Authors: Dr. George F. Zarotis

Corresponding Author:
Dr. George F. Zarotis
Von-Andreae-Str. 1
51427 Bergisch Gladbach, Germany
E-Mail: drgzarotis@t-online.de, E-Mail: zarotisg@rhodes.aegean.gr

Dr. George F. Zarotis studied sports science at the German Sport University Cologne, prevention and rehabilitation through sport at the Ruhr-University Bochum (Master Degree) and sports economics and sports management at the Open University Hagen; Doctorate in the subjects of leisure science and rehabilitation at the German Sport University Cologne (PhD), Lecturer at the Institute for European Sports Development and Leisure Research of the German Sport University Cologne and at the University of Applied Sciences for Applied Management in Unna; since 2004 lecturer at the Faculty for Human Sciences of the Aegean University in Rhodes/Greece.

Fitness and Health Center Evaluation by Resigned Female Members

ABSTRACT
In the evaluations and statistical analyses presented here we examine the question to what extent are the evaluations of a fitness studio, by females dropping out from their contract, age-dependent. In other words: do studio evaluations – that probably have played a role in the quitting decision – have a different basis in older women in relation to younger women? According to the life stages, do other needs and therefore other preferences regarding the studio conditions play a role here?

A total of 164 women, who had terminated their contract with a fitness studio, were questioned. The survey was conducted as a telephone inquiry about their actual decision. Overall, it is found that only a few of the reasons offered in the survey are also indicated in significant frequency as important for the quitting decision. On the whole, the various aspects of the studio offer and its surroundings were largely rated as “good”, the mean values range around the value 2. The respondents particularly expressed their appreciation for the trainers (friendliness, helpfulness, competence), followed by opening hours, trial training and first impression. The membership costs and individual aspects such as spaciousness, music and ventilation are evaluated more critically, if not really badly. As regards the respondents’ age, there are only minor evaluation differences among the age categories.

These small differences in age have, depending on the item evaluated, very different directions. The correlations between age and studio evaluation are usually weak up to practically non-existent and in most cases also clearly not significant. Weak but distinguished from chance effects appear in the characteristics endurance training offer and parking facilities.

Keywords: Fitness- and health centre, evaluation, female, resigned members

INTRODUCTION
The fitness line is characterized both by an almost stagnating number of fitness clubs and an annual fluctuation of total membership numbers within the fitness studios. We also examine whether there are typical priorities in the drop-out justification and which reasons are used, in a statistically significant way, more or less or not at all. The collected data should help to derive recommendations for action in order to increase the customer satisfaction in fitness companies and to reduce the long-term drop-out rates by an adequate service offering (13,12,14).

In the evaluations and statistical analyses presented here we examine the question to what extent are the evaluations of a fitness studio, by females dropping out from their contract, age-dependent. In other words: do studio evaluations – that probably have played a role in the quitting decision – have a different basis in older women in relation to younger women? According to the life stages, do other needs and therefore other preferences regarding the studio conditions play a role here?

High drop-out rates in sports programs are no exception. The long-term commitment of sport active people poses a problem. This also applies to fitness training in studios, as about half of the members end their training prematurely (12).

The question concerning the reasons for dropping out hasn’t, so far, been studied in Germany, so the knowledge about it is only incomplete. Problematic therefore is also the indication of average drop-out rates in German fitness studios because they are not recorded or published.

Oldrige (9) analyzed ten sports programs in the context of preventive measures, setting cancellation rates from 13% to 75%. Analysis of another 18 prevention programs showed drop-out rates from 3% to 87%. In the study by Oldrige (8,10) 42% of the dropouts from a rehabilitation program for patients with coronary diseases mentioned “psychosocial reasons” (e.g. lack of interest, problems in the family). 25% of the dropouts mentioned “unavoidable reasons” (e.g. occupational conflicts, change of employment, change of residence), 22% gave medical reasons and 11% other reasons for quitting.

Brehm and Eberhardt (1,2) questioned fitness studio members about their reasons for quitting training because they had not renewed their membership when their contract ended. The “lack of fun in the sporting activities” was mentioned as a priority factor for quitting the activity. In addition, “motivation problems” (e.g., laziness), “lack of time” (often due to heavy workload) and “financial reasons” (too expensive membership fees) were mentioned as reasons for quitting. In an open question the members were asked for a specific reason for quitting. On this occasion criticism about the “studio atmosphere” (too impersonal) was mentioned, as well as “lack of social support” (e.g. no contact with other members, partner has quit the training, etc.) and “high membership costs” (also for additional services like childcare).

Pahmeier (11) also investigated which factors influence the decision to quit a sports program and found that among 65 respondents each gave an average of 3.6 reasons. The main problems that affected the quitting decision in this case were time management and factors of living and working conditions.

