The Burden of Administrative Household Labor—Measuring Temporal Workload, Mental Workload, and Satisfaction

Abstract

This research paper investigates the temporal and mental workload as well as work satisfaction regarding bureaucratic, administrative household labor, with a focus on socio-demographic differences. The study utilizes a paid online survey with 617 socio-demographically distributed participants. The results show significant differences in the temporal workload of different chore categories and in the quality of work, whereby satisfaction and mental workload are examined. In addition, the influences of gender, age, and education are analyzed, revealing differences in temporal and mental workload as well as work satisfaction. Our findings confirm prevailing literature showing that women have lower work satisfaction and a higher workload. In addition, we also discovered that younger people and groups of people with higher incomes have a higher level of satisfaction and a higher workload. In our study, a perceived high mental workload does not necessarily go hand in hand with a low level of satisfaction. This study contributes to the understanding of the bureaucratic burden on adults in their households and the variety of activities to manage private life.

1. Introduction

Domestic life is often portrayed as a private, relaxing, and entertaining sphere that is not worthy of serious investigation (Hayden 1982). However, feminism has challenged this notion, highlighting that the domestic context is characterized by a multitude of obligations, unpaid labor, and an unequal distribution of tasks (Hayden 1982; Hochschild 1989; Mederer 1993).

Most research in this area has focused on daily chores, which arise internally within the domestic environment, such as cleaning, cooking, and caregiving, to keep the household running. In addition to these internal chores, this paper focuses on the various tasks that are influenced by external factors, stemming from the structural coupling of the household with its broader environment. One prominent example is the administrative work necessitated by bureaucratization (U.S. OMB 2022, 2023). These tasks include managing invoices, handling official documents, coordinating with service providers, and navigating various regulatory requirements. The impact of these external chores is significant, as they represent an additional layer of complexity and workload to the household. Unlike the predictable routine of internal chores, administrative tasks often require interactions with external entities and adherence to external schedules and regulations.

The fulfillment of such administrative work constitutes a bureaucratic burden, which is part of daily household labor (Dethier et al. 2024; Emens 2015). Compared to household chores, such as cooking, cleaning, or caring, administrative household labor is mainly cognitive and invisible work that is difficult to quantify (Daminger 2019; Hochschild 1989; Mederer 1993). Nevertheless, it shares with these other tasks the characteristic that it is unequally distributed within the household generally, for example, between women and men (Ciciolla and Luthar 2019; Coltrane 2000; DeVault 1991; Moreno-Colom 2017; Offer 2014; Twiggs et al. 1999).

Administrative household labor represents the work after work, which has social value but not a monetary price (Hochschild 1989). Its costs are discernible in terms of expended time as well as the impact on personal well-being (Pandve 2017). While the negative effects of excessive bureaucracy are well-known in organizational science (Koppes 2014), they are commonly neglected concerning private life. This also resulted from the fact that domestic work in general is invisible, informal, boundaryless, enduring, and difficult to articulate (Daminger 2019; Daniels 1987; Dean et al. 2022; DeVault 1987, 1991; Illich 1980; Mederer 1993; Winkler and Ireland 2009).

Overall, the prevalence of bureaucratization is undeniable, but its impact on household labor is under-explored, in terms of both temporal and mental workload. For this reason, we conducted a paid online survey to answer the following research questions:

(RQ1) In terms of quantitative workload, what amount of time do individuals spend on different everyday administrative tasks?

(RQ2) In terms of qualitative workload, how do individuals perceive administrative work and its mental demands?

(RQ3) In terms of socio-demographics, are there any differences in both the quantity and quality of work?

Investigating these research questions contributes to gaining a deeper understanding of the effects of bureaucratization on private life as well as identifying potential differences between different population groups.

2. Literature Review of Administrative Household Chores

Household administration has become increasingly recognized as a distinct area of study over the past few decades (DeVault 1987; Hochschild 1989; Mederer 1993). This kind of labor encompasses activities such as filing tax returns, managing insurance claims, renewing licenses, canceling contracts, etc. (Daminger 2019; Emens 2019; Emens 2015; Mederer 1993; Twiggs et al. 1999).

Understanding this kind of labor requires moving beyond the traditional view of the household as an isolated unit. Instead, households function as social systems that are structurally coupled with their external environment (Luhmann 1988, 2020). This coupling is manifested by administrative chores, which are deeply intertwined with the bureaucratic processes and requirements imposed through public authorities (U.S. OMB 2022, 2023) and private companies (Dethier et al. 2024; Emens 2015). They demand cooperation with external entities, adherence to regulatory requirements, and compliance with varying timelines and procedural norms. This external dimension of household labor adds complexity and stress to the everyday management of the household.

Currently, there is no unified taxonomy of the manifold administrative household chores. In this paper, however, we take into account the activities and categories that are often mentioned in the literature (see

Table 1. Overview of administrative household activities.

	Category		Description
Goods & services	Commodity products	Trans-actional	Administration of the purchase and stocking of consumer goods (food, clothing, household goods, etc.) by creating shopping lists, researching information, comparing offers, etc. Not the purchase itself.
		Recurring	Administration of the procurement, management, and termination of term contracts (electricity, water, gas, telephone, internet, streaming/newspaper subscriptions, etc.) by researching information, making comparisons, signing contracts, ensuring payment, enforcing termination, etc.
	Household services	Trans-actional	Administration of work/repairs in the house or on appliances/cars carried out by tradesmen, fitters, workshops, etc., by researching information, making comparisons, contracting, arranging appointments, etc.
		Recurring	Administration of recurring (household) services or employment of helpers (babysitters, cleaners, domestic help, tax consultants, private secretaries, etc.) by researching, contracting, arranging appointments, concluding an employment contract, if necessary, etc.
Public authorities	Governmental affairs		Administration and handling of authority procedures or official matters (registration/registration, identity card, passport, residence permit, driver’s license, etc.) by filling out forms, making and keeping appointments, ensuring that forms are up to date or expired, etc.
	Tax affairs		Administration and handling of tax matters and interaction with the tax office (for income tax, real estate transfer tax, flat rate withholding tax, etc.) through information research, preparation of declarations, submission of documents, etc.
Health and insurance	Insurance management		Administration of the settlement of insurance claims for property insurance (liability, household contents, motor vehicle, cell phone, etc.), including all activities of filing or asserting claims.
	Health management		Administration in the handling of a claim concerning health care, illness, and nursing care (this may include arranging appointments, applying for benefits, submitting receipts, checking payments, etc.), not the visit to the doctor itself.
Supportive activities	Household accounting		Planning/controlling/analyzing everyday expenses and account movements, keeping household books, carrying out banking transactions, etc.
	Private asset management		Administration of long-term investment decisions, private pension savings, and asset management (real estate, shares, funds, etc.) through information research, comparisons, support, maintenance, etc.
	Document management		Management of documents of all kinds, such as official documents (ID cards, passports, tax assessments, etc.), private business documents (contracts, invoices, receipts, etc.), as well as other documents (certificates, wills, etc.) by filing/archiving, retrieving, etc.
	Problem management		Dealing with problems (with invoicing, services/quality, etc.) with companies, authorities, business partners, etc., including all activities for complaints, clarification, or correction of deficiencies

Note: Task categories are collected from various qualitative studies (Daminger 2019; Emens 2015; Mederer 1993).

