Open Journal of Preventive Medicine
Vol.4 No.4(2014), Article ID:44526,11 pages DOI:10.4236/ojpm.2014.44020

Readiness to Screen for Domestic Violence against Women in Healthcare Uganda: Associations with Demographic, Professional and Work Environmental Factors

Stephen Lawoko1*, Emmanuel Ochola2, Geoffrey Oloya3, Joyce Piloya4, Muhamadi Lubega5, Winnie Lawoko-Olwe6, David Guwatudde7

1Department of Public Health Sciences, Karolinska Institutet, Stockholm, Sweden

2Lacor Hospital, Gulu, Uganda

3Anaka Hospital, Gulu, Uganda

4Gulu Referral Hospital, Gulu, Uganda

5Iganga Hospital, Iganga, Uganda

6Associated Children Empowerment Network (ACEN), Gulu, Uganda

7Makerere University, Kampala, Uganda

Email: *

Copyright © 2014 by authors and Scientific Research Publishing Inc.

This work is licensed under the Creative Commons Attribution International License (CC BY).

Received 18 December 2013; revised 6 March 2014; accepted 17 March 2014


Aim: We assessed demographic, professional and work environmental determinants of readiness to screen for Intimate Partner Violence among healthcare practitioners in healthcare Uganda. Methods: The Domestic Violence Healthcare Provider Survey Scale and the Demand-Control-Support questionnaire was administered to a random sample of 376 health care providers (n = 279 valid responses) from Gulu, Anaka, Lacor and Iganga hospital situated in northern and eastern Uganda. Correlation tests, t-tests, ANOVA and Multiple Linear regression were used to analyse the data. Results: Male care providers were more likely than female peers to blame the victim for the occurrence of Intimate Partner Violence in a relationship. Participants from Lacorhospital graded a lower self-efficacy and a poorer support network with regard to screening for Intimate partner violence, and a higher propensity to blame the victim when contrasted with other hospitals. Doctors experienced a lower self-efficacy with regard to IPV screening than other professions. Blaming the victim for abuse was associated with a high work load and low support at work. In addition, with increasing work control and support, participants’ appraisal of system support and self-efficacy increased. Conclusion: Gender, profession, facility of work, work demand, control and support are important determinants of the readiness to screen for IPV in healthcare Uganda, and should inform strategy for the introduction and implementation of routine IPV inquiry in healthcare Uganda.


Screening; Domestic Violence; Women; Healthcare; Uganda; Determinants

1. Introduction

1.1. Epidemiology of Intimate Partner Violence

Intimate Partner Violence (IPV), one form of domestic violence defined as behaviors within an intimate relationship that cause physical, sexual or psychological harm, including acts of physical aggression, sexual coercion, psychological abuse and controlling behaviors, is now recognized as a serious global health problem [1] . Though both male and female are victims of IPV, the known prevalence is higher and health consequences better documented for women. The World Health Organization (WHO) places the global prevalence of IPV against women at between 3% - 38% [1] with higher figures in low income countries. A substantial proportion of physically assaulted women sustain injuries ranging in severity from bruises to fractured bones, exhibit symptoms of depression, anxiety and post-traumatic stress disorder, indulge in health risk behaviors including unhealthy feeding habits, substance abuse, alcoholism and suicidal behaviors and encounter reproductive health complications including terminated and undesired pregnancies and child loss during infancy [1] -[4] . In low income countries, poverty, inadequate health services and a culture of acceptance for violence against women [1] [3] [4] further aggravate the problem. Despite the poorer health scenario, female victims of IPV underutilize community and healthcare services and exhibit constraint in their contact with healthcare providers and employers [5] , a reflection of institutional marginalization and/or incapacity to deal with IPV. The implication for further adaptation of the healthcare system to detect and manage IPV through systematic screening thus seems evident.

