Application of a new municipal management model of home care service in Barcelona: Assessment of workers’ labour conditions,health,and well-being

Abstract

BACKGROUND:

In 2018, Barcelona City Council implemented a pilot phase of an organisational change in the municipal home care service (HCS) system. Inspired by the Buurtzorg model, the new model promotes the creation of self-managing teams operating in a restricted community setting.

OBJECTIVE:

To assess the pilot phase of the new model, focusing on employees’ working and employment conditions as well as on their health and well-being outcomes.

METHODS:

Mixed-methods impact evaluation. First, a quantitative evaluation was conducted between October 2018 and October 2020, using a pre-post study design with one pretest and two posttest measurements in an intervention and a comparison group. The intervention group was composed of the members of the work teams implemented in the pilot phase from October 2018 onwards (baseline n = 44). The comparison group consisted of workers from the same districts working under the usual HCS system (baseline n = 72). Next, a qualitative study was conducted in workers from the intervention group in winter 2021–2022 (n = 10).

RESULTS:

The pre-post study results yielded positive changes for the intervention group in social support and autonomy, as well as in many of the employment conditions. This group also experienced increases in psychological demands, painful positions, fatigue and psychological distress. Two main themes affecting workers’ well-being emerged from the interviews: factors inherent to the self-management model and external factors.

CONCLUSIONS:

Health and well-being outcomes seem to depend on the balance between job demands, resources, and ways of channelling conflicts within teams.

Keywords

Home care services self-organising teams employment conditions working conditions health evaluation study

1 Introduction

The European Union (EU), as many affluent societies, face major sociodemographic changes such as population ageing, falling fertility and declining household sizes [1]. For instance, between 1980 and 2022 the population aged 65 and over has risen from 13% to 21% in the EU; in Spain even more (from 10% to 21%) [2]. The increase in the number of people likely to be dependent on care in the near future and the reduction in the possibilities for informal caregiving raise the need for a reorganisation of formal community home care services (HCS) [3]. While family is a key provider of care, especially in Southern European countries [4], welfare state policies and benefits can contribute to the well-being of people in need of care and lessen the burden on family caregivers [5]. In Catalonia, a region of Spain, HCS refer to support services for individuals with limited autonomy due to advanced age, disability or dependence, organised by the local administration. HCS provide a comprehensive range of services aiming to assist individuals with daily living tasks such as meal preparation and cleaning, as well as providing personal care such as hygiene, dressing and undressing, and mobilisation. These services are carried out by carers with distinct professional profiles such as family workers and cleaning assistants [6].

Home care workers are at risk of negative health outcomes due to their working and employment conditions. For instance, ergonomic risks, such as mobilising users of care services, are associated with musculoskeletal problems in various locations, one of the most frequent being low back pain [7, 8]. Psychosocial risks, such as intense psychological demands, lack of social support, heavy emotional demands and conflicts with users have been linked to anxiety and depression [7 , 9–11] and musculoskeletal problems [7 , 13]. In the traditional HCS system in Barcelona (the capital of Catalonia), employees–almost all of whom are women–work in isolation, are assigned to households located in different parts of the city, and take their instructions from a coordinator. In this model, employment conditions are far from optimal: in 2017, 39% of the HCS workforce in Barcelona held temporary contracts and up to 71% held part-time contracts, while almost 30% were poorly paid and their contracts were both temporary and part-time [14]. Before the COVID-19 pandemic, this workforce already showed signs of organisational distress. Absenteeism exceeded 14% and staff turnover was above 20% [14]. Workers also felt that the quality of HCS was being eroded by a business perspective that tended to equate home care with menial cleaning work not requiring skills or expertise [15, 16].

With more than 24,000 users and 4,000 employees, HCS constitute the second largest public contract of the City Council in Barcelona [14, 16]. The City Council awards HCS contracts to a number of private sector companies and issues a tender every 4 years. For several years, the City Council has been reorganising HCS to improve the service, guaranteeing its sustainability and enhancing employees’ working conditions. As part of this process, the pilot phase of a new management model was launched in 2018. The model was inspired by the Buurtzorg model [17], a community-driven nursing model created in the Netherlands in 2006 that subsequently spread to various European settings [11 , 19]. The main feature of the Buurtzorg model is that it promotes worker autonomy through the formation of self-managing teams of up to 12 nurses who provide community care in neighbourhoods [17]. Thus, patients are guaranteed continuity of care, while professionals gain autonomy and greater responsibility for making both clinical and non-clinical decisions regarding their work, such as organising work schedules, rotas, and staff recruitment [17, 20].

In Barcelona, the new HCS model encourages the creation of self-directed work teams. At the time of the pilot phase, these teams were composed of 10 to 12 professionals consisting of family workers and cleaning assistants. The teams focus on attending a specific group of users, usually consisting of 40 to 60 people living in close proximity. This approach to service provision within a smaller, defined area was first known as social superblocks and is now included in the community care initiative called Vila Veïna, meaning “Neighbourhood Village” in Catalan [21]. The teams work in a self-organising format to provide services according to the instructions of the social services staff of the City Council, taking into account users’ preferences and workers’ needs. Some of the specific objectives of the new model include reducing employees’ travel time between users’ homes, increasing working hours, and fostering employees’ professional development [14, 16]. The new model specifies that the teams must have a place to meet and a workspace. The social services of Barcelona City Council are required to provide premises for the teams while HCS companies are required to provide portable computers, task management software, and internet connection. The new model also involves a modification of the role of the coordinator. In the ‘traditional’ model, their function was to manage and facilitate employees’ work (e.g. by planning their services, solving absences of workers and providing technical support), to liaise with users and social service administrations, and to evaluate the quality of the service. Under the new model, coordinators should support the teams and promote teamwork, while team members are responsible for their day-to-day work.

Working in self-managed home care teams following the Buurtzorg model and greater self-organisation has been associated with greater job satisfaction, autonomy, and team decision-making, as well as enhanced work-life balance for employees [11 , 23]. On the other hand, workers complain of higher administrative workloads, the need for information technology skills and limited autonomy in operational decision-making, such as budgeting [19]. Studies to date have paid less attention to examining workers’ health outcomes, although some of their findings suggest the need to do so systematically [18 , 25]. According to existing evidence, in this type of organisational model, workers’ psychological well-being is related to greater autonomy and social support among coworkers, as well as to workers having sufficient time to complete their tasks [24]. Nonetheless, workers’ mental health is impaired in contexts involving a higher workload [19], interruptions [24], or conflicts between team members [25], among other factors.