).

Goods and services. In modern consumer societies (Sassatelli 2007), consumers satisfy their wishes and needs through the procurement of goods and services. In addition to the price of the goods, conducting transactions on the market causes additional, often hidden costs (Williamson 1979). A specific transaction cost represents the consumers’ administrative work involved in planning purchases, managing contracts, paying invoices, or dealing with problems in the provision of services. With the rise of double-income households, hiring household help has become a common practice to reduce housework time (Craig et al. 2016). Still, this domestic outsourcing also comes with an administrative overhead as appointments must be planned, employment contracts managed, etc. (Daminger 2019; Emens 2015; Winkler and Ireland 2009).

Authorities. Another source of administrative housework is excessive government bureaucracy. By law and regulations, private individuals must interact with public authorities to obtain identification cards, report address changes, apply for driver’s licenses, collect records, and file annual tax returns, etc. (Emens 2015). The United States Government (2015), for instance, estimated that the paperwork burden in the US that has been caused by administrative issues amounted to 9.43 billion hours in 2014.

Health and insurance. In modern societies, a freely functioning insurance market has been established, enabling individuals to procure insurance coverage against a variety of life risks (Pearson 1997). Yet, insurance contracting leads to administrative burdens in two respects: firstly, consumers have to assess future risks, find trustworthy providers, and conclude contracts that are often complex and opaque (Tennyson 2011). Secondly, in the exceptional case of an incident or loss, consumers have to document damages and apply for reimbursements, often resulting in disputes among the parties that have to be settled (Emens 2021; Tennyson 2011). Health insurance is a special case in this regard (Brown and Finkelstein 2008). Concerning administrative work, health incidents trigger a series of administrative procedures, including organizing doctor’s appointments and notifying employers, etc. (Mederer 1993). Especially for chronically ill persons, this can result in significant time expenditures (Emens 2021).

Supportive activities. Administrative work also includes a series of supportive household management activities to plan, organize, and monitor the household administration as a whole (Arienzo 2022). An example of such secondary activity is financial management at home, where we can distinguish between household accounting (Daminger 2019; Emens 2015; Mederer 1993; Molina 2011; Northcott and Doolin 2000; Walker and Llewellyn 2000) and private asset management as part of financial provision (Campbell 2006). Corresponding administrative work includes planning financial investments, searching for reliable information, and seeking advice from financial experts, etc. (Campbell 2006). In addition, domestic practices of doing paperwork and document management (Emens 2015; Walker 2008) address the scriptural and documentation obligations of bureaucratic processes.

This brief overview illustrates the range of bureaucratic processes of companies and public authorities that households are confronted with. This applies to households in general, but it depends on their specific structure, skills, and needs as to how they cope with the bureaucratization of daily life and its associated temporal and mental burdens.

3. Methodological Considerations

3.1. Measuring the Temporal Workload of Domestic Labor

In the literature, it is most common to quantify workload by measuring the time that people need to fulfill the task on average. Still, quantifying the extent and impact of administrative housework is methodologically challenging and various methods exist in the literature. They can be distinguished at the following levels: the timing of the survey (retrospective questionnaires or in situ time-budget studies), the used timescale (duration oriented and/or frequency oriented), and the used activity classification scheme (tailor-made categories or adapting categories of used secondary data).

Regarding timing, two main approaches can be distinguished. Firstly, the retrospective approach, which involves inquiring about the estimated amount of time spent on specific activities in the past. This approach is most common in the literature; however, it has the drawback that participants may not accurately remember the exact time spent when the activity is too far in the past. Secondly, the in situ approach aims to collect the data in near real-time during the task execution. Examples of this approach are ‘time diary’ and ‘point-in-time studies’, where participants were asked to report the activities undertaken during a specific day or time interval (Birch et al. 2009; BLS 2022; Hurst 2015). Point-in-time studies, however, are labor-intensive to implement and are therefore only used in large-scale national or cross-national time-budget surveys conducted by public authorities. Examples of such surveys are the Australian Time Use Survey, the Multinational Time Use Study (MTUS), the Harmonized European Time Use Survey (HETUS), or the most popular American Time Use Survey (ATUS) (Anxo et al. 2011; Craig and Powell 2018; Krantz-Kent 2009; Moreno-Colom 2017; Möser 2010; Winkler and Ireland 2009).

Regarding the timescale used in the survey, we can distinguish between the duration and frequency of activities. The duration-oriented scale asks participants how long an activity lasted. In retrospective surveys, however, the duration of activities is often recalled only vaguely. This is especially true for routine activities, which are systematically forgotten due to recall problems (Te Braak et al. 2023). Another challenge is the fact that household tasks are often performed in parallel with other activities (Emens 2015; Winkler and Ireland 2009). In addition, there are more general challenges in measuring time budgets, as some tasks might be carried out over several days, which makes them difficult to estimate for consumers filling out a one-time survey (Hamermesh et al. 2005).

All of this can lead to biases when the survey records only primary activities with a specific amount of time (Hamermesh et al. 2005). Therefore, to obtain a more robust measure, household activities should not only be measured by their duration but also by their frequency (Hurst 2015). Thus, frequency-oriented scales try to measure the activities by asking how many times an activity has been performed in, for example, a past period (Hurst 2015; Sonnenberg et al. 2012). In this way, an exemplary described activity can be reflected in terms of how often it was performed, for instance, in the last month.

Regarding the activity classification scheme, we can distinguish between the approaches of tailor-made and secondary data categories. This distinction arises because there is no standardized classification of household activities. Instead, the classification schemes used in surveys depend on the specific research question (Bryant et al. 2004; Winkler and Ireland 2009).

The approach of using existing (secondary) data also relies on existing data categories, such as from the American Time Use Survey (ATUS) or the Multinational Time Use Study (MTUS). However, in order to align the data with the specific research objectives and make it interpretable, researchers usually reclassify the dataset in the case of secondary use by summarizing categories (Winkler and Ireland 2009). By doing so, researchers can leverage extensive datasets that have already been collected. However, the categories in secondary data cannot always be adapted, and important details may be lost when categories are combined. In such a case, conducting a survey with tailor-made categories becomes necessary. Since conducting time-budget studies is time-consuming (Sonnenberg et al. 2012) and involves substantially higher costs (Bryant et al. 2004), the approach of tailor-made categories is mainly used in retrospective surveys, which are easier to implement.

Because of various methods measuring the temporal workload in the literature, absolute numbers must also be contextualized to interpret them correctly. Moreover, relative differences in the performance of household work will be more robust than absolute numbers. For instance, while the absolute temporal workload differs, numerous studies consistently reveal a relative disparity between genders (DeVault 1991; Hochschild 1989; Mederer 1993; Twiggs et al. 1999).

