Improving Satisfaction with Assistive Technology Through Better Service Delivery: Evidence from the WHO rATA Survey in Italy

Abstract

Population-level evidence on how different phases of assistive technology service delivery contribute to user satisfaction with assistive products remains limited, despite its importance for strengthening provision systems. This study investigates how different aspects of assistive technology service delivery influence user satisfaction with assistive products and their perceived usefulness. Drawing on data from 992 Italian respondents to the WHO rapid Assistive Technology Assessment (rATA) survey, hierarchical regression and mediation analyses were conducted to examine the relative contribution of pre- and post-delivery services (i.e., assessment and training, and maintenance and follow-up) to overall product satisfaction. Results showed that satisfaction with pre-delivery services (β = 0.571, p < 0.001) was the strongest predictor of product satisfaction, followed by post-delivery services (β = 0.280, p < 0.001). Together, both service dimensions explained nearly 60% of the variance in product satisfaction (R² = 0.595). Mediation analysis further revealed that satisfaction with pre-delivery services partially mediated the relationship between product satisfaction and perceived usefulness (β = 0.147, p < 0.001), accounting for 29% of the total effect. These findings suggest a complementary pattern, in which pre-delivery services may provide a foundation for positive user experiences, while post-delivery services contribute meaningfully to sustaining satisfaction and perceived usefulness. The results provide population-level insights that may support national reflections on how to strengthen assistive technology service delivery, while recognizing that both early- and later-stage service components play important and interdependent roles.

1. Introduction

The assistive technology service delivery process encompasses all the activities an individual undertakes to obtain assistive products that meet their specific needs and fit their context of use [1]. This process generally involves several interconnected stages: gaining access to a service provider, assessing user and stakeholder needs and resources, identifying and selecting the most appropriate assistive solution, adapting or fitting the product, securing authorization for funding, implementing the technology in the user’s environment, and providing follow-up, maintenance, and repair [2,3,4]. Within the assistive technology community, there is broad consensus that the service delivery process can only be considered complete when there is evidence of a satisfactory match between the person and the provided solution [5]. Assessing whether assistive technology services achieve such a match between the proposed product and the user’s goals and expectations lies at the core of service delivery outcome assessment.

Measuring outcomes of assistive technology service delivery is a critical component of any intervention and serves multiple purposes at the individual, service, and system levels [6]. At the individual level, it allows assistive technology and rehabilitation professionals to constantly monitor their interventions and make corrective actions when necessary [7,8]. At the service level, it facilitates assessment and monitoring of the overall functioning of a specific service delivery process over time [7,8]. At the system level, outcome assessment allows the identification of the differences in service delivery practices and processes, programs and policies, as well as the consequences associated with these differences [7,8].

Despite its recognized importance, outcome evaluation in assistive technology service delivery remains challenging. The field still lacks standardized, evidence-based procedures and comprehensive datasets to guide consistent assessment [8,9,10,11,12]. Consequently, little population-level evidence exists on the effectiveness of assistive technology service delivery systems worldwide [6].

Ensuring optimal outcomes from assistive technology service delivery is essential for understanding benefits and developing evidence-based policies toward universal access [13]. Historically, limited attention to outcome assessment in routine practice has left major gaps in knowledge about the effectiveness of assistive technology systems [12]. This neglect was partly driven by the assumption that assistive products benefits were self-evident, rendering evaluation unnecessary or overly costly [12]. However, high rates of assistive product abandonment (reported to reach up to 78%) demonstrate that success depends not only on the quality of the product itself but on a complex interplay of user expectations, needs, and usage contexts [14,15,16]. Continuous monitoring of service delivery outcomes is therefore necessary to prevent abandonment, ensure quality, as well as support the attainment of desired objectives [17,18]. The need for evidence-based strategies to strengthen assistive technology provision has been underscored by major global reports and resolutions [13,19,20,21,22].

Among the various indicators of assistive technology outcomes, satisfaction plays a crucial role [17,18,23]. A recent systematic review [24] focused on available outcome measures suggests functional efficacy and device satisfaction are primary aspects of assistive technology outcome evaluation, with satisfaction considered as the second most used indicator of outcome [24]. In the assistive technology field, satisfaction is conceived as a multifaceted concept, comprising both satisfaction with products and satisfaction with services [23]. Satisfaction with products is often regarded as a real measure of outcome, reflecting how well the device itself meets user needs and expectations [25,26]. Conversely, satisfaction with services is considered more a measure of the quality of services connected to assistive technology, such as delivery, repairs, and follow-up [25,26]. For instance, the Quebec User Evaluation of Satisfaction with Assistive Technology (QUEST 2.0) evaluates both device characteristics and service-related aspects [23]. This distinction is vital because, as research suggests, while an assistive product might improve functional status, it does not automatically mean the user is satisfied with it [9]. Therefore, a comprehensive assessment of assistive technology service delivery process outcome often complements satisfaction assessment with other dimensions of effectiveness, including aspects often overlooked by a purely medical approach (e.g., self-determination, self-esteem) [9,27].