This study aims to evaluate the impact of the pilot phase of the new HCS management model initiated by Barcelona City Council. The evaluation goals were: to determine changes in employees’ labour conditions and health and well-being before and after the application the new organisational model, and to understand the reasons for the results from the perspective of those working under the new model. We hypothesised that change in the organisation of HCS would lead to an improvement in the employment and working conditions of workers, which in turn would have a positive impact on their health and well-being.

2 Materials and methods

2.1 Study design

We performed an assessment study using mixed-methods [26]. The study consisted of a pre-post quasi-experimental evaluation followed by a qualitative descriptive study.

2.1.1 Pre-post evaluation

2.1.1.1. Study population and sample The study population consisted of HCS workers of the three service providers in Barcelona at the beginning of the assessment. The sample was composed of an intervention group and a comparison group. Intervention groups encompassed all workers employed in the four self-organising work teams initiated after October 2018 (n = 44). Comparison groups were composed of HCS employees working within the same district of the city and who were not part of the organisational change during the study period (n = 72). Access to the study population was gained through the service providers.

2.1.1.2. Instrument, fieldwork, and study period We designed a questionnaire to gather information on sociodemographic characteristics and household composition, organisational unrest, working and employment conditions, physical disorders, self-perceived health status, and mental well-being. The questionnaire mostly relied on items from previously validated surveys such as the European Working Conditions Survey 2015, the Catalan Working Conditions Survey, and the questionnaires of the Occupational Health Service of the Public Health Agency of Barcelona. The survey was self-administered by the employees at a venue agreed with the companies. At the time of questionnaire completion, no company representatives were present in the room and Public Health Agency of Barcelona staff was available to answer questions or clarify statements. Fieldwork was conducted between October 2018 and October 2020. The intervention and comparison groups were surveyed in three rounds: the first took place a few days before the launch of the new self-managing teams (at different time points between October 2018 and January 2019), the second between 6 and 12 months after the switch to the new organisational model, and the third between 20 and 22 months after the switch. The three survey rounds were carried out in the intervention and comparison groups at the same time intervals. Fieldwork was disrupted by the COVID-19 pandemic in 2020 and by the decision not to renew the contracts of two of the companies in the new service tender. As a result, we lost one intervention and one comparison group in the third round.

2.1.1.3. Measures We selected the variables from the set of items in the questionnaire that were closest to the objectives of the intervention and the assessment of its impact on the workers:

Employment conditions:

Working hours: full-time or part-time.

Overtime in the last 3 months: more than 1 day per week, at least once a month, never, or very infrequently.

Travel time between users’ homes during the working day in the last week: 0–30 minutes, 31–60 minutes, or 61 minutes or more.

Working conditions – psychosocial risks:

Psychological job demands. A scale was calculated comprising the items: “My job requires working very fast”; “My job is hectic”; “My job requires working very intensely”; “My job requires long periods of intense concentration”; “I am often compelled to work longer than the stipulated time”; “Recently, I have more and more work to do”; “I am frequently interrupted before I can complete my tasks and have to resume them later”; “My work is slowed down by delays by other people or departments”.

Influence was measured with the items: “I can have a substantial influence on the decisions affecting my work group”, “In my work group, decisions are taken collectively”, “I have enough information on the changes that affect my work group”, and “My ideas about the tasks of the work group are taken into account”.

The scale on autonomy and role clarity included the items: “My job allows me to take a lot of decisions on my own”, “I have a lot of influence over what happens in my daily work”, “I have the opportunity to work in what I know how to do best”, “The objectives of my work are clear and planned”, “I know what my responsibilities are”, and “Clear explanations are given about what I have to do”.

For all questions included in the scales on psychological job demands, influence, and autonomy, a four-point scale was used ranging from 1 (strongly disagree) to 4 (strongly agree).

Coworker emotional support was evaluated using the items: “My colleagues are friendly”, “My colleagues are interested in me as a person”, “My colleagues like to work in a team”, “I have problems with my work colleagues”, “At work, I feel part of a team”.

Coworker operational support encompassed the items: “My colleagues are competent” and “My colleagues help me to get the job done”.

Response categories for all questions on support included in the scales consisted of a four-point scale from 1 (never) to 4 (very frequently).

Working conditions - ergonomic hazards:

Painful positions were assessed with the question “To what extent does your work involve painful or tiring positions?” (four response categories from never to very frequently). Responses were dichotomised.

Health and well-being:

Mental health, assessed with the General Health Questionnaire-12 [27]. Psychological distress was attributed to respondents scoring higher than 2.

Fatigue during the past 12 months (yes, no).

Sociodemographic characteristics:

Age, gender, country of origin, educational level, and professional group.

2.1.1.4. Quantitative analysis Data were analysed for the intervention and comparison groups. A descriptive univariate analysis was performed with frequency distribution of categorical variables and calculation of the mean and confidence interval for continuous variables. Psychosocial risk scales were constructed using the baseline responses after a factor analysis and verification of the internal consistency of all scales by means of Cronbach’s alpha coefficient. In this study, Cronbach’s α values were as follows: 0.75 for psychological job demands, 0.92 for influence, 0.66 for autonomy and role clarity, 0.69 for coworker operational support, and 0.86 for coworker emotional support.

To test for statistically significant differences in the changes produced within groups between the baseline measure and post-measurements 1 and 2, we used the Mc-Nemar test for dichotomous variables and the Stuart-Maxwell test for variables with more than two categories. Paired-sample t-tests were applied for continuous variables. Comparisons between the two groups were made using the chi-square or Fisher exact test for categorical variables and, in the case of continuous variables, the Student t-test for comparisons of means for independent samples. Statistical significance was set at p < 0.05. Statistical analyses were performed using SPSS version 20 and Stata version 15 software.

2.1.2 Qualitative study

2.1.2.1. Study population and sample In the qualitative study, the study population consisted of the workers in the new HCS model. The sample was drawn from participants who completed the third round of the survey and who, in the informed consent form for the baseline measurement, agreed to be recontacted for an interview at a later stage of the project. We selected the sample through stratified purposeful sampling [28, 29]. Participants were first stratified according to their self-managing work team. Maximum variation was then applied according to sex and origin. The final sample consisted of ten employees; one person refused to participate.

