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Measurement of perceived pressures in psychiatry: paper-and-pencil and computerized adaptive version of the P-PSY35 scale



Formal coercion in psychiatry is widely studied yet much less is known about pressures patients may experience, partly because of the very few measures available. The goal of this study was to validate the P-PSY35 (Pressures in Psychiatry Scale) and provide a paper-and-pencil and a computerised adaptive test (CAT) to measure pressures experienced by patients in psychiatry.


The P-PSY35 items were developed with users. Patients were evaluated during psychiatric hospitalisation or through an online survey. Mokken scale analysis and Item response theory (IRT) were used to select and estimate the items parameters. A Monte-Carlo simulation was performed to evaluate the number of items needed to transform the paper-and-pencil test into a reliable psychometric CAT.


A total of 274 patients were assessed. The P-PSY35 demonstrated good internal validity, internal consistency, convergent and divergent validity. The P-PSY35 could be substantially shortened while maintaining excellent reliability using the CAT procedure.


The P-PSY35 was developed in collaboration with users. It is a psychometrically rigorous tool designed to measure experienced pressures in French-language. The development and successful validation of the P-PSY35 represent a welcome step towards implementing and evaluating programs aimed at reducing negative consequences of coercion.


In psychiatry, the use of coercion is justified by the need to protect the patients and/or other people. Formal coercion consists of the legal procedures to force someone into treatment while informal coercion comprises various forms of pressure used by medical staff or relatives to persuade someone to undergo treatment [1]. Perceived coercion describes the coercion experienced and felt by a person during treatment [2].

The negative impact of coercion has been well studied [3,4,5,6,7]. Formal coercion has been linked to a negative impact on patients’ quality of life and their clinical course [7]. Formal coercion was also associated with decreased satisfaction with care and treatment adherence in the long-term [3, 8]. Previous experience of formal coercion was linked to a higher risk of use of formal or informal coercion in the future [9,10,11]. Additionally, previous experience of coercive measures may impact patient satisfaction and increase their perception of coercion in subsequent voluntary hospitalisations [12]. Finally, disengagement from services and negative therapeutic relationships are also associated with perceived coercion [4, 6, 13].

While formal coercion in psychiatry has been comprehensively studied, there is a knowledge gap regarding the other forms of pressure experienced in psychiatry. In fact, much less is known about their specifics and potential short-, medium- and long-term adverse effects [14]. Because of their more subtle nature, several accounts of treatment pressures have been proposed in the literature. Lovell [15] described four forms of informal coercion that could be represented on a continuum [16, 17] from the most to the least coercive: coercion, coerced voluntarism, utilitarian compliance and persuasion. Lidz and colleagues [13] also proposed to distinguish positive and negative pressures within informal coercion. The key difference between these symbolic pressures lied in the willingness to encourage or threaten the person. Angell [18] developed a continuum of coercive strategies used by practitioners to maintain treatment compliance. This time, six forms of coercion were included: persuasion, monitoring, incentives, leverage, threat, and invocation of authorities.

The most widespread model of pressures in mental health literature is maybe that of Szmukler & Appelbaum [1]. Treatment pressures are presented as five ordered categories: persuasion, interpersonal leverage, inducements, threats and compulsion. As such, persuasion consists of appealing to the patient’s reason and emotions to make them accept a therapeutic measure. Interpersonal leverage consists of using the emotional connection caregivers or relatives have with the patient to get them to agree to a therapeutic measure. Inducements can be understood as making certain benefits (e.g., cigarettes) contingent on acceptance of a therapeutic measure (e.g., only if the patient takes medication). Threats can be described as suggesting to the patient that they will lose something (e.g., monetary or housing benefits) if they refuse a therapeutic measure. Lastly, compulsion is intended as legally forcing someone to undergo psychiatric treatment, by compulsorily admit them to hospital or commit them to undergo outpatient treatment (OPC). [1]. Among the pressures exerted on patients out of legal status, only threats were however identified by these authors as coercion [1].

Trying to clarify the terminology used in the literature, Yeeles defined “informal coercion” as “a broad term covering various non- statutory treatment pressures used on a day- to- day basis by clinicians, carers, family members, and the welfare and criminal justice systems to improve patients’ stability and treatment adherence.” [19]. This study focused on this specific form of pressures experimented by patients in the context of psychiatry and aimed to provide a rigorous psychometric tool to measure them. Indeed, nowadays it is difficult to measure treatment pressures with existing tools. In a recent literature review, we highlighted that several tools existed to assess the patients’ level of perceived coercion [15]. However, only specific steps of psychiatric care were usually covered, such as patients admission or their interactions with caregivers within the hospital. Few instruments were available to caregivers to evaluate their practice in other settings. The focus on the hospital setting is problematic because it leaves out a variety of contexts where pressures are used and experienced, as well as all forms of pressures applied by relatives. Indeed, results from a qualitative study indicate that patients experience feelings of disempowerment in daily life due to the close monitoring of their adherence to treatment by their informal caregivers [20]. Only one measure [21] included both in- and outpatient services. Burns and colleagues [22] proposed a 4-item instrument, adapted from Monahan and colleagues [23], that aimed, in the context of assisted outpatient treatment, to specifically measure patients’ experiences of leverage in four domains of the social welfare: finance, housing, criminal justice and child custody. However, these four items represented rather severe forms of informal coercion that are most often exerted by professionals but not by relatives.

