Factors influencing trust and mistrust in health promotion partnerships

Abstract

Partnerships between sectors can achieve better outcomes than can be achieved by individual partners working alone. Trust is necessary for partnerships to function effectively. Mistrust makes partnership working difficult, if not impossible. There has been little research into partnership functioning factors that influence trust and mistrust. This study aimed to identify these factors in health promotion partnerships. Data were collected from 337 partners in 40 health promotion partnerships using a postal survey. The questionnaire incorporated multi-dimensional scales designed to assess the contribution of factors that influence partnership trust and mistrust. Newly validated scales were developed for trust, mistrust and power. Multiple regression analysis was used to identify the significance of each factor to partnership trust and mistrust. Power was found to be the only predictor of partnership trust. Power, leadership, and efficiency were the most important factors influencing partnership mistrust. Power in partnerships must be shared or partners will not trust each other. Power-sharing and trust-building mechanisms need to be built into partnerships from the beginning and sustained throughout the collaborative process.

Keywords

power trust mistrust health promotion partnerships

Introduction

Intersectoral partnerships are an integral component of health promotion practice (1). Health promotion actions aim to influence the determinants of health such as educational attainment, poverty, and the overall environment, so partnerships with other sectors are essential. The World Health Organization (WHO)’s Health in All Policies (HiAP) approach calls for partnerships at all levels, international, national, regional, local, to promote and improve population health (2). Partnerships may be defined as collaborative working relationships where partners can achieve more by working together rather than separately. Successful partnerships produce synergistic outcomes where the complementary skills, resources and expertise of the partners produce effective solutions (3). Creating and sustaining effective intersectoral partnerships is core to the implementation of a HiAP approach. Engaging partners from other sectors, identifying opportunities for intersectoral collaboration, negotiating agendas, mediating sectoral interests, and achieving synergy, are all core elements of implementing HiAP (2).

The WHO framework also acknowledges that the knowledge and skills needed for this work may need to be developed and further enhanced (2). Effective partnership working is a core competency for health promotion practice, including the ability to build and maintain successful partnerships (1). There are few empirical studies on partnerships for health promotion, which can be used to inform processes for effective partnership functioning. An earlier study examined the functioning of health promoting partnerships in relation to synergy (3). This paper builds on the earlier study and seeks to examine the importance of trust and the factors influencing its development in health promotion partnerships. Trust ensures that partnerships can function effectively (3). Mistrust makes partnership working difficult, if not impossible. There has been very little research into the partnership functioning factors that influence trust and mistrust.

A literature review of health promotion partnerships (4,5), community health partnerships (6 –8), and management research on partnerships (9,10), showed that few studies have measured trust and mistrust or identified their key predictors. The relationship of trust and mistrust to other partnership functioning factors, such as leadership, has seldom been measured. The present study aimed to identify these factors in health promotion partnerships and measure the extent to which they influence the development of trust and mistrust using scales developed by Jones and Barry (11). The partnerships chosen had promoting health as their main goal as opposed to preventing disease or delivering treatment services more efficiently.

Literature review

Trust and mistrust

Trust has been described from a number of different perspectives, including interpersonal, inter-organizational, and societal (12). It has a number of different dimensions, including trusting (openness and sharing), trustworthiness (support and acceptance), vulnerability, and expectations (reciprocity) (13,14). The literature disagrees as to whether trust and mistrust lie at opposite ends of a continuous variable or whether they are distinct, but linked, dimensions. Studies by Jones and Barry and Benamati et al. found that they are distinct constructs and that low trust is not the same as mistrust (11,14). Whether distinct or not, mistrust is a primary barrier to collaboration (9). Health promotion partnerships often have a history of mistrust, which can exist between public sector organizations such as health and education, between statutory and voluntary organizations, and/or the private and public sectors (8,15). Trust is a prerequisite for effective partnerships (16).

Despite its importance, trust has seldom been measured. A recent literature review of health promotion partnerships found only one study that measured trust specifically, although trust emerged as a component of effective partnerships in a number of qualitative studies (5). A systematic literature review found that the measurement of trust is very underdeveloped (17). Costa et al. (18), in a study of 112 health and social care teams, showed that trust is positively related to performance. Bahraminejad et al. found that a lack of communication led to ‘inadequate or even lack of trust between partners’ and this lack of trust (15), especially at the start-up stage, made partnership ‘impossible’. Their study showed that communication was particularly difficult between academics and community members. Armistead et al. found that (19), although trust is a key element of multi-sector partnerships, it is an intangible phenomenon experienced more when absent than when present.

