In this study, our objective was to distil community-level indicators of safety and peace from two participatory datasets, namely the Photovoice project and the SCRATCHMAPS (Spiritual capacities and Religious Assets for Transforming Community Health by Mobilising Males for Peace and Safety) study. Both datasets were particularly well suited to this aim because they employ participatory, community-engaged methodologies that draw on grounded theory and grounded analytical principles to generate insights directly from community members’ lived experiences. Grounded, inductive approaches of this nature are central to developing contextually relevant, culturally valid and ecologically grounded measurement indicators, which strengthen the content validity and real-world applicability of emerging instruments (Charmaz, 2014; Innes & Booher, 2000; Taliep et al., 2025).

The Photovoice study was conducted in low-income communities in South Africa, Uganda, Mozambique, Zambia, Egypt and Ethiopia. All participants were actively attending school during the study period and were recruited through both formal and informal youth organisations within their respective communities. Utilising established partnerships with community stakeholders aided the recruitment process. Participant identification was facilitated by community leaders associated with local non-governmental and community-based organisations operating within the communities. Additionally, community-engaged researchers and scholars in other countries assisted in identifying existing participants. A total number of 85 participants were recruited for the study, with gender distribution as follows: in Cape Town, South Africa, 50% (n = 10) were female and 50% (n = 10) were male; in Maputo, Mozambique, 50% (n = 5) were female and 50% (n = 5) were male; in Kampala, Uganda, 50% (n = 5) were female and 50% (n = 5) were male; in Lusaka, Zambia, 50% (n = 5) were female and 50% (n = 5) were male; in Ismailia, Egypt, 36% (n = 10) were female and 64% (n = 16) were male and in Axium, Ethiopia, 50% (n = 8) were female and 50% (n = 8) were male (Suffla et al., 2015). The age of participants ranged from 11 years to 17 years (Suffla et al., 2015).

While there were slightly more males among the Photovoice study participants, the majority of SCRATCHMAPS participants were female. Three Community Asset Mapping (CAM) workshops were conducted in a low-income community comprising around 250 households in the Western Cape, South Africa. These workshops attracted 74 attendees aged 18 years and above from diverse faith backgrounds (Christianity, Islam, Khoisan and Rastafarianism), facilitated by wide-reaching invitations through posters, flyers and door-to-door invitations.

The Service Provider Mapping (SPM) workshop was attended by 18 service providers from various sectors.

Two action planning workshops brought together 63 local participants, including stakeholders and community members, with a nearly equal split between sexes (34 males, 29 females). To complete the ‘bricks’, local participants’ age groups, ranging from 13 years to 85 years, were conveniently sampled. The bricks were completed by 175 participants, with a slightly lower number of males (n = 69) than females. Of the respondents who completed the learner essays, most participants identified as female (n = 44; 60.27%) and were all Grade 7 primary school children, aged 12–14 years, from two local schools in the community.

Data analysis for the Photovoice study employed qualitative visual discourse analysis (McMorrow & Musoke, 2023), which involves analysing the photographs, participants’ accompanying narratives and group discussions to identify key themes and insights related to safety and danger from the perspective of young people.

All datasets from the SCRATCHMAPS study were analysed using a participatory a priori thematic framework analysis method (Taliep, 2016; Taliep et al., 2023). The initial predetermined categories for the analysis comprised: (1) community members’ meanings or understandings of the key concepts (safety, peace), (2) factors that promote safety and peace and (3) factors that hinder safety and peace. The predetermined subcategories, utilised under each of the main categories, included: (1) tangible factors, (2) intangible factors and (3) systems levels (individual, relationship, community and societal). These levels aligns with Bronfenbrenner’s Ecological System’s framework, which captures the multilayered influences shaping community safety and peace, which posits that individuals’ experiences of safety are embedded within and shaped by multiple, interrelated ecological levels, from the immediate microsystem of family, peers and local neighbours, to the broader exosystem and macrosystem contexts encompassing social structures, institutional practices and cultural norms (Bronfenbrenner, 1979). To facilitate the collective and participatory process of data analysis, academics within the research team provided training in qualitative thematic analysis to the community research team, which consisted of 10 local community members. The community research team was subdivided into groups and undertook the analysis of the datasets. These were then summarised in two tables, that is, what the community would like to see, and what they want to do to build a safe and peaceful community. An academic then validated the data analysis.