In view of these observations, there is a need for a new tool able to provide an overview of the range of pressures that voluntary and involuntary patients may experience in various in- and outpatient settings. Therefore, the goal of this study was to develop and validate such a rigorous psychometric tool. The scale has been designed to assess the overall perception of pressure for a wide range of psychiatric disorder and, given its adaptive nature, to allow very short administration times. Moreover, the items content was designed to cover pressures from both professionals or relatives.

Material and methods


Participants were recruited between February 2022 and September 2023 using the following recruitment strategy: patients were recruited in six psychiatric hospitals in the French-speaking part of Switzerland, and through an online survey. The set of questions and scales was in both instances identical. Both hospital and online participants should be at least 18 years old and no older than 65 to be included in the study. People diagnosed with dementia (F00-F09) or Intellectual disability (F70-F79) were excluded. Moreover, participants from the online survey were informed that they could take part in the study only if they were or had been under psychiatric care, had a psychiatric diagnosis and were sufficiently proficient in French. A correct answer to two control items (i.e., “In order to check your concentration, please answer "rather yes" to this question”) and to have completed sociodemographic and diagnostic data were also required in order for online participants to be included in the analysis. In hospitals, participants were contacted by a research assistant (trained master degree psychology student) in the presence of their attending nurse who provided them information on the study. After a period of consideration, people who agreed to participate signed the consent form and were interviewed individually. The online survey was advertised on various social media platforms and was relayed by patients’ associations.

A total of 274 patients were recruited and included in the study, of which151 (55.1%) were women. Their age ranged from 18 to 64 years old (M = 37.86, SD = 12.70). Primary diagnosis, based on the International Statistical Classification of Diseases and Related Health Problems 10th Revision (ICD-10), were the following: Mental and behavioural disorders due to alcohol use (F10) N = 8 (2.9%), Mental and behavioural disorders due to psychoactive substance use (F11–F19) N = 11 (4.0%), Schizophrenia (F20–F29) N = 63 (23.0%), Mood affective disorders—mania (F30–F31) N = 29 (10.6%), Mood affective disorders – depression (F32–F39) N = 85 (31.0%), Neurotic, stress-related and somatoform disorders (F40–F48) N = 17 (6.2%), Personality disorders (F60–F69) N = 40 (14.6%), Psychological development disorders (F80–F89) N = 5 (1.8%) and No diagnostic information available (first psychiatric hospitalisation) N = 16 (5.8%).


Patients were asked to report their gender, age, and most significant CIM-10 diagnosis. In some instances, patients were assessed during their first psychiatric hospitalisation and no diagnostic information was yet available.

Development of the pressures in psychiatry scale (P-PSY35)

Being interested in measuring the total amount of pressure experienced by patients, we aimed at designing a unidimensional scale including various forms and levels of severity of pressures, the Pressure in Psychiatry scale (P-PSY35). The items of our pressure questionnaire were generated based on a literature review and through several consultations with a peer specialist and an expert panel [24]. The objective was to generate many items in order to select the best subset for the final scale. Because we were interested in the possibility of measuring change between different measurement occasions, we instructed patients to answer based on the last 3 months period. If needed, this instruction can be easily modified to assess the lifetime experience of treatment pressures in psychiatry.

A research assistant with lived experience of mental illness and recovery embedded within the research team and two psychologists trained in psychometrics and questionnaire development conducted the literature review. About 10 domains in all aspects of life (e.g., health, therapeutic means, belief, finance, work, education, social activities, addiction) related to pressures (stay well pressures, monitoring, persuasion, interpersonal pressure, leverage, threats, deception, decision of one another, show of force, use of violence) were identified. These domains served as a guide to generate items. The peer specialist was involved in reviewing the items suggested by psychologists and proposing new ones. In total, about 200 items were identified. After removing potential duplicates and ill-formulated items, this set was reduced to roughly 115 items. The items were further reviewed and selected using an expert panel session to improve content validity. The panel included three mental health professionals with a track record of research on coercion. All items were reviewed one by one, and changes were discussed on a consensus basis: The first step was to ask panel experts to read all items. The second step involved discarding, rephrasing, or suggesting new items. Items were modified one at a time directly on the screen during the open discussion until validation by all the participants [24]. The final questionnaire contained 98 items answered on a 5-point Likert scale: 0 = “Not at all”, 1 = “Not much”, 2 = “Neutral”, 3 = “A little bit”, and 4 = “Definitively”.

Coercion ladder

The Coercion Ladder [25] was originally adapted from the Cantril Ladder [26]. It is a visual analogue tool on which the patient is asked to mark the degree of perceived coercion on a scale from 1 (Minimum use of coercion) to 10 (Maximum use of coercion). Participants were instructed to answer in relation to their entire experience of psychiatric care.

