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Article(id=1324078550785065965, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1324078333767594037, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202505394, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1748016000000, receivedDateStr=2025-05-24, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1793614526695, onlineDateStr=2026-11-02, pubDate=1767974400000, pubDateStr=2026-01-10, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1793614526695, onlineIssueDateStr=2026-11-02, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1793614526695, creator=13701087609, updateTime=1793614526695, updator=13701087609, issue=Issue{id=1324078333767594037, tenantId=1146029695717560320, journalId=1227665162245664772, year='2026', volume='53', issue='1', pageStart='1', pageEnd='192', issueExtLink='null', onlineDate='null', pubDate='1767974400000', pubDateStr='2026-01-10', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=0, createTime=1793614474956, creator='13701087609', updateTime=1793614571752, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1324078739914621270, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1324078333767594037, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1324078739914621271, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1324078333767594037, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=118, endPage=122, ext={EN=ArticleExt(id=1324078551208690670, articleId=1324078550785065965, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Preferences for digital therapeutics products based on discrete choice experiments—taking hypertension management products as an example, columnId=1228016572892119056, journalTitle=Modern Preventive Medicine, columnName=Primary Health Services, runingTitle=null, highlight=null, articleAbstract=
Objective

To understand the public’s preferences and willingness to pay for digital therapeutics (DTx) products for chronic disease management.

Methods

Based on a discrete choice experiment, an online questionnaire survey was administered via Wenjuanxing in February to March 2025, targeting the adult working population with independent spending capacity across the country. The preference outcomes were analyzed using a mixed logit model.

Results

Higher product accuracy (β=1.006), greater ease of use (β=0.349), superior product efficacy (β=0.569), higher product risk (β=-2.104),significant long-term health benefits (β=0.670), and inclusion in the medical insurance reimbursement list (β=1.458)demonstrated substantial influence on respondents’ preferences (P<0.001). Specifically, compared with low-risk products,respondents’ willingness to pay for high-risk products decreased by 7 891 yuan, and coverage by the medical insurance reimbursement list increased willingness to pay by 5 466 yuan compared with no coverage.

Conclusion

It is necessary to improve the regulatory system for DTx, establish a multi-payment pattern with medical insurance payment as the core and a climate of paying for health value, enhance the usability of products, and ultimately promote the improvement of chronic disease management levels and the promotion of DTx.

, authors=Gao-yuan ZHANG, Qian LI, You-li HAN, authorsList=Gao-yuan ZHANG, Qian LI, You-li HAN, authorCompany=null, correspAuthors=You-li HAN, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1324078551812670447, articleId=1324078550785065965, tenantId=1146029695717560320, journalId=1227665162245664772, language=CN, title=基于离散选择实验的数字疗法产品偏好研究——以高血压管理产品为例, columnId=1228016573533847611, journalTitle=现代预防医学, columnName=基层卫生服务, runingTitle=null, highlight=null, articleAbstract=
目的

了解群众对慢性病管理数字疗法产品的偏好与支付意愿。

方法

基于离散选择实验，于2025年2—3月依托问卷星对全国范围内具有自主消费能力的成年劳动力人口开展线上问卷调查，并利用混合logit模型分析偏好结果。

结果

高准确性(β=1.006)、高易用性(β=0.349)、高产品效果(β=0.569)、高产品风险(β=-2.104)、高长期健康获益(β=0.670)、纳入医保目录(β=1.458)、较低产品价格均会显著影响受访者对数字疗法产品的选择(P<0.001)。其中，相对于低风险产品，受访者对高风险产品的支付意愿减少7 891元；产品纳入医保目录的支付意愿相对于不纳入增加5 466元。

结论

应完善数字疗法产品监管体系，形成以医保支付为核心的多元支付格局和为健康价值付费的氛围，提升产品的易用性，促进慢性病管理水平的提高和数字疗法产品的推广。

, authors=张高源, 李倩, 韩优莉, authorsList=张高源, 李倩, 韩优莉, authorCompany=null, correspAuthors=韩优莉, authorNote=

