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Patient-reported outcome measures for medication treatment satisfaction: a systematic review of measure development and measurement properties

BMC Medicine volume 22, Article number: 347 (2024) Cite this article

Abstract

Background

Medication Treatment Satisfaction (M-TS) from the patients’ perspective is important for comprehensively evaluating the effect of medicines. The extent to which current patient-reported outcome measures (PROMs) for M-TS are valid, reliable, responsive, and interpretable remains unclear. To assess the measurement properties of existing PROMs for M-TS and to highlight research gaps.

Methods

Using PubMed, Embase (Ovid), Cochrane library (Ovid), IPA (Ovid), PsycINFO, Patient-Reported Outcome and Quality of Life Questionnaires biomedical databases, and four Chinese databases, we performed a systematic search for studies addressing the development and validation of PROMs for M-TS. Based on the Consensus-based Standards for the selection of health Measurement Instruments (COSMIN) guideline, pairs of reviewers independently assessed the measurement properties of the PROMs and rated the quality of evidence on the measurement properties of each PROM. (The Open Science Framework registration: https://doi.org/10.17605/OSF.IO/8S5ZM).

Results

This review identified 69 PROMs for M-TS in 114 studies (four generic, 32 disease-specific, and 33 drug-specific) of which 60 were intended for adults. All provided limited or no information regarding interpretability. Most demonstrated appropriate construct validity including convergent validity (39/69) and discriminative or known-groups validity (40/69) (high to moderate quality of evidence). Only a few provided evidence of sufficient content validity (8/69), structural validity (13/69), and internal consistency (11/69). Of 38 PROMs reporting test–retest reliability, results in 24 provided evidence of satisfactory test–retest reliability (18 with high to moderate, 6 with low to very low quality of evidence). Few PROMs reported responsiveness (16/69). Two generic PROMs (Treatment Satisfaction Questionnaire for Medication initial Version 1.4, TSQM-1.4; Treatment Satisfaction with Medicines Questionnaire, SATMED-Q) and one drug-specific PROM (Insulin Treatment Satisfaction Questionnaire, ITSQ) demonstrated both satisfactory validity and reliability.

Conclusions

Most existing PROMs for M-TS require further exploration of measurement properties. Reporting guidelines are needed to enhance the reporting quality of the development and validation of PROMs for M-TS.

Peer Review reports

Background

Medication Treatment Satisfaction (M-TS) is a subjective patient-reported outcome (PRO) that evaluates patients’ perception of medication-taking process and its associated outcomes [1]. Both the US Food and Drug Administration (FDA) [2] and the European Medicines Agency (EMA) [3] encourage involving patient-reported satisfaction with treatment in drug development and evaluation, with an emphasis placed upon patients’ judgment.

M-TS, if captured in a scientifically rigorous way [3, 4], can predict adherence (e.g., by identifying areas where patients are dissatisfied with their medication) [5], inform clinical decision-making (e.g., by allowing health care professionals to select therapies based on patient feedback) [3, 6,7,8], and influence health care policy (e.g., by guiding reimbursement decision and quality improvement initiatives based on patient-centered outcomes) [3, 6,7,8]. Patient-reported outcome measures (PROMs) with poor validity, reliability, or responsiveness in the target population may inadequately capture the changes in M-TS [9, 10] resulting in inaccurate estimates of the effect of drugs and misguided clinical decisions [9,10,11]. With the growing breadth of available PROMs for M-TS [12,13,14,15], heterogeneity in outcome reporting has stifled efforts to synthesize findings across trials [16, 17].

Identifying valid, reliable, responsive, and interpretable PROMs for M-TS therefore is crucial for clinical trials and clinical practice [7, 8, 10]. To date, no study has systematically reviewed existing PROMs for M-TS and assessed their measurement properties. Our systematic review aims to identify currently available PROMs for M-TS, to evaluate the measurement properties of these PROMs, to provide evidence for choosing PROM for M-TS, and if any to highlight the research gap regarding the development and validation of PROMs for M-TS.

Methods

We registered this systematic review on the Open Science Framework (https://doi.org/10.17605/OSF.IO/8S5ZM) and adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) reporting guideline [18] and the Consensus-based Standards for the selection of health Measurement Instruments (COSMIN) guideline for systematic reviews of patient-reported outcome measures [19,20,21]. The COSMIN guideline provides a standardized data abstraction form for characteristics and measurement properties of the included PROMs, and criteria for assessing the measurement properties of PROMs. The reviewers used the COSMIN Risk of Bias checklist to assess the risk of bias of individual studies, and the modified Grading of Recommendations Assessment, Development, and Evaluation (GRADE) to grade the quality of evidence.

The research team formation

We established a multidisciplinary research team, comprising two PROM methodologists, one epidemiology methodologist, three clinicians, three pharmacists, and two pharmacy students, to ensure comprehensive analysis and diverse perspectives in this review.

Literature search and selection

Using PubMed, Embase (Ovid), Cochrane library (Ovid), International Pharmaceutical Abstracts (IPA, Ovid), PsycINFO, Patient-Reported Outcome and Quality of Life Questionnaires biomedical databases (PROQOLID), China National Knowledge Infrastructure (CNKI), Wanfang, Chinese Scientific Journal Database (VIP database), and Chinese Biomedicine Literature Database (CBM) (from inception through 5 December, 2022) and ePROVIDE (https://eprovide.mapi-trust.org/), the reviewers performed a systematic search for literature published in English and Chinese reporting the development (i.e., development study including cognitive interview or other pilot study) and validation (i.e., validation study) of PROMs for M-TS in adults and children with any medical condition (Additional file 1: table S1).

After removing duplicate records, pairs of reviewers (M.Y., X.J., W.Y., and S.Z.) independently screened the titles and subsequent full-text articles, with conflicts handled by a fifth reviewer (L.Z.). For including relevant literature, the reviewers reviewed the references of included articles.

Data extraction

Using a pilot tested data abstraction form, after a calibration exercise, pairs of reviewers (M.Y., X.J., W.Y. and S.Z.) independently extracted data including the characteristics of the individual studies (e.g., study design, country, sample size, study population), the characteristics of the PROMs (e.g., target population, domains, response options, and copyright based on ePROVIDE), and the measurement properties of the PROMs (i.e., content validity, structural validity, construct validity, criterion validity, cross-cultural validity or measurement invariance, internal consistency, test–retest reliability, measurement error, and responsiveness) and information about interpretability of the PROMs [19, 22].

For the PROM development, we extracted the origin of the construct to be measured reported in the study (e.g., a theory, conceptual framework, or disease model used, or a clear rationale provided to define the construct). Then, after group discussion within our research team, we summarized the concepts, components, and influencing factors of treatment satisfaction into a table.

Assessment of measurement properties

Using the criteria for good measurement properties [19, 20], two reviewers (M.Y. and P.Z.) based on individual studies independently assessed the measurement properties of each PROM as sufficient ( +), insufficient ( −), or indeterminate (?) (Additional file 1: table S2 [19, 20, 22]). For example, we rated the test–retest reliability of a PROM as sufficient if the intraclass correlation coefficient (ICC) or weighted Kappa ≥ 0.70, as insufficient if < 0.70, or as indeterminate if ICC or weighted Kappa were not reported. Based on all studies relevant to a particular PROM, the reviewers assessed the overall measurement properties of that PROM as sufficient ( +), insufficient ( −), inconsistent ( ±), or indeterminate (?) [19, 20]. A third reviewer (L.Z.) resolved any disagreement.

Grading the quality of evidence

Using the COSMIN risk of bias checklist [19, 23], two reviewers (M.Y. and P.Z.) independently assessed the risk of bias (RoB) of individual development and validation study as very good, adequate, doubtful, inadequate quality. For example, we rated RoB of a PROM development study as very good if PROM design (including construct to be measured, origin of the construct, target population, context of use etc.) and cognitive interview study or another pilot test regarding the relevance, comprehensibility, and comprehensiveness of the PROM were clearly described; adequate if assumably appropriate but not clearly described; and doubtful or inadequate if not clearly described. A third reviewer (L.Z.) resolved any disagreement.

Using the modified GRADE approach in COSMIN guideline, the reviewers graded the overall quality of evidence on the measurement properties of a PROM as high, moderate, low, or very low (Additional file 1: table S3 [20,21,22, 24]) [19, 24]. When a specific measurement property was assessed as indeterminate (e.g., due to lack of reporting), the reviewers did not rate the quality of evidence on that particular measurement property [19, 20].

Results

Literature screening and characteristics of included studies

The search strategy yielded 2813 records, with 114 studies [25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138] included in this review (Fig. 1). Sixty-three studies (55%) pertained to the development and validation of PROMs for M-TS, while the remaining 51 studies (45%) focused on the validation of PROMs (Additional file 1: table S4 [25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138]). The United States accounted for the majority of studies conducted (46, 40%), followed by Spain (16, 14%) and the UK (15, 13%). The median sample sizes of studies that developed and validated the PROMs is 205 (with a range from 13 to 1336) and that of studies that validated the PROMs is 197 (with a range from 10 to 2511).

Fig. 1
figure 1

Preferred Reporting Items for Systematic Reviews and Meta-Analysis Diagram of Study Selection

Full size image

Characteristics of PROMs for M-TS

The 114 studies [25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138] reported 69 PROMs for M-TS. Sixty PROMs (87%) were intended for adults (Table 1). Most of the PROMs are disease-specific (32, 46%) or drug-specific (33, 48%), while four are generic (6%). The disease-specific PROMs cover 12 categories of diseases under the International Classification of Diseases 11th (ICD-11) [139] with 29 specific diseases (mostly often diabetes, asthma, and migraine). The drug-specific PROMs targeted 12 categories of medicines under the Anatomical Therapeutic Chemical Classification System (ATC) [140] (mostly often anticoagulants, insulin, and iron chelation).