1.2. Screening for IPV: Global Overview, Knowledge Gap and Contribution of Current Study

Screening for IPV in healthcare requires the systematic involvement of healthcare workers in the detection and management of IPV among clients who may or may not present with direct symptoms of victimization/abuse [6] . Though systematic reviews find no evidence for the benefits of screening on women’s health outcomes per se [7] , validation of a battered woman’s situation through inquiries in healthcare may positively affect her response to treatment options [6] . In addition, IPV screening in healthcare settings appears to improve women’s satisfaction with care in general [8] , and there is general consensus among healthcare professionals that routine screening is likely to improve identification of IPV [9] . Data from low, middle and high income societal contexts suggest however that 20% - 70% of women (higher figures in low income countries) hesitate to disclose abuse to formal institutions including healthcare. Pertinent reasons hindering abused women from seeking sanctuary from formal networks include the perceived lack of confidentiality, inappropriate methods of inquiry from care providers, fear of retaliation from the abuser and stigmatizing attitudes from service providers [10] [11] . From the perspective of the healthcare system, evidence suggest that only one in ten healthcare workers routinely screen for IPV [9] , indicating the presence of barriers, which have in recent research been traced to providers’ insufficient knowledge and training in screening, conflicting professional roles governing the provider-client relations (e.g. mutual respect, fear of offending clients etc.), healthcare provider’s individual stigmatizing attitudes towards IPV and conflicting cultural values [11] -[15] . Further, demographic and profession characteristics of healthcare providers have been reported to influence the likelihood of screening, though with inconsistent results across varying study contexts. For instance, in Sweden women, doctors and nurses appear more prone to screen for IPV than males and other staff respectively [13] while in Nigeria males and social workers appear more ready to screen [15] . These discrepancies are plausibly reflecting contextual differences in working environment between the sexes/professions. Thus, the role of demographic and occupational factors as determinants of IPV screening deserves further scrutiny in each unique context, and in this study the Uganda context is scrutinized.

The mechanism through which work environmental factors may cause job strain among care-providers has long been envisaged in the Demand-Control model [16] . In simple terms, it is purported that job strain may result from high work demands coupled by low levels of work control and support, though this finding is not always consistent [17] . In the context of IPV screening, qualitative interviews with healthcare workers [14] [18] [19] have consistently implicated work-environmental characteristics such as high work demands, weak support networks and low levels of decision autonomy as possible hinders to the practice of IPV screening, but the quantification of these factors as determinants of IPV screening remains an important gap in the research. Indeed, systematic reviews of the quantitative research in the field [20] have found majority of studies on barriers to IPV screening in healthcare to focus on individual related barriers (e.g. attitudes), resource barriers e.g. (lack of referrals for abused patients) and patient-related barriers (e.g. lack of trust in care system). Understanding work environmental barriers is fundamental not only for the betterment of working conditions and strain management for staff, but also for improvement of their readiness to deliver to clients.

1.3. Study Purpose and Hypotheses

The purpose of the current study therefore was to quantify demographic, professional and work environmental factors as determinants of readiness to screen for IPV. More specifically we hypothesized that:

1) There would be differences in readiness to screen for IPV depending on demographic and professional characteristics of care providers.

2) High work demands is negatively associated with the readiness to screen for IPV among care providers.

3) Low work control is negatively associated with the readiness to screen for IPV among care providers.

4) Low work support is negatively associated with the readiness to screen for IPV among care providers.

1.4. Study Context

Though the epidemiology of IPV has over the past decade received increasing attention in the research in lowincome countries, the issue of IPV screening in healthcare is not yet sufficiently addressed [1] [3] [4] . In Uganda, the context for the current study, nationally representative data places the prevalence of physical, sexual and emotional abuse with women as victims at 25%, 20% and 33% respectively, and up to 70% of the population justify wife abuse for scenarios where a wife defies from normative roles expected of her in the house hold (e.g. burning food, neglecting her children and denying her husband sex) [21] . Recently, the authors undertook the first study in the country, to the best of our knowledge, to understand care-provider’s views on screening for IPV in healthcare using qualitative methods [14] . The study generated an ecological framework suggesting a complex interaction of factors at the individual (e.g. poor skills in detection, negative individual attitudes justifying abuse), organizational (e.g. work environment) and societal (e.g. societal acceptance of abuse of women) levels as potential barriers to the practice of IPV screening in healthcare Uganda. Basing on this theoretical framework, the current study aims at quantifying the association between readiness to screen and individual/organizational factors (e.g. demographic, occupational and work environmental factors) in healthcare Uganda.

2. Methodology

2.1. Study Design, Population and Participants

The study design was cross-sectional and self-administered structured questionnaires were used to collect participant data on readiness to screen, actual screening, demographic, occupational and work environmental characteristics.