Research into the assistive technology service delivery process highlights numerous factors that influence satisfaction with products. Both Ranada and Lidström [25] as well as Brandt et al. [28] emphasize that user involvement is crucial for achieving positive outcomes and user satisfaction. A client-centered approach, involving collaboration between users, caregivers, and professionals, is considered essential for effective service delivery and satisfied users [25,28]. Different approaches to user involvement, such as self-assessment, professional assessment, or collaborative assessment, have shown positive outcomes, with collaborative approaches often leading to devices being rated as most useful, ultimately leading to increased outcomes for the users and their contexts (e.g., quality of life; decreased caregiver burden) [13,29]. Feeling informed during the service delivery process is also positively associated with user satisfaction [25,30].

Training in the use of assistive products is another key factor repeatedly linked to positive outcomes and satisfaction [25,28]. Studies indicate that training can lead to increased activity performance, higher goal attainment, and greater satisfaction with the product provided [25,28,31]. Lack of sufficient training or instruction, conversely, can lead to increased stress, handling difficulties, underutilization, and ultimately abandonment of the assistive product [25].

The quality of the service delivery and management strategies employed by specialized services also significantly impacts user satisfaction and abandonment rates [25,32]. Services focused on effectiveness, problem-solving, and person-centeredness tend to have higher user satisfaction and lower abandonment rates compared to those focused solely on efficiency [32]. Moreover, the availability of information, timely access to devices, and efficient maintenance and repair services are critical; frequent repairs and long waiting times for service can lead to dissatisfaction and negatively affect participation in daily activities [25,33,34]. Despite these identified correlations, Ranada and Lidström [25] noted that while evidence suggests participation in the service delivery process affects satisfaction and use of assistive products, “it has not become clear whether any one part of the prescription process is more important than another” (p. 94).

Building on research on the relationship between service delivery and user satisfaction, Chen et al. [35] proposed a specific hypothesis regarding the relative importance of different service phases. Using the data collected through the “rapid assistive technology assessment” (rATA) in China, their study found that satisfaction with pre-delivery services (i.e., assessment and training) was positively associated with user satisfaction with assistive products. In contrast, satisfaction with post-delivery services, such as maintenance and follow-up, showed no significant association with assistive product satisfaction. These results suggest that the quality of early interactions between users and service providers plays a significant role in shaping the perceived success of the assistive product. Accordingly, Chen et al. [35] concluded that pre-delivery services play a “critical role” in determining overall satisfaction with assistive products, while post-delivery services have a “less pronounced or non-significant impact” (p. 1203). This leads to the hypothesis that pre-delivery services, such as comprehensive assessment and user training, are more relevant in determining user satisfaction with assistive products compared to post-delivery services, such as maintenance and follow-up.

Aim of the Study

Given the identified gaps in understanding the relative importance of different assistive technology service provision phases for user satisfaction, particularly with assistive products [25], and the specific findings from Chen et al. [36] suggesting a differential impact of pre- and post-delivery services, the scope of the present study is to further investigate the comparative influence of pre-delivery and post-delivery assistive technology services on user satisfaction with assistive products in a sample of Italian users. The primary research question (RQ) addressed in this study was

RQ1: What is the impact of pre-delivery and post-delivery assistive technology services on user satisfaction with assistive products?

In light of the well-established relationship between satisfaction with assistive products and the quality of services on the one hand, and the effective use of those products on the other, this study further aimed to explore whether the perceived quality of the assistive technology service delivery process may help explain how satisfaction with assistive products translates into their effective use. Hence, the secondary research question addressed was

RQ2: To what extent is the relationship between product satisfaction and product use mediated by satisfaction with assistive technology service delivery process?