3.2. Measuring Satisfaction and Mental Workload

“With rare exceptions, time-budget studies have not included measures of the satisfaction people derive from their activities. Similarly, questions about time-use and about the subjective experience of specific situations are rarely included in surveys”.

(Kahneman et al. 2004)

Another limitation of time-budget surveys is that numbers do not capture the qualitative dimension of work, such as giving meaning to activities, work satisfaction, and the physiological and cognitive cost of household labor (Habib et al. 2010; Moreno-Colom 2017). Hence, time-budget surveys should be complemented by workload measures (Dean et al. 2022), acknowledging that optimizing work performance is not the only objective, and also also considering mental workload, satisfaction, and well-being (Pandve 2017).

The mental workload also depends on the nature of the work. In general, all kinds of housework involve physical, affective, and mental elements—but to varying degrees (Dean et al. 2022; Hochschild 1989). For instance, cleaning is more physically demanding, while care work is more emotionally demanding and affective (Lee and Waite 2005; Revenson et al. 2016). In contrast, in the case of cognitive labor, such as administrative work, organization, thinking, and planning are at the forefront (Daminger 2019; Mederer 1993; Voss and Rieder 2005). This nature of labor further includes decision-making authority, scheduling skills, and prioritization of tasks and activities (Offer 2014). Regarding this, Marut and Hedge (1999) found that some domestic tasks, such as scrubbing, are perceived as being more tiring than other domestic tasks, such as preparing meals. Dean et al. (2022) also note that cognitive labor comes along with a high mental workload, which is perceived as complex and mentally stressful (Daminger 2019). Moreover, unlike the completion of physical tasks, the intangible nature of cognitive work often results in a lesser sense of satisfaction (Daminger 2019). However, there are also influences from the life situation of people: Kaye et al. (2014) show that, for low-income earners, dealing with invoices and personal finances can also be emotionally stressful. The workload perception further seems to be gender specific. For instance, Daminger (2019) notes that women are more likely to report stress, anxiety, and feelings of time constraints in doing household labor. When it comes to parenting, the different workloads beyond actual time is also related to a tendency of fathers to be more engaged in “fun” activities (Craig 2006).

As stressed by work economics, labor does not only cause stress and alienation but can also be a source of self-expression, satisfaction, and well-being (Sayers 2011; Ulich 2020). This is also the case for some household activities, as the myriad of “food-porn” (Koh 2017) and do-it-yourself posts on social media demonstrate (Collier and Wayment 2018). Regarding bureaucratization, Emens (2015), however, notes that administration chores are typically associated with negative connotations as undesirable, annoying, and tiresome tasks. However, we are not aware of any study that has attempted to empirically measure this assumption. In a similar vein, Dean et al. (2022) note that there are a lack of appropriate instruments to measure the mental workload of cognitive housework.

In organizational psychology and human factor research (Koppes 2014), workload assessment has a long tradition with the goal of gaining a profound understanding of the workload and stress experienced by employees. In the Anglo-American context, the NASA Task Load Index (NASA-TLX) (Hart 2006) is a well-established tool used to measure the perceived workload of individuals engaged in various tasks. Similarly, the Job Satisfaction Questionnaire (JSQ) (Smith 1969) is widely employed to assess employees’ satisfaction with their jobs. In addition, there are more holistic measurement methods such as KFZA (Prümper et al. 1995) or KAFA (Haarhaus 2016) to evaluate humane working conditions in terms of goal setting, self-monitoring, feedback mechanisms, and the adaptation of strategies to achieve desired outcomes. While these instruments were originally developed concerning organizational context, various researchers have adopted these instruments to the domestic context, to study the workplace ergonomics of household chores (Stübler 1986), the mental workload of physical household activities (Dunckel 1999; Resch 1999), and the stress and physical strain associated with these activities (Albert and Härtig 2014). To the best of our knowledge, there is currently no application of such methods for measuring the mental workload and work satisfaction in administrative household activities.

4. Methodology

To answer our research questions, we conducted an online panel survey in Germany in which we asked the participants about the various administrative housework activities, how much time they spend on such activities, and how they perceive the work.

4.1. Measures and Procedure

We operationalize our research questions through a systematic process. Firstly, we adopt the classification scheme outlined in Table 1. For each category, we have created an introductory text that explains the category and provides examples (cf. Appendix A) for the category description used.

Secondly, we operationalize the temporal workload by taking recommendations from the literature (Bryant et al. 2004; Winkler and Ireland 2009) into account, asking questions about duration as well as frequency to make the results more robust (cf. Appendix B). To reduce the recall bias in surveys (Te Braak et al. 2023), we did not ask about the task duration in general but only asked about the duration of the last task that was performed. Thirdly, we operationalize the issues of work quality by adopting four items from the KFZA short-scale questionnaire (Prümper et al. 1995) (cf. Appendix B) as well as seven items from the KAFA short-scale questionnaire (Haarhaus 2016) (cf. Appendix B). Both questionnaires are established measures in human factor research to measure workload and work satisfaction. As they never apply to administrative household labor, we analyzed their validity by conducting an explorative factor analysis (EFA) (Malhotra et al. 2017). To confirm the hypothesis that administrative tasks are primarily cognitive, we added one question in our survey on the nature of the work (cf. Appendix B).

To avoid statistical bias, each participant was asked to answer the questionnaire for two, randomly selected household chore categories. This random assignment ensured that the task type did not correlate with socio-demographic factors, preventing any confounding effects that might arise if differences in socio-demographic factors were influenced by the task type. By controlling for task type in this manner, we aim to isolate the true impact of socio-demographic variables on the observed outcomes, ensuring that our analysis accurately reflects the relationships between these factors and the various household administrative tasks.

If a participant indicated that they had never performed a particular chore in the past, the corresponding set of questions was omitted. By omitting these questions, the responses became more reliable and accurate, as participants were not forced to provide information about household chores they had never performed.

The survey was conducted as follows: First, there was a general introduction to the background of the study and administrative housework. Then there were two rounds, in each of which one category was selected at random. The category was introduced at the beginning of each round with a picture and descriptive text. Then, participants were asked to answer questions about the temporal workload. Next, participants were asked to rate the work quality of the respective category. Finally, participants were asked demographic questions (gender, age, household income, and level of education).

The survey was pretested twice. The first version was tested with 10 persons. We asked them to think aloud while filling out the survey to determine if the questions and descriptions were understood correctly, or if they were too complex. The revised version was completed online by 60 people as a second pretest. The results show that some questions were too complex so we either rephrased or dropped them.

4.2. Sample and Data Cleaning

The final survey was conducted between October and November 2023, utilizing a paid online panel. The online panel was provided by the market research institute Question Pro GmbH (Berlin, Germany), which was also tasked with recruiting a sample that should correspond to the German population in terms of gender and age. For this, Question Pro GmbH was compensated with a total EUR 2700 for the 617 participants (EUR 4.5 per participant; 17 participants were free of charge for us). The participants granted their informed consent at the beginning of the study and thereby approved the use of the anonymized data for the scientific study.