Coercion experience scale (CES)

The CES [27] is a scale designed to measure patients’ experiences of coercive measures. The scale was first developed in German before being translated and published in English [27] and then validated in French [28]. In this study, we only used the second item which has been designed to evaluate the extent to which patients consider coercive measures stressful on a visual analogue scale from 0 to 100.

Informal coercion dichotomous items

Pressures to adhere to treatment (‘leverage’) were assessed using a 4-item instrument proposed by Burns and colleagues [22], which was adapted from Monahan and colleagues [23]. It aims to measure patients’ lifespan experiences of leverage in four domains of the social welfare: finance, housing, criminal justice and child custody. These items represent rather severe forms of informal coercion. They correspond to inducements and threats as defined by Szmukler & Appelbaum’s [1].

Satisfaction regarding hospitalisation (ANQ)

The Swiss National Association for Quality Development in Hospitals and Clinics (ANQ) developed a satisfaction measure for patients in psychiatry. The questionnaire includes 6 five-point Likert-type items assessing quality of treatment, information and communication, medication, patient’s implication and discharge preparation [29]. We used the first item (that focused on the perceived quality of psychiatric care) and the total score (that can be computed to assess the global satisfaction of the patient).

The self-stigma scale—short (SSS-S)

The SSS-S is a 9-item questionnaire designed to measure the degree of self-stigma of individuals from various minority groups. It consists of a cognition score, an affect score, a behaviour score, and a total score. In the present study, we used the French-version of the SSS-S [30].

The rosenberg self-esteem scale (RSS)

The RSS is the most frequently used instrument to measure self-esteem [31]. It consists of 10 items with a total score ranging from a minimum of 10 to a maximum of 40. Participants respond on a Likert scale by checking one of the four options: “strongly disagree”, “disagree”, “agree”, and “strongly agree”.

The beck hopelessness scale (BHS)

The BHS is a widely used questionnaire that measures negative expectations about the future [32]. The inventory is a self-report measure and consists of 20 items scored on a true–false scale. A total score can be computed and ranges from 0 to 20, with higher scores reflecting higher levels of hopelessness. In the present study, we used the French-version of the BHS [33].

Self-reported health

One item of the ANQ questionnaire is a self-reported five-point Likert-type item about the patient self-perceived global health [29]. Patients can rate their perceived actual health between “bad” and “excellent”.


The internal validity of the P-PSY35 was assessed first. This phase aimed to select the final set of items on the basis of the internal structure of the test. The reliability of the scale and the model goodness of fit were then estimated. Next, to evaluate convergent and divergent validity, we studied the relationship between the P-PSY35 score and several other scales. We hypothesised that the P-PSY35 scores would be positively correlated with the Coercion ladder, the CES 0–100 item, the Informal coercion dichotomous items, the SSS-S and the BHS scores. We also hypothesized a negative correlation with the ANQ and the RSS scores. To evaluate the divergent validity, we hypothesized we would find no significant correlation between the P-PSY35 and the Self-reported Health measure.

Finally, a Monte-Carlo simulation was performed to evaluate the number of items needed to transform the paper-and-pencil test into a psychometric CAT with a high reliability (r ≥ 0.90).

Statistical analysis

Internal validity

Given the large number of items at the beginning of the procedure, these were first screened using Mokken scale analysis. This is a non-parametric method based on the monotonicity of the item response function. Items with low scalability (Ho < 0.30) were discarded. The “mokken” R-package was used [34]. Next, remaining items were selected on the basis of an item fit statistic. We discarded items with significant signed chi-squared test [35, 36]. The Multidimensional Item Response Theory (mirt) package for R was used [37]. Finally, items pairs were screened for local dependency using Yen's Q3, with values under 0.3 suppressed [38, 39]. From the locally dependent pairs, we deleted items which had less information based on their information curves. A final item fit statistic test was performed at the end of the item selection procedure to ensure all final items did not contribute negatively to the overall fit of the scale. Model fit and items parameters were then estimated using the mirt package for R and a graded response model. Several indicators of model fit were used: the Root Mean Square Error of Approximation (RMSEA), the Tucker–Lewis fit Index (TLI), the Comparison Fit Index (CFI) and the Standardized Root Mean Squared Residual (SRMSR). RMSEA values ≤ 0.06, CFI and TLI values ≥ 0.95, and SRMRS ≤ 0.08 were interpreted as good fits, whereas RMSEA values ≤ 0.08, CFI and TLI values ≥ 0.90 and SRMRS ≤ 0.10 were considered as indicating acceptable fit [40].


The reliability of the P-PSY35 scale was estimated using McDonald’s model-based Omega (ω) [41] and Cronbach’s alpha (α) coefficients. We also estimated the Marginal reliability (Rxx) [42]. Reliability coefficients above 0.80 were considered good and above 0.90 were considered excellent [41, 43]. The “psych” and “mirt” R-package were used [37, 44].