2. Materials and Methods

2.1. Study Context, Design, and Data Source

This study is a secondary analysis of data collected through the Italian implementation of the rATA survey. Italy has a tax-funded universal National Health System (NHS) that ensures nationwide provision of assistive products, with primary responsibility for assistive technology resting on municipal and regional health authorities (Aziende Sanitarie Locali). Additional sector-specific mechanisms exist in employment (e.g., through the National System for Insurance for Labor Accidents, INAIL) and education, where schools and Territorial Support Centers (CTS) provide assistive products and support to students with disabilities. The governance structure is highly decentralized across regions, resulting in heterogeneous administrative pathways and collaboration models, including formal agreements with non-governmental providers such as services members of the National Network of Assistive Technology Centers. Population-level data on assistive technology access were lacking until the recent administration of the rATA survey [35]. The national results show that 52.6% of the Italian population has an assistive technology need, with 45.8% having their needs met and 6.7% experiencing unmet need. Use and need are highest among adults aged 60+, who also display the strongest age-related predictors of use [35]. In terms of products, the three most used assistive products in Italy as resulted from the rATA survey are spectacles, smartphones/tablets, and pill organizers.

The original cross-sectional Italian rATA study was conducted between June and September 2021, involving a stratified sample of 10,167 Italian residents, representative by age, sex, and geographic location. Full details of the sampling strategy, administration procedures, and data quality controls are described elsewhere [36]. The present analysis focused on a subsample of respondents who (i) reported using at least one assistive product, (ii) were not users of spectacles only, and (iii) completed the satisfaction module. In particular, the exclusion of respondents using only spectacles was motivated by the fact that, in Italy, spectacles follow a distinct and largely market-based service delivery pathway, typically involving private opticians rather than the assessment, prescription, and follow-up procedures characteristic of other assistive products. Spectacles-only users also represent a demographically different group (e.g., reporting minimal or no functional difficulties) whose inclusion would have introduced substantial heterogeneity unrelated to the service processes examined here. Based on these criteria, responses from 992 participants were retained for the analyses. The characteristics of the participants included in the analyses are reported in

Table 1. Socio-demographic characteristics of the sample included in the analyses.

Variable	Category	n (%)
Sex	Males	502 (50.6%)
	Females	490 (49.4%)
Age	0–17	188 (19.0%)
	18–59	482 (48.6%)
	60+	322 (32.5%)
Functional difficulties	None	92 (9.3%)
	Some	392 (39.8%)
	Severe	360 (36.6%)
	Complete	140 (14.2%)
Domain of AT use	Mobility	70 (7.1%)
	Seeing	76 (7.7%)
	Hearing	16 (1.6%)
	Communication	3 (0.3%)
	Cognition	18 (1.8%)
	Self-care	6 (0.6%)
	Mixed	803 (80.9%)

.

2.2. Measures

The rATA is a standardized survey tool developed by the World Health Organization (WHO) to generate population-level data on access to assistive technology [37]. It is designed to be adaptable across countries and contexts and includes questions on self-reported functional difficulties, assistive product use, unmet needs, and satisfaction with both products and services. In the context of this study, three satisfaction-related items and one related to perceived usefulness of the products in use were analyzed. Details on the items are included in

Table 2. rATA items used in the study.

Dimension	Question Text	Response Scale
Product satisfaction	Over the last month, how satisfied are you with your [PROD#]?	1 = Very dissatisfied; 5 = Very satisfied
Service satisfaction (Pre-delivery)	Thinking about your [PROD#], how satisfied are you with the assessment and training you received?	1 = Very dissatisfied; 5 = Very satisfied
Service satisfaction (Post-delivery)	Please think about your [PROD#]. How satisfied are you with the repair, maintenance and follow-up services based on your last experience?	1 = Very dissatisfied; 5 = Very satisfied
Perceived utility	To what extent does your [PROD#] help you to do what you want?	1 = Not at all; 5 = Completely

. The satisfaction items are designed to be general enough for broad comparability across assistive product types and service delivery systems, while still allowing for interpretation within local contexts. In the rATA tool, respondents could report and rate up to three assistive products they were currently using. For each product, satisfaction with the product, satisfaction with pre-delivery and post-delivery services, and perceived utility were assessed using the items described in Table 2. For this analysis, satisfaction and utility scores were averaged across all rated products for each respondent, resulting in one composite score per dimension per person. Because the study aimed to examine users’ overall experience with assistive technology provision, analyses were conducted at the respondent level, using composite satisfaction scores to capture general perceptions rather than product-specific outcomes.