Factors that influence partnership functioning

Many factors influence partnership functioning. A scoping review by Corbin et al. identified nine core elements that support and inhibit partnership functioning (5), including trust, leadership, and having a wide range of partners. Previous research shows that other factors include how the partnership is administered and managed, efficiency, finance, boundary spanners, community involvement, and shared power (3). Administration and management of a partnership involves inter alia communicating effectively, managing grants and funds, orientating new partners, and evaluating the impact of the partnership on health (4). Jones and Weiss et al. found that efficiency – how resources and time are used by the partnership – was a significant predictor of synergy (20,4), an indicator of successful partnerships. Baron-Epel et al. showed that effective management of a partnership is a key component of its success (8).

Boundary spanners have a set of partnership skills that enable partnerships to function more effectively, such as negotiating skills and being able to see new opportunities (3). Challis et al. and Alter and Hage have identified the need for boundary spanners who can connect partners up with common goals (21,22). Boundary spanners bring a range of skills to partnership functioning, serving as ‘collabronauts’ (23), and establishing a climate of trust, optimism, and perseverance (16). Mays et al. found that boundary spanners are necessary for partnership effectiveness (24).

A key element of health promotion partnerships is that community members are actively involved (25), and Green et al. argue that if they are not (26), the partnerships are not health promoting. Robertson and Minkler define community involvement as communities working with professionals to define and solve health problems (27). Lasker and Weiss stress the critical role of community stakeholders and of sufficient heterogeneity of partners to supply the range of perspectives required (28). Winer and Ray argue that successful partnerships ‘need to involve minority, grassroots, and end-user groups’ (29). Weiner and Alexander and Minkler et al. found limited evidence of community involvement in community health partnerships (30,31). Zahner showed that having a broad array of partners contributed to effectiveness (32).

Collaborative leadership can fix ‘public problems in a shared-power world’ (33). Collaborative leaders understand social and political contexts, can communicate and share a vision, and implement policy decisions. Integrative leadership is required in situations where there is no one person in charge and power is distributed across a number of organizations, as happens in health promotion partnerships. Leadership has been measured more often than any other partnership functioning factor (3), and has been found to have a positive effect on levels of partner participation (34). Lempa et al. found that leadership contributed to more than five times the variance of other factors and concluded that the ‘importance of leadership is the greatest implication for practice that emerges from the study’ (7).

Power is always present in partnerships and it can have a positive (shared power) or a negative (power abuse) effect (29). Power is an important factor in terms of facilitating cooperation and is the functional equivalent of trust (35). The 68^th World Health Assembly recognizes the importance of shared power and recommends supportive structures to deal with power dynamics in partnerships (36). Hemphill et al. argue that research studies have largely ignored the influence of power (37), although anecdotal evidence suggests that shared power is far from the norm. Pratt et al. note that ‘local power struggles … become a painful distraction that can last for years’ (38). A systematic literature review by Gillies found that durable structures which support power-sharing between partners – particularly between professionals and lay partners – are vital to successful partnerships (39). Gillies argues that participation by the lay public must not be ‘mere tokenism’ and ‘must connote a sharing of power and control between the public and key protagonists’. Several analyses of Healthy City projects ‘made visible the difficulties they had in shifting the balance of power and control in cities’ (39).

The present study

This is a new analysis of data collected for a cross-sectional study of partnership functioning. The original analysis explored the relationship between synergy and partnership functioning factors in health promotion partnerships. In the previous study, Jones and Barry found that leadership and efficiency were significant predictors of partnership synergy (3). Administration and management, community assets, and boundary-spanning skills also approached significance. Power was included in the new analysis as it featured in the literature as an important functioning factor although it has seldom been measured. This new analysis explores the relationship between trust and mistrust (the dependent variables) and six other partnership functioning factors (the predictor variables) in the original sample of health promotion partnerships.