Convergent validity

The convergent validity coefficients between the P-PSY35 and the other scales were estimated using Pearson correlation coefficients and Spearman’s Rho coefficient when the indicator was dichotomous. Under Classical Test Theory (CTT) the score reliabilities (more precisely their square root) act as an upper bound for validity coefficients. Therefore, the acceptable range is typically lower than for reliability coefficients [45]. Correlation coefficients between 0.40 and 0.60 were considered as good and any values higher than 0.30 (a medium effect size, according to Cohen [46]) as satisfactory.

CAT Simulations

We used the Firestar software designed to simulate CAT with polytomous items [47]. A large number of participants (10,000) were simulated to achieve accurate estimates under reasonable computing time. The simulated thetas were sampled from a normal distribution with a mean of 0 and a standard deviation of 1 which correspond to the level and dispersion of the original sample. Minimum and maximum thetas ranged between − 4 and 4 with increments of 0.05. The maximum number of items to administer was set to 35 and the minimum was 2. The stopping rule was set to a standard error corresponding to a reliability of 0.90. Interim theta estimations were carried out using expected a posteriori (EAP) estimations. The next items were selected using the Fisher maximum information method. During the Firestar simulation, we recorded the minimum, maximum, mean and median numbers of items administered before the stopping criterion. Pearson correlations were estimated between simulated and estimated thetas, and the mean reliability was based on the final standard errors.


Out of the 98 original items, results of the Mokken analysis allowed us to discard 17 items (#2, #20, #21, #22, #23, #30, #37, #39, #44, #54, #56, #60, #64, #66, #70, #91 & #95). The 81 remaining items were then subjected to item fit analysis. It allowed us to discard 24 items (#3, #5, #11, #13, #15, #16, #31, #32, #33, #38, #42, #43, #47, #50, #57, #63, #69, #73, #80, #87, #89, #90, #92, #94). The 57 remaining items were subjected to local independence analysis. Examination of items pairs allowed use to discard 20 items (#4, #7, #8, #17, #18, #24, #27, #28, #29, #45, #55, #58, #61, #65, #68, #76, #81, #82, #88, #97). Finally, two additional items were discarded based on a significant signed chi-squared test (#36, #86). The final model was fitted on the remaining 35 items (Table 1). The English language translation of the final items is provided in Table 2.

Table 1 French language version of the P-PSY35
Table 2 English language version of the P-PSY35

Estimate of model goodness of fit indicated adequate overall model fit (RMSEA = 0.0648; TLI = 0.9065; CFI = 0.9132; SRMR = 0.0806). The P-PSY35 total information curve is presented in Fig. 1. The maximum information is reached when theta equals 1.15 standard deviation above the mean. Items loadings and parameters are provided in Table 3. All 35 items had substantial loadings.

Fig. 1
figure 1

Information curve of the P-PSY35-

Table 3 Final scale items loadings and graded response model item parameters

Estimates of reliability were excellent (ω = 0.950; α = 0.949; Marginal reliability Rxx = 0.925).

Correlations between the P-PSY35 and other scales are presented in Table 4. Most correlation coefficients were substantial, significant and in the expected direction indicating good convergent validity. Correlations between the P-PSY35, the RSS and the BHS were typically lower and not statistically significant. To elucidate whether this could be attributed to the P-PSY35 scale or if it depicted a more general result indicating no relationship between pressures and Self-esteem respectively Hopelessness, we conducted a post-hoc analysis. We correlated the informal coercion dichotomous items (Finance, Housing, Criminal Justice & Child Custody), the RSS and BHS scores. Correlation ranged from − 0.015 to 0.115 for the RSS score, and from − 0.061 to − 0.147 for the BHS score respectively. This indicated that informal coercion measured by other means than the P-PSY35 was also not related to Self-esteem or Hopelessness. Estimates of divergent validity between the P-PSY35 and Self-reported health indicated that pressures were, as expected, not related to perceived health.

Table 4 Convergent and divergent validity of the P-PSY35 score

Based on the 35 items’ bank, a mean of 15.256 items (SD = 11.671) was administered for the P-PSY35 scale using CAT, with the number of items needed to achieve the expected reliability varying between 3 and 35. The median number of items was 10. Average reliability was 0.891, and the correlation between the simulated and estimated thetas was close to unity (r = 0.978).

Finally, to facilitate clinical use, normative data on the total sample are presented in Table 5. The adaptive version of the P-PSY35 is also directly and freely accessible online for clinicians or researchers [48].

Table 5 Normative data for the paper and pencil version of the P-PSY35


The aim of this study was to develop in close collaboration with users and validate an instrument measuring pressures experienced in psychiatry in French language. The items were generated based on a literature review and the collaboration with people with mental health problems and experts on coercion. The P-PSY35 proved to be a reliable and valid instrument which measures pressures in psychiatry. The P-PSY35 demonstrated good internal validity, internal consistency, convergent and divergent validity on a varied psychiatric sample. The P-PSY35 could be substantially shortened while maintaining excellent reliability using the CAT procedure.