Table 2. Demographics of the sample.

Characteristic	Value	N(p)articpants	Percentage	Mean (SD)	Min	Max
Gender	Female	307	49.8%
	Male	307	49.8%
	Non-binary	3	0.5%
Age				45 (17)	18	85
Income	Not known	17	2.7%
	<EUR 1.2 k	87	14.1%
	EUR 1.2 k–2.5 k	189	30.7%
	EUR 2.5 k–5 k	250	40.6%
	>EUR 5 k	74	12.0%
Education	School or lower	101	16.4%
	Vocational education	361	58.5%
	University or higher vocation education (master)	155	25.1%

shows the demographics of the sample. The age of the participants ranged from 18 to 85, with a mean age of 46 (SD = 17.0). Regarding gender distribution, 49.8% identified as female, 49.8% as male, and 0.5% as non-binary. The median of the education level reported was completion of vocational education, and the median of the household income reported was between EUR 1200 and 2500 net (cf. Table 2).

After the data cleaning process, which entailed the removal of incomplete questionnaires, we had a total of N_{p(articipants)} = 617 entirely completed surveys. Every participant was given questions on two randomly selected task categories, amounting for 2 × 617 = 1234 question blocks in total. In 102 (8.3%) of the cases, participants reported they had never engaged in this type of housework activity in the past. In these cases, we did not require the participant to complete the question block but instead treated these blocks as missing data and excluded them as a standard data-cleaning technique. Due to a technical problem, one block of answers was also damaged, so we excluded it from the analysis. This resulted in a total of N_c(ases) = 1131 valid responses to the different household chores.

4.3. Limitations

We used an online panel for our study, as this is a recognized and widely used method in the literature. However, like all online panel studies, our study is subject to several limitations.

Research shows that participants in such panels tend to be younger and more educated, which can influence the generalizability of the findings (Buhrmester et al. 2011). As Table 2 shows, this is not the case with our sample.

Another concern can be that the exact recruitment process and compensation of participants are proprietary secrets of the online panel providers. This lack of transparency can raise concerns about self-selection effects and potential biases in participant recruitment and engagement (Goodman et al. 2013). Still, previous research shows that online panel studies often yield results similar to those from more traditional samples, especially concerning psychological and social measures (Buhrmester et al. 2011).

The lack of control about when and where the questionnaire will be filled out, and due to incentives, there is also the risk that participants provide hurried or inattentive answers. Besides the checks implemented by the panel provider to mitigate this risk, we additionally checked the meaningfulness of responses to open-ended questions.

Another limitation relates to our retrospective approach, where there is the risk that activity duration might not be accurately recalled (see Section 3). To reduce this risk, we asked to estimate the average task duration (which is mental), but of the last occurrence only (which is easier to recall). We also asked about the frequency of activities, which is generally more reliable. Additionally, our large sample size helps to balance out individual inconsistencies.

4.4. Data Analysis

Before the data analysis, the survey data underwent a screening process to identify outliers and improper and incomplete data. Subsequently, to assess the data and gain an overview, descriptive statistical methods were employed, including the computation of frequencies, means, and standard deviation (SD). For non-metric scales, we computed the median and interquartile range (IQR) as more robust metrics (Malhotra et al. 2017). In addition to the descriptive statistics, inferential statistics were used to draw conclusions about the entire sample (Eid et al. 2015). Analyzing the differences among various socio-demographic groups, we applied analysis of variance (ANOVA) for metric scales, and a Kruskal–Wallis (H) test for ordinal scales (Malhotra et al. 2017). For the adapted items from KFZA and KAFA, the EFA was part of the sociometric scale validation (Moosbrugger and Kelava 2011) using R (version 4.3.0, 21 April 2023) and the psych package (version 2.3.9).

5. Findings

5.1. Temporal Workload

We quantify the temporal workload of various administrative work activities using two measures: the frequency of task execution and the duration of the most recent task performed (cf.

Table 3. Temporal workload of the administrative household activities.

Category	Nc(ases)		Frequency of the Chores		Duration of Last Case		Freq. × Dur.
	All	Never	Median	Q1–Q3	Median	Q1–Q3	Mean
Commodity products (trans.)	116	1	weekly	m.t. a week—weekly	30 min	15 min–1 h	~90 min p.M.
Household accounting	114	6	weekly	m.t. a week—m.t. a month	30 min	15 min–1 h	~90 min p.M.
Health management	107	16	m.t. a month	weekly—m.t. a year	30 min	15 min–1 h	~45 min p.M.
Commodity services (recur.)	95	4	monthly	m.t. a week—annually	1 h	15 min–1 h	~45 min p.M.
Household services (trans.)	104	11	monthly	weekly—m.t. a year	1 h	15 min–3 h	~45 min p.M.
Private asset management.	97	14	monthly	m.t. a month—m.t. a year	1 h	15 min–1 h	~45 min p.M.
Document management	109	5	monthly	weekly—m.t. a year	30 min	15 min–1 h	~25 min p.M.
Problem management	95	3	monthly	weekly—m.t. a year	30 min	15 min–1 h	~25 min p.M.
Household services (recur.)	91	19	m.t. a month	m.t. a week—m.t. a year	1 h	30 min–3 h	~10 min p.M.
Governmental affairs	106	6	m.t. a year	m.t. a month—annually	1 h	15 min–1 h	~10 min p.M.
Tax affairs	103	8	annually	m.t. a month—annually	3 h	1 h–3 h	~10 min p.M.
Insurance management	96	9	annually	m.t. a month—l.t. annually	1 h	15 min–3 h	~5 min p.M.
Total	1233	102					~7.2 h p.M.

Note: Never = an activity was never carried out in the past; Q1 = first quantile; Q3 = third quantile; m.t. = multiple times; l.t. = less than; p.M. = per month; sorted in descending order of frequency.

). Using both metrics enhances the robustness of the results; as in surveys, retrospective reports of task duration tend to be imprecise (Bryant et al. 2004; Winkler and Ireland 2009). For time-related data, we also limit the use of the median as a robust statistical measure of central tendency.

As mentioned, in 102 (8.3%) of all cases, participants answered that they had never performed the activity in the past. This was most prominent in the category of recurring household services (such as domestic help, babysitters, etc.) with N_c = 19 (20.9%), in private asset management with N_c = 14 (14.4%), and in health management with N_c = 16 (15.0%).

Across different categories, administrative household labor displays significant variations. For instance, participants engage in procurement planning (Commodity products transactional) every week, while they only address tax returns once a year on average. In contrast, the median duration for the first category was approximately 30 min, whereas for the second category the duration was notably longer, averaging approximately 3 h.

To ascertain the monthly overall effort involved in administrative household labor, we calculated the average monthly total effort for each category by multiplying frequency and duration and then aggregating the totals (mean of the intervals). This calculation indicates that participants spend an average of approximately 7.2 h per month on administrative household labor. Even if this is only a rough estimate due to survey imprecision, it is in the same order of magnitude as other time-budget surveys, such as ATUS (U.S. Department of Labor 2023).