张高源(2000—)，男，硕士在读，研究方向：卫生经济

, correspAuthorsNote=
韩优莉，E-mail:
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Application and development perspectives of digital therapeutics[J]. Chinese Journal of the Frontiers of Medical Science(Electronic Version), 2023, 15(12): 8-11. (In Chinese), articleTitle=Application and development perspectives of digital therapeutics, refAbstract=null), Reference(id=1324078561027555378, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078550785065965, doi=null, pmid=null, pmcid=null, year=2024, volume=26, issue=null, pageStart=null, pageEnd=null, url=null, language=null, rfNumber=[17], rfOrder=29, authorNames=Wang T, Huang YM, Chan HY, journalName=Journal of Medical Internet Research, refType=null, unstructuredReference=Wang T, Huang YM, Chan HY. Exploration of features of Mobile applications for medication adherence in Asia: narrative review[J]. 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BMC Geriatrics, 2025, 25(1):396., articleTitle=Facilitators, barriers, and recommendations for mobile health applications among Chinese older populations: a scoping review, refAbstract=null)], funds=[Fund(id=1324078556602564628, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078550785065965, awardId=72474140, language=CN, fundingSource=国家自然科学基金资助(72474140), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1324078552030774256, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078550785065965, xref=null, ext=[AuthorCompanyExt(id=1324078552039162865, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078550785065965, companyId=1324078552030774256, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=School of Public Health, Capital Medical University, Beijing 100069, China), AuthorCompanyExt(id=1324078552047551474, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078550785065965, companyId=1324078552030774256, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=首都医科大学公共卫生学院，北京 100069)])], figs=[ArticleFig(id=1324078555361050632, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078550785065965, language=EN, label=Table 1, caption=

Detailed definitions of attributes and levels about DTx

, figureFileSmall=null, figureFileBig=null, tableContent=
属性内涵水平
准确性该产品采集用户心跳、呼吸、血压等生理数据，并根据数据给出健康管理干预建议的准确程度高/低
易用性用户认为自己使用产品获取一次服务的难易程度高/低
产品效果产品在传统治疗手段和用户目前的治疗方案的基础上，对产品适应症主要临床指标的改善程度高/中/低
产品风险由于产品自身问题或用户操作不当，使用户在操作产品和接受服务的过程中感到操作困难、不适或出现其他意外事件高/中/低
长期健康获益该产品通过健康管理、健康宣教等手段，使用户提升健康意识和健康管理能力，从而形成的长效的健康改善效果高/低
纳入医保目录该产品是否纳入医保目录纳入/未纳入
产品价格消费者每年使用该产品所需花费（单位：元）3 500/5 500/7 500
), ArticleFig(id=1324078555449131017, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078550785065965, language=CN, label=表1, caption=

数字疗法产品的相关属性及其水平

, figureFileSmall=null, figureFileBig=null, tableContent=
属性内涵水平
准确性该产品采集用户心跳、呼吸、血压等生理数据，并根据数据给出健康管理干预建议的准确程度高/低
易用性用户认为自己使用产品获取一次服务的难易程度高/低
产品效果产品在传统治疗手段和用户目前的治疗方案的基础上，对产品适应症主要临床指标的改善程度高/中/低
产品风险由于产品自身问题或用户操作不当，使用户在操作产品和接受服务的过程中感到操作困难、不适或出现其他意外事件高/中/低
长期健康获益该产品通过健康管理、健康宣教等手段，使用户提升健康意识和健康管理能力，从而形成的长效的健康改善效果高/低
纳入医保目录该产品是否纳入医保目录纳入/未纳入
产品价格消费者每年使用该产品所需花费（单位：元）3 500/5 500/7 500
), ArticleFig(id=1324078555533017098, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078550785065965, language=EN, label=Table 2, caption=

Example of a choice set

, figureFileSmall=null, figureFileBig=null, tableContent=
属性产品1产品2
产品风险低中
易用性高低
产品效果低中
产品价格（元）5 5007 500
长期健康获益高低
纳入医保目录纳入未纳入
准确性低高
您的选择是□产品1□产品2
现实中，您是否会选择您以上选择的产品□会选择□不会选择
), ArticleFig(id=1324078555608514571, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078550785065965, language=CN, label=表2, caption=

选择集示例

, figureFileSmall=null, figureFileBig=null, tableContent=
属性产品1产品2
产品风险低中
易用性高低
产品效果低中
产品价格（元）5 5007 500
长期健康获益高低
纳入医保目录纳入未纳入
准确性低高
您的选择是□产品1□产品2
现实中，您是否会选择您以上选择的产品□会选择□不会选择
), ArticleFig(id=1324078555692400652, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078550785065965, language=EN, label=Table 3, caption=