2.1.2.2. Instrument and fieldwork Between November 2021 and February 2022, the first author undertook semi-structured interviews using a topic guide addressing the following themes: content and organisation of work, assessment of organisational change, and health and well-being. Interviews were conducted in person or online, depending on the interviewees’ preferences and the stage of the COVID-19 pandemic. Interviews were recorded and took from 45 to 80 minutes.

2.1.2.3. Qualitative analysis. Interviews were transcribed verbatim and textual data were coded and categorised using Atlas.ti. Thematic analysis was carried out by the constant comparative method, generating categories from the thematic guide and the study topics of the quantitative assessment.

Rigour was ensured through data analysis and interpretation being conducted by multiple researchers coming from different academic disciplines (social sciences and medicine). All authors involved in the qualitative analysis are women, have extensive knowledge on work as a social determinant of health, and are committed to addressing work and employment- related social inequalities in health. The first author, with previous qualitative research experience on worker participation, had a leading role in the initial coding. The last author also participated in the preliminary analysis of the data and regularly discussed the data interpretation. As the first author’s views were likely to have more influence on the interpretation of the results, authors discussed potential biases in understanding workers’ discourses.

2.2 Ethical considerations

Ethics approval was obtained from the Ethics Committee on research involving medicines of Parc de Salut Mar in Spain (2021/10090). Throughout the research process, participants were guaranteed confidentiality and anonymity, the right to decline to participate or to leave the study, as well as data protection. Each phase of the assessment was preceded by a letter of informed consent. Participants gave written consent to complete the surveys and oral and written consent for the interviews. Anonymised results were fed back to the participants, as well as to representatives of the social services of the Barcelona City Council and of HCS providers in a feedback session that also served to capture workers’ views on the integrated results.

3 Results

3.1 Sample characteristics

The characteristics of the sample in the quantitative and qualitative studies are shown in Tables 1 and 2. In the pre-post study (Table 1), 116 workers participated in the first round of the survey, 80 in the second, and 54 in the third. In both the intervention and comparison groups, the sample was characterised by the inclusion of mostly family workers, women, workers with secondary education, and age between 41 and 55 years. There were no statistically significant differences between the two groups in socioeconomic or occupational variables. Sample losses throughout the pre-post study did not alter the composition of the sample except for country of origin. In the pre-measurement, more than half the workers in both groups were born outside Spain; in the third survey round, 43.5% of participants in the intervention group were foreign-born compared with 66.7% in the comparison group. However, the Pearson chi-square test of independence showed no statistically significant differences between the groups. The qualitative study sample was composed of workers with characteristics similar to those of the intervention group in the last survey round (Table 2).

Table 1
Baseline characteristics of the pre-post evaluation sample by group

Intervention group Comparison group p-value

(n = 44) (n = 72)

n (%) n (%)

Sex 0.312

Women 42 (95.5%) 65 (90.3%)

Country of origin* 0.095

Not Spain 23 (54.76%) 45 (61.18%)

Age 0.390

≤40 years 8 (18.2%) 14 (19.7%)

41–55 years 27 (61.4%) 35 (49.3%)

>56 years 9 (20.5%) 22 (31.0%)

Educational attainment* 0.561

Primary education 2 (5.0%) 4 (6.2%)

Secondary education 29 (74.4%) 50 (76.9%)

Higher education 9 (23.1%) 11 (16.9%)

Occupational group 0.063

Family worker 35 (79.5%) 65 (91.5%)

Cleaning assistant 9 (20.5%) 6 (8.5%)

	Intervention group	Comparison group	p-value
n (%)	n (%)
Sex			0.312
Women	42 (95.5%)	65 (90.3%)
Country of origin*			0.095
Not Spain	23 (54.76%)	45 (61.18%)
Age**			0.390
≤40 years	8 (18.2%)	14 (19.7%)
41–55 years	27 (61.4%)	35 (49.3%)
>56 years	9 (20.5%)	22 (31.0%)
Educational attainment***			0.561
Primary education	2 (5.0%)	4 (6.2%)
Secondary education	29 (74.4%)	50 (76.9%)
Higher education	9 (23.1%)	11 (16.9%)
Occupational group			0.063
Family worker	35 (79.5%)	65 (91.5%)
Cleaning assistant	9 (20.5%)	6 (8.5%)

^*8 missing values in the Pre measurement. ^**1 missing value in the Pre measurement. ^***11 missing values in the Pre measurement.

Table 2

Characteristics of the qualitative evaluation sample

	Intervention group
	(n = 10)
Work team
Work team 1	3
Work team 2	3
Work team 3	4
Sex
Female	9
Male	1
Country of origin
Spain	6
Other	4

Note: Although work team was a criterion for selecting and stratifying the sample, participants are not shown in this way in any section of the study to ensure their anonymity given the small sample size.

3.2 Employment conditions

3.2.1 Quantitative results

Pre-post evaluation revealed that full-time work increased and time spent commuting between users’ homes decreased. These changes were statistically significant between baseline and post-measurement 1 in the intervention group. In contrast, overtime increased in the intervention group and decreased in the comparison group. These changes were statistically significant between baseline and post-measurement 2 only for the comparison group (Table 3).

Table 3
Work-related features and health and well-being outcomes before and after the implementation of the new HCS organisational model

Group Survey round Type of analysis

Pre Post1 Post 2¥ Within groups Between groups

Intervention (n = 44) Intervention (n = 34) Intervention (n = 24) p-value pre-post 1 p-value pre-post 2 p-value pre p-value post 1 p-value post 2

Comparison (n = 72) Comparison (n = 46) Comparison (n = 30)

Employment conditions n (%) n (%) n (%)

Working hours (full-time) Intervention 17 (39.5%) 20 (58.8%) 15 (62.5%) 0.031 0.070 0.728 0.926 0.561

Comparison 30 (42.9%) 26 (57.8%) 21 (70.0%) 0.125 0.687

Overtime in the last 3 months

More than 1 day per week Intervention 18 (43.9%) 13 (41.9%) 9 (40.9%) 0.121 0.063 0.692 0.573 0.072

At least once a month 14 (34.1%) 8 (25.8%) 10 (45.5%)