In addition to the absolute numbers, the relative differences between the categories are quite informative. As can be seen in Figure 1, three to four areas can be identified: The focal point is the middle range, where household labor occurs monthly and typically requires about one hour of effort. Representing this category are tasks related to the management of household services and utilities such as electricity, water, and gas. This area also includes administrative tasks and asset management, even if they occur less frequently. Further, problem management, health management, and document management fall into this area, whereby the completion of the corresponding tasks is shorter. Two other areas also stand out. Firstly, the frequent but brief tasks, such as planning purchases and monitoring income and expenditure. Secondly, the infrequent but time-consuming tasks represented by making tax returns annually. A fourth area is given by insurance management as it is distinguished by the fact that it has a similar frequency as tax returns but is less time-consuming on average.

Table 3 further shows another important finding: The interquartile range (Q1–Q3) shows a remarkable variance between the respondents. The wide spread of the range indicates that there are considerable differences, not only among the categories but also within the categories in terms of the temporal workload of individuals. In other words, even though they live in an equally bureaucratized environment, they have developed individual strategies for structuring the work involved in terms of time.

5.2. Nature of Work

Each task requires varying degrees of physical, emotional, and cognitive work (Dean et al. 2022; Hochschild 1989). Administrative work is often described as being primarily cognitive (Emens 2015). This view is confirmed by our survey. On average across all categories, 64.0% of participants state that administrative tasks are primarily cognitive, 24.1% of participants describe it as primarily emotional work, and only 11.8% describe it as primarily physical (cf.

Table 4. Percentage of respondents classifying the identified work categories as having more of a cognitive, emotional, or physical nature.

	Nc	Cognitive	Emotional	Physical
Total	1131	64.0%	24.1%	11.8%
Commodity Services (recurring)	91	74.7%	16.5%	8.8%
Tax Affairs	95	74.7%	16.8%	8.4%
Insurance Management	87	69.0%	20.7%	10.3%
Document Management	104	65.4%	23.1%	11.5%
Governmental Affairs	101	63.4%	20.8%	15.8%
Health Management	91	62.6%	24.2%	13.2%
Household Accounting	108	61.1%	23.1%	15.7%
Household Services (recurring)	72	61.1%	23.6%	15.3%
Problem Management	92	60.9%	32.6%	6.5%
Household Services (transactional)	93	59.1%	23.7%	17.2%
Private Asset Management	83	59.0%	31.3%	9.6%
Commodity Products (transactional)	114	57.4%	33.0%	9.6%

Note: N_c: number of cases.

). This shows that administrative chores are perceived primarily as cognitive, but also have an emotional as well as a physical component.

However, there are large fluctuations between the individual categories. The top three cognitive activities are managing recurring commodity services (74.7%), tax affairs (74.7%), and insurance management (69.0%). This could be attributed to the fact that these activities deal with complex contractual clauses and administrative regulations. In comparison, the planning and organization of procuring commodity products (transactional) is far less complex, which explains why only 57.4% stated that this is primarily a cognitive task, but also as emotional (33.0%).

At first glance, the low rating of private asset management was surprising. Only 59.0% describe this type of work as primarily cognitive, while at 31.3%, a fairly large proportion of participants, described the situation as primarily emotional. Still, this is in line with Kaye et al.’s (2014) observation that dealing with one’s own financial situation is an emotional issue. However, health management has the highest share, with 24.2% classifying it as primarily emotional work. This finding is consistent with the fact that health and care work in general has a high need for empathy and emotional involvement (Craig 2006; Emens 2021; Revenson et al. 2016).

As mentioned, most participants do not regard administrative activities as physical work. The highest physical component is household services management, with 17.2% of respondents. This relatively high proportion aligns with the existing literature, which discusses physical aspects such as overseeing craftsmen, handing over keys, etc.

Overall, our survey confirms the cognitive nature of administrative work. Furthermore, our findings underscore Dean et al.’s (2022) argument that the emotional component of mental work should not be overlooked. The detailed category system we used in the survey offers additional insights, shedding light on the proportion of the different nature of work among the categories and emphasizing the significant differences.

5.3. Quality of Work

We adopted seven items from the KAFA and four items from the KFZA. Both are established work economic measures, but so far they have only been psychometrically validated within the organizational context only. For this reason, we analyzed the validity of the scale. In the first step, the Kaiser–Meyer–Olkin test (MSA = 0.85) showed the adequacy of the dataset for factor analysis. The analysis of the eigenvalues of principal factors showed that two factors are above one, while the others are below. For that reason, we conducted an EFA with two factors, using varimax as the rotation method, minimum residual as the factor model estimation method, and performing a maximum of 1000 iterations (cf.

Table 5. Factor loadings of the explorative factor analysis (EFA).

Item	M1 (Workload)	M2 (Satisfaction)	Com.	Uni.	Compl.
I find such activities stressful.	0.774	−0.249	0.662	0.338	1.21
I am often under time pressure.	0.725	0.043	0.528	0.472	1.01
I have too much to do.	0.710	0.071	0.509	0.491	1.02
There are things that are too complicated for me.	0.663	−0.037	0.441	0.559	1.01
The activities are not to be wished on anyone.	0.612	−0.318	0.476	0.524	1.50
The activities are exciting.	0.137	0.812	0.677	0.323	1.06
I like the activities.	−0.070	0.790	0.629	0.371	1.02
I find the activities pleasant.	0.004	0.732	0.536	0.464	1.00
The activities challenge me.	0.466	0.240	0.274	0.726	1.50
The activities bore me.	0.454	−0.412	0.375	0.625	1.98
The activities are uninteresting.	0.407	−0.458	0.375	0.625	1.97
SS loadings	3.055	2.428
Proportion Var	0.278	0.221
Cumulative Var	0.278	0.498

Note: The used factor method: Minimizes residuals. Rotation varimax. High loadings are in bold.

).

The results show that these two factors collectively account for 49.8% of the total variance. Examining the factor loadings provides further insights into the nature and interpretation of the two main factors. The first factor (named “mental workload”) primarily comprises the mental workload measured by items such as working stress, time pressure, too much work, too complex, and not wished on anyone. The second factor (named “satisfaction”) refers to the work satisfaction measured by items such as being excited, liking it, and finding it pleasant. Other items such as interesting, boring, and challenging have neither a high loading to the first nor to the second factor.

In the subsequent analysis, we utilized newly created non-standardized factor scores instead of the raw item values. These non-standardized scores were derived to represent the underlying constructs more accurately and were calculated by averaging the non-standardized item responses associated with each factor. The non-standardization improves the interpretability, where factor scores with a value of 3.0 can be interpreted as neutral, while a value of 1.0 means low mental workload/satisfaction and a value of 5.0 means high mental workload/satisfaction.

The findings show that, across all categories, participants on average maintain a neutral stance towards administrative household tasks (cf.

Table 6. Perceived mental workload and satisfaction in the various work categories.