The population of interest where healthcare providers in Northern and Eastern Uganda, where the prevalence of IPV is comparatively higher when contrasted with other parts of the country [21] . In northern Uganda, Gulu referral hospital (250 beds), Anaka district hospitals (120 beds) and Lacor Hospital (480 beds) were chosen, while in eastern Uganda, Iganga district hospital (120 beds) participated. These hospitals serve mainly patients from the northern and eastern Uganda regions, though patients are received from neighbouring communities and countries including DRC Congo, Southern Sudan and Kenya. Currently, there are no specific guidelines on routine screening for IPV at these hospitals, as is the case in all Ugandan hospitals.

The inclusion criteria were healthcare providers in regular contact with female patients. Excluded workers comprised laboratory personnel, administrative personnel and other categories that do not interact with patients (e.g. technical staff). The eligible participants were randomly drawn from all relevant departments that female clients come in contact with. These include (but are not limited to) general outpatients unit, emergency department, obstetrics and gynaecology, maternity wards, Ear, Nose and Throat (ENT), pediatric care and dental care. At each hospital, a registry of eligible participants was obtained from the administration. At initiation of the study, the 4 hospitals together had approximately 620 healthcare workers meeting the inclusion criteria with the following approximate distribution 300 from Lacor hospital, 130 from Gulu hospital, 60 from Anaka hospital and 130 from Iganga hospital. Stratified random sampling was used to draw a representative sample of 376 participants, of which 282 agreed to participate in the study. Three questionnaires were returned unfilled, resulting in an effective sample of 279 participants with the following distribution per hospital; Lacor hospital n = 122, Gulu hospital n = 63, Iganga hospital n = 61, Anaka hospital n = 33. The total response rate was 79%.

Demographic and Occupational Characteristics of Participants

As indicated in Table 1, the majority of participants were from Lacor hospital, of midwife occupation, female gender, Catholic religion, of Nilotic/Nilo-hamite ethnic group and with 0 - 5 years in service. Participants were on average 34 years old.

2.2. Procedures and Ethical Considerations

Workers within all departments were informed verbally by department heads of the impending study a number of weeks in advance. The selected participants received the questionnaire and information while registering for their work session. The questionnaires, accompanied by information letters about the study, were self-administered. The information included background to the study, its relevance, procedures and ethical considerations. The ethical considerations emphasized informed consent, voluntary participation and confidentiality. Ethical approval was sought and granted by the Institutional Review Board (IRB) of Makerere University School of Public Health (MUSPH) and the Uganda National Council of Science and Technology (UNCST), the two bodies with mandate to approve research concerning human subjects in Uganda.

2.3. Study Variables

2.3.1. Dependent Variables

Healthcare providers responded to a previously validated questionnaire, the domestic violence healthcare provider survey scales [22] , which assess the readiness to screen for IPV as well as actual frequency of IPV screening. The instrument has been tested for reliability and validity in the study context Uganda [23] and its contextual validity verified in a qualitative study in the same context [14] .

The Readiness to screen measure consists of the following six subscales, with varying number of items scored on a Likert scale that ranges from 1 (strongly disagree) to 5 (strongly agree). For each individual, a score is calculated under each scale as the sum of individual item responses:

The perceived self-efficacy subscale scale (7 items) assesses providers own perceived efficacy in inquiring about IPV with regard to time constraints, strategies for inquiry, access to information and confidence. Individual scores range between 7 - 35, and the higher the individual score the higher the perceived self-efficacy in handling IPV.

The system support sub-scale (4 items) assesses healthcare providers’ access to support networks for referral/ management of IPV victims. Individual scores range between 4 - 20, and the higher the individual score the higher the perceived system support.

The professional roles resistant/fear of offending clients sub-scale (7 items) assesses whether providers perceive inquiries about IPV to conflict with ethical issues/roles governing their communication with clients (e.g. fear of offence, privacy invasion and provocative). Individual scores range between 7 - 35, and the higher the individual score the higher the professional role resistance/fear of offence.

Table 1. Demographic and professional characteristics of participants.

The blame victim sub-scale (7 items), assesses providers attitudes towards victims (e.g. views that victim’s personality, breaking of normative roles, passivity and provocation are causes of abuse). Individual scores range between 7 - 35, and the higher the individual score the higher the propensity to blame the victim.