Methods

Sample

Eligible partnerships were identified from a database of health promotion partnerships developed for a previous study (3). Partnerships had to have been in existence for a year or more, have a minimum of five partners and a health promotion purpose. Initial contact was made by telephone with the partnerships’ chairs/leads. Of the 73 partnerships deemed to be eligible 42 partnerships agreed to participate. Two partnerships participated in the pilot study leaving 40 for the main study. The partnerships had members from a range of sectors including the community, voluntary organizations, health professionals, and the education sector, and represented all four provinces of the Republic of Ireland. Partners were involved in a wide variety of projects and programs including: increasing involvement in physical activity, improving the health of children and families, and alleviating the effects of poverty. The original data were collected between January and March 2007 via questionnaires to partnerships’ chairs/leads and partners (total N for both groups = 469). Two reminders were sent after two and four weeks, respectively. The methodology is described in full in previously published papers (3,11). The present study is a new analysis of the original data set.

Measures

The questionnaire incorporated specifically designed and validated multi-dimensional scales designed to assess the relationship of six functioning factors to partnership trust and mistrust (3). Most questions were in the form of five-point Likert scales, where ‘always’ scored 5 and ‘never’ scored 1. A ‘don’t know’ option was included (40). New scales were developed and validated by Jones and Barry for trust and mistrust (11). The nine-item trust scale measured low to high trust and the five-item mistrust scale measured low to high mistrust. Sample trust items included ‘partners keep the promises they make to the partnership’ and ‘partners eagerly volunteer to take on tasks associated with the partnership’. Sample items for mistrust included ‘decisions are made by a minority of partners outside of the main partnership meetings’ and ‘partners’ time and energy is wasted due to mistrust’. Predictor measures included an ‘administration and management’ scale (8 items), an ‘efficiency’ scale (3 items), and a ‘leadership’ scale (11 items), all developed by Weiss et al. (4). New scales were developed for ‘boundary-spanning skills’ (14 items), ‘community assets’ (5 items), and ‘shared power’ (9 items), based on a literature review.

Statistical analysis

SPSS version 20 was used to carry out all statistical analyses. Variability within partnerships was significantly less (p < 0.0005) than variability between partnerships for all scales, allowing individual responses to be aggregated at the partnership level (4). Reliability and validity tests of all measures were carried out on individual partner-level data. Pearson’s correlations and regression analysis were carried out on aggregated partnership-level data. Partner- and partnership-level scores for all scales were obtained by calculating the scale scores for each respondent and then calculating an aggregate score for respondents within each partnership. A detailed description of the statistical analyses was given in a previous paper (3), including Pearson’s correlation coefficients for the predictors and dependent variables.

Results

The number of valid partners was 469. A total of 337 questionnaires were returned, giving a 72% response rate. All partnerships were involved in many health promotion actions, including training (80%), research (75%), education (65%), and health campaigns (40%). More than half (54%) were involved in several different activities. Partnerships’ duration ranged from one to more than five years. The health services (37%) and voluntary sector (14%) between them accounted for more than half the partners with other sectors less well represented, for example, education (7%), local authority (6%), and the private sector (1%). Table 1 shows descriptive properties of the measures for partnership-level data.

Table 1.

Measures for partner- and partnership-level data, including Cronbach’s alpha, variances, means, and standard deviations.

Measure	Number of items (possible scores)	Partner level means (SD)	Actual range of scores	Cronbach’s alpha	Partnership level means (SD)	Actual range of scores
Administration and management (n = 298)	8 (8–40)	29.5 (6.5)	9–40	0.92	29.0 (3.6)	22.6–38.0
Boundary-spanning skills (n = 255)	14 (14–70)	52.7 (8.6)	26.9–70	0.95	52.6 (4.6)	41.3–67.3
Community assets (n = 292)	5 (5–25)	19.3 (3.1)	10.0–25.0	0.81	19.2 (1.7)	15.7–23.3
Efficiency (n = 276)	3 (3–15)	12.3 (2.1)	3.0–15.0	0.84	12.2 (1.1)	9.4–14.6
Leadership (n = 307)	11 (11–55)	38.9 (9.3)	11.0–15.0	0.96	38.7 (5.1)	27.2–50.0
Mistrust (n = 258)	5 (5–25)	20.4 (3.3)	6.0–25.0	0.82	20.4 (2.1)	13.6–23.9
Power (n = 290)	9 (9–45)	36.2 (5.4)	20.0–45.0	0.87	36.1 (2.9)	29.6–41.5
Trust (n = 309)	9 (9–45)	35.4 (5.6)	15.0–45.0	0.91	35.5 (3.0)	29.7–41.3