		Mental Workload		Satisfaction
Category	Nc	Mean	SD	Mean	SD
Total	1131	3.00	1.56	2.97	1.39
Tax affairs	95	3.62	1.61	2.66	1.50
Private asset management	83	3.27	1.30	3.34	1.36
Household services (recur.)	72	3.24	1.35	3.15	1.50
Problem management	92	3.15	1.42	2.66	1.34
Insurance management	87	3.13	1.58	3.00	1.40
Commodity services (recur.)	91	3.01	1.46	2.80	1.57
Household services (trans.)	93	3.00	1.36	3.17	1.23
Governmental affairs	101	2.95	1.70	2.65	1.48
Health management	91	2.85	1.45	2.81	1.33
Household accounting	108	2.73	1.83	3.29	1.24
Document management	104	2.72	1.63	2.65	1.37
Commodity products (trans.)	115	2.59	1.57	3.42	1.04

Note: 1 = low, 3 = neutral, 5 = high. High resp. low values are marked in bold. Sorted in descending order by satisfaction. N_p: number of participants. N_c: number of cases.

). This applies to both the perceived mental workload (mean = 3.00, SD = 1.56) as well as work satisfaction (mean = 2.97, SD = 1.39). The neutrality in their attitude towards mental workload suggests that they likely perceive it as neither excessively burdensome nor exceptionally light. Similarly, the neutral stance on job satisfaction suggests that participants neither find significant fulfillment nor dissatisfaction in their engagement with administrative household tasks. Carrying out bureaucratic tasks is a job that needs to be done, yet it is not one of the domestic work “fun” activities (R. Fluegge-Woolf 2014; Sullivan 1996).

As for temporal workload, there are significant differences in work satisfaction and the perceived mental workload across the categories. This becomes evident when plotting the ratings on a 2 × 2 matrix (cf. Figure 2). The resulting four quadrants could be described as follows.

Quadrant I (Easy work getting fun): Tasks in the quadrant are likely to align with participants’ preferences and contribute positively to their overall experience. A good example is the purchasing planning of commercial goods (cf. Figure 2). Shopping is not just a necessity, but also a means of self-gratification and identity formation (Belk 1988).

Quadrant II (Hard work but enjoyable): Tasks in this quadrant are challenging or demanding, but individuals find them enjoyable, perhaps due to a sense of accomplishment or personal fulfillment. An illustrative instance is private assessments, which are complex, demanding, and could be financially stressful. Still, people should be intrinsically motivated to care about their financial future, and people seem to derive gratification and personal growth by engaging with financial products.

Quadrant III (Simple but disliked work): Tasks in this quadrant are simple, but do not translate into a positive experience for participants. A notable case is document management (cf. Figure 2). This work is needed to maintain organization; it is also not inherently complex and can usually be done without time pressure. However, organizing documents does not provide a source of fulfillment, possibly due to lack of excitement and creativity.

Quadrant IV (Hard, unsatisfying work): Tasks in this quadrant are perceived as stressful, difficult, alienating, and demanding. They do not contribute to satisfaction at all. This is exemplified by activities such as filing tax returns (cf. Figure 2). The complexity and difficulty of this task, coupled with time pressure, the sense of vulnerability, and the perception of unfair treatment, lead to a sense of dissatisfaction.

Overall, our findings reveal that none of the quadrants in Figure 2 is unoccupied. This indicates that mental workload and satisfaction cannot be equated. Instead, a high mental workload may coexist with a sense of satisfaction, and vice versa. This demonstrates that making administrative household labor measurable requires both measures for the mental workload as well as for work satisfaction.

Figure 2 further shows that the rating of various administrative housework tasks tends to be neutral, both in terms of its burden and its satisfaction. This means that this kind of work does not stand out as particularly positive or negative in the memory but tends to remain inconspicuous.

5.4. Socio-Demographical Differences

5.4.1. Gender

A well-explored topic in the literature is the unequal distribution of household labor overall. The works of Daminger (2019); Emens (2015), Hochschild (1989), etc. suggest that cognitive labor is also distributed unevenly. In the administrative tasks we examined, we were also able to identify a tendency towards a higher mental workload for women.1 While the frequency is the same for both genders (median = monthly, Q1–Q3 range = weekly to multiple times annually), for women, the temporal workload is higher in terms of the task duration (female: median = 1 h, Q1–Q3 = 15 min–3 h; male: median = 30 min, Q1–Q3 = 15 min–1 h). As the scales used to measure frequency and duration are not metrically distributed, we opted for the non-parametric Kruskal–Wallis (H) test. In both frequency (H(df) = 0.768(1), p = 0.381) and duration (H(df) = 3.105(1), p = 0.078), gender differences were not statistically significant.

However, the gender differences are particularly pronounced in the rating of the quality of work. Men have a higher level of work satisfaction (mean = 3.08, SD = 1.33) than women (mean = 2.84, SD = 1.42). Conversely, men rate the mental workload lower (mean = 2.90, SD = 1.61) than women (mean = 3.09, SD = 1.50). Conducting an ANOVA shows that these gender-specific differences are significant for both mental workload (F = 4.696, p = 0.030, η² = 0.004) and work satisfaction (F = 8.039, p = 0.0005, η² = 0.007). Even though the effect size (η²) is rather small in both cases, they are still significant (cf.

Table 7. Differences between the sexes over all questions.

				Frequency		Duration			Satisfaction	Men. Workload
	Np	Nc	Never	Median	Q1–Q3	Median	Q1–Q3		Mean (SD)	Mean (SD)
Female	307	571	43	monthly	weekly—m.t. a year	1 h	15 min–3 h		2.84 (1.42)	3.09 (1.50)
Male	307	554	59	monthly	weekly—m.t. a year	30 min	15 min–1 h		3.08 (1.33)	2.90 (1.61)
Non-binary	3	6	0	weekly	m.t. a week—annually	1 h	30 min–3 h		4.60 (1.30)	4.66 (1.66)
H-Test (df) 1				0.768 (1)		3.105 (1)		F 1	8.039	4.696
Asymp. Sig. 1				0.381		0.078		P 1	0.005	0.030
								η2 1	0.007	0.004

Note: High resp. low values are marked in bold. N_p: number of participants. N_c: number of cases. Due to the low number of non-binary participants, we excluded them from the statistical analysis. ¹ Q1: first quantile; Q3: third quantile; m.t.: multiple times; l.t.: less than.

).

Regarding the existing body of research on gender inequalities in the household, we did not observe gender differences regarding the temporal workload in our study. However, the difference was significant for other aspects, such as the perception of mental workload and satisfaction with the tasks performed. This result indicates the importance of considering the subjective experience of work when assessing the unequal burden of administrative labor across genders.

5.4.2. Age

In the literature on domestic labor, age differences have been scarcely explored so far. As bureaucratic demands vary across different life stages, it is reasonable that administrative housework differs among age groups. This is confirmed by our findings, both in terms of work quantity as well as work quality (cf.

Table 8. Differences between the ages over all questions.

