation in Dutch, which has been published in the Netherlands legally until 2002 (by Harcourt Test Publishers). There is also a translation into Japanese, published in 1970 by Nihon Bunka Kagakusha, Tokyo. The EPPS is translated into Spanish in 2014 in Mexico.

Currently copyrights are held by The Allen L Edwards Living Trust worldwide. The EPPS is published by Test Dimensions Publishers in English, Dutch and Spanish.


Get help with infant parenting plans and schedules

Creating a plan and schedule on your own can feel overwhelming. You have to be sure to use airtight legal language and can't omit any required information.

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As a result, you get documents and calendars that meet your family's needs, as well as the court's standards.

For quick, reliable and affordable help making a parenting plan and custody schedule, turn to Custody X Change.

Custody X Change is software that helps parents create a parenting plan and schedule for a baby.