Table 1 Characteristics of PROMs for medication treatment satisfaction
Full size table

The majority of M-TS PROMs (61, 88%) were self-reported, four (6%) were either self-reported or proxy-reported (e.g., by parents or clinicians), and the remaining four (6%) were health practitioner administered (e.g., through interviews). Data collection modes for self-reported PROMs include questionnaires (in paper and pen or electronic versions), interviews (face-to-face or via phone script), and mobile applications. All included 69 M-TS PROMs have questionnaire data mode; only the TSQM-1.4, TSQM-II, and TSQM-9 (3, 4%) have further developed phone scripts and mobile applications [141]. In practical applications, patients can independently complete self-reported M-TS PROMs on paper or electronic devices, or with the assistance of researchers, who will read the questions aloud and record the patient’s answers (e.g., in-person or telephone interviews). Thirty-eight PROMs (55%) reported copyright information, of which 28 belong to the pharmaceutical industry. Sixty-four PROMs (93%) provided free access to full questionnaires. Ten PROMs (14%) proved easy to be administrated and completed in the context of clinical trials.

The most commonly measured domains were convenience (40, 58%), side effects (39, 57%), and perceived effectiveness of medication (29, 42%) (Table 1). The most commonly used response option was a 5-point Likert scale (32, 46%). Less than half of the PROMs (32, 46%) clarified the timing for measuring M-TS. Among those clarified, the most common recall period for measuring M-TS was 2 to 4 weeks after the initiation of medication.

Measurement properties of PROMs for M-TS with quality of evidence

Among sixty-four PROMs reported the development process (Table 2). All of these 64 PROMs described the construct measured and the target population. Ten reported the conceptual framework or theory for defining the construct being measured that supported their generation of measurement items (Additional file 1: table S5 [1, 30, 44, 66, 82, 95, 100, 117, 125, 126, 129, 142]). No common framework or theory was used. Figure 2 summarizes the concepts, components, and influence factors of treatment satisfaction from the ten frameworks [30, 44, 66, 82, 95, 100, 117, 125, 126, 129] and two theories [1, 142].

Table 2 Development and content validity of PROMs for medication treatment satisfaction
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Fig. 2
figure 2

The concept, component and influence factors of medication treatment satisfaction from current conceptual frameworks

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Eight PROMs (12%) had sufficient overall content validity (i.e., relevance: items were relevant for the construct of interest, the target population, and the context of use; comprehensiveness: all key concepts were included; comprehensibility: the PROM was understood by the target population) (5/8, moderate; 3/8, low quality of evidence) (Table 2). The other PROMs failed to simultaneously meet the criteria of relevance, comprehensiveness, or comprehensibility or did not report the content validity. Among 54 PROMs that reported structural validity (all of which applied classical test theory), 13 had sufficient structural validity (i.e., comparative fit index (CFI) or Tucker–Lewis index (TLI) or comparable measure > 0.95, or Root Mean Square Error of Approximation (RMSEA) < 0.06 or standardized root mean residuals (SRMR) < 0.08) (high to moderate quality of evidence). The others did not report or meet the criteria for structural validity (Table 3 and Additional file 1: table S6 [25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138]) [19, 20]. Among 56 PROMs that reported construct validity, 39 had sufficient convergent validity (e.g., correlations with instruments measuring similar constructs ≥ 0.50) (39/44, 89%; 38/39, high to moderate; 1/39, low quality of evidence) and 43 had sufficient discriminative or known-groups validity (e.g., correlations with instruments measuring unrelated construct < 0.30) (42/45, 93%; 41/43, high to moderate; 2/42, low quality of evidence).

Table 3 Measurement propertiesa of PROMs for medication treatment satisfaction
Full size table

Among 63 PROMs that reported internal consistency, 11 PROMs demonstrated sufficient (i.e., Cronbach’s alpha(s) ≥ 0.70 and at least low evidence for sufficient structural validity) (11/63, 17%, high quality of evidence). Thirty-eight PROMs reported test–retest reliability, of which 24 had sufficient test–retest reliability (i.e., ICC and weighted Kappa ≥ 0.70) (24/38, 63%; 18/24, high to moderate; 6/24, low to very low quality of evidence). The others did not report or meet the criteria for test–retest reliability.

Sixteen PROMs reported responsiveness, of which six drug or disease-specific PROMs demonstrated sufficient (e.g., area under the ROC Curve (AUC) ≥ 0.7). No generic PROMs had sufficient responsiveness.

Four PROMs for M-TS [60, 78, 80, 87] proposed the minimal important difference (MID) (Additional file 1: table S7 [25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138]). Four PROMs demonstrated normally distributed scores in the study population while 11 PROMs showed negatively or positively skewed scores. Thirty-two PROMs for M-TS reported floor or ceiling effects.

PROMs for M-TS with sufficient validity and reliability

One drug-specific PROM (Insulin Treatment Satisfaction Questionnaire, ITSQ) [42, 43] demonstrated sufficient construct validity, internal consistency, test–retest reliability and responsiveness (high to moderate quality of evidence), and content validity (low quality evidence). Two generic PROMs (TSQM-1.4 [25,26,27,28,29] and SATMED-Q) [31, 37,38,39,40] demonstrated sufficient construct validity, structural validity, and internal consistency (high quality of evidence) and content validity (moderate to low quality of evidence), but lack of evidence on test–retest reliability or responsiveness.

Discussion

Summary of findings

This review systematically searched and evaluated current PROMs for M-TS. Over 85% of the PROMs targeted adult patients. Most PROMs demonstrated sufficient construct validity including convergent validity (39/69, 57%) and discriminative or known-groups validity (40/69, 58%) (high to moderate quality of evidence) but failed to demonstrate sufficient content validity (61/69, 88%), structural validity (56/69, 81%), internal consistency (58/69, 84%), or test–retest reliability (45/69, 65%). Few PROMs reported responsiveness (16/69, 23%). Only four PROMs provided an approach for interpreting the results of the PROMs (i.e., the MIDs).

Introduction of the three PROMs for M-TS with sufficient validity and reliability

The ITSQ [42, 43] is a drug-specific PROMs for insulin treatment satisfaction including domains of inconvenience of regimen (5 items), lifestyle flexibility (3 items), glycemic control (3 items), hypoglycemic control (5 items), and insulin delivery device satisfaction (6 items). According to the Allie database (i.e., a database for searching studies in PubMed and MEDLINE that involve a particular abbreviation and long form) [143], 12 trials in adults have applied the ISTQ. Due to unclear recall period and lack of evaluation on content validity, the quality of evidence on the content validity of ITSQ was still low.

Both TSQM-1.4 [25,26,27,28,29] (with 14 items) and SATMED-Q [31, 37,38,39,40] (with 17 items) are generic PROMs for adults with chronic diseases. The two PROMs shared four common domains including perceived effectiveness, side effects, convenience, and global satisfaction. The SATMED-Q had two additional domains (i.e., impact on daily living or activity, process of medical care or medical follow-up). The TSQM-1.4 was the most widely used PROMs for M-TS (106 trials applied, 4 of which were in children and adolescents) while SATMED-Q was rarely used in trials (ten trials in adults applied during the last 15 years) [143]. Both PROMs still lack high quality of evidence on content validity and responsiveness.

Limitations of current PROMs for M-TS

Although conceptual framework is not mandatory for developing measures, providing a theoretical foundation facilitates defining key components and their relationships within the construct [6, 7]. Our study revealed that over 70% PROMs did not define a conceptual framework for treatment satisfaction. The existing frameworks draw heavily from Shikiar’s pyramid theory [1] and Weaver’s concept of treatment satisfaction [142]. These frameworks, however, have limitations on considering the difference between patients with chronic disease and those with acute disease toward treatment satisfaction (e.g., chronic disease patients tend to emphasize long-term outcomes and quality of life, while acute disease patients prioritize immediate relief and symptom management) [144] and the difference between adults and children (e.g., children might prioritize medication side effects and ease of administration, whereas adults focus more on the effectiveness) [145]. These differing priorities highlight the need for PROMs that are tailored to specific disease contexts to accurately capture patient satisfaction. More than half of the PROMs (41/69, 59%) did not clearly report the process of cognitive interviews or other pilot tests of the PROMs damaging the transparency and rigor of the development process [146,147,148].

Regarding content validity, because the context of use was vague, we rated the relevance of most of the PROMs as indeterminate (e.g., whether the PROMs is for clinical trial or clinical practice, for discriminative, evaluative, or predictive purpose was unclear); due to paucity of justification on the appropriateness of response option and recall period, we rated the comprehensiveness as insufficient; due to lack of justification on the understandability of the PROMs in target population, we rated the comprehensibility as insufficient (Additional file 1: table S6 [25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138]).

Our systematic search found six PROMs for M-TS were developed specifically for children and adolescents. These PROMs, however, lacked of evidence on sufficient validity, reliability, or responsiveness [51, 101, 102, 134,135,136]. Compared with adults children and adolescents have limited vocabulary, comprehension, and self-awareness, which probably influence their ability to respond accurately to adult-oriented measures [149]. The validity, reliability, responsiveness, and feasibility of the PROMs developed for adults should be evaluated before they are applied in children and adolescents.

According to Allie [143], we found most PROMs were infrequently used with 38% never applied by any trial and 42% applied by less than 5 trials. Patient and Partner Treatment Satisfaction Scale in Erectile Dysfunction (TSS), the second most often used PROM (the first was TSQM), had inconsistent content validity (moderate quality of evidence) (Table 2). The infrequent application of the PROMs for M-TS and wide use of PROMs with poor measurement properties indicates that potential stakeholders (e.g., clinicians or researchers) probably lack awareness and access to validated PROMs for M-TS.

The practical application of self-reporting in M-TS PROMs faces several challenges, particularly for specific populations. Individuals with mental health issues may struggle to report treatment satisfaction accurately due to cognitive impairments or emotional distress [150]. Those with limited digital skills may find electronic PROMs difficult, resulting in incomplete or biased data [151]. Similarly, individuals with reading difficulties or low literacy may misinterpret questions, compromising response reliability [152]. These challenges underscore the need for inclusive PROM design, ensuring accessibility and comprehension for diverse patients. Alternative data collection methods, such as interviews or caregiver reports, should be considered for those unable to self-report reliably.

Strengths and limitations of this systematic review

We conducted a comprehensive search for current PROMs for M-TS. This review included four Chinese databases, which expanded the scope beyond English-language publications to provide a more comprehensive understanding of M-TS across different cultural contexts and enhance the diversity, comprehensiveness, robustness, and applicability of our systematic review [153]. Following the COSMIN guideline [19, 20] we assessed the measurement properties of the PROMs, risk of bias of individual studies, and rated the quality of body of evidence on the development and validation of the PROMs.