The data analysis process for the learner essays and the asset mapping data consisted of five steps, as outlined in Figure 2.

These categories, as shown in Figure 2, provided a framework for the development of the indicators. All three datasets were analysed according to an identical initial analysis framework, wherein understandings of safety and peace were drawn out and where factors that promote safety and factors that negate safety and peace were identified. The subsequent steps in the analysis were identical for the learner essays and asset mapping report but differed when the ‘bricks’ for the house of peace and safety were examined. The bricks were divided into two groups: those that represented ‘unsafe/unpeaceful’ factors. Similar bricks were grouped, and the frequency of each idea was determined by adding up the total number of ‘bricks’ within each main group. Following this, the predetermined subcategories outlined above (i.e. tangible, intangible and systems-level factors) were used to group the ‘bricks’ according to their subcategories and emerging themes.

Ethical clearance for the study was obtained from the University of South Africa Human Science Ethics Committee (CHS-CREC), University of South Africa (NHREC Registration No: Rec-240816-052; CREC Reference No: 2019-CHS-CREC – 0273). Ethical clearance and written informed consent and assent had been previously obtained from the Multicountry Photovoice Project on Safety and Danger Indicators and the SCRATCHMAPS Study to further distil and identify indicators of peace and safety from these two studies.

This section outlines the global-level indicators of safety and peace and explains how they informed the early conceptual framing for the development of community-level indicators. The primary steps in developing a measuring instrument involve reviewing the literature to establish whether similar instruments already exist and to provide a clear conceptualisation of the constructs that underpin the measurement instrument (i.e. the CSPI). In this paper, we focus specifically on global measures of safety and peace. Table 1 outlines the dimensions and indicators used to measure macro-level indices.

As depicted in Table 1, global-level safety and peace indicators include the Global Peace Index (Institute for Economics and Peace [IEP], 2017), the Human Development Index (United Nations Development Programme [UNDP], 2016), Measuring Progress in Conflict Environments (Eds. Agloglia et al., 2010) and the South African Development Indicators (Department of Planning, Monitoring and Evaluation, 2014).

The Global Peace Index (GPI) measures global peacefulness using 23 qualitative and quantitative indicators, which were selected and reviewed by a panel of experts. The GPI aims to measure the level of negative peace through three thematic domains: (1) ongoing domestic and international conflict (six indicators), which measures the degree to which countries are embroiled in domestic and external conflicts and their role and length of time involved in conflicts, (2) level of societal safety (11 indicators) assessing peacefulness revealed by low levels of crime, terrorism and violent demonstrations; a stable political environment, harmonious relations with neighbouring nations and a low number of the population internally displaced or made refugees and (3) extent of militarisation (six indicators) measuring the relation between military build-up and weapon access and a country’s level of peacefulness at both domestic and international level (IEP, 2017). Nasar and Naqvi (2024) explain that even though the focus of the GPI is on negative peace (delineated as ‘the absence of violence or the fear of violence’), the instrument transcends the analysis of ‘armed conflict’ and centres on violence more generally. It provides an important shift in the narrative and analysis from ‘conflict’ related to a ‘peace’ index. Nair (2016) highlights the following critique levelled at the GPI: the availability of data for each indicator in different countries, the combination of elements that do not point in the same direction (e.g. ‘military expenditure’ might not necessarily increase conflict), the absence of ‘violence against women’ as an indicator and the weight given to the components of the Index that leads to an imbalanced ranking of countries. For example, Equatorial Guinea (a repressive dictatorship, which censors and crushes protests) is ranked 81, whereas South Africa was ranked 136 out of 162 countries, ranking the country as substantially less peaceful than Equatorial Guinea.