Never or very infrequently 9 (22.0%) 10 (32.3%) 3 (13.6%)

More than 1 day per week Comparison 23 (37.1%) 12 (30.8%) 4 (16.0%) 0.220 0.029

At least once a month 21 (33.9%) 14 (35.9%) 11 (44.0%)

Never or very infrequently 18 (29.0%) 13 (33.3%) 10 (40.0%)

Travel time between users’ homes on working day

0–30 minutes Intervention 15 (34.1%) 24 (70.6%) 16 (66.7%) 0.001 0.123 0.101 0.132 1.000

31–60 minutes 18 (40.9%) 9 (26.5%) 6 (25.0%)

61 minutes or more 11 (25.0%) 1 (2.9%) 2 (8.3%)

0–30 minutes Comparison 35 (53.0%) 23 (51.1%) 18 (62.1%) 0.596 0.473

31–60 minutes 16 (24.2%) 16 (35.6%) 8 (27.6%)

61 minutes or more 15 (22.7%) 6 (13.3%) 3 (10.3%)

Ergonomic risk factors n (%) n (%) n (%)

Painful positions (frequently or Intervention 19 (46.3%) 15 (44.1%) 12 (57.1%) 1.000 1.000 0.193 0.001* 0.022*

very frequently) Comparison 23 (33.8%) 7 (16.3%) 7 (25.0%) 0.727 1.000

Psychosocial risk factors Mean (95% CI) Mean (95% CI) Mean (95% CI)

Psychological job demands Intervention 2.37 (2.25-2.49) 2.35 (2.23-2.46) 2.44 (2.26-2.63) 0.864 0.589 0.119 0.006* 0.030*

Comparison 2.22 (2.10-2.35) 2.08 (1.94-2.22) 2.21 (2.08-2.33) 0.529 0.918

Autonomy and role clarity Intervention 2.85 (2.70-2.99) 3.05 (2.93-3.17) 3.14 (2.99-3.29) 0.092 0.012 0.689 0.084 0.277

Comparison 2.89 (2.76-3.02) 2.87 (2.72-3.03) 3.00 (2.82-3.18) 0.278 0.148

Influence Intervention 2.77 (2.30-3.23) 3.14 (3.02-3.27) 3.14 (2.93-3.35) 0.745 0.317 0.557 0.002* 0.473

Comparison 2.60 (2.21-2.98) 2.55 (2.06-3.04) 3.29 (2.83-3.75) 0.335 0.553

Coworker emotional support Intervention 3.06 (2.74-3.37) 3.28 (3.12-3.44) 3.19 (2.99-3.39) 0.654 0.696 0.217 0.038* 0.836

Comparison 2.78 (2.47-3.10) 2.90 (2.49-3.31) 3.22 (2.90-3.55) 0.115 0.817

Coworker operational support Intervention 2.61 (2.18-3.04) 3.41 (3.21-3.61) 3.22 (3.02-3.42) 0.028 0.021 0.185 0.012* 0.264

Comparison 2.16 (1.68-2.64) 2.80 (2.20-3.39) 3.00 (2.58-3.41) 0.095 0.203

Health and well-being outcomes n (%) n (%) n (%)

General fatigue Intervention 22 (52.4%) 24 (75.0%) 18 (78.3%) 0.125 0.180 0.809 0.002* 0.029*

Comparison 33 (50.0%) 15 (37.5%) 13 (48.2%) 1.000 1.000

Psychological distress Intervention 15 (34.1%) 13 (38.2%) 13 (54.2%) 0.754 0.109 0.692 0.167 0.039*

Comparison 22 (30.6%) 11 (23.9%) 8 (26.7%) 0.454 0.453

	Group	Survey round	Type of analysis
Employment conditions		n (%)	n (%)	n (%)
Working hours (full-time)	Intervention	17 (39.5%)	20 (58.8%)	15 (62.5%)	0.031	0.070	0.728	0.926	0.561
	Comparison	30 (42.9%)	26 (57.8%)	21 (70.0%)	0.125	0.687
Overtime in the last 3 months
More than 1 day per week	Intervention	18 (43.9%)	13 (41.9%)	9 (40.9%)	0.121	0.063	0.692	0.573	0.072
At least once a month		14 (34.1%)	8 (25.8%)	10 (45.5%)
Never or very infrequently		9 (22.0%)	10 (32.3%)	3 (13.6%)
More than 1 day per week	Comparison	23 (37.1%)	12 (30.8%)	4 (16.0%)	0.220	0.029
At least once a month		21 (33.9%)	14 (35.9%)	11 (44.0%)
Never or very infrequently		18 (29.0%)	13 (33.3%)	10 (40.0%)
Travel time between users’ homes on working day
0–30 minutes	Intervention	15 (34.1%)	24 (70.6%)	16 (66.7%)	0.001	0.123	0.101	0.132	1.000
31–60 minutes		18 (40.9%)	9 (26.5%)	6 (25.0%)
61 minutes or more		11 (25.0%)	1 (2.9%)	2 (8.3%)
0–30 minutes	Comparison	35 (53.0%)	23 (51.1%)	18 (62.1%)	0.596	0.473
31–60 minutes		16 (24.2%)	16 (35.6%)	8 (27.6%)
61 minutes or more		15 (22.7%)	6 (13.3%)	3 (10.3%)
Ergonomic risk factors		n (%)	n (%)	n (%)
Painful positions (frequently or	Intervention	19 (46.3%)	15 (44.1%)	12 (57.1%)	1.000	1.000	0.193	0.001*	0.022*
very frequently)	Comparison	23 (33.8%)	7 (16.3%)	7 (25.0%)	0.727	1.000
Psychosocial risk factors		Mean (95% CI)	Mean (95% CI)	Mean (95% CI)
Psychological job demands	Intervention	2.37 (2.25-2.49)	2.35 (2.23-2.46)	2.44 (2.26-2.63)	0.864	0.589	0.119	0.006*	0.030*
	Comparison	2.22 (2.10-2.35)	2.08 (1.94-2.22)	2.21 (2.08-2.33)	0.529	0.918
Autonomy and role clarity	Intervention	2.85 (2.70-2.99)	3.05 (2.93-3.17)	3.14 (2.99-3.29)	0.092	0.012	0.689	0.084	0.277
	Comparison	2.89 (2.76-3.02)	2.87 (2.72-3.03)	3.00 (2.82-3.18)	0.278	0.148
Influence	Intervention	2.77 (2.30-3.23)	3.14 (3.02-3.27)	3.14 (2.93-3.35)	0.745	0.317	0.557	0.002*	0.473
	Comparison	2.60 (2.21-2.98)	2.55 (2.06-3.04)	3.29 (2.83-3.75)	0.335	0.553
Coworker emotional support	Intervention	3.06 (2.74-3.37)	3.28 (3.12-3.44)	3.19 (2.99-3.39)	0.654	0.696	0.217	0.038*	0.836
	Comparison	2.78 (2.47-3.10)	2.90 (2.49-3.31)	3.22 (2.90-3.55)	0.115	0.817
Coworker operational support	Intervention	2.61 (2.18-3.04)	3.41 (3.21-3.61)	3.22 (3.02-3.42)	0.028	0.021	0.185	0.012*	0.264
	Comparison	2.16 (1.68-2.64)	2.80 (2.20-3.39)	3.00 (2.58-3.41)	0.095	0.203
Health and well-being outcomes		n (%)	n (%)	n (%)
General fatigue	Intervention	22 (52.4%)	24 (75.0%)	18 (78.3%)	0.125	0.180	0.809	0.002*	0.029*
	Comparison	33 (50.0%)	15 (37.5%)	13 (48.2%)	1.000	1.000
Psychological distress	Intervention	15 (34.1%)	13 (38.2%)	13 (54.2%)	0.754	0.109	0.692	0.167	0.039*
	Comparison	22 (30.6%)	11 (23.9%)	8 (26.7%)	0.454	0.453