This review has some limitations. First, we only included studies published in English and Chinese and might have missed PROMs for M-TS reported in other languages. Second, poor reporting of individual studies impeded our ability to assess the measurement properties and to rate the quality of evidence. To minimize the impact of ambiguous reporting, we searched for and abstracted data from all available literature for each included PROM. Third, some evaluation criteria for measurement properties were subjective (e.g., for the criteria for content validity: “are all key concepts included?”). We attempted to reduce the difference between reviewers by conducting calibration exercises, duplicated assessments and group discussions when discrepancy occurred. Fourth, we did not recommend PROMs based on the COSMIN guideline criteria (i.e., PROMs that have potential to be recommended as the most suitable PROM for those with evidence for sufficient content validity (any level) and sufficient internal consistency (at least low level) [19, 20]) because we think the evaluation of content validity was subjective. We, however, based on the evaluation of measurement properties, highlighted three PROMs with sufficient validity (particularly construct validity) and reliability (particularly internal consistency).

Recommendations for future research and clinical practice

Confident use of current available PROMs for M-TS will require validation study to assess their measurement properties (especially content validity, test–retest reliability, and responsiveness), interpretability, and feasibility in different context and population. Further studies can pay more attention to assess the measurement properties of current PROMs in children and adolescents or to develop PROMs targeted at this population. Although COSMIN provided a reporting guideline for validation study [154], our review found that the guideline was not widely used. A uniformed standard for reporting the development and validation of PROMs is needed to improve the reporting quality of studies on the development and validation of PROMs for M-TS. Additionally, collaborative efforts among researchers, clinicians, and policymakers are essential to develop and implement robust M-TS PROMs applicable to diverse patient groups. This will bridge the gap between current PROMs and patient needs, enhancing patient care and treatment outcomes.

The implementation of validated and reliable M-TS PROMs in clinical practice can significantly enhance patient care by providing healthcare providers with better tools to assess and address patient satisfaction and treatment outcomes. By accurately capturing patient experiences and preferences, PROMs can help tailor treatments to individual needs, leading to improved adherence and better health outcomes. Moreover, the use of PROMs can facilitate shared decision-making, empowering patients to be active participants in their own care. This patient-centered approach not only improves satisfaction but also contributes to more effective and efficient healthcare delivery. Ensuring that PROMs are culturally sensitive and accessible to all patient groups, including those with mental health issues, limited digital skills, and reading difficulties, is crucial for their widespread adoption and utility in diverse clinical settings.

Conclusions

Most current PROMs for M-TS demonstrated sufficient construct validity while only a few had sufficient content validity, structural validity, internal consistency, and test–retest reliability. Few PROMs reported responsiveness. Confident use of current PROMs requires further evaluation on the validity, reliability, responsiveness, and interpretability of current PROMs. Reporting guidelines are needed to enhance the reporting quality of the development and validation of PROMs for M-TS.

Availability of data and materials

All data in this systematic review are publicly available. All extracted data are available in the online supplementary files.

Abbreviations

M-TS:

Medication Treatment Satisfaction

PROMs:

Patient-reported outcome measures

COSMIN:

Consensus-based Standards for the selection of health Measurement Instruments

TSQM:

Treatment Satisfaction Questionnaire for Medication

TSQM-1.4:

Treatment Satisfaction Questionnaire for Medication initial Version

TSQM-II:

Treatment Satisfaction Questionnaire for Medication Version II

TSQM-9:

Treatment Satisfaction Questionnaire for Medication—9 items (an abbreviated 9-item TSQM)

SATMED-Q:

Treatment Satisfaction with Medicines Questionnaire

ITSQ:

Insulin Treatment Satisfaction Questionnaire

PRO:

Patient-reported outcome

FDA:

US Food and Drug Administration

EMA:

European Medicines Agency

PRISMA:

Preferred Reporting Items for Systematic Reviews and Meta-Analyses

GRADE:

Grading of Recommendations Assessment, Development, and Evaluation

ICC:

Intraclass correlation coefficient

RoB:

Risk of bias

ICD-11:

International Classification of Diseases 11th

ATC:

Anatomical Therapeutic Chemical Classification System

CFI:

Comparative fit index

TLI:

Tucker–Lewis index

RMSEA:

Root mean square error of approximation

SRMR:

Standardized root mean residuals

AUC:

Area under the ROC curve

MID:

Minimal important difference

TSS:

Patient and Partner Treatment Satisfaction Scale in Erectile Dysfunction

VAS:

Visual analogue scale

NR:

Information was not reported

PSIT:

Patient Satisfaction with Insulin Therapy questionnaire

DiabMedSat:

Diabetes Medication Satisfaction Questionnaire

DTTQ:

Diabetes Tablet Treatment Questionnaire

SOADAS:

Satisfaction with Oral Anti-Diabetic Agents Scale

DM-SAT:

Diabetes Medication Satisfaction Questionnaire

PAM-D:

Perceptions About Medications for Diabetes questionnaire

PRAM-TSQ:

Treatment Satisfaction Associated With Pramlintide Use Questionnaire

DTSQ-IP:

Diabetes Treatment Satisfaction Questionnaire for in-patients

OHA-Q:

Oral Hypoglycemic Agent Questionnaire

DMSRQ:

Diabetes Medication System Rating Questionnaire

DMSRQ-SF:

Diabetes Medication System Rating Questionnaire-Short Form

DIDS:

Diabetes Impact and Device Satisfaction Questionnaire

ThyTSQ:

Underactive Thyroid Treatment Satisfaction Questionnaire

MS-TSQ:

Menopause Symptoms Treatment Satisfaction Questionnaire

Acro-TSQ:

Acromegaly Treatment Satisfaction Questionnaire

DASS:

Duke Anticoagulation Satisfaction Scale

PACT-Q2:

Perception of Anticoagulant Treatment Questionnaire 2

ACTS:

Anticlot Treatment Scale

PSAM:

Patient Satisfaction with Asthma Medication questionnaire

SATQ:

Satisfaction with Asthma Treatment Questionnaire

PASAPQ:

Patient Satisfaction and Preference Questionnaire

PPMQ:

Patient Perception of Migraine Questionnaire

PPMQ-R:

Patient Perception of Migraine Questionnaire-Revised

MTSM:

Migraine Treatment Satisfaction Measure

SPM:

Patient Satisfaction with Pain Medication Questionnaire

PTSS:

Pain Treatment Satisfaction Scale

MSTCQ:

Multiple Sclerosis Treatment Concerns Questionnaire

CTSQ:

Cancer Therapy Satisfaction Questionnaire

RASQ:

Rituximab Administration Satisfaction Questionnaire

TSQ-G:

Treatment Satisfaction Questionnaire for Gastro-esophageal reflux disease

GTSQ:

Gastroesophageal Reflux Disease Treatment Satisfaction Questionnaire

TSQ-C:

Treatment Satisfaction Questionnaire for Crohn’s Disease

SPACE-Q:

Satisfaction of PAtients with Crohn's disease Questionnaire

SWAM Scale ®:

Satisfaction With Antipsychotic Medication scale ®

SAMS:

Satisfaction with Medication Scale

PASAP:

PAtient SAtisfaction with Psychotropics questionnaire

MSQ:

Medication Satisfaction Questionnaire

SASMAT-METHER:

Satisfaction with Medications for Addiction Treatment-methadone for Heroin Addiction questionnaire

SASMAT-BUNHER:

Satisfaction with Medications for Addiction Treatment-Buprenorphine-Naloxone for Heroin addiction questionnaire

HIVTSQs:

Human Immunodeficiency Virus (HIV) Treatment Satisfaction Questionnaire—Status version

HIVTSQc:

HIV Treatment Satisfaction Questionnaire—Change version

ESTAR:

Escala de Satisfacción con el Tratamiento Antirretroviral, Antiretroviral Treatment Satisfaction scale

GHerpTSQ:

Genital Herpes Treatment Satisfaction Questionnaire

HCVTSat:

Chronic Hepatitis C Virus Treatment Satisfaction questionnaire

TSS-IOP:

Treatment Satisfaction Survey for Intraocular Pressure

RetTSQs:

Retinopathy Treatment Satisfaction Questionnaire (status)

EDSQ:

Eye-Drop Satisfaction Questionnaire

MacTSQ:

Macular Disease Treatment Satisfaction Questionnaire

DermaSat:

Satisfaction with dermatological treatment of hand eczema questionnaire

OPSAT-Q:

Osteoporosis Patient Satisfaction Questionnaire

OAB-S:

Overactive Bladder Satisfaction Questionnaire

PESaM:

Patient Experiences and Satisfaction with Medications Questionnaire

EDITS:

Erectile Dysfunction Inventory of Treatment Satisfaction Questionnaire

ESPIA:

Satisfaction Scale for Patients Receiving Allergen Immunotherapy Questionnaire

SSQ:

Systemic Lupus Erythematosus Steroid Questionnaire

SICT:

Satisfaction with Iron Chelation Therapy Questionnaire

ICT-Sat:

Satisfaction with Iron Chelation Therapy for patients questionnaire

SQ-ISHI:

Satisfaction Questionnaire with Intravenous or Subcutaneous Hemophilia Injection

TASQ:

Therapy Administration Satisfaction Questionnaire

TASQ-SC:

Therapy Administration Satisfaction Questionnaire—subcutaneous

TASQ-IV:

Therapy Administration Satisfaction Questionnaire—intravenous

TSTMQ:

Treatment Satisfaction with Traditional Medicines Questionnaire

References

  1. Shikiar R, Rentz AM. Satisfaction with medication: an overview of conceptual, methodologic, and regulatory issues. Value Health. 2004;7(2):204–15. https://doi.org/10.1111/j.1524-4733.2004.72252.x.

    Article  PubMed  Google Scholar 

  2. U.S. Food and Drug Administration (FDA). FDA patient-focused drug development guidance series for enhancing the incorporation of the patient’s voice in medical product development and regulatory decision making. 2018–2023. [Online]. Available at: https://www.fda.gov/drugs/development-approval-process-drugs/fda-patient-focused-drug-development-guidance-series-enhancing-incorporation-patients-voice-medical. Accessed 18 Aug 2023.

  3. European Medicines Agency Committee for Medicinal Products for Human Use. 2 to the Guideline on the Evaluation of Anticancer Medicinal Products in Man: The Use of Patient-Reported Outcome (PRO) Measures in Oncology Studies EMA/CHMP/292464/2014. London, England: European Medicines Agency; 2016.