Items of the eHEALS literacy questionnaire

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维度条目
应用能力我知道如何在互联网上查找有用的健康信息
我知道如何通过互联网解答自己的健康问题
我知道可以从互联网上获取的健康信息有哪些
我知道互联网上哪里可以获取有用的健康信息
我知道如何利用获取的健康信息帮助自己
评判能力我具备评价互联网上健康信息好坏的能力
我能够区分网络上高质量和低质量的健康信息
决策能力我自信能利用互联网上的健康信息进行健康决策
), ArticleFig(id=1324078555776286733, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078550785065965, language=CN, label=表3, caption=

eHEALS问卷题目设置

, figureFileSmall=null, figureFileBig=null, tableContent=
维度条目
应用能力我知道如何在互联网上查找有用的健康信息
我知道如何通过互联网解答自己的健康问题
我知道可以从互联网上获取的健康信息有哪些
我知道互联网上哪里可以获取有用的健康信息
我知道如何利用获取的健康信息帮助自己
评判能力我具备评价互联网上健康信息好坏的能力
我能够区分网络上高质量和低质量的健康信息
决策能力我自信能利用互联网上的健康信息进行健康决策
), ArticleFig(id=1324078555872755726, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078550785065965, language=EN, label=Table 4, caption=

Demographic characteristics of respondents (n=521)

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变量人数构成比（%）
性别
男28554.7
女23645.3
年龄（岁）
18～25275.18
26～3011922.84
31～4030358.16
41～495310.17
≥50193.65
受教育程度
高中及以下152.88
大学本科/专科47090.21
研究生及以上366.91
个人月收入（元）
5 0009217.66
5 001～10 00026651.05
10 001～15 00011321.69
15 001～20 000295.57
≥20 001214.03
个人是否确诊高血压
没有35167.37
高血压1级14127.06
高血压2级275.18
高血压3级20.38
家庭成员是否确诊高血压
没有11722.46
有40477.54
个人是否患有其他慢性病
无32562.38
患有一种17132.82
患有两到三种244.61
患有三种以上10.19
对数字疗法的了解
完全不了解9418.04
听说过30458.35
比较了解11822.07
了解并使用过产品81.54
数字健康素养得分（分）
<3219437.24
≥3232762.76
), ArticleFig(id=1324078555981807631, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078550785065965, language=CN, label=表4, caption=

受访者的一般人口学特征（n=521）

, figureFileSmall=null, figureFileBig=null, tableContent=
变量人数构成比（%）
性别
男28554.7
女23645.3
年龄（岁）
18～25275.18
26～3011922.84
31～4030358.16
41～495310.17
≥50193.65
受教育程度
高中及以下152.88
大学本科/专科47090.21
研究生及以上366.91
个人月收入（元）
5 0009217.66
5 001～10 00026651.05
10 001～15 00011321.69
15 001～20 000295.57
≥20 001214.03
个人是否确诊高血压
没有35167.37
高血压1级14127.06
高血压2级275.18
高血压3级20.38
家庭成员是否确诊高血压
没有11722.46
有40477.54
个人是否患有其他慢性病
无32562.38
患有一种17132.82
患有两到三种244.61
患有三种以上10.19
对数字疗法的了解
完全不了解9418.04
听说过30458.35
比较了解11822.07
了解并使用过产品81.54
数字健康素养得分（分）
<3219437.24
≥3232762.76
), ArticleFig(id=1324078556061499408, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078550785065965, language=EN, label=Table 5, caption=

Regression analysis results of mixed logit model for product attribute preference of DTx (n=521)

, figureFileSmall=null, figureFileBig=null, tableContent=
属性和水平（参照水平）系数β（95%CI）标准误P值
ASC0.110 (-0.170～0.390)0.1430.442
产品价格<-0.001 (-3.20×10-4～-2.20×10-4)0.001<0.001
产品风险（低）
中-0.726 (-0.880～-0.571)0.079<0.001
高-2.104 (-2.388～-1.820)0.145<0.001
易用性（低）
高0.349 (0.208～0.490)0.072<0.001
产品效果（低）
中0.077 (-0.096～0.249)0.0880.383
高0.569 (0.414～0.724)0.079<0.001
长期健康获益（低）
高0.670 (0.521～0.819)0.076<0.001
纳入医保目录（未纳入）
纳入1.458 (1.254～1.662)0.104<0.001
准确性（低）
高1.006 (0.834～1.178)0.088<0.001
), ArticleFig(id=1324078556141191185, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078550785065965, language=CN, label=表5, caption=