¥ The third round of the survey was affected by the loss of one work team included in the intervention group and its corresponding comparison group. NOTE: Within-group differences are highlighted in bold and between-group differences with an asterisk.

3.2.2 Qualitative results

The increase in working hours was explained in the qualitative results by the following reasons: an increase in contracted hours as a consequence of extending the working day of self-organising work teams (Table 4, quote a); an increase in contracted hours resulting from the loss of team members who were not replaced and after a period of overtime by some of the remaining members (Table 4, quote b); an increase in overtime due to team organisation tasks carried out by members outside their working hours (Table 4, quote c).

Table 4
Examples of changes in employment conditions

Category Examples

Increased working hours

a. Application of the clauses of the new organisational model increased working hours “I started with 20 [hours], now I’ve got 37. They offered to increase my hours and I accepted at the start of the new model.” (Interview_K)

b. Lack of personnel meant overtime and increase in contracted hours [in the work team with two fewer members after June 2020]: “... I was working 32 hours per week, but my contract was increased to 37 hours 2 months ago.” (Interview_N)

c. Organisational tasks meant overtime “...when you’re fully committed to doing this job [organising the team’s timetable], there's not enough time, really, and more than time, it’s being on the lookout 24 hours a day to see what’s going to happen. And on weekends too (...) it’s not like saying: “I’ll devote this week, on Thursday from 4 pm to 6 pm to do all the computer tasks and as they give me two hours, that’s it”. No, it’s all the time, things happen to you all the time...” (Interview_O)

Reduction of travel time within households “We used to have commutes of up to 20 minutes. And when I was working special weekend hours, it was up to 40 minutes.” (Interview_E)

Category	Examples
Increased working hours
a. Application of the clauses of the new organisational model increased working hours	“I started with 20 [hours], now I’ve got 37. They offered to increase my hours and I accepted at the start of the new model.” (Interview_K)
b. Lack of personnel meant overtime and increase in contracted hours	[in the work team with two fewer members after June 2020]: “... I was working 32 hours per week, but my contract was increased to 37 hours 2 months ago.” (Interview_N)
c. Organisational tasks meant overtime	“...when you’re fully committed to doing this job [organising the team’s timetable], there's not enough time, really, and more than time, it’s being on the lookout 24 hours a day to see what’s going to happen. And on weekends too (...) it’s not like saying: “I’ll devote this week, on Thursday from 4 pm to 6 pm to do all the computer tasks and as they give me two hours, that’s it”. No, it’s all the time, things happen to you all the time...” (Interview_O)
Reduction of travel time within households	“We used to have commutes of up to 20 minutes. And when I was working special weekend hours, it was up to 40 minutes.” (Interview_E)

3.3 Psychosocial working conditions

3.3.1 Quantitative results

After the change in organisational model, an improvement in psychosocial working conditions related to control and social support was observed, but also greater job demands (Table 3). In the intervention group, autonomy in work tasks and role clarity significantly increased from baseline to post-measurement 2. Throughout the intervention, coworker operational support grew in both groups but the results were statistically significant only for the intervention group in all rounds of the survey in the within-group analysis. Between-group analysis also revealed a statistically significant difference in post-measurement 1. Other changes consisted of workers having greater influence on service decisions and receiving more emotional support from colleagues, with a statistically significant difference between the comparison group and the intervention group in post-intervention measurement 1 (although the difference between groups disappeared in post-measurement 2). Psychological job demands followed a similar pattern in the two groups but were consistently higher in the intervention group. No statistically significant differences were observed between the two groups in the baseline survey but were found in post-measurements 1 and 2.

3.3.2 Qualitative results

The quantitative results regarding social support, control and job demands were reflected in workers’ discourse. With respect to social support, operational support was facilitated by open communication between team members and by members sharing the care of the same users. This aided worker rotations among users with complex needs, relieved workers who lacked rapport with particular users (Table 5, quote a), and allowed workers to help each other with tasks requiring strong physical efforts (Table 5, quote b), or when incidents arose (Table 5, quote c). Emotional support was facilitated by teamwork, as carers no longer worked in isolation. Perceived support from colleagues and bonding emerged in carers’ discourse and were associated with a source of well-being: “That gives you a feeling of well-being in the sense that you have someone to lean on” (Interview_D). However, respondents also mentioned that working in a team could also lead to conflicts and even harassment in some extreme cases (for further details, see the “Health and well-being” subheading of the Results section).