These studies show that quitting a sports program always depends on several factors. The features of quitting a sports activity may be personal and situational characteristics (12).

It is often possible to identify reasons which ultimately lead to dropping out, but the participation behavior is influenced by a complex factor structure.

Dishman (4,5) several times remarks critically on the often-unsystematic approach of many studies and describes them as atheoretical. He criticizes the limited data base and imputes it to the lack of uniform models that could simplify research.
Due to this lack of standardization of theories and examination methods, the comparability of the studies is severely restricted.

METHODS

Survey methodology
A total of 164 women, who had terminated their contract with a fitness studio, were questioned. The survey was conducted as a telephone inquiry about their actual decision.

The advantages of the telephone survey are the low cost per interview, the possibility of responding to queries and the high external validity. Disadvantages are the lower possible data volume caused by the difficulty to access the responder or lack of interest in a telephone survey, and the possible influence of the interviewer (6).

The study was conducted in a health-oriented fitness center in east Cologne. The fitness facility was opened in 1994 and has a size of 1,100 square meters. At the time of the study, the gym had up to 1.151 memberships. Among them, 59% of the members were women and 41% were men.

The survey was conducted by telephone in July 2016. The respondents are persons who have terminated their membership in the period between 01.07.2015 and 30.06.2016. In the aforementioned period, 305 members departed. Of those 225 persons were found and questioned. 54 people could not be found, probably due to relocation or change of telephone number. 26 persons did not wish to participate in the survey (15, 16, 17).

The persons were asked about different aspects of the training possibilities, equipment, support and environment factors of the fitness studio. Each evaluation aspect was queried on a 5-point Likert scale. The scaling ranged from “excellent” (coded with the numerical value 1) to “inadequate” (coded with the numerical value 5). The scaling corresponds to a school note scaling without the grade 6, the intermediate stages are correspondingly with “good”, “satisfactory” and “sufficient” verbally anchored.

In this way it is questionable in the strict metrological sense whether the distances between the scale stages can be regarded as equidistant and therefore whether the items have an interval scale level, or whether one would not have to assume an ordinal scale level here.

However, it can be shown that when using Likert scaled rating scales the use of parametric procedures can lead to statistically correct decisions even if the distances between the scale stages are not exactly equidistant.

For the significance testing of the dependency of the evaluation of the characteristics on age correlations were calculated. Here, age was used for age in years, not age categories. The age is clearly interval scaled. The reviews on the Likert scales are also treated here – as already mentioned – as interval-scaled. Therefore, all relationships with age are tested through Pearson correlations. As significance level, the conventional significance level of p <0.05 is used for the alpha error. All correlations / significance tests were calculated using the IBM SPSS Statistics version 22 program.

Such scaling can thus be evaluated as being “sufficiently similar” in practice as an “interval scale”, so that mean values and parametric procedures can be used accordingly.

In most of the questionnaire items there were no response refusals, so that in 17 of the 19 questionnaires there are valid values even N = 164. In two items there was a missing value, so that in these items there are N = 163 valid values. In the data analysis, the sample characteristics are initially described in terms of age and duration of membership in the studio.

With regard to the question of the relationship between the importance of quitting reasons and the age, the female respondents of the sample are presented in a descriptive manner in their distribution characteristics of the quitting reasons and by age groups. Therefore, age data were divided into the following four age categories:

  • Age group 1: Respondents up to 25 years old
  • Age group 2: Respondents between 26 and 40 years old
  • Age group 3: Respondents between 41 and 55 years old
  • Age group 4: Respondents from 56 years old and over

To ensure the inferential statistic of the relationship between the studio evaluation and the age, however, these age groups are not used, but correlations of the age in years with the evaluation using the Pearson correlation coefficients, to make use of the full variance of the characteristic age in the correlation analysis. These correlations are used to determine for each requested studio evaluation the extent to which the age determines the evaluation of individual studio aspects in this sample, and whether such a relationship in the sample -if it is worth mentioning- is statistically significant. The conventional significance level of p <.05 is used here. If the values are below the significance threshold, it can be assumed that the correlation can be generalized, beyond the sample, to all the population and does not merely represent a random effect of this specific sample.

The sample’s age range is between 16 and 74 years with a respondents’ average age of 43.3 years and a distribution of 11.4 years. In the age categories mentioned, exactly the half of the respondents are in the age category 3 and a further 32.3% in the age category 2. Very young respondents represent only 5.5% of the respondents and respondents over 55 years 12% of the respondents. Contract terminations were made on average after 4.1 years of membership, with a very large distribution (standard deviation) of 3.7.

Table 1. Sample distribution characteristic values
Table 1

Descriptive Statistics

Studio evaluation in general
Table 2 shows the mean values, median and standard deviations of the 19 questions concerning the quitting reasons.