The victim (4 items) and provider (5 items) safety sub-scales, which assess whether providers perceive inquiries about IPV from batterers to jeopardize safety of victims and care provider. For provider safety, individual scores range between 5 - 25, and the higher the individual score the lower the concerns about care provider safety. For victim safety, individual scores range between 4 - 20, and the higher the individual score the lower the concerns about victim safety.

2.3.2. Independent Variables

Working conditions/environment was measured using the Demand-Control-Support Questionnaire (DCQ) [16] . Initially developed for use in healthcare settings, the questionnaire assesses; work-related demands in terms of working speed, intensity, efforts, time and conflicting demands (5 items), work control in terms of possibilities for new knowledge, skill development, initiative taking, work variation and autonomy (5 items) and work support with regard to co-worker/supervisor support and apprehension, work atmosphere, getting on/enjoyment with colleagues (6 items). The responses to each item range between 1 - 4 (strongly disagree to strongly agree). For each individual, a score (index) is created on work demands, control and support respectively based on individual sum on responses to each item. The questions have been extensively validated previously.

Demographic and professional attributes: The questionnaire gathered data on demographic and occupational information on each respondent (i.e., age, gender, marital status, religion, ethnicity, profession and years of work experience).

2.4. Statistical Analysis

Data were checked for normality before analysis and conditions were fulfilled. Means and frequencies were used to describe study participants with respect to studied variables. Correlation tests, t-tests, ANOVA, and Multiple Linear Regressions were applied in the assessment of associations between outcome measures and demographic, professional and work environment indicators. Statistical significance was assumed at p < 0.05 for all analyses, and all data were analyzed in SPSS version 21.

3. Results

3.1. Associations between Readiness to Screen Indicators and Demographic/Occupational Variables

Table 2 provides means and standard deviations for the DVHPS subscales by demographic/professional characteristics. Healthcare workers from Iganga hospital (F = 4.2; p < 0.01) and of male gender (t = 2.2; p < 0.05) were more likely to blame the victim for being abused. In addition, male participants to a higher degree than female peers reported concerns regarding provider safety in relation to IPV screening (t = 2.2; p < 0.05). Doctors (F = 3.5; p < 0.05) and participants from Lacor and Iganga hospitals (F = 3.3; p < 0.05) on average reported lower efficacy in relation to IPV screening than other participants. Further, respondents from Lacor hospital reported on average a poorer system support with regard to IPV screening than peers in other hospital (F = 9.2; p < 0.001). Nilotic/Nilo-hamite participants expressed on average more concerns about victim safety in relation to IPV screening than other participants (t = 2.2; p < 0.05). Finally, religion, years in service and age showed no association with any of the indicators of readiness to screen examined in this study.

3.2. Bivariate Associations between Readiness to Screen Indicators and Working Conditions

As shown in Table 3, work demand was negatively associated with self-efficacy but positively associated with victim blame, i.e. with an increasing work demand, perceived self-efficacy (p < 0.05) reduced and propensity to blame the victim for IPV increased (p < 0.05). Work control on the other hand was positively associated with self-efficacy and system support, i.e. with increasing work control, perceived self-efficacy (p < 0.01) and system support increased (p < 0.01). Work support correlated positively with self-efficacy and system support but negatively with victim blame and professional role conflicts, i.e. with increasing work support perceived self-efficacy (p < 0.01) and system support (p < 0.05) increased, but propensity to blame the victim (p < 0.05) and professional role conflicts in relation to IPV screening decreased (p < 0.05).

3.3. Multivariable Models for Readiness to Screen Indicators

As indicated in Table 4, hospital, profession, work control and work support remained significantly associated with Self-efficacy in the multivariable analysis. Participants from Anaka hospital exhibited a higher efficacy than peers at Lacor. Doctors reported a lower efficacy than other health workers and with increasing work control and support self-efficacy increased.

Hospital, work control and support remained significantly associated with system support in the multivariable analysis (Table 4). Participants from Lacor hospital reported a lower system support than peers in other participating hospital and with increasing control and support at work, participants’ appraisal of system support increased.

Table 2. Bivariate association between demographic/professional characteristics, Subscales of the DVHPS and frequency of screening.

Note. M = mean; SD = Standard Deviation; aScores stretch between 7 - 35; b4 - 20; c7 - 35; d7 - 35; e4 - 20; f5 - 25.