Table 5
Examples of changes in psychosocial working conditions

Category Examples

Improved coworker operational support

a. User rotation improved “[the user] is no longer “mine”, they belong to the team, they become the team’s, and the good thing is that when there’s a problem, we discuss it, and can be rotated among the team, which may not suit you for whatever reason, but maybe it does suit me. So, then, we can swap.” (Interview_I)

b. Better assistance to team members when strong physical effort is needed ... the teams, that’s what we are, if necessary or if we say: “look, we can’t move this man” or “[name of person], can you please come and help me because I can’t lift him?”, we went and helped ... ”. (Interview_F)

c. Improved occasional help when needed “... we have our group, we telephone each other, right? If anything happens to me, I know that they will respond immediately, they’ll help me, you know?” (Interview_S)

Productive and improductive outcomes from autonomy and influence

d. Management of the team’s day-to-day work d1) “... as we have self-management, we can vary the hours. In the traditional HCS, you had a fixed schedule.” (Interview_B)

d2) “... we couldn’t cover all the services that had come in, and they hired a person on a trial basis for 3 months and in the end they said “the decision is yours”. And among the whole group we decided that that person didn’t fit in our team and they have respected that...” (Interview_K)

e. Better knowledge of the user’s situation “Before, you never knew what you were going to find. Even though I had work restrictions I was sent to people who were a dead weight (...) Now, however, it's better controlled.” (Interview_E)

Category	Examples
Improved coworker operational support
a. User rotation improved	“[the user] is no longer “mine”, they belong to the team, they become the team’s, and the good thing is that when there’s a problem, we discuss it, and can be rotated among the team, which may not suit you for whatever reason, but maybe it does suit me. So, then, we can swap.” (Interview_I)
b. Better assistance to team members when strong physical effort is needed	... the teams, that’s what we are, if necessary or if we say: “look, we can’t move this man” or “[name of person], can you please come and help me because I can’t lift him?”, we went and helped ... ”. (Interview_F)
c. Improved occasional help when needed	“... we have our group, we telephone each other, right? If anything happens to me, I know that they will respond immediately, they’ll help me, you know?” (Interview_S)
Productive and improductive outcomes from autonomy and influence
d. Management of the team’s day-to-day work	d1) “... as we have self-management, we can vary the hours. In the traditional HCS, you had a fixed schedule.” (Interview_B)
	d2) “... we couldn’t cover all the services that had come in, and they hired a person on a trial basis for 3 months and in the end they said “the decision is yours”. And among the whole group we decided that that person didn’t fit in our team and they have respected that...” (Interview_K)
e. Better knowledge of the user’s situation	“Before, you never knew what you were going to find. Even though I had work restrictions I was sent to people who were a dead weight (...) Now, however, it's better controlled.” (Interview_E)

Autonomy and influence refer to decision-making by team members in their day-to-day tasks. In the new model, teams work in committees and decide on a wide range of issues, such as changing and organising schedules, covering short leaves of up to 3 days, managing new user entries or incidents, and approving new recruits to join the team (Table 5, quotes d1, d2). The interviewees reported that, instead of relying on sometimes outdated administrative assessments, they now had first-hand knowledge of users’ needs, allowing them to act accordingly (Table 5, quote e). All these changes were seen as positive by the workers, but, in line with the quantitative results on psychological demands, most participants stated that these enhancements had increased their workload and responsibility: “Right now I have two health cards of a user because when I finished working I went to the primary care centre to book an appointment for her, right? So, it’s more responsibility for us, right? But it’s more rewarding, at least for me ... ” (Interview_B).

3.4 Ergonomic working conditions

3.4.1 Quantitative results

Exposure to ergonomic risks was moderate to high in both groups but greater in the intervention group. The percentage of staff having to adopt painful or strenuous positions increased between post-measurements 1 and 2 with a statistically significant difference between the intervention group and the comparison group in both rounds (Table 3).

3.4.2 Qualitative results

The increase in painful positions may be at least partly a result of the reduced travel time between users’ homes. In the past, workers may have been able to rest during this time but the new model increased actual working hours: “... maybe we do work more now because previously, out of 37 hours a week, you spent seven travelling on the metro” (Interview_G).

3.5 Health and well-being

3.5.1 Quantitative results

During the study period, outcomes related to psychological distress and fatigue worsened in the intervention group. For both variables, no statistically significant differences were found within groups in the three survey rounds, but differences were statistically significant when the intervention group was compared with the comparison group (in the third round for psychological distress, and in the second and third rounds for fatigue) (Table 3).

3.5.2 Qualitative results

Some elements of the new HCS model that may result in physical and emotional fatigue are detected in the interviews. Physical fatigue could be the result of longer working hours, shorter travel time and higher exposure to ergonomic risks due to more effective work. Mental fatigue can be explained by greater responsibilities leading to increased work for team members (Table 6, quotes a1, a2) and to an inability to switch off from work, whether digitally (Table 6, quote b1) or mentally (Table 6, quote b2). Many interviewees mentioned the increase in work and inability to switch off as increasing their stress levels. Another factor that could lead to fatigue was the loss of team members who could not be quickly replaced (Table 6, quote c).

Table 6
Examples of factors that might affect workers’ fatigue

Category Examples

Elements of the new HCS model that could cause fatigue

a. Increase in work a1) “...stress is mainly because of committees, because you have a lot of work (...) And apart from that, the next day, two people don’t show up at all, two colleagues and, of course, your work increases because the job has to be done.” (Interview_S)

a2) “... previously, it is true that I used to leave, I did my job, I left at 15 : 00, 15 : 30 and I didn’t have to get more involved. But now, yes, it’s like... you feel more comfortable working because you do things your own way and you feel better because, I don’t know, more fulfilled, but that does mean that you take extra work home with you. It's like I said at the beginning, it’s true that sometimes I feel tense.” (Interview_D)

b. Difficulty in detaching after work b1) “[about the fact that there is no one on duty in the afternoon]... it has already been flagged as a problem (...) and that’s why they told us that, of course, we can’t disconnect [from the phone].” (Interview_E)

b2) “... it’s a job that never ends, you know? It’s not that you’re working, that’s not true either, is it? You’ve already finished, but you can't switch off. It's that feeling that you’re connected to work.” (Interview_O)

External elements impacting on the new HCS model that can cause fatigue

c. Staff shortage after the departure of team members without a replacement “ ... [our team] started in 2019 with 10 people and... yes, during the pandemic, last year, two people decided to leave, and then, well, we have continued with these eight people, which this year is making it impossible to continue. We are very short-staffed.” (Interview_N)