2.3. Statistical Analysis

All the data are expressed as proportions (%) or means (M) and standard deviations (SD). Following the Global Report on Assistive Technology [13], for descriptive statistics respondents’ age was coded as a categorical variable using three age groups (0–17 years; 18–59 years; 60+ years), while age was used as continuous variable for the analyses (see below). Similarly, functional difficulty was coded using four severity levels (i.e., no difficulty, some difficulty; severe/a lot of difficulty; complete difficulty) for descriptive statistics, while the number of difficulties (range 0–18) was used for the statistical analyses.

Preliminary exploratory analyses were conducted to assess the potential influence of socio-demographic and assistive technology-related characteristics on satisfaction scores. t-tests and one-way ANOVAs were used to evaluate group differences in satisfaction by sex, age group, functional difficulty, and proxy respondent status. When comparing two group means, Welch’s t-test was applied in cases where the assumption of equal variances was violated.

Geographical origin was also assessed by distinguishing among five areas: North-east, North-west, South, Center, and Islands. Pearson correlations were calculated to assess associations between satisfaction scores and continuous variables such as age, number of assistive products used, and total functional difficulties. These analyses informed the selection of predictors and control variables included in the hierarchical regression model (see below).

A hierarchical linear regression was conducted to assess whether satisfaction with assistive technology services predicts satisfaction with assistive products. The dependent variable was product satisfaction, averaged across up to three products reported per respondent. In Step 1, control variables were entered: age, sex, total number of functional difficulties, number of assistive products used, and proxy respondent status. In Step 2, satisfaction with pre-delivery services (assessment and training) was added. In Step 3, satisfaction with post-delivery services (maintenance and follow-up) was included. This approach was chosen as it allowed to evaluate the incremental contribution of service satisfaction domains while adjusting for potential confounding variables. Change in explained variance (ΔR²) and significance of model comparisons were assessed using F-tests (p < 0.05).

To explore whether satisfaction with assistive technology services mediates the relationship between satisfaction with assistive products and their perceived impact, a mediation analysis was conducted using the Advanced Mediation Models module in jamovi. The model specified product satisfaction as the independent variable (X), perceived utility of the assistive product as the dependent variable (Y), and one service satisfaction dimension as the mediator (M). In this study, perceived utility was treated as a proxy for perceived impact of assistive technology use, e.g., [38], reflecting how satisfaction with the product translates into perceived benefit, rather than as a determinant of satisfaction. The specific service dimension included as mediator was selected based on prior analyses identifying it as most strongly associated with product satisfaction (see Results Section). To note, given the exploratory nature of the present study and the cross-sectional design, the mediation analysis was conducted solely to examine patterns of association among variables, without inferring any causal or temporal ordering. The analysis was conducted using the product-of-coefficients approach, with bootstrap resampling (5000 samples) and completely standardized estimates (β). Indirect, direct, and total effects were estimated, and statistical significance was determined using 95% confidence interval and a threshold of p < 0.05. To control for potential confounding effects, the model included the following covariates: age, functional difficulty score, number of assistive products used, sex, and proxy respondent status.

Because the analyses were conducted on a restricted subsample (i.e., users who completed the satisfaction items), population weights from the full rATA dataset were not applied, as they are calibrated for the entire representative sample and would not yield valid estimates for a subset. The findings should therefore be interpreted as exploratory associations within the analytic sample rather than weighted population estimates.

3. Results

3.1. Preliminary Explorative Analyses

To inform the selection of predictors and control variables in the regression model, preliminary exploratory analyses were conducted. Because Levene’s test indicated unequal variances, differences in product satisfaction by sex and proxy respondent were assessed using Welch’s t-test. Analyses revealed significant group differences in product satisfaction by sex (Welch’s t(982) = 2.42, p = 0.016) and proxy respondent status (Welch’s t(741) = 2.18, p = 0.029). Satisfaction with pre-delivery services also differed significantly by proxy use (t(990) = 2.33, p = 0.020), while a similar trend was observed for post-delivery services (t(990) = 2.18, p = 0.029).

Significant age effects were found for product satisfaction, F(2, 989) = 10.25, p < 0.001, pre-delivery service satisfaction, F(2, 989) = 9.28, p < 0.001, and post-delivery service satisfaction, F(2, 989) = 10.83, p < 0.001. In all three dimensions, mean scores increased across age groups: for product satisfaction (0–17: M = 3.69; 18–59: M = 3.85; 60+: M = 4.04), pre-delivery services (0–17: M = 3.85; 18–59: M = 3.98; 60+: M = 4.16), and post-delivery services (0–17: M = 3.91; 18–59: M = 3.98; 60+: M = 4.24). Post hoc comparisons showed that older adults (60+) reported significantly higher satisfaction than both younger groups across all outcomes (all ps < 0.05).