				Frequency		Duration			Satisfaction	Men. Workload
	Np	Nc	Never	Median	Q1–Q3	Median	Q1–Q3		Mean (SD)	Mean (SD)
Young adults (18–29)	145	277	12	weekly	m.t. a week—monthly	1 h	30 min–3 h		3.41 (1.25)	3.44 (1.33)
Adults (30–62)	346	625	67	monthly	weekly—m.t. a year	1 h	15 min–1 h		2.82 (1.37)	3.11 (1.50)
Elderly (>63)	126	229	23	m.t. a year	weekly—annually	30 min	15 min–1 h		2.84 (1.46)	2.19 (1.69)
H-Test (df)				33.322 (1)		5.252 (1)		F	19.543	46.654
Asymp. Sig.				<0.001		0.022		p	<0.001	<0.001
								η2	0.033	0.076

Note: High resp. low values are marked in bold. N_p: number of participants. N_c: number of cases. Q1: first quantile; Q3: third quantile; m.t.: multiple times; l.t.: less than.

).

Younger adults complete tasks here more frequently (median = weekly; Q1–Q3 = multiple times a week to monthly) than adults (median = monthly; Q1–Q3 = weekly to multiple times a year), as well as elderlies (median = multiple times annually; Q1–Q3 = weekly to annually). Regarding task duration, the differences are smaller. The average task duration for young adults (median = 1 h, Q1–Q3 = 30 min–3 h) and adults (median = 1 h, Q1–Q3 = 15 min–1 h) is the same. In contrast, the task duration of elderlies is lower (median = 30 min, Q1–Q3 = 15 min–1 h). The Kruskal–Wallis (H) test shows that for both frequency (H(df) = 33.322 (1), p = < 0.001) and duration (H(df) = 5.252 (1), p = 0.002), age differences were highly significant.

The analysis of work quality reveals a surprising outcome. Among these groups, young individuals perceive the highest workload (mean = 3.41, SD = 1.25), while the elderly perceive the lowest workload (mean = 2.19, SD = 1.69). The surprising issue was that, despite the high mental workload, young individuals exhibited the highest work satisfaction (mean = 3.41, SD = 1.25), whereas it is considerably lower for adults (mean = 2.82, SD = 1.37) and the elderly (mean = 2.84, SD = 1.46). The ANOVA indicates that age differences are highly significant in both satisfaction (F = 19.543, p < 0.001; η² = 0.033) and mental workload (F = 46.654, p < 0.001; η² = 0.076). In the case of satisfaction, however, η² is rather small, which means that the age factor has a small but still significant impact. As η² shows, the effect of age on mental workload is quite high.

An explanation for the surprising observation might be that younger individuals may be more resilient and adaptable, allowing them to cope better with high workloads. It could also indicate a shift in preferences and attitudes toward cognitive work. It is important to note that this interpretation cannot be directly derived from the available numbers. Further research, especially in the field of age-related household labor studies, would be necessary to gain deeper insights into the underlying mechanisms and factors that contribute to the observed differences in the perception of workload and satisfaction.

5.4.3. Income

Income is another factor to be considered as it generally relates to access to resources, stress resilience, or time management (Marmot et al. 2013; Thilagavathy and Geetha 2021). Regarding this, monthly household income is a common indicator used to assess financial well-being, even though the financial situation is also affected by various household circumstances, such as the number of family members, the employment status of household members, and their ages. In our study, we also adopt monthly household income as an indicator of financial well-being to evaluate its effect on administrative housework.

Our findings (cf.

Table 9. Differences between income groups over all questions.

				Frequency		Duration			Satisfaction	Men. Workload
	Np *	Nc *	Never	Median	Q1–Q3	Median	Q1–Q3		Mean (SD)	Mean (SD)
low (<EUR 1.2 k)	87	146	28	m.t. a month	m.t. a week—m.t. a year	30 min	15 min–1 h		3.01 (1.49)	3.17 (1.62)
medium (EUR 1.2 k–2.5 k)	189	345	33	monthly	weekly—annually	1 h	15 min–3 h		2.99 (1.37)	3.11 (1.46)
Medium-high (EUR 2.5 k–5 k)	250	470	30	m.t. a month	weekly—m.t. a year	1 h	15 min–3 h		2.92 (1.37)	2.80 (1.62)
high (>EUR 5 k)	74	141	7	m.t. a month	weekly—m.t. a year	1 h	30 min–3 h		3.14 (1.43)	3.26 (1.51)
H-Test (df)				8.709 (3)		7.237 (3)		F	0.926	5.181
Asymp. Sig.				0.033		0.065		p	0.427	0.001
								η2	0.003	0.014

Note: High resp. low values are marked in bold. N_p: number of participants. N_c: number of cases. Q1: first quantile; Q3: third quantile; m.t.: multiple times; l.t.: less than. * 33 answers are not given, because 17 participants did not know their household income.

) show some small differences among income groups. Individuals with a household income of EUR 1200–2500 per month are, on average, least frequently engaged in administrative household labor (median = monthly, Q1–Q3 = weekly—annually). In contrast, the shortest task duration on average is for individuals with lower incomes (median = 30 min, Q1–Q3 = 15 min–1 h). The Kruskal–Wallis (H) test, however, indicates that the differences are small and only significant for task frequency (H(df) = 8.709 (3), p = 0.033).

We further observe differences in work quality among income groups. Here again, we observe the surprising fact that a high mental workload does not necessarily correspond to low work satisfaction. Quite the contrary, for households with an income of more than EUR 5000 per month, the mental workload is the highest (mean = 3.26, SD = 1.51), yet they also have the highest work satisfaction (mean = 3.14, SD = 1.43). The ANOVA test, however, reveals that the effect is only significant in the case of mental workload (F = 5.181; p = 0.001; η² = 0.014).

5.4.4. Education

Administrative housework encompasses duties that demand cognitive skills such as arithmetic, reading, writing, and comprehension of complex texts and forms. Therefore, it is reasonable to assume that education impacts both work quantity and quality. Our results, however, show a mixed result.

Regarding frequency, participants with higher education engage in administrative work more frequently (median = m.t. a month; Q1–Q3: weekly to m.t. a year) compared to others. The Kruskal–Wallis (H) test (H(df) = 12.516, p = 0.002) indicates that this difference is significant. Regarding task duration, our findings did not show a significant difference between the groups.

Concerning work quality, we expected that a higher education would accompany a lower mental load. Still, we could not observe a significant effect. Surprisingly, such an effect is noticeable in work satisfaction. Participants with a higher level of education generally report higher satisfaction. The ANOVA test (F = 5.984; p = 0.003; η² = 0.010) reveals that, while this effect is small, it is still significant (cf.

Table 10. Differences in education over all questions.