The final scale demonstrated a good model fit and a high reliability of the test scores. Much shorter measures with excellent reliability could also be obtained using CAT. Patients may be tired or may find questionnaires too long. When the time required to complete a psychometric questionnaire constitutes a barrier to effective clinical evaluation, professionals should have access to shorter but equally accurate tests. Today, open-source, online adaptive testing platforms, such as Concerto, are freely available [49]. Efforts to modernise test engineering using computerised adaptive testing (CAT) models make it possible to increase the comfort of testing for patients without altering data quality.

Good convergent validity was evidenced with significant relationship between P-PSY35 scores and global measures of experienced coercion and more specific informal coercion measures. As hypothesized, P-PSY35 scores were negatively correlated with satisfaction with psychiatric care. While our measure of pressures was positively correlated with cognitive and affective measures of Self-Stigma, we did not find a relationship with behavioural aspects of self-stigma. We may hypothesize that pressures experienced in psychiatry may have an impact on affect and cognition, yet no substantial effects on behaviours. This is interesting considering that theories of coercion define coercion as mainly a behavioural phenomenon [50].

Interestingly, we also did not find a relationship between pressures, Self-esteem and Hopelessness. This finding may be robust and not limited to the P-PSY35 because informal coercion measured by other means than the P-PSY35 was also not related to Self-esteem or Hopelessness. This highlights the need of measuring pressures more specifically, with a new scale such as P-PSY35. This may be related to the notion of paradoxical empowerment [51,52,53]. Within the concept of self-stigma and its well-documented negative consequences, research has also outlined a paradox: some people react to stigma by being righteously angry and becoming more empowered to fight against the injustice experienced [52, 54,55,56]. Righteous anger and coming out proud might therefore protect people from detrimental effects of stigma and this phenomenon may contribute to explain why Self-esteem and Hopelessness were not affected by experienced pressures.

Our study has several limitations that could be the focus of future research. First, our study did not consider diagnostics but aimed at covering a wide range of psychiatric conditions. Second, this study was mainly cross-sectional and longitudinal designs may be used to examine the P-PSY35 sensitivity to change. Third, even if our sample of 274 participants is substantial, further studies may be useful to replicate our findings on bigger samples. Fourth, our item generation process did not include a systematic rating of items by the participants. Therefore, content validity indexes could not be calculated. Fifth, we acknowledge that pressures felt by patients could be a byproduct of various factors such as treatment or aggressiveness. Sixth, even if all patients were informed that the investigators were independent of the hospital staff and that their responses would not be transmitted to anyone, we cannot exclude the possibility of response distortion. Seventh, we examined the potential for scale length reduction using a simulation approach as it is the only way to assess whether our instrument would be able to accurately recover the participants’ theta value: this value is known in the simulation context but totally unknown with real participants. While simulation work may have excellent internal validity, it may lack external validity. Finally, because of the convenience sampling procedure, refusals or response rate were not documented.

The significance of our results lies in the additional possibility offered to study various aspects of pressures experienced in psychiatry in French-speaking populations. Moreover, pressures were not related to perceived health status. Therefore, the P-PSY35 may not be particularly biased with patients with very low perceived health. We hope this tool will allow us a better understanding of coercion and its effects, to monitor and evaluate programs aimed at reducing its negative consequences and to have a significant impact on treatment.

Regarding individual actions, mental health professionals should be encouraged to discuss the topic and implications of pressures with their patients. The P-PSY35 could be an effective tool to monitor different aspects of coercion but also to stimulate discussion around this topic with everyone involved in treatment.

Regarding community responsibilities, the negative consequences of coercion and the need for specific interventions must be put at the top of the agenda. Awareness campaigns must be developed to ultimately reduce coercion with health professionals but also with relatives. Regarding policy implication, additional regulations are obviously needed to protect patients from coercion and warrant them access to specialized care and adequate treatment. Pressures can be exerted by professionals or relatives in order to improve treatment adherence or to limit the use of formal coercion [13, 14, 57] but the perception of not being involved in a fair decision making process (procedural justice) can reinforce perceived coercion with detrimental effects [58, 59].


Coercion is still too often associated exclusively with formal measures such as involuntary hospitalisation, seclusion or restraint. Having tools to measure pressures makes it possible to highlight the more insidious forms of coercion faced by people suffering from mental disorders, to make patients and those around them aware of these pressures and to consider approaches aimed at limiting their use, given their potential negative effects on the people concerned. The P-PSY35 is a psychometrically rigorous tool developed in close collaboration with users and designed to measure pressures experienced in psychiatry in French. The development and validation of the P-PSY35 represent a welcome step towards implementing and evaluating programs aimed at reducing negative consequences of coercion.

Data availability

The data that support the findings of this study are available from the corresponding author upon reasonable request.


  1. Szmukler G, Appelbaum PS. Treatment pressures, leverage, coercion, and compulsion in mental health care. J Ment Health. 2008;17(3):233–44.

    Article  Google Scholar 

  2. O’Donoghue B, Roche E, Shannon S, Creed L, Lyne J, Madigan K, Feeney L. Longer term outcomes of voluntarily admitted service users with high levels of perceived coercion. Psychiatry Res. 2015;229(1–2):602–5.