数字疗法产品属性偏好混合logit模型的回归结果(n=521)

, figureFileSmall=null, figureFileBig=null, tableContent=
属性和水平（参照水平）系数β（95%CI）标准误P值
ASC0.110 (-0.170～0.390)0.1430.442
产品价格<-0.001 (-3.20×10-4～-2.20×10-4)0.001<0.001
产品风险（低）
中-0.726 (-0.880～-0.571)0.079<0.001
高-2.104 (-2.388～-1.820)0.145<0.001
易用性（低）
高0.349 (0.208～0.490)0.072<0.001
产品效果（低）
中0.077 (-0.096～0.249)0.0880.383
高0.569 (0.414～0.724)0.079<0.001
长期健康获益（低）
高0.670 (0.521～0.819)0.076<0.001
纳入医保目录（未纳入）
纳入1.458 (1.254～1.662)0.104<0.001
准确性（低）
高1.006 (0.834～1.178)0.088<0.001
), ArticleFig(id=1324078556225077266, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078550785065965, language=EN, label=Table 6, caption=

Respondents’ willingness to pay for DTx with different attributes

, figureFileSmall=null, figureFileBig=null, tableContent=
属性和水平（参照水平）WTP（元）（95%CI）P值
产品风险（低）
中-2 723 (-3 471～-1 976)<0.001
高-7 891 (-9 627～-6 155)<0.001
易用性（低）
高1 309 (728～1 889）<0.001
产品效果（低）
中287 (-361～936）0.386
高2 133 (1 428～2 837）<0.001
长期健康获益（低）
高2 512 (1 808～3 216)<0.001
纳入医保目录（未纳入）
纳入5 466 (4 265～6 667)<0.001
准确性（低）
高3 771 (2 819～4 724)<0.001
), ArticleFig(id=1324078556346712083, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078550785065965, language=CN, label=表6, caption=

受访者对不同属性数字疗法产品的支付意愿

, figureFileSmall=null, figureFileBig=null, tableContent=
属性和水平（参照水平）WTP（元）（95%CI）P值
产品风险（低）
中-2 723 (-3 471～-1 976)<0.001
高-7 891 (-9 627～-6 155)<0.001
易用性（低）
高1 309 (728～1 889）<0.001
产品效果（低）
中287 (-361～936）0.386
高2 133 (1 428～2 837）<0.001
长期健康获益（低）
高2 512 (1 808～3 216)<0.001
纳入医保目录（未纳入）
纳入5 466 (4 265～6 667)<0.001
准确性（低）
高3 771 (2 819～4 724)<0.001
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基于离散选择实验的数字疗法产品偏好研究——以高血压管理产品为例
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张高源 , 李倩 , 韩优莉
现代预防医学 | 基层卫生服务 2026,53(1): 118-122
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现代预防医学 |基层卫生服务 2026 , 53 (1) : 118 -122
基于离散选择实验的数字疗法产品偏好研究——以高血压管理产品为例
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张高源(2000—)，男，硕士在读，研究方向：卫生经济

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张高源, 李倩, 韩优莉
作者信息
  • 首都医科大学公共卫生学院，北京 100069
通讯作者:
韩优莉，E-mail:
作者简介:

张高源(2000—)，男，硕士在读，研究方向：卫生经济

Preferences for digital therapeutics products based on discrete choice experiments—taking hypertension management products as an example
Gao-yuan ZHANG, Qian LI, You-li HAN
Affiliations
  • School of Public Health, Capital Medical University, Beijing 100069, China
出版时间: 2026-01-10 doi: 10.20043/j.cnki.MPM.202505394
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摘要
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目的

了解群众对慢性病管理数字疗法产品的偏好与支付意愿。

方法

基于离散选择实验，于2025年2—3月依托问卷星对全国范围内具有自主消费能力的成年劳动力人口开展线上问卷调查，并利用混合logit模型分析偏好结果。

结果

高准确性(β=1.006)、高易用性(β=0.349)、高产品效果(β=0.569)、高产品风险(β=-2.104)、高长期健康获益(β=0.670)、纳入医保目录(β=1.458)、较低产品价格均会显著影响受访者对数字疗法产品的选择(P<0.001)。其中，相对于低风险产品，受访者对高风险产品的支付意愿减少7 891元；产品纳入医保目录的支付意愿相对于不纳入增加5 466元。

结论

应完善数字疗法产品监管体系，形成以医保支付为核心的多元支付格局和为健康价值付费的氛围，提升产品的易用性，促进慢性病管理水平的提高和数字疗法产品的推广。

慢性病  /  数字疗法  /  离散选择实验
Objective

To understand the public’s preferences and willingness to pay for digital therapeutics (DTx) products for chronic disease management.