Table 3. Bivariate correlations between indicators of working conditions, subscales of the DVHPS and frequency of screening.

*p < 0.05; **p < 0.01.

Table 4. Regression models for self-efficacy, system support and victim blame.

Note: Only variables significantly related with the outcome variable at bivariate level are included in each model. Modeling was not performed for provider safety, victim safety and professional role conflicts as they were each associated with only one factor at the bivariate level. *p < 0.05; **p < 0.01; ***p < 0.001.

Hospital, gender and work support remained significantly associated with victim blame in the multivariable analysis. Participants from Anaka hospital and of female gender were less likely to blame the victim than Lacor hospital and male peers respectively, and propensity to blame the victim reduced with increasing support (Table 4).

4. Discussion

We examined the demographic, occupational and environmental determinants of readiness to screen for IPV in healthcare in Uganda, using data from 4 regional hospitals in Northern and Eastern Uganda. In general, the readiness to screen was associated with many of the studied factors as discussed more in detail in the following text.

4.1. Readiness to Screen vs Demographic/Occupational Factors

Female care providers were less likely to blame the victim for IPV, and expressed lower concerns about victim safety in relation to IPV screening in healthcare than male peers. These findings corroborate previous work in the field [13] , and could be reflecting circumstances where female care providers are more likely to understand patient peers, being themselves potentially exposed to IPV. Studies show indeed that between 23% - 33% of female care providers are victims of IPV [24] [25] , a figure comparable to IPV prevalence observed in the general population of women, including in Uganda [21] . The findings are however at odds with other studies suggesting a higher likelihood of screening among men [15] , warranting further scrutiny. Whatever the case, the genderdividein care providers’ attitudes regarding IPV screening present bottlenecks to the practice. Male practitioners in Uganda may benefit from training packages tailored to address attitudinal change if IPV screening is to develop to an effective practice in Ugandan healthcare.

Participants from Lacor hospital (a private mission non-profit facility) experienced in general a lower preparedness to screen for IPV than peers at other hospitals (government owned facilities). The Ugandan government recently endorsed the domestic violence bill, sending a clear message to the public and institutions on its commitment to champion gender equality in the country. Following this crucial milestone, the health sector followed suite in developing tools and orienting staff and health units in gender-based violence healthcare. It is plausible that public owned health facilities are to a higher degree than private owned facilities, under pressure and better oriented to adopt measures to detect and manage violence against women.

Doctors experienced in general a lower efficacy in handling IPV than other staff. Due to their position at the frontline of healthcare, nurses and midwives represent women’s first contact with healthcare, when the known physical symptoms of IPV are most pronounced (e.g. bruises and fractures). They are therefore more prone to react through inquiry than doctors. Another plausible explanation is that nursing and midwifery remain largely female dominated professions, while doctors comprise mainly men in Uganda. The associations observed thus may be a reflection of the underlying gender-inequality in professions, where as previously discussed, men disguised here as doctors, are less prepared to screen. Future studies to scrutinize this hypothesis will however benefit from a gender-stratified analysis of determinants of readiness to screen. Contrasting with previous works, the current findings to some extent corroborate works showing lower proneness to screen for IPV among doctors, nurses and midwives when contrasted with social workers in Nigeria [15] , but are inconsistent with data indicating a higher proneness among doctors and nurses when compared with midwives in Sweden [13] . Such contradictions demonstrate further that the association between demographic/professional characteristics and readiness to screen is not uni-directional but could vary depending on underlying differences in the socio-cultural context in which professionals practice.

4.2. Readiness to Screen vs Work Environment

The role of work environmental factors as possible determinants of IPV screening has previously been implied in qualitative studies [14] , though to the best of our knowledge, studies on their quantification until now have been lacking. Blaming the victim for IPV was associated with a high work load and low work support as hypothesized. Further, low control and low support at work diminished participants’ appraisals of system support. Moreover, a low work control and low support was associated with a poor self-efficacy in relation to IPV screening. Overall therefore, the readiness to screen for IPV appeared negatively affected by heavy work load, poor support and control. Understaffing in the health sector in many low income countries and its implication on work environment for practitioners has been a subject of discussion in many years [26] . With poor environmental conditions at work, screening for IPV may be viewed as an extra stressor among already over-worked care providers, leading to negative sentiments and low appraisals of their efficacy in screening as observed in this study. This coupled with lack of knowledge of supportive networks (e.g. referral services) for IPV victims, lack of protocols for IPV screening, and lack of autonomy on critical issues related to IPV [14] potentially render the practice of IPV screening difficult in Uganda and elsewhere. Consequently, organizational interventions addressing the wider resource shortages in healthcare, development of feasible and simple screening tools, and strategic management schemes for IPV victims could ease the work environmental tensions likely related to screening. In addition staff training initiatives directed at attitudinal change may gradually increase acceptance of the practice as an integral part in the healthcare of women.