    Article  PubMed  Google Scholar 

  3. Nyttingnes O, Ruud T, Rugkasa J. “It’s unbelievably humiliating’-Patients” expressions of negative effects of coercion in mental health care. Int J Law Psychiatry. 2016;49(Pt A):147–53.

    Article  PubMed  Google Scholar 

  4. Theodoridou A, Schlatter F, Ajdacic V, Rossler W, Jager M. Therapeutic relationship in the context of perceived coercion in a psychiatric population. Psychiatry Res. 2012;200(2–3):939–44.

    Article  PubMed  Google Scholar 

  5. Kinner SA, Harvey C, Hamilton B, Brophy L, Roper C, McSherry B, Young JT. Attitudes towards seclusion and restraint in mental health settings: findings from a large, community-based survey of consumers, carers and mental health professionals. Epidemiol Psychiatr Sci. 2017;26(5):535–44.

    Article  CAS  PubMed  Google Scholar 

  6. Katsakou C, Marougka S, Garabette J, Rost F, Yeeles K, Priebe S. Why do some voluntary patients feel coerced into hospitalisation? A mixed-methods study. Psychiatry Res. 2011;187(1–2):275–82.

    Article  PubMed  Google Scholar 

  7. Rusch N, Muller M, Lay B, Corrigan PW, Zahn R, Schonenberger T, Bleiker M, Lengler S, Blank C, Rossler W. Emotional reactions to involuntary psychiatric hospitalization and stigma-related stress among people with mental illness. Eur Arch Psychiatry Clin Neurosci. 2014;264(1):35–43.

    Article  PubMed  Google Scholar 

  8. de Haan L, van Amelsvoort T, Dingemans P, Linszen D. Risk factors for medication non-adherence in patients with first episode schizophrenia and related disorders; a prospective five year follow-up. Pharmacopsychiatry. 2007;40(6):264–8.

    Article  PubMed  Google Scholar 

  9. Jaeger S, Pfiffner C, Weiser P, Langle G, Croissant D, Schepp W, Kilian R, Becker T, Eschweiler G, Steinert T. Long-term effects of involuntary hospitalization on medication adherence, treatment engagement and perception of coercion. Soc Psychiatry Psychiatr Epidemiol. 2013;48(11):1787–96.

    Article  PubMed  Google Scholar 

  10. Kalisova L, Raboch J, Nawka A, Sampogna G, Cihal L, Kallert TW, Onchev G, Karastergiou A, Del Vecchio V, Kiejna A, et al. Do patient and ward-related characteristics influence the use of coercive measures? Results from the EUNOMIA international study. Soc Psychiatry Psychiatr Epidemiol. 2014;49(10):1619–29.

    Article  PubMed  Google Scholar 

  11. Silva B, Golay P, Morandi S. Factors associated with involuntary hospitalisation for psychiatric patients in Switzerland: a retrospective study. BMC Psychiatry. 2018;18(1):401.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Martinez D, Brodard A, Silva B, Diringer O, Bonsack C, Morandi S, Golay P. Satisfaction and perceived coercion in voluntary hospitalisations: impact of past coercive experiences. Psychiatr Quat. 2022.

    Article  Google Scholar 

  13. Lidz CW, Mulvey EP, Hoge SK, Kirsch B, Monahan J, Eisenberg M, Gardner W, Roth L. Factual sources of psychiatrice patients’ perceptions of coercion in the hospital admission process. Am J Psychiatry. 1998;155(9):1254–60.

    Article  CAS  PubMed  Google Scholar 

  14. Hotzy F, Jaeger M. Clinical relevance of informal coercion in psychiatric treatment—systematic review. Front Psychiatry. 2016.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Lovell AM. Coercion and social control. In: Dennis DL, Monahan J, editors. Coercion and aggressive community treatment. Boston: Springer US; 1996. p. 147–66.

    Chapter  Google Scholar 

  16. Diamond RJ. Coercion and tenacious treatment in the community: applications to the real world. In: Dennis DL, Monahan J, editors. Coercion and aggressive community treatment: a new frontier in mental health law. Berlin: Springer; 1996. p. 51–72.

    Chapter  Google Scholar 

  17. Valenti E, Giacco D. Persuasion or coercion? An empirical ethics analysis about the use of influence strategies in mental health community care. BMC Health Serv Res. 2022;22(1):1–15.

    Article  Google Scholar 

  18. Angell B. Measuring strategies used by mental health providers to encourage medication adherence. J Behav Health Serv Res. 2006;33:53.

    Article  PubMed  Google Scholar 

  19. Yeeles K. 95Informal coercion: current evidence. In: Molodynski A, Rugkåsa J, Burns T, editors. Coercion in community mental health care: international perspectives. Oxford: Oxford University Press; 2016.

    Google Scholar 

  20. Canvin K, Rugkasa J, Sinclair J, Burns T. Patient, psychiatrist and family carer experiences of community treatment orders: qualitative study. Soc Psychiatry Psychiatr Epidemiol. 2014;49(12):1873–82.

    Article  PubMed  Google Scholar 

  21. Nyttingnes O, Rugkasa J, Holmen A, Ruud T. The development, validation, and feasibility of the experienced coercion scale. Psychol Assess. 2017;29(10):1210–20.