Methods

Based on a discrete choice experiment, an online questionnaire survey was administered via Wenjuanxing in February to March 2025, targeting the adult working population with independent spending capacity across the country. The preference outcomes were analyzed using a mixed logit model.

Results

Higher product accuracy (β=1.006), greater ease of use (β=0.349), superior product efficacy (β=0.569), higher product risk (β=-2.104),significant long-term health benefits (β=0.670), and inclusion in the medical insurance reimbursement list (β=1.458)demonstrated substantial influence on respondents’ preferences (P<0.001). Specifically, compared with low-risk products,respondents’ willingness to pay for high-risk products decreased by 7 891 yuan, and coverage by the medical insurance reimbursement list increased willingness to pay by 5 466 yuan compared with no coverage.

Conclusion

It is necessary to improve the regulatory system for DTx, establish a multi-payment pattern with medical insurance payment as the core and a climate of paying for health value, enhance the usability of products, and ultimately promote the improvement of chronic disease management levels and the promotion of DTx.

Chronic disease  /  Digital therapeutics  /  Discrete choice experiment
张高源, 李倩, 韩优莉. 基于离散选择实验的数字疗法产品偏好研究——以高血压管理产品为例. 现代预防医学, 2026 , 53 (1) : 118 -122 . DOI: 10.20043/j.cnki.MPM.202505394
Gao-yuan ZHANG, Qian LI, You-li HAN. Preferences for digital therapeutics products based on discrete choice experiments—taking hypertension management products as an example[J]. Modern Preventive Medicine, 2026 , 53 (1) : 118 -122 . DOI: 10.20043/j.cnki.MPM.202505394
正文
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随着经济社会的发展及疾病谱、死亡谱的变化，慢性非传染性疾病已逐渐成为威胁我国人民的主要健康问题，截至2019年，因慢性病导致的死亡占我国总死亡的88.5%[1]。慢性病的防控形势要求开展综合性的预防干预和健康教育[2]，但往往因患者健康素养低、依从性差而效果不理想[3]。数字疗法(digital therapeutics)的发展为慢性病管理提供了新工具。数字疗法基于循证证据，利用数字技术和人工智能，通过移动客户端提供个性化服务，为患者提供指标监测、健康管理等服务[4]，在便捷长效的同时提高了患者的自我管理能力。2024年11月6日，国家卫生健康委、国家中医药管理局、国家疾病预防控制局联合印发《卫生健康行业人工智能应用场景参考指引》，提出要提供个性化健康管理方案的智能慢性病管理场景[5]。但数字疗法在国内尚属于新兴技术，群众了解程度不高，作为一种更加面向消费市场的产品[6]，消费者对数字疗法产品属性的偏好是数字疗法产品普及的重要依据。基于上述背景，本研究利用离散选择实验方法，了解群众对慢性病管理数字疗法产品的产品属性的偏好，为我国数字疗法的发展提供决策依据。
1　资料与方法