				Frequency		Duration			Satisfaction	Men. Workload
	Np	Nc	Never	Median	Q1–Q3	Median	Q1–Q3		Mean (SD)	Mean (SD)
School or lower	101	179	23	monthly	weekly—m.t. a year	1 h	30 min–3 h		2.81 (1.48)	3.15 (1.45)
Vocational education	361	657	64	monthly	weekly—annually	1 h	15 min–1 h		2.91 (1.36)	2.92 (1.52)
University or higher vocational education	155	295	15	m.t. a month	weekly—m.t. a year	1 h	30 min–3 h		3.20 (1.37)	3.10 (1.70)
H-Test (df)				12.516 (2)		3.215 (2)		F	5.984	2.313
Asymp. Sig.				0.002		0.200		p	0.003	0.099
								η2	0.010	0.004

Note: Q1: High resp. low values are marked in bold. N_p: number of participants. N_c: number of cases. Q1: first quantile; Q3: third quantile; m.t.: multiple times; l.t.: less than.

).

One possible explanation is that, due to their level of education, they have a more positive attitude towards cognitive tasks and enjoy more mentally demanding work. Still, further studies are needed to understand the observed effect in more detail.

6. Discussion

Administrative work and bureaucracy not only affect organizations but also everyday private life (Emens 2019). It is increasingly recognized that the extensive hours spent by citizens on bureaucratic processes lead to economic damage (U.S. OMB 2022, 2023). However, the hidden costs on a personal level, such as mental workload, which involves feelings of stress, anxiety, and alienation, are often neglected. Moreover, authors such as Daminger (2019), Emens (2015), and Hochschild (1989) have drawn attention to the fact that housework is not only materially shaped but also consists of a broad spectrum of administrative and cognitive work, which is often unequally distributed between the sexes. The underlying reason for the unequal distribution, according to Dean et al. (2022), is that this work is largely invisible and difficult to measure. The authors therefore call for research to focus more on measuring cognitive household labor and the resulting qualitative workload, even if the operationalization of valid measurement results requires innovative approaches (Daminger 2019). Furthermore, Daminger (2019) calls on future research to review the previous qualitative research on a representative basis for an entire population (of adults), as well as to investigate demographic differences between population groups.

In this regard, our study makes a significant contribution by offering a nuanced perspective by, firstly, examining the wide range of activities involved (Emens 2015) and, secondly, considering not only the temporal but also the mental workload associated with these tasks (Daminger 2019; Dean et al. 2022). Firstly, the classification scheme enabled us to gain a deeper understanding of administrative work within the household and how it is influenced by the external environment. Concerning the second, we have shown how methods for measuring temporal workload can be combined with methods for measuring mental workload to gain a comprehensive understanding of the nature of bureaucratic household labor.

Applying the measures in an online survey, we are gaining novel insights into the nature and quality of administrative work. Even if our study only focuses on the German population and the results cannot be easily generalized to other countries or cultures, our study further indicates that there are socio-demographic factors that can influence differences in the quantity and quality of perceived administrative work.

Doing the fun stuff. Regarding work quantity and quality, our survey shows that there are major differences among the various administrative household labor tasks in terms of satisfaction and mental workload. These differences may manifest themselves in the nature of the job, with complex, highly formalized, and alienating activities, such as tax affairs, or more self-fulfilling activities, such as shopping planning. Moreover, our results show that a high mental workload must not go hand in hand with low work satisfaction. Instead, the work quality depends on the nature of the work.

Previous studies show that a distinction can be made between physical, emotional, and cognitive housework (Daminger 2019; Dean et al. 2022; Hochschild 1989). In this respect, our study confirms that administrative work is primarily cognitive but also involves emotional and physical components. However, our study also points to a second, relevant feature classifying household labor that has been underexposed in previous studies, namely the categorization of the work along the dimension of autonomy versus heteronomy. Heteronomous chores are highly constrained by external parties and bureaucratic demands. This includes chores such as problem management or tax returns, where people deal with legal issues. Moreover, they must rely on the cooperation of external authorities as being right does not mean getting justice. The system of the private household reacts (passively) to external influences and has little room for creativity or negotiation in this social process (DeShon and Gillespie 2005; Luhmann 1988). For most people, these chores therefore belong to the large area of “non-fun stuff” of household labor (cf. Figure 2, Quadrants III & IV, including “insurance management”) characterized by a low level of work satisfaction.

In contrast, there is household labor that is characterized by a high degree of autonomy, self-direction, and self-fulfillment, so that individuals are intrinsically motivated to engage in the tasks. In our study, this type of work is represented by the planning of purchases and asset management. Both planning purchases and managing assets require individuals to make independent decisions. Additionally, asset management offers the opportunity to gain competence experience (Burmester et al. 2010), while planning purchases offers the chance to cultivate the social identity through symbolic consumption (Belk 1988). This type of housework is therefore not only perceived as a burden but also as a source of well-being and satisfaction.

Regarding quality of work, however, we discovered a tendency towards neutrality in most cases. We explain this by the fact that most administrative chores are extrinsically motivated, but the necessity is accepted and not perceived as too much burden (DeShon and Gillespie 2005; Miebach 2006). The fact that this kind of cognitive labor remains neither positive nor negative in the memory could also explain why it often goes unnoticed, overseen, and neglected in research (Daminger 2019; Daniels 1987; Dean et al. 2022).

One size does not fit all. Our survey reveals significant variability, both in terms of types of activities and individual differences concerning temporal and mental workload. This demonstrates that there is no determinism in how people will be affected by the bureaucratization of societies (U.S. OMB 2022, 2023). Instead, households function as autopoietic systems (Luhmann 2008), which are structurally connected to their environment, but also demonstrate their internal autonomy through the different reactions to external bureaucratic demands.

Despite the observed heterogeneity, we were able to discover important socio-demographic effects. First of all, similar to previous studies on domestic work, we found gender-specific differences. Women tend to have a slightly higher perceived workload and significantly lower work satisfaction. However, the socio-demographic effects were far greater in terms of age. These results point to a hitherto largely unexplored relevance of age differences, which should be given greater consideration in future research on domestic work.

A closer look at income and education differences yielded another unexpected result. Due to higher cognitive skills, we would have expected that the mental workload would decrease in the group with a high income or a high level of education. However, we were unable to observe this. Instead, we make the surprising observation that work satisfaction increased in these groups.

This result underlines the demand that satisfaction, enjoyment, and fun are neglected but centrally important topics in domestic work research (Dean et al. 2022; Offer 2014). Only if we take the quantitative as well as the qualitative side seriously can we gain a comprehensive understanding of this kind of domestic work. This insight also has practical consequences. For instance, tutorials and courses on home economics mainly focus on the transfer of knowledge and best practices (Piorkowsky 2000; Walker 2008). In contrast, our results pinpoint the necessity of addressing the work attitude, showing how cognitive work can be enjoyable.

7. Conclusions

This study shows the quantitative (temporal) and qualitative (mental) workload that the bureaucratization of our world has led to for households (RQ1, RQ2). It motivates us to take a closer look at the nature of the work in addition to the time spent on it. Furthermore, our work also sets priorities for reducing the burden on households. It is not only the degree of heteronomy and the regulatory formalism of a workplace that can make a difference, but also demographic differences besides gender, such as in age groups or wealth (RQ3).