    Article  PubMed  Google Scholar 

  22. Burns T, Yeeles K, Molodynski A, Nightingale H, Vazquez-Montes M, Sheehan K, Linsell L. Pressures to adhere to treatment ('leverage’) in English mental healthcare. Br J Psychiatr. 2011;199(2):145–50.

    Article  Google Scholar 

  23. Monahan J, Redlich AD, Swanson J, Robbins PC, Appelbaum PS, Petrila J, Steadman HJ, Swartz M, Angell B, McNiel DE. Use of leverage to improve adherence to psychiatric treatment in the community. Psychiatr Serv. 2005;56(1):37–44.

    Article  PubMed  Google Scholar 

  24. Golay P, Moga M, Devas C, Staecheli M, Poisat Y, Israël M, Suter C, Silva B, Morandi S, Ferrari P, et al. Measuring the paradox of self-stigma: psychometric properties of a brief scale. Ann Gen Psychiatry. 2021;20(1):5.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Høyer G, Kjellin L, Engberg M, Kaltiala-Heino R, Nilstun T, Sigurjónsdóttir M, Syse A. Paternalism and autonomy: a presentation of a Nordic study on the use of coercion in the mental health care system. Int J Law Psychiatry. 2002;25(2):93–108.

    Article  PubMed  Google Scholar 

  26. Cantril H. The pattern of human concerns. New Brunswick: Rutgers University Press; 1965.

    Google Scholar 

  27. Bergk J, Flammer E, Steinert T. “ Coercion experience scale”(CES)-validation of a questionnaire on coercive measures. BMC Psychiatry. 2010;10(1):5.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Golay P, Favrod J, Morandi S, Bonsack C. Psychometric properties of the French-language version of the coercion experience scale (CES). Ann Gen Psychiatry. 2019;18:1–10.

    Article  Google Scholar 

  29. Köhn S, Oedekoven M, Bernert S, Spyra K: Enquête nationale de l'ANQ sur la satisfaction en soins aigus, en psychiatrie et en réadaptation: Étude de test scientifique du nouveau questionnaire succint de l'ANQ sur la satisfaction des patients, rapport final parties 1 et 2. In.; 2018.

  30. Golay P, Martinez D, Silva B, Morandi S, Bonsack C. Validation psychométrique d’une échelle française d’auto-stigmatisation auprès d’un échantillon de patients souffrant de troubles mentaux: la Self-Stigma Scale-Short (SSS-S). Ann Méd-Psychol, Rev Psychiatr. 2022;180:899–904.

    Google Scholar 

  31. Rosenberg M. Rosenberg self-esteem scale (RSE). Accept Commit Ther Measures Package. 1965;61:52.

    Google Scholar 

  32. Beck AT, Weissman A, Lester D, Trexler L. The measurement of pessimism: the hopelessness scale. J Consult Clin Psychol. 1974;42(6):861.

    Article  CAS  PubMed  Google Scholar 

  33. Bouvard M, Charles S, Guérin J, Aimard G, Cottraux J. Étude de l’échelle de désespoir de Beck (Hopelessness Scale). Encéphale. 1992;18:237–40.

    CAS  PubMed  Google Scholar 

  34. Van der Ark LA. New developments in Mokken scale analysis in R. J Stat Softw. 2012;48:1–27.

    Article  Google Scholar 

  35. Orlando M, Thissen D. Likelihood-based item-fit indices for dichotomous item response theory models. Appl Psychol Meas. 2000;24(1):50–64.

    Article  Google Scholar 

  36. Orlando M, Thissen D. Further investigation of the performance of S-X2: an item fit index for use with dichotomous item response theory models. Appl Psychol Meas. 2003;27(4):289–98.

    Article  Google Scholar 

  37. Chalmers RP. mirt: a multidimensional item response theory package for the R environment. J Stat Softw. 2012;48:1–29.

    Article  Google Scholar 

  38. Yen WM. Effects of local item dependence on the fit and equating performance of the three-parameter logistic model. Appl Psychol Meas. 1984;8(2):125–45.

    Article  Google Scholar 

  39. Christensen KB, Makransky G, Horton M. Critical values for Yen’s Q 3: Identification of local dependence in the Rasch model using residual correlations. Appl Psychol Meas. 2017;41(3):178–94.

    Article  PubMed  Google Scholar 

  40. Hu L-t, Bentler PM. Fit indices in covariance structure modeling: Sensitivity to underparameterized model misspecification. Psychol Methods. 1998;3(4):424.

    Article  Google Scholar 

  41. Canivez GL. Bifactor modeling in construct validation of multifactored tests: Implications for understanding multidimensional constructs and test interpretation. In: Schweizer K, DiStefano C, editors. Principles and methods of test construction: standards and recent advancements. Gottingen: Hogrefe Publishers; 2017. p. 247–71.