Category	Examples
Elements of the new HCS model that could cause fatigue
a. Increase in work	a1) “...stress is mainly because of committees, because you have a lot of work (...) And apart from that, the next day, two people don’t show up at all, two colleagues and, of course, your work increases because the job has to be done.” (Interview_S)
	a2) “... previously, it is true that I used to leave, I did my job, I left at 15 : 00, 15 : 30 and I didn’t have to get more involved. But now, yes, it’s like... you feel more comfortable working because you do things your own way and you feel better because, I don’t know, more fulfilled, but that does mean that you take extra work home with you. It's like I said at the beginning, it’s true that sometimes I feel tense.” (Interview_D)
b. Difficulty in detaching after work	b1) “[about the fact that there is no one on duty in the afternoon]... it has already been flagged as a problem (...) and that’s why they told us that, of course, we can’t disconnect [from the phone].” (Interview_E)
	b2) “... it’s a job that never ends, you know? It’s not that you’re working, that’s not true either, is it? You’ve already finished, but you can't switch off. It's that feeling that you’re connected to work.” (Interview_O)
External elements impacting on the new HCS model that can cause fatigue
c. Staff shortage after the departure of team members without a replacement	“ ... [our team] started in 2019 with 10 people and... yes, during the pandemic, last year, two people decided to leave, and then, well, we have continued with these eight people, which this year is making it impossible to continue. We are very short-staffed.” (Interview_N)

Turning to psychological distress, internal and external factors were identified. Two relevant factors inherent to the new HCS model emerged: the sense of pressure and the emergence of conflicts and their management. The sense of pressure was related to increased workload and the inability to disconnect (Table 6, quotes a, b1, b2). On the other hand, co-decision-making in a context of intensified social relations could lead to conflicts and, in one team, in workplace harassment. Social conflicts arose because the teams were able to decide on their daily functioning but not on strategic issues, such as budgeting and the number of workers on the team, and therefore the pressure to achieve group objectives fell to the existing team members (Table 7, quotes a1, a2). In turn, several factors modified how conflicts were channelled within groups including: the extent to which companies provided intervention/arbitration resources such as individual and group coaching sessions (Table 7, quote b1), the provision of more or less guidance from the coordinators of self-managed teams (Table 7, quote b2), and training to improve the team’s performance (Table 7, quote b3). In addition, groups could make decisions through different routes (consensus or majority), creating greater group cohesion or marginalising minority opinions (Table 7, quotes c1, c2).

Table 7

Examples of factors that might affect workers’ psychological distress

Category	Examples
Elements of the new HCS model that could cause psychological distress
a. Pressure to meet group objectives together with reduced power to decide on strategic topics (which can lead to social conflicts and harassment)	a1) “Not all services are in the morning, there are services in the afternoon as well and “no, I don’t want to work in the afternoon. Give me my schedule, I have my own timetable, I finish at such and such an hour”. OK, but what do we do with the other services?” (Interview_K)
	a2) “ ... one of the people who left the pilot (...) had a 26-hour contract and was studying and they wanted her to take morning and afternoon services. Then, of course, they started harassing her until the girl couldn’t take it any more and left...” (Interview_E)
b. Resources facilitated by the company to reduce social conflicts (coaching, coordinators of self-managed teams, training)	b1) “When the team was set up (...) they did give us sessions and, well, we had our ups and downs, which we continue to have because we don’t all think alike and, well, we have been strengthening some things more than others and working on our strengths and weaknesses. When we need to, we ask for other coaching sessions to work on it... “ (Interview_I)
	b2) “...[the coordinator] always acted as an arbitrator and put the cards on the table. So we’d say, “Well, we want to do this”. “Legally we can, legally we can’t, we can go this far, we can’t go that far”. He was the one who was in charge of that. Of course, now it seems that... the coordinators have changed and now it seems that they have an order from above that we have to solve certain conflicts ourselves. They can be there and mediate, but they can’t decide anything at all, which I think is fine as long as we all know what it’s all about.” (Interview_E)
	b3) [Question: Have you received any kind of training, for example on how to work as a team?] “No, no. None. No, no, we are learning on a day-to-day basis, but no.” (Interview_G)
c. Form of team decision-making (consensus or majority)	c1) “So we all reach a unanimous consensus in the [group] meetings but outside them, nothing gets decided.” (Interview_N)
	c2) “What we have said is that we are going to do everything by voting, so that they can’t say that there is discrimination.” (Interview_K)
External elements impacting the new HCS model that can cause distress
d. Deviations between the HCS model presented to the employees and the actual one	“...at first, it was great, we liked it a lot. I mean, we still like it, but at the beginning nothing happened and it was left up to us to say, for example: “well, I’ll do this service, I’ll try and do it later because first I have to go to the doctor and he’s telling me, I’ll do it myself”. But of course, now you also have to clock in. If you change it, how do you change the clocking in?” (Interview_F)
COVID-19 pandemic	“[COVID-19 pandemic] It was hard because we started, now the restrictions started, the protocols started, the protocol changes and now we are going to do this... (...)Taking the metro completely empty and now there are more and more cases and then you were afraid of, since you were going but you are working with a sick person, an elderly person ... People, users who had contact and then they had, no, they didn’t have COVID, but as they had had contact they had to go through the 14 or 10 day protocol, right? So you had to, you had to go completely in a [personal protective equipment] suit.... (...) So that was very stressful. As a result of that, a colleague who, well, she and I got on very well, she broke down, broke down. Because of the COVID issue, yes.” (Interview_B)

An external factor related to the rise of psychological distress concerned the discrepancy between the HCS model presented to employees and the system that was actually implemented. An example is the introduction by the City Council of a new clocking system for all HCS workers. Some workers mentioned that this system contradicted the flexible working hours of the self-organising work teams and that they feared that a sudden change in working hours could lead to a reprimand (Table 7, quote d). Finally, another external factor impacting HCS working was the COVID-19 pandemic, which caused stress for multiple reasons (Table 7, quote e). Some arguments mentioned by interviewees included having to work during lockdown (and with little social or financial reward for their efforts); the shortage of personal protective equipment at the beginning of the pandemic; fear of being infected and of infecting their loved ones; having to adapt to repeated changes in the protocols; the stress of working in accordance with procedures for case and contact tracing; and the use of personal protective equipment.