Recently, the IEP developed the Positive Peace Index (PPI) to supplement the GPI. Positive Peace is defined as the ‘attitudes, institutions and structures that create and sustain peaceful societies’ (IEP, 2018, p. 6). The IEP has identified eight domains, or Pillars, that comprise positive peace: a well-functioning government, a sound business environment, recognition of the rights of others, low levels of corruption, high levels of human capital, a free flow of information, good relations with neighbours and an equitable distribution of resources. The PPI can be utilised to ‘measure a country’s resilience – its ability to absorb, adapt and recover from shocks, such as climate change or economic transformation’, help calculate the probability of conflict, violence and instability and indicate areas where policy intervention could contribute to peace (IEP, 2018, p. 7; Syropoulos et al., 2021). A key drawback of both the GPI and the PPI is that they largely neglect the cultural and subjective domains of peace that influence people’s viewpoints (Das, 2024; Nasar & Naqvi, 2024).

The Human Development Index (HDI) measures a country’s overall social and economic development using three dimensions: a long and healthy life, level of educational attainment and standard of living or gross national income per capita (UNDP, 2016). The HDI is based on international data from the United Nations Population Division, the United Nations Educational, Scientific and Cultural Organisation Institute for Statistics and the World Bank (UNDP, 2016). Key drawbacks of the HDI include its being a simplification and limited evaluation of human development, and it does not consider the quality-of-life aspects, such as overall feelings of security (Yin et al., 2023).

Measuring Progress in Conflict Environments (MPICE, pronounced M-Peace) is a metric framework of indicators that aim to identify potential sources of ongoing violent conflict and instability at a national level and to longitudinally measure progress in reducing the means and precursors of violent conflict and enhancing citizens ability to resolve conflict peacefully using five domains, namely governance, sustainable economics, safety and security, rule of law and social well-being (Eds. Agloglia et al., 2010; Khosa & Abdulkareem, 2023).

The MPICE guide recommends a range of quantitative and qualitative data collection and analysis methods that can be used in conjunction with the MPICE framework, including content analysis, expert knowledge, quantitative data and survey data (Eds. Agloglia et al., 2010; Khosa & Abdulkareem, 2023). Increasing government institutional performance and reducing conflict drivers are key to increasing stability, as outlined in MPICE, which essentially serves as a monitoring and evaluation tool within the stabilisation context (Stabilization Unit, 2014). The MPICE inventory consists of several stabilisation outcome measurements, arranged into five essential ‘sectors’ that are necessary for conflict resolution: (1) safe and secure environment, (2) political moderation and stable governance, (3) rule of law, (4) sustainable economy and (5) social well-being (Eds. Agloglia et al., 2010). Like the GPI and the HDI, the MPICE comprises universal indicators developed by experts using top-down approaches. Apgar et al. (2024) caution that universal indicators may not adequately account for local political, cultural and historical contextual complexities and argue that local indicators are better suited to address unique local circumstances (Apgar et al., 2024).

The Governance Peace and Security Index (GPSI) measures perceptions of population groups at a sub-regional level and utilises the methodology adopted to compute the Global Governance Index (Adechian, 2020). The GPSI measures three dimensions, namely ‘human rights and participation’, ‘rule of law’ and ‘peace and security’ (Adechian, 2020, p. S27). The demand for data in Africa generally focuses on conventional macroeconomic management areas and sectoral programmes, but there has been an increase in recent years in requests for data related to new policy and development areas, including human rights and freedom, governance, and democracy. This requirement is addressed through GPI macro-level indicators by applying data from the eight West African Economic and Monetary Union member states’ Integrated Regional Survey on Employment and the Informal Sector (Adechian, 2020).