Geographical origin, as well as difficulty type, did not yield significant differences across all three satisfaction scores (i.e., with products and pre/post-delivery services).

Pearson correlation analyses indicated small but statistically significant associations between satisfaction scores and several continuous variables (see correlation matrix in Appendix A;

Table A1. Correlation matrix.

		Product Satisfaction	Service Satisfaction (Pre-Delivery)	Service Satisfaction (Post-Delivery)	Age	Sum of Difficulties	Sum of Products
Product satisfaction	Pearson’s r
	df
	p-value
Service satisfaction (pre-delivery)	Pearson’s r	0.731 ***
	df	990
	p-value	<0.001
Service satisfaction (post-delivery)	Pearson’s r	0.660 ***	0.670 ***
	df	990	990
	p-value	<0.001	<0.001
Age	Pearson’s r	0.184 ***	0.153 ***	0.186 ***
	df	990	990	990
	p-value	<0.001	<0.001	<0.001
Sum of difficulties	Pearson’s r	−0.104 ***	−0.084 **	−0.102 **	0.270 ***
	df	990	990	990	990
	p-value	<0.001	0.008	0.001	<0.001
Sum of products	Pearson’s r	−0.120 ***	−0.070 *	−0.093 **	−0.127 ***	0.299 ***
	df	990	990	990	990	990
	p-value	<0.001	0.028	0.003	<0.001	<0.001

Note. * p < 0.05, ** p < 0.01, *** p < 0.001.

). Age was positively correlated with satisfaction across all dimensions (e.g., r = 0.184 with product satisfaction, p < 0.001), whereas number of assistive products used and functional difficulty showed weak negative correlations. These results supported the inclusion of age, sex, functional difficulty, product count, and proxy status as control variables in the regression analysis.

In the exploratory analyses, satisfaction with pre-delivery services (M = 4.01) and post-delivery services (M = 4.05) did not significantly differ. Satisfaction with pre-delivery services and post-delivery services were both significantly correlated with product satisfaction (r = 0.731 and r = 0.660, respectively; p < 0.001). Despite a strong correlation between the two service dimensions (r = 0.670), multicollinearity diagnostics indicated no redundancy (VIFs < 2), supporting their inclusion as independent predictors in the hierarchical regression model.

3.2. RQ1: What Is the Impact of Pre-Delivery and Post-Delivery Assistive Technology Services on User Satisfaction with Assistive Products?

A hierarchical linear regression was conducted to assess the extent to which service satisfaction predicts product satisfaction, after adjusting for relevant user and usage characteristics. The analysis included 992 respondents with complete data. In Model 1, control variables (age, sex, number of assistive products, functional difficulty, and proxy status) explained a modest but significant proportion of the variance in product satisfaction (R² = 0.064, F(5986) = 13.4, p < 0.001). In Model 2, the addition of satisfaction with pre-delivery services (assessment and training) significantly improved model fit, increasing explained variance to R² = 0.549 (ΔR² = 0.486, F(6985) = 200.1, p < 0.001).

In the third final model illustrated in

Table 3. Hierarchical regression predicting product satisfaction (N = 992).

Predictor	Estimate (β)	SE	t	p-Value
Age	0.002	0.001	2.040	0.042
Sex (Female vs. Male)	0.090	0.037	2.444	0.015
Number of Products	−0.012	0.006	−1.901	0.058
Proxy vs. Self-report	0.030	0.039	0.761	0.447
Functional Difficulty	−0.011	0.007	−1.655	0.098
Pre-delivery Satisfaction	0.571	0.030	19.074	<0.001
Post-delivery Satisfaction	0.280	0.027	10.537	<0.001

, including post-delivery service satisfaction (maintenance and follow-up), led to a further increase in explained variance (R² = 0.595; ΔR² = 0.046, F(7984) = 206.5, p < 0.001). Satisfaction with assessment and training was the strongest predictor of product satisfaction (β = 0.571, p < 0.001), followed by maintenance and follow-up services (β = 0.280, p < 0.001). Age (p = 0.042) and sex (p = 0.015) also had small but statistically significant effects, while functional difficulty, number of products, and proxy use were not significant predictors in the model.

3.3. RQ2: To What Extent Is the Relationship Between Product Satisfaction and Product Use Mediated by Satisfaction with Assistive Technology Service Delivery Process?

Building on the hierarchical regression findings, satisfaction with pre-delivery services (assessment and training) was identified as the strongest service-related predictor of product satisfaction and was therefore selected as the mediator in the mediation model. Full mediation outputs, including all path coefficients and covariate effects, are provided in Appendix B (

Table A2. Mediation analysis.