4.3. Methodological Issues and Future Research

The methodology applied in this study responds adequately to the research questions. In addition, the questionnaire used was previously tested for structural validity in a pilot study in the study context with promising results [23] , and its contextual validity verified in a qualitative study in the same context [14] . Nonetheless, we limited our study of determinants to demographic, occupational and environmental factors. Other potential determinants can be found at the macro-levels of society (e.g. community acceptance of IPV, availability of resources at the community level etc.). Such Macro-level attributes are likely to impact on actions at the organizational and individual levels as well. With the relatively recent emergence of multilevel analysis techniques, modeling the ecological profile of determinants of IPV screening will soon be possible. Finally, our study was geographically limited to northern and eastern Uganda. A part from Iganga hospital, all other studied hospitals are located in regions that have only recently (2008) attained peace following a 20-year long civil war. One may argue that healthcare facilities in recently hostile environments are under-resourced, and therefore ill-prepared to address IPV issues. Caution should be exercised in generalizing these finding to Uganda as a country until the results can be replicated in other regions of the country, even though the results appear congruent with findings in other countries with longstanding democracy and peace [13] .

5. Conclusion

In conclusion, gender, profession and working conditions are important determinants of the readiness to screen for IPV in healthcare Uganda. Male staff, doctors and participants from private health facility appeared less ready to screen for IPV than female, other staff and participants from public facilities. In addition, High work demands, low support and weak autonomy over work, impacted negatively on the readiness to screen. These findings strengthen the growing literature highlighting the important role of demographic and professional factors in screening for IPV in healthcare, and add new knowledge regarding work environmental factors as determinants of readiness to screen for IPV, which should inform strategy for the introduction and implementation of routine IPV inquiry in healthcare Uganda.


Funding: We are most grateful to the Swedish Council for Working Life and Social Research (FAS/Forte) and the Marie-curie program for funding this study as part of the COFAS program. We are also most grateful to the efforts of the administrative staff at each respective hospital, and all participants in the current study without whom this work would not have been realized.

Competing Interest


Ethical Approval

Granted by the Institutional Review Board (IRB) of Makerere University School of Public Health (MUSPH) and the Uganda National Council of Science and Technology (UNCST).