The South African Development Indicators (SADI) serve as quantitative benchmarks to monitor progress towards key policy objectives in the country. Tracking these indicators allows for the evaluation of South Africa’s developmental path, pinpointing areas that require enhancement and crafting targeted interventions to promote sustainable development and inclusive growth. The SADI comprises 10 dimensions and 92 individual indicators: (1) Economic Growth and Transformation (16 indicators); (2) Employment (4 indicators); (3) Poverty and Inequality (7 indicators); (4) Household and Community Assets (6 indicators); (5) Health (9 indicators); (6) Education (10 indicators); (7) Social Cohesion (9 indicators); (8) Safety and Security (13 indicators); (9) International Relations (5 indicators) and (10) Good Governance (7 indicators) (DPME, 2014). Data are gathered from various sources, including official statistics (Statistics South Africa), government administrative systems (South African Reserve Bank), national census data and research from international institutions (DPME, 2014). Key challenges associated with the SADI encompass concerns regarding data reliability and consistency across the various sources utilised, which stem from disparities in reporting standards and methodologies (Statistics South Africa, 2018). There are further constraints regarding data accessibility and availability, notably in marginalised and remote regions, and the dynamic nature of development challenges necessitates ongoing enhancements in methodologies to accurately capture the intricate dynamics of development (Statistics South Africa, 2018).

Global indicators of peace and safety, as illustrated in Table 1, provide a comprehensive overview of peace and safety worldwide, focusing on key factors such as political stability, governance, international relations, conflict resolution and military expenditures. Compiled by international organisations, these indicators draw data from diverse sources, including government reports, surveys and expert assessments. While global indicators offer a broad perspective on peace and safety trends at a macro level, community-level indicators provide insights into the lived experiences of individuals within specific communities. Unlike macro-level indicators that focus on more high-level and aggregate data across global populations, often comprising data on militarisation, international wars, terrorism or the overall level of violence in countries, community-level indicators can provide data on multiple levels, from individual personal and community-specific data to larger structural factors that hamper safety and peace.

Several attempts have been made to develop community-informed indicators of safety and peace. Such measures include the Everyday Peace Indicator (Mac Ginty, 2013a, 2013b) and the Community Resilience Measure (Ahmed et al., 2004). The Everyday Peace Indicator (EPI) used an inductive or bottom-up approach to identify community-informed indicators of peace and social change, particularly in societies emerging from violent conflict, and uses a participatory framework to design and develop these indicators (Mac Ginty, 2013a, 2013b). The EPI was developed to assess subjective and locally pertinent indicators of peace in societies recovering from conflict, especially those transitioning from civil war or political violence (Mac Ginty & Firchow, 2016, Firchow & Mac Ginty, 2017). The dimensions of the EPI, which focuses to a large degree on peace-building and positive peace, include: (1) security, (2) dealing with the past, (3) rights and dignity (these three dimensions are the most state-oriented, addressing state-guaranteed rights, transitional justice mechanisms, and institutions such as the military and police), (4) armed actors, (5) culture and safety and (6) livelihood and health (Firchow & Dixon, 2025). The Community Resilience Measure (CRM) offers another example of a community-participatory framework used to identify community-relevant indicators. Like the EPI, the CRM questionnaire was developed through several participatory steps involving community members. The dimensions of resilience were operationalised, delineating the following seven measures of community resilience: business ownership, household security, communal unity, community structures, social support, access to knowledge and community hope (Ahmed et al., 2004). The CMR was used to measure resilience in three local neighbourhoods in the Western Cape (Ahmed et al., 2004).

The next subsection describes how community-level indicators were extrapolated using a grounded analytical approach applied to the datasets.

The Photovoice and SCRATCHMAPS datasets were analysed separately using grounded analytical principles, and their findings were later triangulated to generate a unified set of community-level indicators.

Although global indicators of safety and peace provide a broad overview of country-level data, given their shortcomings, identifying community-level indicators was deemed crucial for assessing everyday safety and peace at the community or neighbourhood level. This study used a grounded analytical approach to identify community-level indicators of peace and safety. This method comprises a systematic and iterative participatory process that involves the community, gathers data and analyses it systematically. Themes and concepts arose directly from the lived experiences and viewpoints of community members who possess valuable knowledge and insights regarding safety and peace challenges within their community.

As outlined below, subphase 2 of the study comprised distilling the core indicators of peace and safety from the Photovoice and SCRATCHMAPS projects.

One significant drawback of this study is that we only identified community-level dimensions and indicators within low-income African settings. While these indicators might apply to other low-income settings worldwide, the community-driven approaches we adopted could be considered by others in various settings; however, different cultural and social contexts may yield different indicators.