				95% C.I. (a)
Type	Effect	Estimate	SE	Lower	Upper	β	z	p
Indirect	Product satisfaction ⇒ Service satisfaction (pre-delivery) ⇒ Perceived utility	0.146	0.023	0.100	0.193	0.167	6.154	<0.001
	Proxy respondent ⇒ Service satisfaction (pre-delivery) ⇒ Perceived utility	−0.014	0.011	−0.037	0.008	−0.009	−1.245	0.213
	Age (0–17) ⇒ Service satisfaction (pre-delivery) ⇒ Perceived utility	−0.004	0.014	−0.033	0.024	−0.002	−0.279	0.781
	Age (18–59) ⇒ Service satisfaction (pre-delivery) ⇒ Perceived utility	0.013	0.013	−0.012	0.039	0.008	1.026	0.305
	Sex (Male) ⇒ Service satisfaction (pre-delivery) ⇒ Perceived utility	−0.019	0.008	−0.036	−0.003	−0.012	−2.326	0.020
Component	Product satisfaction ⇒ Service satisfaction (pre-delivery)	0.666	0.020	0.626	0.705	0.727	33.300	<0.001
	Service satisfaction (pre-delivery) ⇒ Perceived utility	0.220	0.03	0.151	0.289	0.229	6.262	<0.001
	Proxy respondent ⇒ Service satisfaction (pre-delivery)	−0.065	0.051	−0.166	0.035	−0.039	−1.270	0.204
	Age (0–17) ⇒ Service satisfaction (pre-delivery)	−0.018	0.067	−0.150	0.113	−0.011	−0.279	0.780
	Age (18–59) ⇒ Service satisfaction (pre-delivery)	0.061	0.058	−0.054	0.176	0.035	1.041	0.298
	Sex (Male) ⇒ Service satisfaction (pre-delivery)	−0.089	0.035	−0.159	−0.019	−0.055	−2.505	0.012
Direct	Product satisfaction ⇒ Perceived utility	0.357	0.032	0.294	0.420	0.407	11.091	<0.001
	Proxy respondent ⇒ Perceived utility	−0.146	0.057	−0.258	−0.034	−0.091	−2.573	0.010
	Age (0–17) ⇒ Perceived utility	−0.089	0.074	−0.235	0.056	−0.057	−1.198	0.231
	Age (18–59) ⇒ Perceived utility	0.042	0.065	−0.085	0.169	0.025	0.649	0.517
	Sex (Male) ⇒ Perceived utility	0.050	0.039	−0.027	0.128	0.032	1.281	0.200
Total	Product satisfaction ⇒ Perceived utility	0.504	0.022	0.460	0.548	0.575	22.313	<0.001
	Proxy respondent ⇒ Perceived utility	−0.161	0.058	−0.275	−0.047	−0.100	−2.771	0.006
	Age (0–17) ⇒ Perceived utility	−0.093	0.076	−0.242	0.055	−0.060	−1.229	0.219
	Age (18–59) ⇒ Perceived utility	0.055	0.066	−0.07	0.185	0.033	0.839	0.401
	Sex (Male) ⇒ Perceived utility	0.031	0.040	−0.048	0.110	0.020	0.771	0.440

).

Overall, the analysis confirmed that satisfaction with pre-delivery services partially mediated the relationship between product satisfaction and perceived utility of the assistive product (Figure 1). The indirect effect was statistically significant (β = 0.147, SE = 0.024, 95% CI [0.100, 0.193], p < 0.001), accounting for approximately 29% of the total effect. The direct effect of product satisfaction on perceived utility remained significant (β = 0.358, SE = 0.032, 95% CI [0.295, 0.421], p < 0.001), as did the total effect (β = 0.505, SE = 0.023, 95% CI [0.460, 0.549], p < 0.001), indicating a robust overall association. Among the control variables, proxy respondent status and sex were significantly associated with lower levels of perceived utility and service satisfaction, respectively. Other covariates, including age and functional difficulty score, did not show significant associations in this model. These findings suggest that, while product satisfaction plays a direct and significant role in influencing perceived utility, the quality of pre-delivery services contributes meaningfully to this relationship.