  1. WHO (2002) World Report on Violence and Health. World Health Organization, Geneva.
  2. Campbell, J. (2002) Health Consequences of Intimate Partner Violence. Lancet, 359, 1331-1336.
  3. Emenike, E., Lawoko, S. and Dalal, K. (2008) Intimate Partner Violence and Reproductive Health of Women in Kenya. International Nursing Review, 55, 97-102.
  4. Okenwa, L., Lawoko, S. and Jansson, B. (2011) Contraception, Reproductive Health and Pregnancy Outcomes among Women Exposed to Intimate Partner Violence in Nigeria. The European Journal of Contraception and Reproductive Health Care, 16, 18-25.
  5. Gage, A. (2005) Women’s Experience of Intimate Partner Violence in Haiti. Social Science & Medicine, 61, 343-364.
  6. (1992) American Medical Association Diagnostic and Treatment Guidelines on Domestic Violence. Archives of Family Medicine, 1, 39-47
  7. (2004) Screening for Family and Intimate Partner Violence. Systematic Evidence Review, Number 28, US Department of Health and Human Services Agency for Healthcare Research and Quality, Rockville.
  8. John, I.A., Lawoko, S. and Oluwatosin, A. (2011) Acceptance of Screening for Intimate Partner Violence, Actual Screening and Satisfaction with Care Amongst Female Clients Visiting a Health Facility in Kano, Nigeria. African Journal of Primary Health Care & Family Medicine, 3, 6 p.
  9. Furniss, K., McCaffrey, M., Parnell, V. and Rovi, S. (2007) Nurses and Barriers to Screening for Intimate Partner Violence. MCN: The American Journal of Maternal/Child Nursing, 32, 238-243.
  10. Okenwa, L, Lawoko, S. and Jansson, B. (2009) Factors Associated with Disclosure of Intimate Partner Violence among Women in Lagos Nigeria. International Journal of Injury and Violence Research, 1, 37-47.
  11. WHO (2005) WHO Multi-country Study on Women’s Health and Domestic Violence against Women. World Health Organization, Geneva.
  12. Erikson, M.J., Hill, T.D. and Siegal, R.M. (2001). Barriers to Domestic Violence Screening in the Padiatric Setting. Pediatrics, 108, 98-102.
  13. Lawoko, S., Sanz, S., Helstrom, L. and Castren, M. (2011) Screening for Intimate Partner Violence against Women in Healthcare Sweden: Prevalence and Determinants. ISRN Nursing, 2011, Article ID 510692.
  14. Lawoko, S., Seruwagi, G.K., Marunga, I., Mutto, M., Ochola, E., Oloya, G., Piloya, J. and Lubega, M. (2013) Healthcare Provider’s Perceptions on Screening for Intimate Partner Violence in Healthcare: A Qualitative Study of Four Health Centres in Uganda. Open Journal of Preventive Medicine, 3, 1-11.
  15. John, I.A., Lawoko, S., Svanström, L. and Mohammed, A.Z. (2010) Health Care Providers Readiness to Screen for Intimate Partner Violence in Northern Nigeria. Violence and Victims, 25, 689-704.
  16. Karasek, R.A. (1979) Job Demands, Job Decision Latitude, and Mental Strain: Implications for Job Redesign. Administrative Science Quarterly, 24, 285-307.
  17. Kain, J. and Jex, S. (2010), Karasek’s (1979) Job Demands-Control Model: A Summary of Current Issues and Recommendations for Future Research. In: Perrewé, P.L. and Ganster, D.C., Eds., New Developments in Theoretical and Conceptual Approaches to Job Stress (Research in Occupational Stress and Well-Being, Volume 8), Emerald Group Publishing Limited, Bingley, 237-268.
  18. Laisser, R.M., Lugina, H.I., Lindmark, G., Nystrom, L. and Emmelin, M. (2009) Striving to Make a Difference: Health Care Worker Experiences with Intimate Partner Violence Clients in Tanzania. Health Care for Women International, 30, 64-78.
  19. Djikanovic, B., Celik, H., Simic, S., Matejic, B. and Cucic, V. (2009) Healthcare Professionals’ Perceptions of Intimate Partner Violence against Women in Serbia: Opportunities and Barriers for Response Movement. Patient Education and Counseling, 80, 88-93.
  20. Sprague, S., Madden, K., Simunovic, N., Godin, K., Ngan, K., Bhandari, M. and Goslings, J.C. (2012) Barriers to Screening for Intimate Partner Violence. Women & Health, 52, 587-605.
  21. Uganda Bureau of Statistics (UBOS) and ICF International Inc. (2012) Uganda Demographic and Health Survey 2011. UBOS and Calverton, Kampala, ICF International Inc., Maryland.
  22. Maiuro, R.D., Vitaliano, P.P., Sugg, N.K., Thompson, D.C., Rivara, F.P. and Thompson, R.S. (2000) Development of a Health Care Provider Survey for Domestic Violence: Psychometric Properties. American Journal of Preventive Medicine, 19, 245-252.
  23. Lawoko, S., Mutto, M. and Guwatudde, D. (2012) Piloting the Domestic Violence Healthcare Providers’ Survey for Use in Uganda: Testing Factorial Structure and Reliability. Psychology, 3, 947-952.
  24. Stenson, K. and Heimer, G. (2008) Prevalence of Experiences of Partner Violence among Female Health Staff: Relevance to Awareness and Action When Meeting Abused Women Patients. Women’s Health Issues, 18, 141-149
  25. Rodríguez-Borrego, M.A., Vaquero Abellán, M., Bertagnolli, L., Muñoz-Gomariz, E., Redondo-Pedraza, R. and Mu- ñoz-Alonso, A. (2011) Intimate Partner Violence: Study with Female Nurses (in Spanish). Atención Primaria, 43, 417- 425.


*Corresponding author.