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1.1　离散选择实验设计
本研究通过查阅相关文献，获得了影响消费者选择数字疗法产品的主要因素，邀请具有医学教育背景的本科生、研究生开展焦点小组访谈确定属性和水平，设计离散选择实验调查问卷。最终确定准确性、易用性、产品效果、产品风险、长期健康获益、纳入医保目录、产品价格七个属性，见表1。七个属性中，三个属性包含三个水平，四个属性包含二个水平，根据完全析因设计将会生成(33×24)个可能的假设场景，因此采用Ngene软件进行高效设计(D—Efficient Design)，最终生成20个选择集，随机分为二个版本，每个版本中还设置一个最优方案选择集以检查问卷质量，最终每个版本包含11个选择集，包括退出选项。表2呈现了一个选择集示例。
最终形成的调查问卷分为三个部分。第一部分涉及受访者的个人信息，包括性别、年龄、收入、高血压家族史情况、对数字疗法的认识等。第二部分是针对数字疗法产品偏好的调查。高血压在各类慢性病中具有重要的共病地位，与其他慢性病高度关联[7]，在慢性病管理中意义重大，且数字疗法产品在该领域较为成熟[8]，具有代表意义。基于此，本研究构建了高血压管理数字疗法产品的使用情景，由受访者对不同方案进行选择。第三部分是针对受访者的数字健康素养情况的调查。本部分采用Norman等[9]编制的、经郭帅军等[10]汉化的电子健康素养量表(eHealth Literacy Scale，eHEALS)问卷，测量受访者评判、利用互联网健康信息和服务能力，包括对互联网健康信息服务的应用能力（5题）、评判能力（2题）以及决策能力（1题），采用李克特五级选项，分别计1～5分，得分越高说明其电子健康素养越高，以32分为合格[11]。题目设置见表3。本研究中该量表的Cronbach α系数为0.811，KMO值为0.873。
1.2　调查对象
根据最小样本量计算公式：N>500c/(t×a)，500为固定变量，c为任一属性的最大水平数，t为选择集数，a为每个选择集的选项数，本研究问卷所需的最小样本量为：N>500×3 / (11×2)=68人，问卷共两个版本，因此最小样本量为136人。数字疗法产品是一种更加面向消费市场的健康消费产品[6]，因而本研究以具有一定自主消费能力的成年劳动力人口作为产品的潜在消费群体，依托问卷星平台，于2025年2—3月在全国范围内对该群体开展问卷调查。最终回收问卷737份，有效问卷521份，有效应答率70.69%。
1.3　统计学方法
本研究利用Excel 2021建立数据库，使用Stata 18.0进行数据整理与统计分析。数据处理方面，首先将离散选择实验产生的数据转换成适用于统计分析的特定格式。在本研究中，每份问卷包含10个选择集，每个选择集均含3个选择即：产品1、产品2、退出选项，每一位被调查者生成30×(10×3)个观测值，数据转换后共产生30行数据。将离散选择实验数据转换格式后，7个属性编码为虚拟变量(dummy variables)，使用混合logit模型分析数据。检验水准α=0.05。
1.4　质量控制
最终发放问卷的每个版本均包含一个最优选择集，在此选择集中，产品1的各项属性水平均优于产品2，受访者应当选择产品1，否则可被视为没有理解问卷含义，视为无效。通过质量控制选择集的问卷符合以下任一标准的问卷被视为无效：（1）问卷存在未回答的问题；（2）受访者对问卷的作答具有规律性或选项全部一致。
2　结果
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2.1　调查对象一般情况
521名受访者中，共有男性285名，女性236名。受访者平均年龄34.2岁，其中31～40岁的受访者最多。教育程度方面，大学本科/专科学历者占比达90.21%。个人月收入方面，5 001～10 000元收入群体占比较多，占51.05%。在高血压患病情况方面，32.63%的受访者患有高血压，其中处于高血压1级（收缩压140～159 mm Hg或者舒张压90～99 mm Hg）的受访者最多，有77.54%的受访者直系亲属患有高血压。此外，37.62%的受访者还患有其他慢性病。在对于数字疗法的了解方面，有58.35%的受访者听说过这一概念。数字健康素养调查的结果显示，62.76%的受访者数字健康素养得分32分及以上，总分平均值为32.01分，受访者整体对数字健康素养的自我评价较高。见表4。
2.2　受访者数字疗法产品偏好
混合logit模型的评估结果显示，七个属性对于受访者选择数字疗法产品的偏好均有显著影响。对受访者选择产品影响程度最大的属性水平是高产品风险(β=-2.104)，其次为纳入医保目录(β=1.458)、高准确性(β=1.006)，高长期健康获益(β=0.670)、高产品效果(β=0.569)、高易用性(β=0.349)等属性水平影响程度也较高。本研究中，产品价格虽然也具有显著的统计学意义，但对受访者的影响系数较低(β<-0.001)。见表5。
2.3　受访者对不同属性产品的支付意愿分析
结果显示，六个非经济属性均会影响受访者的支付意愿(P<0.001)。产品风险对受访者的影响最为显著，较之低产品风险，产品风险上升至中水平和高水平分别会使受访者支付意愿减少2 723和7 891元。产品纳入医保目录会使受访者愿意多花费5 466元，受访者也愿意多花费3 771元以换取产品更好的准确性。高长期健康获益(2 511元)、高产品效果(2 133元)、高易用性(1 309元)也是受访者愿意提升花费的属性水平。见表6。