4. Discussion

The present study aimed to investigate the relative influence of pre-delivery (assessment and training) and post-delivery (maintenance and follow-up) assistive technology services on user satisfaction with assistive products (RQ1), and to explore whether satisfaction with services mediates the relationship between product satisfaction and perceived utility (RQ2) among a subsample of Italian users drawn from the WHO rATA survey [35]. Our findings revealed that satisfaction with pre-delivery services was the strongest predictor of product satisfaction (β = 0.571, p < 0.001), and that this same element of service satisfaction partially mediated the link between product satisfaction and the product’s perceived usefulness. These findings, based on the first comprehensive assistive technology access assessment in Italy using the rATA tool, should be viewed as initial evidence that can contribute to ongoing policy reflection on assistive technology provision in the Italian context.

4.1. The Comparative Impact of Pre- and Post-Delivery Services (RQ1)

Measuring outcomes and impacts is essential for understanding the benefits of assistive technology and creating evidence-based policies to ensure universal access [13,24]. Satisfaction is considered a crucial indicator of assistive technology outcome, frequently evaluated alongside functional efficacy [24,25].

Our primary finding directly addresses RQ1 by documenting that satisfaction with assessment and training (pre-delivery services) was the most significant predictor of product satisfaction (β = 0.571, p < 0.001), followed by satisfaction with maintenance and follow-up (post-delivery services; β = 0.280, p < 0.001). This distinction supports the idea that the quality of early-stage assistive technology service delivery may influence overall satisfaction with the assistive product. Notably, the average satisfaction scores reported in this study for pre-delivery and post-delivery services were numerically very similar (i.e., M = 4.01 and M = 4.05, respectively). While this suggests that the quality of both service phases (assessment/training and maintenance/follow-up) was perceived similarly and positively by Italian users, the regression analysis established a dominant predictive role for the pre-delivery phase on product satisfaction.

This numeric similarity in service satisfaction average scores in the Italian context contrasts with findings at global level [13] and from other rATA surveys available in the literature. In the China rATA study [35], for instance, lower average satisfaction scores were reported for post-delivery maintenance (M = 3.76) compared to pre-delivery services (M = 4.03). Furthermore, the Chinese study found that only pre-delivery services were positively correlated with user satisfaction (β = 0.514), whereas post-delivery services showed no significant effect on product satisfaction. Importantly, the Chinese study also noted that a large majority of respondents perceived both pre-delivery services (78.8%) and post-delivery services (90%) as unnecessary, a result that may reflect different expectations about the role of service provision, the simplicity of the products used, or the limited availability of structured follow-up pathways. Similarly, a large rATA study conducted in India [39] showed a descending satisfaction gradient, reporting 88.4% satisfaction with assessment and training and 85.2% satisfaction with repair and maintenance services.

In the Italian context, the relative similarity of mean satisfaction levels across service phases may suggest a more even perceived quality across pre- and post-delivery components. However, this pattern should be interpreted with caution, as multiple factors could account for cross-country differences. These include differences in product complexity, the availability and structure of follow-up services, and users’ expectations regarding the usefulness or necessity of service components. Given that the present sample includes a high proportion of users relying on multiple and potentially more complex assistive products, differences in product mix may also contribute to the observed associations. It should also be noted that, because the analysis is restricted to current users, the observed satisfaction levels may partly reflect selection effects, and interpretations of absolute satisfaction scores should therefore be made with caution.

Cross-country comparisons would benefit from future analyses that explicitly account for product type, service availability, and user expectations when examining satisfaction with assistive technology delivery services.

4.2. Mediation of Service Satisfaction in Product Use (RQ2)

The secondary aim (RQ2) investigated the role of service quality (specifically, satisfaction with assessment and training) in mediating the relationship between product satisfaction and perceived utility. It is important to emphasize that, because the data are cross-sectional and non-experimental, the mediation analysis does not imply a causal pathway. In this context, mediation is used only as a statistical tool to examine how these variables relate to one another, without assuming temporal ordering or directionality [40]. The model tested represents one plausible specification of these associations, but alternative models (e.g., where perceived utility influences satisfaction) are equally possible.

Within this exploratory framework, the analysis showed a statistically significant indirect effect (β = 0.147, p < 0.001), accounting for approximately 29% of the total association, while the direct association between product satisfaction and perceived utility remained significant (β = 0.358, p < 0.001). These results suggest that users who report higher satisfaction with assessment and training also tend to report a stronger link between product satisfaction and perceived utility; however, longitudinal or experimental designs would be required to establish whether service quality exerts a causal influence on these perceptions.