    Google Scholar 

  42. Thissen D, Wainer H. Test scoring. Milton Park: Routledge; 2001.

    Book  Google Scholar 

  43. George D, Mallery M. Using SPSS for Windows step by step: a simple guide and reference. Boston: Allyn & Bacon; 2003.

    Google Scholar 

  44. Revelle WR: psych: Procedures for personality and psychological research. 2017.

  45. Golay P, Laloyaux J, Moga M, Della Libera C, Larøi F, Bonsack C. Psychometric investigation of the French version of the Aberrant Salience Inventory (ASI): differentiating patients with psychosis, patients with other psychiatric diagnoses and non-clinical participants. Ann Gen Psychiatry. 2020;19:58.

    Article  PubMed  PubMed Central  Google Scholar 

  46. Cohen J. Statistical power analysis for the behavioral sciences. Hilsdale: Lawrence Earlbaum Associates; 1988.

    Google Scholar 

  47. Choi SW. Firestar: computerized adaptive testing simulation program for polytomous item response theory models. Appl Psychol Meas. 2009;33(8):644.

    Article  Google Scholar 

  48. P-PSY35 computerized adaptive test. Accessed 1 Feb 2024.

  49. Concerto Open Source Online Adaptive Testing Plateform. Accessed 1 Feb 2024.

  50. Anderson S. Of theories of coercion, two axes, and the importance of the coercer. J Moral Philos. 2008;5(3):394–422.

    Article  Google Scholar 

  51. Corrigan PW, Kerr A, Knudsen L. The stigma of mental illness: explanatory models and methods for change. Appl Prev Psychol. 2005;11(3):179–90.

    Article  Google Scholar 

  52. Corrigan PW, Watson AC. The paradox of self-stigma and mental illness. Clin Psychol Sci Pract. 2002;9(1):35–53.

    Article  Google Scholar 

  53. Corrigan PW, Michaels PJ, Vega E, Gause M, Watson AC, Rüsch N. Self-stigma of mental illness scale—short form: reliability and validity. Psychiatry Res. 2012;199(1):65–9.

    Article  PubMed  PubMed Central  Google Scholar 

  54. Deegan PE. Spirit breaking: when the helping professions hurt. Humanist Psychol. 2000;28(1–3):194–209.

    Article  Google Scholar 

  55. Lysaker PH, Roe D, Yanos PT. Toward understanding the insight paradox: internalized stigma moderates the association between insight and social functioning, hope, and self-esteem among people with schizophrenia spectrum disorders. Schizophr Bull. 2007;33(1):192–9.

    Article  PubMed  Google Scholar 

  56. Golay P, Moga M, Devas C, Staecheli M, Poisat Y, Israël M, Suter C, Silva B, Morandi S, Ferrari P. Measuring the paradox of self-stigma: psychometric properties of a brief scale. Ann Gen Psychiatry. 2021;20(1):1–11.

    Article  Google Scholar 

  57. Klingemann J, Switaj P, Lasalvia A, Priebe S. Behind the screen of voluntary psychiatric hospital admissions: a qualitative exploration of treatment pressures and informal coercion in experiences of patients in Italy, Poland and the United Kingdom. Int J Soc Psychiatry. 2022;68(2):457–64.

    Article  PubMed  Google Scholar 

  58. Poythress NG, Petrila J, McGaha A, Boothroyd R. Perceived coercion and procedural justice in the broward mental health court. Int J Law Psychiatry. 2002;25(5):517–33.

    Article  PubMed  Google Scholar 

  59. Lidz CW, Hoge SK, Gardner W, Bennett NS, Monahan J, Mulvey EP, Roth LH. Perceived coercion in mental hospital admission pressures and process. Arch Gen Psychiatry. 1995;52(12):1034–9.

    Article  CAS  PubMed  Google Scholar 

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The authors would like to thank Charlotte Bonalumi, Maude Bertusi, Sylfa Fassasi Gallo, Lilith Abraham-Empson, Isabelle Gothuey, Laurent Loutrel, Philippe Rey-Bellet, Remy Volet, Laure Muheim, Tania Vispo, Rachele Brodard, Yves Cossy, Didier Wrobel, Manuel Simon and Oana Diringer for their help with patients’ recruitment.


Open access funding provided by University of Lausanne. This study was based on institutional funding.

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PG, DM & CB designed the study. DM, NPF, AB, JP and LAR acquired the data. PG & LAR analysed and interpreted the data. PG, LAR and DM drafted the first version of the manuscript. MB, BS, AB, JP, NPF, LAR, CB and SM critically revised the manuscript for important intellectual content.

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Correspondence to Philippe Golay.

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Approval for this study was granted by the Human Research Ethics Committee of the Canton Vaud, Switzerland (protocol #2016–00768). Informed consent was obtained from all participants and all methods were carried out in accordance with the recommendations of the Human Research Ethics Committee of the Canton Vaud and the Declaration of Helsinki.

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The authors declare no competing interests in relation to the subject of the study.

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Golay, P., Martinez, D., Bachelard, M. et al. Measurement of perceived pressures in psychiatry: paper-and-pencil and computerized adaptive version of the P-PSY35 scale. Ann Gen Psychiatry 23, 18 (2024).

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