4 Discussion

In this study, we assessed the pilot phase of an organisational change in the HCS system based on self-managing work teams and implemented by Barcelona City Council. We examined the impact of this new model on the working and employment conditions of the staff, as well as on their health and well-being. In the quantitative assessment, the new organisational model was associated with improvements in employment conditions and psychosocial working conditions due to enhanced control and support. Nevertheless, negative results were also observed: the pre-post study revealed an increase on exposure to uncomfortable positions and psychological job demands and the worsening of health outcomes (general fatigue and psychological distress). The qualitative findings indicated that certain factors inherent to the self-managing work model such as increased social relations and autonomy may have different facets and repercussions on health and well-being. External factors that could have affected both the implementation of the new HCS model and workers’ health include the COVID-19 pandemic and inter-service provider variations in the way teams function, which emerged particularly in the qualitative results.

The factors most likely mediating the health and wellbeing outcomes in this study were stress and exposure to painful positions. The new HCS model focuses on reducing commuting times, which seems to have had the unintended consequence of limiting worker’s breaks and increasing exposure to ergonomic risk factors, resulting in greater fatigue. Similarly, lengthening contracted hours may also have increased painful positions and fatigue. Some of the stress-related factors found in this study have also been reported by previous studies of Buurtzorg-inspired HCS models, such as greater responsibility and subsequent workload [20, 25], an inability to disconnect [25], and services overload [19]. The latter factor was particularly notable in one team who had fewer members after the switch to the new model.

Salient positive factors emerging from our assessment were greater coworker support and control due to enhanced role clarity, as well as the ability to make decisions on the team’s day-to-day functioning. In line with previous research [24], we found that interviewees rated being part of a team favourably and felt that it increased their insight into users’ needs and decision-making ability. Nevertheless, the benefits of greater support and autonomy were somewhat compromised by other factors that could lead to distress among workers. This was true of the inability to make decisions on strategic issues in conjunction with the pressure to meet group goals [19], conflicts between team members [25], and the discrepancy between how the HCS was supposed to function and its actual functioning. In this regard, a literature review reported that a key determinant of how well teams function is the way in which companies facilitate resources to teams [20]. In this study, we found major differences regarding resource facilitation between companies providing HCS in Barcelona.

Our study also shows the effects of the outbreak of the COVID-19 pandemic on the functioning of self-organising teams. Some common elements producing unease and concern among the workers are shared by the workers of traditional HCS, mostly regarding safety issues and lack of recognition of their work during the pandemic [30, 31].

4.1 Strengths and limitations

Through a mixed-methods evaluation, this study examined the implementation of the pilot phase of a municipal policy to change the organisational model of HCS. It broadens the spectrum of knowledge on the effects of a Buurtzorg-inspired model due to several factors: its social policy nature, the occupational group concerned (family workers or cleaning assistants rather than nurses), the systematic analysis of the impact of this new HCS model on workers’ health and well-being, and its application in a southern European country with a different welfare state model than previous studies (see for instance the country distribution of the studies analysed in the review by [20]). In southern European countries, the historically underinvestment in social benefits has led to a care system in which families play a leading role [4], therefore HCS policies have the potential to reduce social inequalities in health, and particularly gender inequalities [5]. Moreover, precarious employment is extensive in these countries [32] and the new HCS model affected a professional group particularly exposed to negative labour conditions and lack of recognition [7, 15]. Thus, the intervention could also mitigate work-related inequalities in health among these workers. As the evaluation shows where it has worked and not, the results offer valuable insights to policy-makers, managers, and other stakeholders in the implementation of the new model in the rest of the city and in other interested cities.

This study also has some limitations. The sample size in the quantitative evaluation was small. This was because it was subject to the implementation of new self-managing work teams by the City Council and by the loss of an intervention and a comparison group. In addition, we cannot exclude the possibility that our analysis showed a certain survivor bias, as the most dissatisfied - and possibly worst performing - workers may have resigned from the new HCS model. Finally, despite the undeniable value of the qualitative assessment, the interviews were conducted 1 year after the third round of the surveys.

4.2 Recommendations for action

This evaluation had an important practical purpose, both for the intervention itself in the pilot phase as well as for its replication in the rest of the city and surrounding municipalities. In view of the results, the following is recommended:

Work teams need to have access to organisational resources (e.g., initial team training, specific training in information technologies, communication and team decision-making, as well as other forms of training required by the teams themselves; access to space and equipment; and coaching and support from back-office services).

Job demands should be balanced against the decision-making ability of self-organising work teams and measures should be implemented to reverse negative repercussions on workers’ health and well-being (for example, ensuring break times and digital disconnection, and including coordination time within the workday).

Painful postures and general fatigue should be reduced (for instance, by assessing the number of users assigned to equipment, tasks involving strenuous postures and ergonomic measures and muscle recovery times).

The mental health of HCS staff must be protected with the existence and effective implementation of protocols for investigating harassment, and securing workers’ right to disconnection.

Salaries should be reviewed for possible adjustment given the new tasks and workloads.

5 Conclusion

The evaluation yields positive outcomes for workers in self-managing working teams regarding support, autonomy and employment conditions, but also detected increased fatigue and psychological distress. In these teams, factors such as social relationships and autonomy can affect workers’ health and well-being in different ways. Workers’ health and wellbeing outcomes seem to be determined by the balance between job demands, the resources available to work teams, and ways of managing conflict within the team. Outcomes were also influenced by the reduction in travel time and by external factors such as the COVID-19 pandemic and differences between service providers regarding team management and functioning.

Ethical approval

The study was approved by the Ethics Committee on research involving medicines of Parc de Salut Mar in Spain (2021/10090).

Informed consent

Both the quantitative and qualitative phases of the evaluation were preceded by a letter of informed consent as well as oral information about the study. Participants gave written consent to complete the surveys and oral and written consent for the interviews.

Conflict of interest

At the time the fieldwork for this assessment was conducted, the third and fourth authors worked for the Barcelona City Council and participated in the design and development of the new organisational model analysed in the study. The remaining authors have no conflict of interest to declare.

Footnotes

Acknowledgments

The authors are very grateful to all of the workers who participated in the study for sharing their time and experiences, and to those who made it possible to contact them.

Funding

This research was partly funded by the City Council of Barcelona. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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