Despite these limitations, the pattern of associations aligns with the existing literature, showing that early service quality is closely related to users’ evaluations of assistive technology outcomes and their long-term engagement with devices [14,15]. This reinforces the value of incorporating user perspectives (i.e., not only on satisfaction with the product itself but also on the quality of the services supporting its selection and setup) when evaluating assistive technology provision.

4.3. Practical Implications

Beyond their scientific relevance, the findings may also have practical implications. In a context of growing demand for assistive technology [13] and increasing pressure on health and social budgets [41], exploratory evidence on how different phases of service delivery relate to user satisfaction can provide useful insights. The association observed between pre-delivery services and satisfaction suggests that this early phase of provision may represent a potential leverage point within the assistive technology system. Importantly, however, the rATA measure used in this study to assess satisfaction with pre-delivery services combines two distinct components (i.e., assessment and training) and the present data cannot determine whether one, the other, or a combination of both contributes to the observed association. This distinction is crucial for practice and policy, and future research should separate these elements to understand their individual contributions more precisely. While causal interpretations cannot be drawn, the observed patterns should be viewed as hypothesis-generating and may serve to highlight areas warranting further investigation, with practical decisions requiring confirmation through longitudinal evidence and careful consideration of local- and system-level contexts.

However, the current results and emphasis on pre-delivery services should not be interpreted as a call to focus exclusively on the earlier stages of the service delivery process. All elements of the process are interdependent, and so are the broader components of the assistive technology system (i.e., People, Products, Provision, Personnel, and Policy [42]). The greater weight of pre-delivery services observed here should therefore be appreciated in relation to other aspects of service delivery, such as post-delivery maintenance and follow-up, which remain essential for ensuring sustained product use and long-term satisfaction.

4.4. Limitations

This study has some limitations that should be acknowledged. First, the rATA questionnaire relies on single-item measures to capture satisfaction with both assistive products and service phases. This represents an important limitation, as complex constructs such as satisfaction cannot be fully captured through single questions, and meaningful differences may therefore remain undetected. Collecting all measures from the same respondents at a single time point may introduce common method variance, including a potential halo effect, whereby generally positive (or negative) respondent perceptions could inflate associations between product- and service-related satisfaction ratings. Moreover, because the analysis includes only current users, individuals who may have discontinued assistive technology use due to poor service quality are not represented, which may lead to an overestimation of satisfaction levels.

As already mentioned earlier, the level of granularity of the rATA does not allow distinguishing between the different components of pre- and post-delivery services. Future studies should adopt a multidimensional approach to satisfaction (ideally combined with longitudinal designs), using instruments that include separate, validated subscales for each phase and component of service delivery, to enable a more precise understanding of what drives positive user experiences.

Second, the analyses were conducted on the full sample of respondents, which includes users of diverse assistive products addressing a wide range of functional needs. Notably, around 80% of the respondents reported using a combination of assistive products for different functional domains, rather than a single product type. This heterogeneity implicates an important limitation: by averaging satisfaction across multiple products, product-specific differences may be obscured. For instance, a respondent may be highly satisfied with a mobility aid but dissatisfied with a communication device, and such differences cannot be detected in the aggregated rATA measures.

Future analyses should therefore explore stratified models by product category or functional domain to better capture these differences and inform more tailored service improvements.

5. Conclusions

In conclusion, this study offers initial evidence suggesting that pre-delivery services (assessment and training) may play an important role in shaping users’ perceptions of assistive technology products. These findings, stemming from the first comprehensive assistive technology access assessment in Italy using the rATA tool [8], provide a useful foundation for informing policy discussions and budget considerations aimed at improving assistive technology provision within the Italian context.

More broadly, the study illustrates the potential of the rATA as a strategic instrument for generating comparable and policy-relevant data on access to assistive technology. For over three decades, the assistive technology community has advocated for stronger evidence-based practice and policymaking, yet progress has been constrained by the absence of systematic and comparable data across settings [19]. The development of the rATA represents an important step toward addressing this gap by enabling countries to collect standardized data and benchmark their systems against global indicators. Although the tool has recognized limitations in scope and depth, its structured design and growing global implementation can contribute meaningfully to advancing evidence-informed policy in the field.

In particular, the present findings highlight the value of identifying potential leverage points within the assistive technology service delivery process (e.g., pre-delivery phase) that may be associated with more positive user experiences. At the same time, the non-negligible association observed for post-delivery services supports a complementary interpretation, whereby pre-delivery may provide a foundation for positive outcomes, while post-delivery services contribute to sustaining satisfaction and perceived usefulness over time. Successful assistive technology provision ultimately depends on the coordinated functioning of all service phases and system components.