All of the scales had more than adequate reliability with Cronbach’s alphas ranging from 0.81 to 0.96 (41). Scores were identical for both levels of data but standard deviations for partner-level data were twice that of partnership-level. This means that the scores for partnership-level data are more bounded and constrained than for partner-level data, an inevitable consequence of using mean scores (42). Principal components analysis (PCA) showed that with the exception of ‘shared power’, all scales had a simple structure (one component) with excellent to good factor loadings (43). Variances for each PCA ranged from 55% to 72%. Convergent and discriminant validity were established for all scales. Corrected-item-total-correlations for each scale were correlated with the total scores of the other scales. All items correlated more highly with their own scale than with any other scale, indicating their validity. Although the power scale yielded two components – shared and unshared power – all items were retained in one scale following parallel analysis. Pattern coefficients for all scales ranged from 0.512 to 0.894.

Inter-correlations between the predictors were examined because multicollinearity means that, even though significant factors remain significant, they cannot be ranked in the regression model (43). Pearson correlation coefficients for partnership-level data ranged from 0.47 to 0.85 and all were significant at the p < 0.01 level. A number of the aggregated predictors have high correlations (>0.8) with others, for example community assets and leadership. Multicollinearity was confirmed by examining the condition indices most of which were more than 30. Regression analyses were conducted on partnership-level data to explore the relationships between trust and mistrust and the six predictor variables. Table 2 presents the results of the regression analyses for trust and mistrust.

Table 2.

Results of regression analysis predicting partnership trust and mistrust by six dimensions of partnership functioning.

Predictors	Standardized β and significance level
Predictors	Trust	Mistrust
Administration and management	0.21 NS	−0.22 NS
Boundary-spanning skills	0.09 NS	−0.03 NS
Community assets	0.16 NS	0.25 NS
Efficiency	−0.13 NS	−0.34*
Leadership	0.23 NS	0.53*
Power	0.31*	0.62**
Adjusted R² for trust and six predictors = 0.73, F = 21.18, df = 39 Adjusted R² for mistrust and six predictors = 0.82, F = 18.13, df = 39

NS: not significant.

Note: *p < 0.05, **p < 0.01. All tolerance and variance inflation factors (VIF) are well within acceptable limits.

Results show that, for partnership-level data, partnership trust is predicted only by power. Mistrust is predicted by power, leadership, and efficiency.

Discussion

The aim of this study was to identify factors that influence trust and mistrust in health promotion partnerships. Power emerged as the only predictor of trust. The finding confirms Bachmann’s view that power is trust’s functional equivalent and that trust affects partnerships in the same way as shared power (35). The study shows that trusting relationships can exist only when power is shared, as argued by Gillies and Gray (16,39). Shared power ensures a partnership can work smoothly whereas misuse of power and power abuses prevent a partnership from functioning at all.

Shared power and leadership were shown to have a positive relationship to mistrust. This may seem strange until the mistrust scale is examined. Items were scored from 1 to 5, where 1 signifies high mistrust and 5 signifies low mistrust. Shared power and leadership ameliorate the effects of mistrust and ensure that mistrust does not develop in a partnership. Efficiency was shown to have a negative relationship with mistrust which is counterintuitive. The most likely explanation for this finding is multicollinearity, which can generate direction signs that are the opposite to those of the correlation coefficients between the predictors. Tabachnick and Fidell argue that ‘if the only goal of analysis is prediction you can ignore it’ [multicollinearity] (43). Another alternative is to examine the correlation coefficients whereby the exact order of the significant predictors can be established. These were power, leadership, and efficiency, in that order. This means that mistrust in partnership can be kept to a minimum when power is shared, leadership is present and partners’ financial and in-kind resources, such as time, are used efficiently (4). Mistrust can be prevented by not allowing partners to undermine the main partnership agenda, and sharing power and decision-making (22).