Table 2. mean values, median and distribution of the studio evaluations
Table 2

Studio evaluations according to age categories
Table 3 shows the distribution characteristic values (mean value, median, standard deviation) and the sample size differs according to the four age categories.

Table 3. Distribution characteristic values of studio evaluations according to age categories
Table 3

Significance test of the correlations between studio evaluations and age
In Table 4, the correlation coefficients (product-moment correlations according to Pearson) of individual studio evaluations are presented each time with the respective age:

Table 4. Correlations between quitting reasons and age
Table 4

DISCUSSION
In general, the mean values of the evaluations vary between 1.3 and 2.4, i.e. all are consistently in the positive evaluation range of the scale. Most items are a little below or slightly above the value of 2, which is “good”. Clearly, the best scores are found in the last three items, in which the studio trainers are evaluated. Also opening hours, trial training and first impression are on average closer to the rating level “very good” than the rating level “good”. The – relatively speaking – worst ratings appear at the features of membership costs, spaciousness, music and ventilation.

In the research made by Rampf (12) it becomes also evident that 19 % of the respondent group stated “too high cost for membership” as the main single reason for quitting the sports program. However, the real amount of cost is not the actual problem but rather the negative cost/benefit balance. There is also evidence in other studies that financial aspects of dropout play an important role. In the survey by Breuer et al. (3) even 45.1% of the 149 respondents cite as a reason “membership costs”, which is why they discontinue fitness training. Financial aspects are also mentioned in a study by the IHRSA (7) as main arguments for the termination of membership in a fitness club. 52.2% of the 1,000 respondents surveyed said they were no longer able to afford their membership or rated them as expensive. Therefore, in future work, the collection of the income should be considered in order to assess its impact on the dropout.

It is important that the customer feels comfortable in the training area and in all other parts of the fitness-club. Comfortable feelings are for example guaranteed by not crowding the training area with training equipment. Sufficient space for movement during training, facilitates a positive training experience. Background music also creates a positive atmosphere. Sufficient ventilation is of special significance in that regard (12). A concentration of negative aspects in terms of training, will over time lead to an abandonment of the activity. Overall these results confirm the assumption that drop-outs are more critical towards general conditions and thereby support the results of other studies released on this topic (1, 11).

The differentiation by age groups shows in most evaluation categories only slight differences between the age groups of a few tenths of a scale in the mean values. More than half a scale difference in the mean values can only be found in the item parking facilities with a significantly better rating in the youngest age category, and in the item studio atmosphere, which is rated particularly better by the youngest age category. On the other hand, it is noticeably worse rated by the second youngest age category.

Within the small differences between the age groups, there are inconsistent trends across all age groups. For most items, a kind of “reversed u-shaped” relationship between age and evaluation is descriptive in the form that the oldest and the youngest respondents give the best ratings, while the middle age groups are slightly more critical. In the case of monotonous trends between age and evaluation, the direction of the trend is that the younger the respondents, the better the ratings. In the three items concerning the trainer evaluation it is interesting to see that there is practically no difference between the ages. On the whole, however, the differences between age categories – with the exception of parking facilities and studio atmosphere – are rather low.

The following correlations were found:

  • In the correlations between studio evaluations and age there are consistently only weak up to very weak trends; the most frequently occurring correlation amounts to 23. Accordingly, in 17 of the 19 correlations the outcome is also a – mostly obvious- not significant result; the slight correlations in the sample cannot therefore be distinguished from chance.
  • From the two significant correlations one is at a 1%-level and the other at a 5%-level distinguished from chance but both are consistently in the weak correlation intensity range. In detail these correlations indicate:
  • The evaluation of the endurance training offer correlates with age at r = .223 (p = .004; 5,0% explained variation), with increasing age, this aspect of the studio tends to receive worse evaluation
  • The evaluation of parking facilities correlates with age at r = .161 (p = .040; 2,6% explained variation), with increasing age, this aspect of the studio tends to receive worse evaluation

Overall, studio evaluation seems to be largely independent of the age of the women interviewed. The few resilient correlations are rather marginal in correlation intensity.

The overall conclusion is that there are still too few studies on the drop-out problem available globally as far as the fitness area is concerned. There is reason to believe that the companies reluctantly release such sensitive data for scientific purposes or that they don’t collect the data in the first place. However, this would be an essential instrument in order to decrease the termination ratio and to improve the success of the fitness companies in the long run (15,16,17).

CONCLUSIONS
On the whole, the various aspects of the studio offer and its surroundings were largely rated as “good”, the mean values range around the value 2. The respondents particularly expressed their appreciation for the trainers (friendliness, helpfulness, competence), followed by opening hours, trial training and first impression. The membership costs and individual aspects such as spaciousness, music and ventilation are evaluated more critically, if not really badly.