    Google Scholar 

  4. Tunis SR, Stryer DB, Clancy CM. Practical clinical trials increasing the value of clinical research for decision making in clinical and health policy. JAMA. 2003;290(12):1624–32. https://doi.org/10.1001/jama.290.12.1624.

    Article  PubMed  CAS  Google Scholar 

  5. Barbosa CD, Balp MM, Kulich K, Germain N, Rofail D. A literature review to explore the link between treatment satisfaction and adherence, compliance, and persistence. Patient Prefer Adherence. 2012;6:39–48. https://doi.org/10.2147/ppa.S24752.

    Article  PubMed  PubMed Central  Google Scholar 

  6. DeVellis RF, Thorpe CT. Scale Development: Theory and Applications. 5th ed. Thousand Oaks, CA: SAGE Publications; 2021.

    Google Scholar 

  7. U.S. Food and Drug Administration (FDA). Guidance for industry: patient-reported outcome measures: use in medical product development to support labeling claims. Silver Spring, MD: US Food and Drug Administration; 2009.

    Google Scholar 

  8. Black N. Patient reported outcome measures could help transform healthcare. BMJ. 2013;346:f167. https://doi.org/10.1136/bmj.f167.

    Article  PubMed  Google Scholar 

  9. Krogsgaard MR, Brodersen J, Jensen J, Hansen CF, Comins JD. Potential problems in the use of patient reported outcome measures (PROMs) and reporting of PROMs data in sports science. Scand J Med Sci Sports. 2021;31(6):1249–58. https://doi.org/10.1111/sms.13888.

    Article  PubMed  Google Scholar 

  10. Mokkink LB, Prinsen CA, Bouter LM, Vet HC, Terwee CB. The COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) and how to select an outcome measurement instrument. Braz J Phys Ther. 2016;20(2):105–13. https://doi.org/10.1590/bjpt-rbf.2014.0143.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Ioannidis JPA, Greenland S, Hlatky MA, et al. Increasing value and reducing waste in research design, conduct, and analysis. Lancet. 2014;383(9912):166–75. https://doi.org/10.1016/S0140-6736(13)62227-8.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Rofail D, Taylor F, Regnault A, Filonenko A. Treatment satisfaction instruments for different purposes during a product’s lifecycle: keeping the end in mind. Patient. 2011;4(4):227–40. https://doi.org/10.2165/11595280-000000000-00000.

    Article  PubMed  Google Scholar 

  13. Bharmal M, Viswanathan S. Treatment satisfaction with medication: a review of conceptual frameworks and applications. Value Health. 2010;13(7):A338. https://doi.org/10.1016/S1098-3015(11)72335-X.

    Article  Google Scholar 

  14. Guglieri M, Bushby K, McDermott MP, et al. Effect of different corticosteroid dosing regimens on clinical outcomes in boys with Duchenne muscular dystrophy: a randomized clinical trial. JAMA. 2022;327(15):1456–68. https://doi.org/10.1001/jama.2022.4315.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  15. Buse JB, Nauck M, Forst T, et al. Exenatide once weekly versus liraglutide once daily in patients with type 2 diabetes (duration-6): a randomised, open-label study. Lancet. 2013;381(9861):117–24. https://doi.org/10.1016/S0140-6736(12)61267-7.

    Article  PubMed  CAS  Google Scholar 

  16. Basch E, Reeve BB, Mitchell SA, et al. Development of the national cancer institute’s patient-reported outcomes version of the common terminology criteria for adverse events (PRO-CTCAE). JNCI: Journal of the National Cancer Institute. 2014;106(9). https://doi.org/10.1093/jnci/dju244.

  17. Sælen MG, Hjelle LV, Aarsæther E, et al. Patient-reported outcomes after curative treatment for prostate cancer with prostatectomy, primary radiotherapy or salvage radiotherapy. Acta Oncologica. 2023;62(6):657–65. https://doi.org/10.1080/0284186X.2023.2224051.

    Article  PubMed  Google Scholar 

  18. Page MJ, McKenzie JE, Bossuyt PM, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ. 2021;372:n71. https://doi.org/10.1136/bmj.n71.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Prinsen CAC, Mokkink LB, Bouter LM, et al. COSMIN guideline for systematic reviews of patient-reported outcome measures. Qual Life Res. 2018;27(5):1147–57. https://doi.org/10.1007/s11136-018-1798-3.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  20. Mokkink LB, Prinsen CA, Patrick DL, Alonso J, Bouter LM, De Vet HC, et al. COSMIN methodology for systematic reviews of Patient-Reported Outcome Measures (PROMs) - user manual version 1.0 February. 2018. Available at: https://cosmin.nl/wp-content/uploads/COSMIN-syst-review-for-PROMs-manual_version-1_feb-2018.pdf. Accessed 23 May 2023.

  21. Terwee CB, Prinsen CA, Chiarotto A, et al. COSMIN methodology for assessing the content validity of PROMs - user manual version 1.0 February. 2018. Available at: https://cosmin.nl/wp-content/uploads/COSMIN-methodology-for-content-validity-user-manual-v1.pdf. Accessed 23 May 2023.

  22. Terwee CB, Bot SDM, de Boer MR, et al. Quality criteria were proposed for measurement properties of health status questionnaires. J Clin Epidemiol. 2007;60(1):34–42. https://doi.org/10.1016/j.jclinepi.2006.03.012.

    Article  PubMed  Google Scholar 

  23. Mokkink LB, de Vet HCW, Prinsen CAC, et al. COSMIN risk of bias checklist for systematic reviews of patient-reported outcome measures. Qual Life Res. 2018;27(5):1171–9. https://doi.org/10.1007/s11136-017-1765-4.

    Article  PubMed  CAS  Google Scholar 

  24. Guyatt G, Oxman AD, Akl EA, et al. GRADE guidelines: 1. Introduction—GRADE evidence profiles and summary of findings tables. J Clin Epidemiol. 2011;64(4):383–94. https://doi.org/10.1016/j.jclinepi.2010.04.026.

    Article  PubMed  Google Scholar 

  25. Atkinson MJ, Sinha A, Hass SL, et al. Validation of a general measure of treatment satisfaction, the treatment satisfaction questionnaire for medication (TSQM), using a national panel study of chronic disease. Health Qual Life Outcomes. 2004;2(1):12. https://doi.org/10.1186/1477-7525-2-12.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Regnault A, Balp MM, Kulich K, Viala-Danten M. Validation of the treatment satisfaction questionnaire for medication in patients with cystic fibrosis. J Cyst Fibros. 2012;11(6):494–501. https://doi.org/10.1016/j.jcf.2012.04.007.

    Article  PubMed  Google Scholar 

  27. Trujols J, Iraurgi I, Sinol N, Portella MJ, de los Cobos JP, et al. Satisfaction with methadone as a medication psychometric properties of the Spanish version of the treatment satisfaction questionnaire for medication. J Clin Psychopharmacol. 2012;32(1):69–74. https://doi.org/10.1097/JCP.0b013e3182401e09.

    Article  PubMed  Google Scholar 

  28. Shilbayeh SAR, Alyahya SA, Alshammari NH, Almutairi WA, Shaheen E. Treatment satisfaction questionnaire for medication: validation of the translated Arabic version among patients undergoing warfarin therapy in Saudi Arabia. Value Health Reg Issues. 2018;16:14–21. https://doi.org/10.1016/j.vhri.2018.01.007.

    Article  PubMed  Google Scholar 

  29. AL-M LAI, Allela OQB, Salih HM, Ahmed IH. Medication satisfaction in diabetic patients: Kurdish version. J Public Health (Berl). 2020;30(4):879–84. https://doi.org/10.1007/s10389-020-01367-z.

    Article  Google Scholar 

  30. Atkinson MJ, Kumar R, Cappelleri JC, Hass SL. Hierarchical construct validity of the treatment satisfaction questionnaire for medication (TSQM Version II) among outpatient pharmacy consumers. Value Health. 2005;8:S9–24. https://doi.org/10.1111/j.1524-4733.2005.00066.x.

    Article  PubMed  Google Scholar 

  31. Delestras S, Roustit M, Bedouch P, et al. Comparison between two generic questionnaires to assess satisfaction with medication in chronic diseases. PLoS ONE. 2013;8(2):e56247. https://doi.org/10.1371/journal.pone.0056247.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  32. Shang YB, Liu HX, Yu LX, et al. Transcultural adaptation of the treatment satisfaction questionnaire for medication. Chin Nurs Manag. 2018;18(05):612-616. Available at: http://www.zghlgl.com/EN/https://doi.org/10.3969/j.issn.1672-1756.2018.05.008. 23 May 2023.

  33. Shen ZY, Ding SQ, Zhong ZQ, Shi SJ, Li SG.Validity and reliability of the Chinese version of the treatment satisfaction questionnaire for medication-second edition in patients with hypertension. Chin Men. Health J. 2021;35(04):277-283. Available at: https://kns.cnki.net/kcms/detail/11.1873.R.20210309.1832.008.html. 23 May 2023.

  34. Watanabe-Fujinuma E, Banderas BF, Koretsune Y, et al. Psychometric validation of anti-clot treatment scale and treatment satisfaction questionnaire for medication version II in Japanese patients with atrial fibrillation. J Med Econ. 2019;22(8):798–805. https://doi.org/10.1080/13696998.2019.1609003.

    Article  PubMed  Google Scholar 

  35. Abdshah A, Parsaeian M, Nasimi M, Ghiasi M. Validating the “treatment satisfaction questionnaire for medication” in Persian and evaluating treatment satisfaction among patients with psoriasis. Value Health Reg Issues. 2022;29:16–20. https://doi.org/10.1016/j.vhri.2021.06.008.

    Article  PubMed  Google Scholar 

  36. Bharmal M, Payne K, Atkinson MJ, Desrosiers MP, Morisky DE, Gemmen E. Validation of an abbreviated treatment satisfaction questionnaire for medication (TSQM-9) among patients on antihypertensive medications. Health Qual Life Outcomes. 2009;7:36. https://doi.org/10.1186/1477-7525-7-36.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Ruiz MA, Pardo A, Rejas J, Soto J, Villasante F, Aranguren JL. Development and validation of the “treatment satisfaction with medicines questionnaire” (SATMED-Q)©. Value Health. 2008;11(5):913–26. https://doi.org/10.1111/j.1524-4733.2008.00323.x.