3　讨论
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3.1　产品风险对选择产品的影响显著
结果显示，产品风险是受访者最为看重的因素。既往研究表明，对隐私风险、使用风险等潜在风险的担忧显著影响消费者对移动健康应用产品的选择[12]。目前我国尚未形成针对数字疗法产品的专门性政策法规，而德国等先行国家已形成较完整的数字疗法技术指标[6]。对此，应当尽快完善数字疗法产品的监管体系，明确数字疗法的形态、功能、适用范围和产品分类规则，对功能性、安全性、可操作性、适老性、信息安全等指标做出规范；形成详尽的操作文档，明确操作人员能力、临床使用建议、不良事件处置等内容。同时，建立健全不良事件报告和风险管理制度。
3.2　医保支付是推动产品发展的关键因素
是否纳入医保目录是仅次于产品风险的第二大影响因素。慢性病往往治疗周期较长，费用负担较重[13]；作为一种新兴产品，当前数字疗法产品研发成本高,致使定价较高[14]，患者费用负担大且对其认知程度低，使用意愿低。本研究中产品价格对受访者的影响较为靠后，但从国内外既往研究来看，对产品实行医保支付可降低费用负担；纳入医保支付作为官方认证，也会提振患者的使用信心，提升消费者的使用意愿[12,15]。目前国内外数字疗法的医保支付处于摸索阶段，海南省作为国内数字疗法的先行者正尝试部分优质产品纳入医保支付，多款产品列入慢性病健康服务包[14]。建议首先开展数字疗法产品卫生经济学评估，推动优质产品逐步纳入医保支付。对临床效果较传统手段等效或更优、有效降低医疗成本的产品加速纳入医保支付；对部分成本高、证据不足的产品实施定期审查和医保目录动态调整。将优质产品纳入家庭医生服务包，打通利用数字疗法健康管理、辅助诊断到临床治疗的全流程打包付费，鼓励商业保险开发数字疗法险，形成医保支付为核心，消费者自付、商业保险支付两翼并举的格局。
3.3　临床指标改善和消费者赋能是产品效果的主要体现
准确性、长期健康获益、产品效果对受访者影响亦十分显著。作为一款医疗产品，数字疗法通过个性化的健康管理，使患者养成良好的健康行为，形成长远的健康效果，这种特点使慢性病患者使用意愿较高[16-17]。应以循证为抓手，推动更多高质量循证证据产出，证明其与传统治疗手段及同类产品相比在指标上等效或更优，将循证证据作为医保目录调整的重要依据，根据临床和消费者需求和反馈进行持续性的研究。
3.4　易用性对提升产品使用体验的影响不容忽视
慢性病患者中老龄群体较多[18]，在移动设备上操作产品有一定困难，产品易用性的提升可提升慢性病患者特别是老龄慢性病患者使用意愿和满意度，促进其对产品的持续使用[19-20]。应根据产品消费群体的特点，完善产品适老性、无障碍操作设计，提供远程协作等辅助服务，提升产品可操作性。应提供简单易懂的产品操作指南，提升患者及家属、照护者使用能力。结合家庭医生签约服务、基层医疗卫生机构服务等形式，由医护人员为使用者提供操作指导，提升产品的易用性。
本研究利用离散选择实验方法探究消费者对慢性病管理数字疗法产品的选择偏好，为提高慢性病管理水平和促进数字疗法产品的推广提供了参考。本研究基于慢性病管理数字疗法的模拟情景，受访群体集中在大学本科/专科学历、对数字疗法产品有一定了解、数字健康素养较高的中青年中等收入群体，较多受访者患有或其家属患有高血压和其他慢性病，是此类产品的潜在消费群体，但受调查规模、调查对象等客观条件的限制，展现的结果可能与现实消费者偏好的实际情况有一定差异，未来还有待进一步拓展更多消费者群体，以及直接面向高血压及其他慢性病群体的偏好研究。
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  • 国家自然科学基金资助(72474140)
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参考文献 引证文献
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2026年第53卷第1期
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doi: 10.20043/j.cnki.MPM.202505394
  • 接收时间：2025-05-24
  • 首发时间：2026-11-02
  • 出版时间：2026-01-10
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  • 收稿日期：2025-05-24
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国家自然科学基金资助(72474140)
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    首都医科大学公共卫生学院，北京 100069

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