Another finding of interest is the number of partners who had left the partnerships for a variety of reasons. Partners leaving partnerships is a major problem (10,30), and Kegler et al. had to delete 157 inactive partners from their sampling frame (44). Leadership and trust are associated with partner satisfaction and retention levels (18,45). Corbin et al. and Gray et al. found that high levels of synergy (29,46), developed during the start-up stage of a partnership, can be undermined by the addition of new partners, resulting in a loss of consensus on mission. Greater efforts must be made to recruit and retain necessary partners.

Implications for research and practice

The study has practical implications for health promotion partnership working. HiAP calls on governments to strengthen partnership capacity across all sectors (2). Health promotion involves influencing the determinants of health including education, poverty, social inclusion, inequalities, employment, and the overall environment. Indeed it can be argued that population health cannot be promoted without partnerships because so many sectors create health. Climate change, for example, will not be tackled without a global partnership between nations. On a smaller scale, a community might want to develop a safer environment for children and will require a partnership between themselves, law enforcement officials, health professionals, and local authorities. Partnerships often begin enthusiastically and subsequently collapse when trust, mistrust, and shared power are not taken seriously. Jones and Barry found that a majority of partners in health promotion partnerships think trust is a ‘taken for granted’ phenomenon (3). Those involved in partnerships may need training on the concepts of trust and power to ensure that partners understand their importance, know how to build and maintain trust, how to share power, and how to deal with mistrust when it arises (1). Weiner et al. recommend procedural fairness as a way of building trusting relationships (45). Other methods that can be used to build trust include having a common purpose or mission all are agreed on, clear roles, and valuing the contributions of all partners equally (5). Partnerships characterized by mistrust and power abuses will not succeed and will waste resources that could be spent on effective health promotion interventions. Boundary-spanning skills did not emerge as a significant predictor for either trust or mistrust in the regression analysis. However, they were highly correlated with community assets (0.85). It can be inferred that boundary spanners are needed to fully and fairly integrate the public’s perspective into the partnership’s mission. Boundary spanners are particularly important in health promotion partnerships because of the well-established vertical hierarchies of professional groups (3). Further research is needed into the role of boundary spanners.

Limitations

The study had a number of limitations. The study sample was a convenience and not a random sample. Although every effort was made to include partnerships that were performing less well, it was inevitable that those performing adequately to very well were more likely to participate. The resulting restricted variance of the dependent variable made statistical analysis more conservative. Loss of variability is an inevitable consequence of using aggregated scores, leading to inflated correlations between variables (42), and consequent multicollinearity which was a problem in this study and the previous study. The only way to avoid multicollinearity is to recruit a large enough sample, not always an easy task.

Conclusion

This study adds to the evidence base on health promotion partnership functioning, and identifies the key predictors of partnership trust and mistrust, and the role of power. Facilitating effective partnership working which reflects health promotion values and principles is a core competency for health promotion practitioners (1). This includes ensuring that partners and key stakeholders are enabled and empowered to engage in health promotion action. Shared power and facilitative leadership are at the heart of this process, which, in turn, help to build trust (20). Trust-building and power-sharing mechanisms need to be built into the partnership-forming stage and this trust and power-sharing must be sustained throughout the collaborative process. Shared power involves sharing the credit for partnership activities, keeping promises, being consistent and contributing expertise freely when that expertise would benefit the partnership (3). Mistrust can be prevented by not allowing partners to undermine the main partnership agenda, and sharing power and decision-making (22). Partners may need training in the skills to build trust and prevent mistrust, and understand the importance of shared power. Paying explicit attention to trust during the start-up phase will enable health promotion partnerships to achieve their full potential.

While these processes are important for all effective partnerships, they take on a particular importance for health promotion partnerships in view of the core values and principles which underpin health promotion practice and the focus on intersectoral working (2). Developing and enhancing the requisite knowledge and skills for effective partnership working is key to strengthening health promotion workforce capacity on HiAP implementation (1).

Footnotes

Declaration of conflicting interests

The authors declare that there are no conflicts of interest.

Funding

This work was supported by the Health Service Executive West, in the Republic of Ireland. The views expressed are those of the authors.

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