    Article  PubMed  Google Scholar 

  38. Rejas J, Ruiz M, Pardo A, Soto J. Detecting changes in patient treatment satisfaction with medicines: the SATMED-Q. Value Health. 2013;16(1):88–96. https://doi.org/10.1016/j.jval.2012.08.2224.

    Article  PubMed  Google Scholar 

  39. López-Torres López J, Rabanales-Sotos J, López-Torres Hidalgo MR, MiliánGarcía RM, LópezMartínez C, Blázquez Abellán G. Reliability and validity of the treatment satisfaction with medicines questionnaire (SATMED-Q) in persons with arterial hypertension. Int J Environ Res Public Health. 2021;18(6):3212. https://doi.org/10.3390/ijerph18063212.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Świątoniowska-Lonc N, Kołtuniuk A, Jankowska-Polańska B. Psychometric properties of the treatment satisfaction with medicines questionnaire (SATMED-Q) in patients with diabetes, arterial hypertension and heart failure. Int J Environ Res Public Health. 2022;19(3):1088. https://doi.org/10.3390/ijerph19031088.

    Article  PubMed  PubMed Central  Google Scholar 

  41. Cappelleri JC, Gerber RA, Kourides IA, Gelfand RA. Development and factor analysis of a questionnaire to measure patient satisfaction with injected and inhaled insulin for type 1 diabetes. Diabetes Care. 2000;23(12):1799–803. https://doi.org/10.2337/diacare.23.12.1799.

    Article  PubMed  CAS  Google Scholar 

  42. Anderson RT, Skovlund SE, Marrero D, et al. Development and validation of the insulin treatment satisfaction questionnaire. Clin Ther. 2004;26(4):565–78. https://doi.org/10.1016/S0149-2918(04)90059-8.

    Article  PubMed  Google Scholar 

  43. Brod M, Christensen T, Bushnell D. Maximizing the value of validation findings to better understand treatment satisfaction issues for diabetes. Qual Life Res. 2007;16(6):1053–63. https://doi.org/10.1007/s11136-007-9209-1.

    Article  PubMed  Google Scholar 

  44. Brod M, Skovlund SE, Wittrup-Jensen KU. Measuring the impact of diabetes through patient report of treatment satisfaction, productivity and symptom experience. Qual Life Res. 2006;15(3):481–91. https://doi.org/10.1007/s11136-005-1624-6.

    Article  PubMed  Google Scholar 

  45. Woodcock A, Bain S, Charlton M, Bradley C. Extent of satisfaction with tablets and food-timing in sulphonyl urea-treated diabetes. Diabetes Res Clin Pract. 2007;78(3):324–33. https://doi.org/10.1016/j.diabres.2005.07.013.

    Article  PubMed  CAS  Google Scholar 

  46. Donatti C, Wild D, Horblyuk R, et al. Psychometric evaluation of the satisfaction with oral anti-diabetic agent scale (SOADAS). Diabetes Res Clin Pract. 2008;80(1):108–13. https://doi.org/10.1016/j.diabres.2007.11.005.

    Article  PubMed  Google Scholar 

  47. Lin YJ, Wang CY, Chang EH, Cheng SW, Ko Y. Translation, revision, and validation of the Chinese version of the satisfaction with oral anti-diabetic agent scale (C-SOADAS) in patients with type 2 diabetes mellitus. Patient Prefer Adherence. 2018;12:667–72. https://doi.org/10.2147/ppa.S162268.

    Article  PubMed  PubMed Central  Google Scholar 

  48. Anderson RT, Girman CJ, Pawaskar MD, et al. Diabetes medication satisfaction tool: a focus on treatment regimens. Diabetes Care. 2009;32(1):51–3. https://doi.org/10.2337/dc08-0856.

    Article  PubMed  PubMed Central  Google Scholar 

  49. Monahan PO, Lane KA, Hayes RP, McHorney CA, Marrero DG. Reliability and validity of an instrument for assessing patients’ perceptions about medications for diabetes: the PAM-D. Qual Life Res. 2009;18(7):941–52. https://doi.org/10.1007/s11136-009-9510-2.

    Article  PubMed  Google Scholar 

  50. Rubin RR, Peyrot M. Psychometric properties of an instrument for assessing treatment satisfaction associated with pramlintide use. Diabetes Educ. 2009;35(1):136–46. https://doi.org/10.1177/0145721708326989.

    Article  PubMed  Google Scholar 

  51. Sampson MJ, Singh H, Dhatariya KK, Jones C, Walden E, Bradley C. Psychometric validation and use of a novel diabetes in-patient treatment satisfaction questionnaire. Diabet Med. 2009;26(7):729–35. https://doi.org/10.1111/j.1464-5491.2009.02754.x.

    Article  PubMed  CAS  Google Scholar 

  52. Ishii H, Oda E. Reproducibility and validity of a satisfaction questionnaire on hypoglycemic agents: the oral hypoglycemic agent questionnaire (OHA-Q). Diabetol Int. 2012;3(3):152–63. https://doi.org/10.1007/s13340-012-0074-y.

    Article  Google Scholar 

  53. Peyrot M, Harshaw Q, Shillington AC, Xu Y, Rubin RR. Validation of a tool to assess medication treatment satisfaction in patients with type 2 diabetes: the diabetes medication system rating questionnaire (DMSRQ). Diabet Med. 2012;29(8):1060–6. https://doi.org/10.1111/j.1464-5491.2011.03538.x.

    Article  PubMed  CAS  Google Scholar 

  54. Peyrot M, Xu Y, Rubin RR. Development and validation of the diabetes medication system rating questionnaire-short form. Diabet Med. 2014;31(10):1237–44. https://doi.org/10.1111/dme.12453.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  55. Manning ML, Singh H, Stoner K, Habif S. The development and psychometric validation of the diabetes impact and device satisfaction scale for individuals with type 1 diabetes. J Diabetes Sci Technol. 2020;14(2):309–17. https://doi.org/10.1177/1932296819897976.

    Article  PubMed  PubMed Central  Google Scholar 

  56. Mcmillan CV, Bradley C, Woodcock A, Razvi S, Weaver JU. Design of new questionnaires to measure quality of life and treatment satisfaction in hypothyroidism. Thyroid. 2004;14(11):916–25. https://doi.org/10.1089/thy.2004.14.916.

    Article  PubMed  CAS  Google Scholar 

  57. McMillan C, Bradley C, Razvi S, Weaver J. Psychometric evaluation of a new questionnaire measuring treatment satisfaction in hypothyroidism: the ThyTSQ. Value Health. 2006;9(2):132–9. https://doi.org/10.1111/j.1524-4733.2006.00091.x.

    Article  PubMed  Google Scholar 

  58. Hill CD, Fehnel SE, Bobula JD, Yu H, McLeod LD. Development and preliminary validation of the menopause symptoms treatment satisfaction questionnaire (MS-TSQ). Menopause. 2007;14(6):1047–55. https://doi.org/10.1097/gme.0b013e31803816b8.

    Article  PubMed  Google Scholar 

  59. Fleseriu M, Fogelfeld L, Gordon MB, et al. Development of a novel patient-reported measure for acromegaly: the Acro-TSQ. Pituitary. 2019;22(6):581–93. https://doi.org/10.1007/s11102-019-00986-4.

    Article  PubMed  PubMed Central  Google Scholar 

  60. Fleseriu M, Fogelfeld L, Gordon MB, et al. An evaluation of the acromegaly treatment satisfaction questionnaire (Acro-TSQ) in adult patients with acromegaly, including correlations with other patient-reported outcome measures: data from two large multicenter international studies. Pituitary. 2020;23(4):347–58. https://doi.org/10.1007/s11102-020-01038-y.

    Article  PubMed  PubMed Central  Google Scholar 

  61. Samsa G, Matchar DB, Dolor RJ, et al. A new instrument for measuring anticoagulation-related quality of life: development and preliminary validation. Health Qual Life Outcomes. 2004;2:22. https://doi.org/10.1186/1477-7525-2-22.

    Article  PubMed  PubMed Central  Google Scholar 

  62. Pelegrino FM, Dantas RA, Corbi IS, da Silva Carvalho AR, Schmidt A, Pazin FA. Cross-cultural adaptation and psychometric properties of the Brazilian-Portuguese version of the duke anticoagulation satisfaction scale. J Clin Nurs. 2012;21(17–18):2509–17. https://doi.org/10.1111/j.1365-2702.2011.03869.x.

    Article  PubMed  Google Scholar 

  63. Riva N, Borg Xuereb C, Ageno W, Makris M, Gatt A. Validation and psychometric properties of the Maltese version of the duke anticoagulation satisfaction scale (DASS). Psychol Res Behav Manag. 2019;12:741–52. https://doi.org/10.2147/prbm.S216617.

    Article  PubMed  PubMed Central  Google Scholar 

  64. AlAmmari M, Sultana K, AlHarbi SN, et al. Validation and psychometric properties of the Arabic version of the duke anticoagulation satisfaction scale (DASS). Original Research. Front Pharmacol. 2020;11. https://doi.org/10.3389/fphar.2020.587489.

  65. Wu Y, Dong S, Li X, Xu H, Xie X. The transcultural adaptation and validation of the Chinese version of the duke anticoagulation satisfaction scale. Front Pharmacol. 2022;13:790293. https://doi.org/10.3389/fphar.2022.790293.

    Article  PubMed  PubMed Central  Google Scholar 

  66. Prins MH, Guillemin I, Gilet H, et al. Scoring and psychometric validation of the perception of anticoagulant treatment questionnaire (PACT-Q). Health Qual Life Outcomes. 2009;7:30. https://doi.org/10.1186/1477-7525-7-30.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  67. Riva N, Borg Xuereb C, Makris M, Ageno W, Gatt A. Reliability and validity of the Maltese version of the perception of anticoagulant treatment questionnaire (PACT-Q). Patient Prefer Adherence. 2019;13:969–79. https://doi.org/10.2147/ppa.S207498.

    Article  PubMed  PubMed Central  Google Scholar 

  68. Cano SJ, Lamping DL, Bamber L, Smith S. The anti-clot treatment scale (ACTS) in clinical trials: cross-cultural validation in venous thromboembolism patients. Health Qual Life Outcomes. 2012;10:120. https://doi.org/10.1186/1477-7525-10-120.