As regards the respondents’ age, there are only minor evaluation differences among the age categories. These small differences in age have, depending on the item evaluated, very different directions. The correlations between age and studio evaluation are usually weak up to practically nonexistent and in most cases also clearly not significant. Weak but distinguished from chance effects appear in the characteristics endurance training offer and parking facilities. Only the supposed excessive costs play a role for quitting the membership. As a recommendation for action this again suggests a more flexible and differentiated price policy on the part of the fitness companies (15, 16, and 17).

APPLICATIONS IN SPORT
Thus, the overall conclusion of the collected data is that only the high fees play an important role for quitting the membership. As a recommendation for action this suggests a more flexible and differentiated price policy on the part of the fitness company. This is the only way to respond to the individual needs of the members and thereby to achieve a better cost/benefit balance for them. A company might consider for example a price concept that includes a variety of class passes or memberships, such as Power Plate classes or cardio classes or an EMS (Electro-Myo-Stimulation) membership. Also, interesting could be a weekend membership or a morning pass from 9 a.m. to 5 p.m. with reduced fees or a sauna pass only. For persons who would like to exercise only sporadically or people who are often away on business or those who exercise elsewhere a 10-days pass or a day pass would be appropriate. The aim of all these measures is to maintain member loyalty and to customize the membership to changed life circumstances.

ACKNOWLEDGMENTS
None

REFERENCES
1. Brehm W., Eberhardt J. (1995). Drop-Out and adherence in Fitness-Studio. Sports science, 25(2), 174-186.
2. Brehm W., Pahmeier I. (1990). Dropping out or remaining; Breakpoints of a broad sports career and conditions of a withdrawal. Spectrum of Sports Science, 2(2), 33-56.
3. Breuer, C., Wicker, P., & Nagel, N. (2013). A time-economic analysis of fitness training. Cologne: German Sport University Cologne, Institute of Sport Economics and Sport Management.
4. Dishman R. K. (1982). Compliance/Adherence in Health-Related Exercise. Healthy Psychology, 1, 237-267.
5. Dishman R. K. (1988). Exercise Adherence – Its Impact on Public Health. Champaign, Human Kinetics Books.
6. Homburg, Ch., Krohmer, H. (2008). The process of market research: definition of data collection, sample formation and questionnaire design. In Herrmann, A., Homburg, Ch., Klarmann, M. (2008). Handbook Market Research (3rd Edition), 21-51, Wiesbaden: Gabler.
7. IHRSA2. (May 2012). Why did you leave / quit your former health club?
In Statista – The Statistics Portal. Retrieved January 05, 2015, from
http://www.statista.com/statistics/246978/reasons-for-quiting-healthclub membership/.
8. Oldrige, N. B. (1979a). Compliance of Post Myocardial Infarction Patients to Exer¬cise Programs. Medicine and Science in Sports, 11(4), 373-375.
9. Oldrige, N. B. (1981) Dropout and Potential Compliance – Improving Strategies in Exercise Rehabilitations, in: Nagele F., Montoye H. (Ed.), Exercise in Health and Disease. Springfield.
10. Oldrige, N. B., Steiner D. L. (1990). The Health Belief Model: Predicting Compliance and Dropout in Cardiac Rehabilitation. Medicine and Science in Sports and Exercise, 22(5), 678-683.
11. Pahmeier, I. (1994). Drop-out and adherence in recreational and health sport. Favourable and unfavourable conditions for sports participation, 24(2), 117-150.
12. Rampf, J. (1999). Drop-out and adherence in fitness sports. Favourable and unfavourable conditions for activities in the gym. Cwalina, Hamburg.
13. Zarotis, G. (1999). Goal Fitness-Club: Motivation in Fitness-Sport. Meyer & Meyer, Aachen.
14. Zarotis, G., Tokarski, W. (2005). Gender-specific differences for motivation in health-oriented sports and fitness facilities. Spectrum free time, 28(2), 81-89.
15. Zarotis, G., Athanailidis, I., Arvanitidou, V., Mourtzios, Ch. (2017). Age-specific reasons for dropping out of the Fitness-Sport. Journal of Physical Education and Sport, 17(2), 916-924.
16. Zarotis, G., Athanailidis, I., Arvanitidou, V., Mourtzios, Ch. (2017). Age-dependent fitness centre evaluation by resigned members. Journal of Physical Education and Sport, 17(3), 1926-1933.
17. Zarotis, G., Athanailidis, I., Tosunidis, A., Mastrogiannopoulos, N. (2017). Drop-Out in Fitness-Sport. Comparing the general relevance of reasons for quitting. TRENDS in Sport Sciences, 24 (4), 175-181.

Print Friendly, PDF & Email