    Article  PubMed  PubMed Central  Google Scholar 

  69. Suárez C, Pose A, Montero-Pérez-Barquero M, et al. Validation of satisfaction questionnaire ACTS in outpatients with atrial fibrillation treated with oral anticoagulants in Spain. ALADIN study Med Clin (Barc). 2016;147(5):192–8. https://doi.org/10.1016/j.medcli.2016.05.024.

    Article  PubMed  Google Scholar 

  70. Comuth WJ, Lauridsen HH, Kristensen SD, Münster A-MB. Translation, cultural adaptation, and psychometric properties of the Danish version of the anti-clot treatment scale. TH Open. 2018;02(03):e280–90. https://doi.org/10.1055/s-0038-1670631.

    Article  Google Scholar 

  71. Shilbayeh SAR, Ibrahim AA. The anti-clot treatment scale (ACTS): validation of the translated Arabic version among patients undergoing warfarin therapy in Saudi Arabia. Health Qual Life Outcomes. 2020;18(1):215. https://doi.org/10.1186/s12955-020-01471-4.

    Article  PubMed  PubMed Central  Google Scholar 

  72. Shilbayeh SAR, Ismail S. Translation, pilot psychometric validation, and comparative performance of the Arabic version of the anti-clot treatment scale (ACTS). J Pharm Bioallied Sci. 2021;13(1):61–8. https://doi.org/10.4103/jpbs.JPBS_395_20.

    Article  PubMed  Google Scholar 

  73. Yi YL. Translation and preliminary application of the anti-clot treatment scale (ACTS). Nanhua University, China; 2021. https://doi.org/10.27234/d.cnki.gnhuu.2021.000959.

  74. Mathias SD, Warren EH, Colwell HH, Sung JC. A new treatment satisfaction measure for asthmatics: a validation study. Qual Life Res. 2000;9(7):873–82. https://doi.org/10.1023/a:1008913209828.

    Article  PubMed  CAS  Google Scholar 

  75. Campbell JL, Kiebert GM, Partridge MR. Development of the satisfaction with inhaled asthma treatment questionnaire. Eur Respir J. 2003;22(1):127–34. https://doi.org/10.1183/09031936.03.00097503.

    Article  PubMed  CAS  Google Scholar 

  76. Martin Fernandez J, Barcina Sanchez C, Jimenez Barcia FJ, Marazuela Bermejo R. Validation study of the Spanish adaptation of the satisfaction with inhaled asthma treatment questionnaire. Arch Bronconeumol. 2006;42(11):575.

    Article  PubMed  Google Scholar 

  77. Dońka K, Czarnocki KJ, Emeryk A. Validation of the polish version of satisfaction with asthma treatment questionnaire (SATQ). Postepy Dermatol Alergol. 2017;34(1):77–81. https://doi.org/10.5114/ada.2017.65625.

    Article  PubMed  PubMed Central  Google Scholar 

  78. Kozma CM, Slaton TL, Monz BU, Hodder R, Reese PR. Development and validation of a patient satisfaction and preference questionnaire for inhalation devices. Treat Respir Med. 2005;4(1):41–52. https://doi.org/10.2165/00151829-200504010-00005.

    Article  PubMed  Google Scholar 

  79. Davis KH, Black L, Sleath B. Validation of the patient perception of migraine questionnaire. Value Health. 2002;5(5):422–30. https://doi.org/10.1046/J.1524-4733.2002.55120.x.

    Article  PubMed  Google Scholar 

  80. Revicki DA, Kimel M, Beusterien K, et al. Validation of the revised patient perception of migraine questionnaire: measuring satisfaction with acute migraine treatment. Headache. 2006;46(2):240–52. https://doi.org/10.1111/j.1526-4610.2006.00289.x.

    Article  PubMed  Google Scholar 

  81. Kimel M, Hsieh R, McCormack J, Burch S, Revicki D. Validation of the revised patient perception of migraine questionnaire (PPMQ-R): measuring satisfaction with acute migraine treatment in clinical trials. Cephalalgia. 2008;28(5):510–23. https://doi.org/10.1111/j.1468-2982.2007.01524.x.

    Article  PubMed  CAS  Google Scholar 

  82. Patrick DL, Martin ML, Bushmell DM, Pesa J. Measuring satisfaction with migraine treatment: expectations, importance, outcomes, and global ratings. Clin Ther. 2003;25(11):2920–35. https://doi.org/10.1016/S0149-2918(03)80345-4.

    Article  PubMed  Google Scholar 

  83. Martin ML, Patrick DL, Bushnell DM, Gandra SR, Gilchrist K. Further validation of an individualized migraine treatment satisfaction measure. Value Health. 2008;11(5):904–12. https://doi.org/10.1111/j.1524-4733.2008.00320.x.

    Article  PubMed  Google Scholar 

  84. Baró E, Casado A, García-Cases C, Clerch L, Ribas S. Assessing satisfaction with pain medication in primary care patients: development and psychometric validation of a new measure. Clin Ther. 2004;26(7):1124–36. https://doi.org/10.1016/s0149-2918(04)90185-3.

    Article  PubMed  Google Scholar 

  85. Evans CJ, Trudeau E, Mertzanis P, et al. Development and validation of the pain treatment satisfaction scale (PTSS): a patient satisfaction questionnaire for use in patients with chronic or acute pain. Pain. 2004;112(3):254–66. https://doi.org/10.1016/j.pain.2004.09.005.

    Article  PubMed  Google Scholar 

  86. Wong WS, Chen PP, Chow YF, Wong S, Fielding R. The reliability and validity of the Cantonese version of the pain treatment satisfaction scale (ChPTSS) in a sample of Chinese patients with chronic pain. Pain Med. 2015;16(12):2316–23. https://doi.org/10.1111/pme.12790.

    Article  PubMed  Google Scholar 

  87. Cramer JA, Cuffel BJ, Divan V, Al-Sabbagh A, Glassman M. Patient satisfaction with an injection device for multiple sclerosis treatment. Acta Neurol Scand. 2006;113(3):156–62. https://doi.org/10.1111/j.1600-0404.2005.00568.x.

    Article  PubMed  CAS  Google Scholar 

  88. Muntéis Olivas E, Navarro Mascarell G, Meca Lallana J, et al. Cultural adaptation and validation of a peninsular Spanish version of the MSTCQ (©) (multiple sclerosis treatment concerns questionnaire). Neurologia. 2017;32(1):29–39. https://doi.org/10.1016/j.nrl.2014.12.011.

    Article  PubMed  Google Scholar 

  89. Biraben A, Allaf B. An instrument to assess patient satisfaction with epilepsy treatment. Epilepsy Behav. 2015;43:24–9. https://doi.org/10.1016/j.yebeh.2014.11.031.

    Article  PubMed  Google Scholar 

  90. Abetz L, Coombs JH, Keininger DL, et al. Development of the cancer therapy satisfaction questionnaire: item generation and content validity testing. Value Health. 2005;8:S41–53. https://doi.org/10.1111/j.1524-4733.2005.00073.x.

    Article  PubMed  Google Scholar 

  91. Trask PC, Tellefsen C, Espindle D, Getter C, Hsu M-A. Psychometric validation of the cancer therapy satisfaction questionnaire. Value Health. 2008;11(4):669–79. https://doi.org/10.1111/j.1524-4733.2007.00310.x.

    Article  PubMed  Google Scholar 

  92. Park SJ, An SM, Kim SH. Development of a Korean version of the cancer therapy satisfaction questionnaire (CTSQ): cross-cultural adaptation, reliability, and validity. Qual Life Res. 2013;22(2):431–6. https://doi.org/10.1007/s11136-012-0164-0.

    Article  PubMed  Google Scholar 

  93. Cheung K, de Mol M, Visser S, Den Oudsten BL, Stricker BH, Aerts JGJV. Reliability and validity of the cancer therapy satisfaction questionnaire in lung cancer. Qual Life Res. 2016;25(1):71–80. https://doi.org/10.1007/s11136-015-1062-z.

    Article  PubMed  CAS  Google Scholar 

  94. Norhaliza Abd H, Nur Amirah H, Nizuwan A, Mohammad Farris Iman Leong Bin A. Validation of the Malay version of the cancer therapy satisfaction questionnaire among Malaysian cancer patients. Malaysian J Public Health Med. 2021;21(1):274–285. https://doi.org/10.37268/mjphm/vol.21/no.1/art.845.

  95. Theodore-Oklota C, Humphrey L, Wiesner C, Schnetzler G, Hudgens S, Campbell A. Validation of a treatment satisfaction questionnaire in non-Hodgkin lymphoma: assessing the change from intravenous to subcutaneous administration of rituximab. Patient Prefer Adherence. 2016;10:1767–76. https://doi.org/10.2147/ppa.S108489.

    Article  PubMed  PubMed Central  Google Scholar 

  96. Coyne KS, Wiklund I, Schmier J, Halling K, Degl’ Innocenti A, Revicki D. Development and validation of a disease-specific treatment satisfaction questionnaire for gastro-oesophageal reflux disease. Aliment Pharmacol Ther. 2003;18(9):907–15. https://doi.org/10.1046/j.1365-2036.2003.01674.x.

    Article  PubMed  CAS  Google Scholar 

  97. Shikiar R, Flood E, Siddique R, Howell J, Dodd SL. Development and validation of the gastroesophageal reflux disease treatment satisfaction questionnaire. Dig Dis Sci. 2005;50(11):2025–33. https://doi.org/10.1007/s10620-005-3002-1.

    Article  PubMed  Google Scholar 

  98. Coyne K, Joshua-Gotlib S, Kimel M, Thompson C, Lewis A, Danilewitz M. Validation of the treatment satisfaction questionnaire for Crohn’s disease (TSQ-C). Dig Dis Sci. 2005;50(2):252–8. https://doi.org/10.1007/s10620-005-1591-3.

    Article  PubMed  Google Scholar 

  99. Marant C, Arnould B, Marrel A, et al. Assessing patients’ satisfaction with anti-TNFα treatment in Crohn’s disease: qualitative steps of the development of a new questionnaire. Clin Exp Gastroenterol. 2011;4:173–80. https://doi.org/10.2147/CEG.S18585.

    Article  PubMed  PubMed Central  Google Scholar 

  100. Gilet H, Arnould B, Fofana F, et al. Measuring patients’ satisfaction with their anti-TNF treatment in severe Crohn’s disease: scoring and psychometric validation of the satisfaction for patients in Crohn’s disease questionnaire (SPACE-Q©). Patient Prefer Adherence. 2014;8:1671–81. https://doi.org/10.2147/PPA.S72004.

    Article  PubMed  PubMed Central  Google Scholar 

  101. Rofail D, Gray R, Gournay K. The development and internal consistency of the satisfaction with antipsychotic medication scale. Psychol Med. 2005;35(7):1063–72. https://doi.org/10.1017/s0033291705004526.

    Article  PubMed  Google Scholar 

  102. Görtz-Dorten A, Breuer D, Hautmann C, Rothenberger A, Döpfner M. What contributes to patient and parent satisfaction with medication in the treatment of children with ADHD? A report on the development of a new rating scale. Eur Child Adolesc Psychiatry. 2011;20 Suppl2(Suppl 2):S297-307. https://doi.org/10.1007/s00787-011-0207-z.

    Article  Google Scholar 

  103. Nordon C, Falissard B, Gerard S, et al. Patient satisfaction with psychotropic drugs: validation of the patient satisfaction with psychotropic (PASAP) scale in patients with bipolar disorder. Eur Psychiatry. 2014;29(3):183–90. https://doi.org/10.1016/j.eurpsy.2013.03.001.

    Article  PubMed  CAS  Google Scholar 

  104. Kalali A. Patient satisfaction with, and acceptability of, atypical antipsychotics. Curr Med Res Opin. 1999;15(2):135–7. https://doi.org/10.1185/03007999909113374.

    Article  PubMed  CAS  Google Scholar 

  105. Vernon MK, Revicki DA, Awad AG, et al. Psychometric evaluation of the medication satisfaction questionnaire (MSQ) to assess satisfaction with antipsychotic medication among schizophrenia patients. Schizophr Res. 2010;118(1):271–8. https://doi.org/10.1016/j.schres.2010.01.021.

    Article  PubMed  Google Scholar 

  106. de los Cobos JP, Trujols J, Siñol N, Batlle F. Development and validation of the scale to assess satisfaction with medications for addiction treatment-methadone for heroin addiction (SASMAT-METHER). Drug Alcohol Depend. 2014;142:79–85. https://doi.org/10.1016/j.drugalcdep.2014.05.024.

    Article  PubMed  CAS  Google Scholar 

  107. de los Pérez Cobos J, Trujols J, Alcaraz S, Siñol N, Lozano Ó, González-Saiz F. Development and validation of the scale to assess satisfaction with medications for addiction treatment - buprenorphine-naloxone for heroin addiction (SASMAT-BUNHER). Int J Drug Policy. 2018;58:126–34. https://doi.org/10.1016/j.drugpo.2018.06.007.

    Article  Google Scholar 

  108. Woodcock A, Bradley C. Validation of the HIV treatment satisfaction questionnaire (HIVTSQ). Qual Life Res. 2001;10(6):517–31. https://doi.org/10.1023/a:1013050904635.

    Article  PubMed  CAS  Google Scholar 

  109. Woodcock A, Bradley C. Validation of the revised 10-item HIV treatment satisfaction questionnaire status version and new change version. Value Health. 2006;9(5):320–33. https://doi.org/10.1111/j.1524-4733.2006.00121.x.

    Article  PubMed  Google Scholar 

  110. Ventura Cerdá JM, Casado Gómez MA, Morales González JM, Ortega Valín L, Ibarra Barruéta O, Escobar RI. Psychometric characteristics of the antiretroviral treatment satisfaction scale (ESTAR): ARPAS study (I). Farm Hosp. 2007;31(6):331–9. https://doi.org/10.1016/s1130-6343(07)75405-3.

    Article  PubMed  Google Scholar 

  111. Taback NA, Bradley C. Validation of the genital herpes treatment satisfaction questionnaire (GHerpTSQ) in status and change versions. Qual Life Res. 2006;15(6):1043–52. https://doi.org/10.1007/s11136-006-0048-2.

    Article  PubMed  Google Scholar 

  112. Szeinbach SL, Baran RW, Dietz B, Gazzouola Rocca L, Littlefield D, Yawn BP. Development and validation of the chronic hepatitis C virus treatment satisfaction (HCVTSat) instrument. Aliment Pharmacol Ther. 2013;37(5):573–82. https://doi.org/10.1111/apt.12202.

    Article  PubMed  CAS  Google Scholar 

  113. Atkinson MJ, Stewart WC, Fain JM, et al. A new measure of patient satisfaction with ocular hypotensive medications: the treatment satisfaction survey for intraocular pressure (TSS-IOP). Health Qual Life Outcomes. 2003;1:67. https://doi.org/10.1186/1477-7525-1-67.

    Article  PubMed  PubMed Central  Google Scholar 

  114. Woodcock A, Bradley C, Plowright R, Ffytche T, Kennedy-Martin T, Hirsch A. The influence of diabetic retinopathy on quality of life: interviews to guide the design of a condition-specific, individualised questionnaire: The RetDQoL. Patient Educ Couns. 2004;53(3):365–83. https://doi.org/10.1016/j.pec.2003.10.007.

    Article  PubMed  Google Scholar 

  115. Brose LS, Bradley C. Psychometric development of the retinopathy treatment satisfaction questionnaire (RetTSQ). Psychol Health Med. 2009;14(6):740–54. https://doi.org/10.1080/13548500903431485.

    Article  PubMed  Google Scholar 

  116. Karadzic J, Stojkovic M, Risimic D, et al. Cross-cultural validation of the retinopathy treatment satisfaction questionnaire status version (RetTSQs) in Serbian community: a cross-sectional study. BMJ Open. 2020;10(1):e031236. https://doi.org/10.1136/bmjopen-2019-031236.

    Article  PubMed  PubMed Central  Google Scholar 

  117. Nordmann J-P, Denis P, Vigneux M, Trudeau E, Guillemin I, Berdeaux G. Development of the conceptual framework for the eye-drop satisfaction questionnaire (EDSQ©) in glaucoma using a qualitative study. BMC Health Serv Res. 2007;7(1):124. https://doi.org/10.1186/1472-6963-7-124.

    Article  PubMed  PubMed Central  Google Scholar 

  118. Regnault A, Viala-Danten M, Gilet H, Berdeaux G. Scoring and psychometric properties of the eye-drop satisfaction questionnaire (EDSQ), an instrument to assess satisfaction and compliance with glaucoma treatment. BMC Ophthalmol. 2010;10:1. https://doi.org/10.1186/1471-2415-10-1.

    Article  PubMed  PubMed Central  Google Scholar 

  119. Ruiz MA, Pardo A, de la Martinez Casa JM, Polo V, Esquiro J, Soto J. Development of a specific questionnaire measuring patient satisfaction with glaucoma treatment: Glausat. Ophthalmic Epidemiol. 2010;17(3):131–43. https://doi.org/10.3109/09286581003734852.

    Article  PubMed  Google Scholar 

  120. Mitchell J, Bradley C. Design and development of the MacTSQ measure of satisfaction with treatment for macular conditions used within the Ivan trial. J Patient Rep Outcomes. 2018;2(1):5. https://doi.org/10.1186/s41687-018-0031-z.

    Article  PubMed Central  Google Scholar 

  121. Marakis TP, Koutsandrea C, Chatzistefanou KI, Tountas Y. Treatment satisfaction of patients with neovascular age-related macular degeneration treated with anti-vascular endothelial growth factor agents. Int Ophthalmol. 2018;38(2):565–76. https://doi.org/10.1007/s10792-017-0492-8.

    Article  PubMed  Google Scholar 

  122. Shikiar R, Halpern MT, McGann M, Palmer CS, Seidlin M. The relation of patient satisfaction with treatment of otitis externa to clinical outcomes: development of an instrument. Clin Ther. 1999;21(6):1091–104. https://doi.org/10.1016/s0149-2918(99)80027-7.

    Article  PubMed  CAS  Google Scholar 

  123. Ruiz MA, Heras F, Alomar A, et al. Development and validation of a questionnaire on “satisfaction with dermatological treatment of hand eczema” (DermaSat). Health Qual Life Outcomes. 2010;8(1):127. https://doi.org/10.1186/1477-7525-8-127.

    Article  PubMed  PubMed Central  Google Scholar 

  124. Flood EM, Beusterien KM, Green H, et al. Psychometric evaluation of the osteoporosis patient treatment satisfaction questionnaire (OPSAT-Q™), a novel measure to assess satisfaction with bisphosphonate treatment in postmenopausal women. Health Qual Life Outcomes. 2006;4(1):42. https://doi.org/10.1186/1477-7525-4-42.

    Article  PubMed  PubMed Central  Google Scholar 

  125. Piault E, Evans CJ, Espindle D, Kopp Z, Brubaker L, Abrams P. Development and validation of the overactive bladder satisfaction (OAB-S) questionnaire. Neurourol Urodyn. 2008;27(3):179–90. https://doi.org/10.1002/nau.20455.

    Article  PubMed  Google Scholar 

  126. Kimman ML, Rotteveel AH, Wijsenbeek M, et al. Development and pretesting of a questionnaire to assess patient experiences and satisfaction with medications (PESaM Questionnaire). Patient. 2017;10(5):629–42. https://doi.org/10.1007/s40271-017-0234-z.

    Article  PubMed  PubMed Central  Google Scholar 

  127. Kimman ML, Wijsenbeek MS, van Kuijk SMJ, et al. Validity of the patient experiences and satisfaction with medications (PESaM) questionnaire. Patient. 2019;12(1):149–62. https://doi.org/10.1007/s40271-018-0340-6.

    Article  PubMed  Google Scholar 

  128. Althof SE, Corty EW, Levine SB, et al. Edits: development of questionnaires for evaluating satisfaction with treatments for erectile dysfunction. Urology. 1999;53(4):793–9. https://doi.org/10.1016/s0090-4295(98)00582-2.

    Article  PubMed  CAS  Google Scholar 

  129. Kubin M, Trudeau E, Gondek K, Seignobos E, Fugl-Meyer AR. Early conceptual and linguistic development of a patient and partner treatment satisfaction scale (TSS) for erectile dysfunction. Eur Urol. 2004;46(6):768–74. https://doi.org/10.1016/j.eururo.2004.08.001. discussion 774-5.

    Article  PubMed  CAS  Google Scholar 

  130. DiBenedetti DB, Gondek K, Sagnier PP, et al. The treatment satisfaction scale: a multidimensional instrument for the assessment of treatment satisfaction for erectile dysfunction patients and their partners. Eur Urol. 2005;48(3):503–11. https://doi.org/10.1016/j.eururo.2005.05.008.

    Article  PubMed  Google Scholar 

  131. Justícia JL, Baró E, Cardona V, et al. Development of a questionnaire to assess patient satisfaction with allergen-specific immunotherapy in adults: item generation, item reduction, and preliminary validation. Patient Prefer Adherence. 2011;5:239–50. https://doi.org/10.2147/PPA.S19219.

    Article  PubMed  PubMed Central  Google Scholar 

  132. Justicia JL, Cardona V, Guardia P, et al. Validation of the first treatment-specific questionnaire for the assessment of patient satisfaction with allergen-specific immunotherapy in allergic patients: the ESPIA questionnaire. J Allergy Clin Immunol. 2013;131(6):1539-1546.e2. https://doi.org/10.1016/j.jaci.2012.11.049.

    Article  PubMed  Google Scholar 

  133. Mathias SD, Berry P, De Vries J, et al. Development of the systemic lupus erythematosus steroid questionnaire (SSQ): a novel patient-reported outcome tool to assess the impact of oral steroid treatment. Health Qual Life Outcomes. 2017;15(1):43. https://doi.org/10.1186/s12955-017-0609-9.

    Article  PubMed  PubMed Central  Google Scholar 

  134. Rofail D, Abetz L, Viala M, Gait C, Baladi JF, Payne K. Satisfaction and adherence in patients with iron overload receiving iron chelation therapy as assessed by a newly developed patient instrument. Value Health. 2009;12(1):109–17. https://doi.org/10.1111/j.1524-4733.2008.00390.x.

    Article  PubMed  Google Scholar 

  135. Elalfy MS, Massoud W, Elsherif NH, et al. A new tool for the assessment of satisfaction with iron chelation therapy (ICT-SAT) for patients with β-thalassemia major. Pediatr Blood Cancer. 2012;58(6):910–5. https://doi.org/10.1002/pbc.23413.

    Article  PubMed  Google Scholar 

  136. Kempton C, Trask P, Parnes A, et al. Development and testing of the satisfaction questionnaire with intravenous or subcutaneous hemophilia injection and results from the phase 3 HAVEN 3 study of emicizumab prophylaxis in persons with hemophilia a without FVIII inhibitors. Haemophilia. 2021;27(2):221–8. https://doi.org/10.1111/hae.14222.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  137. Doll H, Coşkun U, Hartford C, Tomazos I. Concept confirmation of the treatment administration satisfaction questionnaire (TASQ) in rare paroxysmal nocturnal hemoglobinuria. J Patient Rep Outcomes. 2021;5(1):45. https://doi.org/10.1186/s41687-021-00319-9.

    Article  PubMed  PubMed Central  Google Scholar 

  138. Fataneh H-D, Fatemeh Sadat H-B, Fatemeh Y, Samira K. Development and validation of the “treatment satisfaction with traditional medicines” questionnaire (TSTMQ). Trad Integr Med. 2022;7(3):302–9. https://doi.org/10.18502/tim.v7i3.10772.

    Article  Google Scholar 

  139. Geneva: World Health Organization. International Classification of Diseases Eleventh Revision (ICD-11). Geneva: World Health Organization. 2022. License: CC BY-ND 3.0 IGO. Available at: https://icd.who.int/en. Accessed 23 May 2023.

  140. World Health Organization. Anatomical Therapeutic Chemical (ATC) Classification. Available at: https://www.who.int/tools/atc-ddd-toolkit/atc-classification. Accessed 21 Aug 2023.

  141. IQVIA. Treatment Satisfaction Questionnaire for Medication (TSQM). Available from: https://www.iqvia.com/solutions/research-and-development/consulting/patient-centered-endpoints/clinical-outcome-assessments-coa/tsqm. Accessed 3 Jul 2024.

  142. Weaver M, Patrick DL, Markson LE, Martin D, Frederic I, Berger M. Issues in the measurement of satisfaction with treatment. Am J Manag Care. 1997;3(4):579–94.

    PubMed  CAS  Google Scholar 

  143. Yamamoto Y, Yamaguchi A, Bono H, Takagi T. Allie: A database and a search service of abbreviations and long forms. Database. 2011;2011:bar013. https://doi.org/10.1093/database/bar013 The Allie service is available at http://allie.dbcls.jp/. Accessed 20 Aug 2023.

  144. Niño de Guzmán Quispe E, Martínez García L, Orrego Villagrán C, et al. The perspectives of patients with chronic diseases and their caregivers on self-management interventions: a scoping review of reviews. Patient. 2021;14(6):719–740. https://doi.org/10.1007/s40271-021-00514-2.

  145. Ahmed R, Aslani P. Attention-deficit/hyperactivity disorder: an update on medication adherence and persistence in children, adolescents and adults. Expert Rev Pharmacoecon Outcomes Res. 2013;13(6):791–815. https://doi.org/10.1586/14737167.2013.841544.

    Article  PubMed  Google Scholar 

  146. Patrick DL, Burke LB, Gwaltney CJ, et al. Content validity–establishing and reporting the evidence in newly developed patient-reported outcomes (PRO) instruments for medical product evaluation: ISPOR PRO good research practices task force report: part 2–assessing respondent understanding. Value Health. 2011;14(8):978–88. https://doi.org/10.1016/j.jval.2011.06.013.

    Article  PubMed  Google Scholar 

  147. Lasch KE, Marquis P, Vigneux M, et al. PRO development: rigorous qualitative research as the crucial foundation. Qual Life Res. 2010;19(8):1087–96. https://doi.org/10.1007/s11136-010-9677-6.

    Article  PubMed  PubMed Central  Google Scholar 

  148. Ioannidis JPA. How to make more published research true. PLoS Med. 2014;11(10):e1001747. https://doi.org/10.1371/journal.pmed.1001747.

    Article  PubMed  PubMed Central  Google Scholar 

  149. Varni JW, Burwinkle TM, Lane MM. Health-related quality of life measurement in pediatric clinical practice: an appraisal and precept for future research and application. Health Qual Life Outcomes. 2005;3(1):34. https://doi.org/10.1186/1477-7525-3-34.

    Article  PubMed  PubMed Central  Google Scholar 

  150. Thornicroft G, Brohan E, Rose D, Sartorius N, Leese M. Global pattern of experienced and anticipated discrimination against people with schizophrenia: a cross-sectional survey. Lancet. 2016;373(9661):408–15. https://doi.org/10.1016/S0140-6736(08)61817-6.

    Article  Google Scholar 

  151. van Deursen AJAM, van Dijk JAGM. The digital divide shifts to differences in usage. New Media Soc. 2014;16(3):507–26. https://doi.org/10.1177/1461444813487959.

    Article  Google Scholar 

  152. Parker RM, Ratzan SC, Lurie N. Health literacy: a policy challenge for advancing high-quality health care. Health Aff. 2003;22(4):147–53. https://doi.org/10.1377/hlthaff.22.4.147.

    Article  Google Scholar 

  153. Neimann Rasmussen L, Montgomery P. The prevalence of and factors associated with inclusion of non-English language studies in Campbell systematic reviews: a survey and meta-epidemiological study. Syst Rev. 2018;7(1):129. https://doi.org/10.1186/s13643-018-0786-6.

    Article  PubMed  PubMed Central  Google Scholar 

  154. Gagnier JJ, Lai J, Mokkink LB, Terwee CB. COSMIN reporting guideline for studies on measurement properties of patient-reported outcome measures. Qual Life Res. 2021;30(8):2197–218. https://doi.org/10.1007/s11136-021-02822-4.

    Article  PubMed  Google Scholar 

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Acknowledgements

None.

Funding

A grant from the medical cross key project of Sichuan University, China (to Lingli Zhang) supported this work.

Author information

Authors and Affiliations

  1. Department of Pharmacy/Evidence-Based Pharmacy Center, West China Second University Hospital, Sichuan University, Chengdu, China

    Mengting Yang, Puwen Zhang, Kun Zou, Liang Huang, Linan Zeng & Lingli Zhang

  2. Children’s Medicine Key Laboratory of Sichuan Province, Chengdu, China

    Mengting Yang, Puwen Zhang, Kun Zou, Liang Huang, Linan Zeng & Lingli Zhang

  3. NMPA Key Laboratory for Technical Research On Drug Products In Vitro and In Vivo Correlation, Chengdu, China

    Mengting Yang, Puwen Zhang, Kun Zou, Liang Huang, Linan Zeng & Lingli Zhang

  4. Key Laboratory of Birth Defects and Related Diseases of Women and Children, Sichuan University, Ministry of Education, Chengdu, China

    Mengting Yang, Puwen Zhang, Kun Zou, Liang Huang, Xiaoxi Lu, Linan Zeng & Lingli Zhang

  5. West China School of Medicine, Sichuan University, Chengdu, China

    Mengting Yang & Puwen Zhang

  6. The Matilda Centre for Research in Mental Health and Substance Use, University of Sydney, Camperdown, NSW, Australia

    Jillian Halladay

  7. Joseph’s Healthcare Hamilton (SJHH), Research Institute of St. Joe’s Hamilton Mental Health and Addictions Research Program, McMaster University, Hamilton, ON, Canada

    Jillian Halladay

  8. School of Medicine, University of Nottingham, Nottingham, UK

    Imti Choonara

  9. West China School of Pharmacy, Sichuan University, Chengdu, China

    Xiaorui Ji, Shuya Zhang & Weiyi Yan

  10. Department of Paediatric Haematology and Oncology, West China Second Hospital, Sichuan University, Chengdu, China

    Xiaoxi Lu

  11. Medical Simulation Centre, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China

    Huiqing Wang

  12. School of Mathematics, Sichuan University, Chengdu, China

    Yuxin Jiang & Xinyu Liu

  13. Chinese Evidence-Based Medicine Center, West China Hospital, Sichuan University, Chengdu, China

    Lingli Zhang

  14. Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada

    Gordon H. Guyatt

  15. Department of Medicine, McMaster University, Hamilton, ON, Canada

    Gordon H. Guyatt

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  1. Mengting Yang
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  2. Puwen Zhang
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  3. Jillian Halladay
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  4. Kun Zou
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  5. Imti Choonara
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